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MONGOLIA
ECONOMIC UPDATE
From Relief to Recovery
February 2021
Mongolia InfraSAP Infrastructure for Connectivity and Economic Diversification
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02
02
MONGOLIA ECONOMIC UPDATE
From Relief to Recovery
February 2021
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
CONTENTS
ACKNOWLEDGMENTS
VI
EXECUTIVE SUMMARY
VII
I. ECONOMIC PERFORMANCE AND PROSPECTS
A. Recent Economic Developments
2
A1. Output contracted sharply during the first nine months of 2020
2
A2. Inflation moderated notably, reflecting subdued domestic demand and lower oil prices
7
A3. The COVID-19 shock affected the structure and conditions of the labor market
8
A4. The budget deficit widened sharply in 2020 but is expected to narrow in 2021
10
A5. External pressures considerably eased following notable current account adjustment
15
A6. Monetary conditions have eased, but risks in the banking sector are building as asset
quality deteriorates
18
B. Outlook and Risks
II. COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
23
29
A. Channels of COVID-19 Shocks to Households
30
B. Impacts on Employment and Labor Income
32
C. Impacts on Non-labor Income
38
D. Potential Impacts on Poverty
39
E. Potential Mitigation Impacts of Policy Responses
43
References
II
1
47
CONTENTS
BOXES
Box I.1.
The government’s measures to contain the COVID-19 pandemic
Box I.2.
Government fiscal relief measures to alleviate the economic impact of the COVID-19 pandemic
12
3
Box I.3.
Summary of the 2021 budget
14
Box I.4.
The Bank of Mongolia’s measures to mitigate the impact of COVID-19
19
Box I.5.
Medium-term Banking Sector Strengthening Program for 2020-2023
26
Box I.6.
Global and regional outlook and risks
27
Box II.1.
Mongolia COVID-19 Household Response Phone Survey
32
FIGURES
Figure ES.1.
Mongolia: Key Indicators
Figure ES.2.
Mongolia: Key Indicators (continued)
X
Figure I.1.
Output contraction was mostly driven by the mining and services sectors
4
Figure I.2.
Steady growth of private consumption was not enough to compensate sharp drop in investment
4
Figure I.3.
Exports were hit hard in H1 but quickly recovered
5
Figure I.4.
Imports were also affected by subdued domestic demand and lower oil prices
5
Figure I.5.
Mining output fell sharply in H1 but recovered strongly
6
Figure I.6.
The services sector explained most of the contraction in non-mining output
6
Figure I.7.
Inflation moderated amid lower oil prices and subdued domestic demand …
7
Figure I.8.
…and compounded by the contraction of domestic credit
7
Figure I.9.
The COVID-19 pandemic has put some jobs at risk...
8
Figure I.10.
…thereby reversing declining trends of the unemployment rate
8
Figure I.11.
Relevance of cash transfers for people currently out of work increased in H1 2020
9
Figure I.12.
For unemployed, main source of income support shifted in Q2 2020
9
Figure I.13.
Government revenue has declined in all categories…
10
Figure I.14.
…while government spending soared driven by social welfare spending and public investment
10
Figure I.15.
The revenue shortfall was exacerbated by huge spending…
11
Figure I.16.
…reversing the fiscal surplus trajectory of the past three years
11
Figure I.17.
COVID-19 fiscal relief measures
12
Figure I.18.
Mongolia’s fiscal relief package is one of the highest among EAP countries
12
Figure I.19.
Income support and tax exemptions dominated fiscal relief measures
12
Figure I.20.
The deficit widened sharply in 2020 but is expected to narrow notably in 2021
13
Figure I.21.
The revenue projections in the 2021 budget are moderately optimistic …
13
Figure I.22.
Current account adjustment was enough to ease external pressures
15
Figure I.23.
Current account surplus in recent months is unprecedented in Mongolia’s recent history
15
Figure I.24.
Exports were hit hard in H1 but have recovered quickly
16
Figure I.25.
Import compression has largely been driven by lower fuel and capital goods imports
16
Figure I.26.
FX reserves recovered strongly after a sharp fall in H1, supported by eased current account
adjustment and gold purchases…
17
Figure I.27.
…and the exchange rate stabilized in H2 after a moderate depreciation in the first half.
17
Figure I.28.
The tugrug depreciation was moderate compared to Mongolia’s structural peers...
17
Figure I.29.
…supported by FX interventions by the BoM, particularly in the first half of 2020
17
Figure I.30.
The monetary policy rate was lowered to a historical low to revive credit growth
18
Figure I.31.
However, banks have been reluctant to lend despite having sizable excess reserves
18
Figure I.32.
Corporate loans issuance has been declining across sectors
20
Figure I.33.
Banks have also tightened new loan issuance to individuals, entrepreneurs, and SMEs
20
XI
III
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Figure I.34.
Loan quality has deteriorated notably…
21
Figure I.35.
…mainly in the mining, construction, and trade sectors
21
Figure I.36.
Provisions to loans of risky sectors seem low
22
Figure I.37.
Banks should also take hefty charges as the COVID-19 inpact intensifies
22
Figure I.38.
The liquidity of the banking system has remained steady...
22
Figure I.39.
…however, the banking system remains vulnerable to risk of currency mismatch
22
Figure I.40.
The government debt-to-GDP ratio is estimated to have risen in 2020 in many selected peers
24
Figure I.41.
The size of external bonds maturing during 2022-24 is significant
26
Figure I.42.
Real GDP growth (percent)
27
Figure I.43.
World commodity price forecast (Index=nominal U.S. dollars, 2016=100)
27
Figure I.44.
East Asia and Pacific country forecasts
28
Figure II.1.
Authorities tightened containment measures as the number of COVID-19 cases increased
31
Figure II.2.
Transmission channels of COVID-19 impacts to households
31
Figure II.3.
More than half of workers who worked pre-pandemic stopped working by the second lockdown
33
Figure II.4.
Large shares of workers in the industry and private services sectors faced employment disruptions
33
Figure II.5.
Share of workers in affected sectors in 2019
34
Figure II.6.
The number of carried passengers in 2020 declined during the first and second lockdowns
35
Figure II.7.
The number of tourists in 2020 was considerably lower than in previous years
35
Figure II.8.
The mobility of people to get certain services was significantly affected by government restrictions
35
Figure II.9.
Lower-skilled individuals working in the informal sectors are most vulnerable
36
Figure II.10.
Non-farm business owners were hit severely
36
Figure II.11.
Employment and income losses across welfare distribution
37
Figure II.12.
Urban workers were more likely to stop working in 2020
38
Figure II.13.
Percent of households receiving a remittance, 2018
39
Figure II.14.
Share of remittance to total household income (among households that received a remittance)
39
Figure II.15.
Projected poverty rates
41
Figure II.16.
Projected number of poor people
41
Figure II.17.
Consumption growth incidence (% change of per capita consumption from 2018 to 2020)
41
Figure II.18.
Average welfare loss from 2018 to 2020 by poverty status
41
Figure II.19.
Poverty headcount by location (%)
42
Figure II.20.
Distribution of the poor by location
42
Figure II.21.
Distribution of the poor by economic sector
42
Figure II.22.
Share of population living in households receiving CMP, 2018
43
Figure II.23.
Shares of CMP and other household income sources, 2018
43
Figure II.24.
CMP additional benefits as share of per capita consumption, 2020
45
Figure II.25.
Welfare changes with CMP additional benefits compared to pre-COVID case, 2020
45
Figure II.26.
Poverty headcount rates with and without policy responses, 2020
45
Figure II.27.
Perception of usefulness of government assistance
46
Table ES.1.
Key macroeconomic indicators
XII
Table I.1.
Mongolia: Improvements in the overall fiscal balance in 2021 (% of GDP)
14
Table I.2.
Key macroeconomic indicators
25
Table II.1.
Overview of HRPS Rounds 1–3
32
Table II.2.
GDP growth and inflation assumptions
40
Table II.3.
Government responses to COVID-19 (Social protection-related measures)
44
TABLES
IV
ABBREVIATIONS
MONGOLIA – GOVERNMENT FISCAL YEAR
January 1 - December 31
CURRENCY EQUIVALENTS
(Exchange Rate Effective as of December 31, 2020)
Currency Unit
=
Tugrug (MNT)
US$1.00
=
MNT 2,850
ABBREVIATIONS
ADB Asian Development Bank
BoM Bank of Mongolia
CMP Child Money Program
CPI consumer price index
EAP East Asia and Pacific
EMDEs emerging market and developing economies
FDI foreign direct investment
FX foreign exchange
GDP gross domestic product
GIR gross international reserves
HRPS Household Response Phone Survey
HSES Household Socio-Economic Survey
H1 first half of the year
H2 second half of the year
IMF International Monetary Fund
LFS Labor Force Survey
LLP loan loss provisions
MoF Ministry of Finance
MPC Monetary Policy Committee
NPLs nonperforming loans
NSO National Statistics Office
OxCGRT Oxford COVID-19 Government Response Tracker
Q1 first quarter of the year
Q2 second quarter of the year
Q3 third quarter of the year
Q4 fourth quarter of the year
SEC State Emergency Commission
SMEs small and medium-sized enterprises
y/y year-over-year
V
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
ACKNOWLEDGMENTS
This edition of the Mongolia Economic Update (MEU)
was prepared by Jean Pascal Nganou (Senior Economist),
Davaadalai Batsuuri (Economist), Undral Batmunkh
(Research Analyst), Maheshwor Shrestha (Economist),
and Ikuko Uochi (Economist). Sebastian Eckardt
(Lead Economist), Ibrahim Saeed Chowdhury (Senior
Economist), and Eka T. Vashakmadze (Senior Economist)
provided constructive comments. The MEU was
prepared under the direction of Martin Raiser (Country
Director), Hassan Zaman (Regional Director), Deepak
Mishra (Practice Manager), and Andrei Mikhnev (Country
Manager). The team is grateful to Sukhchimeg Tumur
(Program Assistant) and Indra Baatarkhuu (External
Affairs Officer) for their support on administrative and
communication affairs.
Each edition of the MEU consists of two parts. Part I
discusses recent economic developments and presents
the medium-term economic outlook, and Part II focuses
on a specific theme. The theme for this edition is the
socioeconomic impacts of COVID-19 on households,
based on the recent Household Phone Survey. The MEU
is intended for a wide audience, including policymakers,
business leaders, financial market participants, and the
community of analysts and professionals engaged in
Mongolia.
VI
The findings, interpretations, and conclusions expressed
in this update are those of the World Bank staff and do
not necessarily reflect the views of the Executive Board
of the World Bank or the governments they represent.
For information about the World Bank and its activities
in Mongolia, please visit https://www.worldbank.org/
en/country/mongolia. For questions and comments
on the content of this publication, please contact Jean
Pascal Nganou (jnganou@worldbank.org). The cutoff
date for this edition of the MEU is December 31, 2020.
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY
Recent Economic Developments
Strict implementation of social distancing, mobility
restrictions, and quarantine measures have helped
Mongolia contain the worst health effects of the
COVID-19 pandemic, though the country remains in
the midst of a significant outbreak. While the swiftness
of these measures was key to containing the pandemic,
their strictness is taking a significant toll on the
economy. Particularly, the unavoidable strict lockdown
measures from mid-November 2020 in response to the
domestic transmission of the pandemic have reduced
mobility and stalled economic activity. However, by
bringing the pandemic under control, these measure
are not only saving precious lives but are also expected
to facilitate a swifter and robust recovery.
The economic impact of the COVID-19 pandemic has
been severe and widespread. In the first nine months
of 2020, the Mongolian economy contracted by 7.3
percent, one of the worst contractions since the 1990s.
The mining sector was affected significantly by a sharp
decline in demand for key commodities and border
closures with China. The services sector was also hit
hard due to mobility restrictions and falling incomes. In
fact, firm-level surveys indicate that the impact of the
COVID-19 shock was most severe for small and young
firms, and for enterprises in the manufacturing, tourism,
trade, transportation, construction, and education
sectors. However, generous economic support provided
by the government has so far prevented a wave of
business closures.
The COVID-19 shock also affected the structure and
conditions of the labor market. While some sectors
including hospitality and entertainment experienced
declining employment, employment increased in some
sectors such as information technology, as demand
for online services increased. Overall, the labor force
participation rate shrank by 1.1 percent in September
2020 from a year ago and the unemployment rate
slightly edged up in Q3 2020, reflecting weakening
labor market conditions. However, sizable policy
support partially mitigated the impact of COVID-19
and encouraged firms to limit layoffs and opt for
reduced working hours instead. At the same time,
generous income support and the lack of adequate
and affordable childcare service during the closure
of schools partly contributed to declining labor force
participation.
The pandemic-induced economic crisis has been severe.
Households from various segments of the income
distribution were affected by COVID-19-related shocks,
with those employed in the low-skilled informal
sectors, with limited economic buffers or job protection,
and those living just above the national poverty line, at
greater risk of falling below the poverty line. The latest
Household Response Phone Surveys (HRPS) jointly
conducted by the National Statistics Office of Mongolia
and World Bank reveal that household labor income
was affected by the pandemic shock, as many people
stopped working due to business closures or faced
a reduction in working hours, particularly under the
second nationwide lockdown in mid-November. The
government’s generous direct transfers to households
helped partially mitigate the negative income shock. A
poverty micro-simulation analysis, using the Household
Socio-Economic Survey from 2018 and latest GDP
growth forecasts, indicates that without mitigating
measures, approximately 195,000 to 260,000 more
VII
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
people could have been pushed into poverty as a result
of the pandemic, bringing the poverty rate up to 33.6
percent in 2020 from 28.4 percent in 2018. In fact, the
analysis shows that the quintupling of benefits under
the Child Money Program during May 2020–July 2021,
on its own would be enough to bring poverty incidence
below the pre-COVID level (see Part II for details).
The external position improved substantially faster
than initially expected, mainly supported by the
notable current account adjustment. After a sharp
deterioration in the early months of 2020, pressures
notably eased in the second half of the year, and the
current account even recorded a surplus amid a quick
recovery of exports and persistent imports compression
(due to lower demand for capital and intermediate
goods and declining service fees). Meanwhile, despite
a fall in foreign direct investment and sizable private
sector external repayments, the balance of payments
improved, with the authorities taking advantage of
improved financing conditions to refinance external
debt. The Mongolian tugrug depreciated moderately
and the level of foreign exchange reserves reached
a historical high of US$4.5 billion, supported also by
higher gold purchases by the authorities.
The cost of fiscal relief measures is estimated to be
over 9 percent of GDP.1 Fiscal imbalances had started
to emerge in early 2020 prior to the introduction of
COVID-19-related measures, with the government’s
decision to increase wages and pensions and to
write off pension loans. Fiscal imbalances widened
significantly further between April and December
2020, as the effects of the pandemic intensified. The
budget deficit reached 9.5 percent of GDP in 2020, its
highest level since 2016, amid a large revenue shortfall
and sizable fiscal relief (spending) measures. Overall,
the authorities’ fiscal response has provided adequate
support to firms and households, but the size of the
deficit has raised questions over its sustainability.
Monetary policy was loosened to fight the economic
impact of the pandemic through policy rate cuts,
increased banking sector liquidity, and the introduction
of regulatory forbearance. Moreover, the monetary
authorities engaged in quasi-fiscal activities, thus
violating the Law on Central Bank, which prohibits the
Bank of Mongolia from engaging in these activities. The
looser policy stance followed a period of tightening
starting in late 2018, which helped slow credit growth
and stabilize inflation, giving the central bank some
room to relax when the pandemic hit. Nonetheless,
monetary policy space continues to be limited by the
country’s relatively weak external position.
With respect to the financial sector, despite the
relaxation of macroprudential regulations and buffers,
banks remain cautious in issuing loans. In 2020,
domestic credit contracted by about 5 percent (yearover-year) compared to growth of 5.1 percent in 2019.
While a sizable portion of this contraction is explained
by the authorities’ decision to write off the pension
loans in January 2020, issuance of new loans remained
subdued due to heightened perceptions of risk,
deteriorating asset quality, and significant currency
mismatches (including deposit dollarization). Moreover,
regulatory forbearance may be hiding more serious
problems in the financial sector and thus complicates
a full assessment of financial sector stability.
Outlook and Risks
Recovery in the post-pandemic period is likely to be slow
and erratic. Following an estimated contraction of 5.2
percent in 2020, the Mongolian economy is expected
to grow by 4.3 percent in 2021, as the authorities take
control of the pandemic, stimulus measures prop up
domestic demand, the adverse impact of the global
economy recedes, businesses and consumers adjust
to the new norm of living with the pandemic, and a
vaccine is introduced. However, the recovery is subject
to risks of (i) a sharp rise in domestic COVID-19 cases
that could trigger stricter and prolonged lockdowns; (ii)
the potential for further global waves of the virus that
would worsen the domestic and external environment;
(iii) possible financial instability as regulatory
forbearance is withdrawn and the underlying fragile
condition of bank balance sheets is revealed; (iv)
weather-related shocks (for example, a harsh winter,
which could hit the agriculture sector); and (v) the
likelihood of new spending and overstretched public
finances in the run-up to the presidential election.
It includes the extension of some measures which are expected to be implemented until July 2021. But it does not include the government’s recent
decision on exempting utilities fees for households and enterprises.
1
VIII
EXECUTIVE SUMMARY
Mongolia, like other countries, will need to transition
from policies focused on short-term economic relief
to accelerating recovery and building resilience. The
challenge Mongolia faces in this regard is that the
fiscal space to continue the generous support policies
enacted during 2020 is quite limited, while their rapid
withdrawal as long as the economy remains weakened
by public-health-related mobility restrictions could
create significant difficulties for households and firms.
The government’s fiscal consolidation plan takes
this into account by committing to medium-term
adjustment but keeping current support measures in
place until the summer of 2021. This plan will need
to be implemented, as further fiscal expansion beyond
what has been agreed in the 2021 budget could erode
confidence, lead to currency pressures and capital
outflows, and require harsher austerity measures to
reestablish macroeconomic control. Mongolia has
so far managed to avoid a repeat of the traditional
macro boom-and-bust cycles. It should cherish this
achievement. Further exchange rate flexibility could
help cushion additional external shocks and thereby
preserve the limited domestic policy room.
Finally, Mongolia should adopt an integrated and
fiscally sustainable approach to boosting mediumterm economic prospects and job creation. Such
an integrated approach would place the highest
emphasis on leveraging private sector investment in
the mining and non-mining sectors to create higherproductivity jobs and sustainable income opportunities
for Mongolians. These efforts would be complemented
by better-prioritized and targeted government
investments in infrastructure and a more efficient and
fiscally affordable social safety net. They would also
require continued attention to the generation of skills
required for successful employment, and addressing the
possible losses of human capital, particularly among
the poor, as a result of repeated school closures. While
over the coming year government policy will need to
remain attentive to national and global developments
in the management of the pandemic and react flexibly
to any downside risks, the rollout of vaccines raises the
prospect that policy efforts can gradually return to this
critical medium-term agenda.
Another priority is to prevent the COVID-19 shock from
undermining financial stability. While a swift policy
response was welcome and necessary, the extension
of regulatory forbearance would further reduce
transparency around the underlying quality of banking
sector balance sheets, while delaying the necessary
adjustments in the real sector. The COVID-19 shock has
left scars among companies and some may not be able
to survive. They should be allowed to close and their
resources reallocated to other, more profitable ventures.
Banks play a key role in facilitating this reallocation of
resources, but excessive forbearance may lock funds in
poor investment decisions made in the past, increasing
the long-run costs of the shock to the economy.
Relatedly, Mongolia’s efforts to implement structural
reforms in the banking sector should gain traction. Key
elements of these reforms include the strengthening
of capital buffers and improved corporate governance
of banks (including ongoing reforms in ownership
structure of banks), both of which would be facilitated
by the gradual exit from COVID-19 related regulatory
forbearance.
IX
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Figure ES.1. Mongolia: Key Indicators
Figure ES.1. Mongolia: Key Indicators
Strict containment measures have helped Mongolia
check the spread in most of 2020
However, relative to some of its regional peers, the
number of confirmed infections has surged since
November 2020
Stringency of government measures and cases of COVID‐19
Cumulative reported cases of COVID‐19
100
1600
90
80
800
600
400
20
Jan-21
Dec‐20
Nov‐20
Oct‐20
Sep‐20
Aug‐20
Jul‐20
Jun‐20
May‐20
Apr‐20
Mar‐20
Jan‐20
Feb‐20
Dec-20
0
0
Nov-20
200
10
0
Oct-20
10
Sep-20
30
1000
Aug-20
20
Vietnam
Mongolia
Jul-20
40
1200
Jun-20
50
Papua New Guinea
May-20
30
Cambodia
Apr-20
60
Feb-20
70
40
Fiji
Lao PDR
1400
Mar-20
50
Stringency index
New COVID‐19 cases
Stringency index
Jan-20
New COVID‐19 cases
60
Source: Oxford University (OxCGRT).
Source: Oxford University (OxCGRT).
Exports were significantly affected in H1, but have
recovered quickly…
…while the hard‐hit nontradeable services sector has
been slow to recover
Note: The stringency index measures the stringency of government
containment measures, including school and workplace closings
and restrictions on gatherings in response to the COVID‐19. Higher
value indicates more stringent measures.
Quarterly real exports of goods and services (y/y change)
19.6%
9.0%
Supply contribution to GDP growth, percentage points
10%
16.3%
5%
8.8%
0%
Sources: NSO; World Bank staff estimates.
Additional health-related spending
25%
Additional spending and revenue measures
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
Q4-18
Q2-18
Household consumption
Public consumption
GDP growth
Gross capital formation
Net exports
15%
Sources: NSO; World Bank staff estimates.
12
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
Q4-18
LAO
MMR
VNM
KHM
MYS
PHL
IDN
CHN
THA
-25%
Q3-18
-15%
Q2-18
-5%
2
Q1-18
5%
4
MNG
Percent of GDP
Quasi-fiscal operations
Sources: MoF; World bank (2020); World Bank staff
estimates.
X
…which supported household consumption
Demand contribution to GDP growth, percentage points
6
0
GDP growth
Sources: NSO; World Bank staff estimates.
Government provided sizable fiscal relief package…
8
Services
Agriculture
Q1-18
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
-15%
10
Non-mining industry
-10%
-36.1%
12
Mining
-5%
Q3-18
-2.7%
-5.8%
EXECUTIVE SUMMARY
Figure ES.2. Mongolia: Key Indicators (continued)
Figure ES.2. Mongolia: Key Indicators (con�nued)
With subdued infla�on, the monetary policy rate
reached a historic low
Credit growth (y/y, %): LHS
12
10
25%
40%
35%
Sources: BoM; World Bank staff es�mates.
Note: RHS = right-hand side; LHS = le�-hand side.
Sources: BoM; World Bank staff es�mates.
Note: RHS = right-hand side; LHS = le�-hand side.
…mainly explained by a deteriora�on in the loan
quality and rising NPLs
The banking system remains exposed to risk of
currency mismatch
12
33%
NPLs and past-due loans in percent of total outstanding
loans
Currency mismatch is defined by difference in dollariza�on
of deposits (bank’s liabili�es) and credits (bank’s assets)
FX deposit/total deposits: LHS
FX loans/total loans: LHS
MNT/USD: RHS
28%
NPLs (% of Total Loans)
9
Dec-20
Jun-20
Sep-20
Jun-18
Dec-19
0%
Mar-20
5%
-10%
0
Jun-19
10%
-5%
Sep-19
15%
0%
Dec-18
4
Mar-19
20%
5%
Sep-18
10%
Dec-17
25%
6
Mar-18
15%
Jun-17
30%
8
Sep-17
Dec-20
Sep-20
Jun-20
Mar-20
Dec-19
Sep-19
Jun-19
Mar-19
Dec-18
Excess reserves to deposit ra�o (%): RHS
Domes�c credit growth (y/y): LHS
30%
20%
2
Sep-18
Excess reserves and loan growth in the banking sector
Mar-17
Core inflation (y/y, %): RHS
Policy rate: RHS
Jun-18
28
25
22
19
16
13
10
7
4
1
-2
-5
-8
However, banks with excess liquidity have been
reluctant to lend…
2,830
2,780
2,730
23%
Past Due Loans (% of Total Loans)
2,680
2,630
18%
6
2,580
2,530
Oct-20
Dec-20
Jun-20
Aug-20
Apr-20
Feb-20
Oct-19
Dec-19
Jun-19
Aug-19
Apr-19
Feb-19
Oct-18
Dec-18
2,480
Aug-18
8%
Jun-18
Nov-20
Sources: BoM; World Bank staff es�mates.
Note: RHS = right-hand side; LHS = le�-hand side.
Sources: BoM; World Bank staff es�mates.
Note: RHS = right-hand side; LHS = le�-hand side.
Current account surplus in recent months has
contributed to reserves accumula�on…
…while the exchange rate has stabilized following
easing of external pressures
1.5
-800
1.0
-1000
Q3-20
Q1-20
Q3-19
Q1-19
Q3-18
Q1-18
Q3-17
Q1-17
Q3-16
Q1-16
Q3-15
Q1-15
-1200
0.5
0.0
Sources: BoM; World Bank staff es�mates.
Note: FX = foreign exchange; RHS = right-hand side; LHS =
le�-hand side.
120
115
110
105
100
95
Jun-20
2.0
Dec-19
2.5
-600
125
Jun-19
-400
Depreciation
130
Dec-18
3.0
MNT/CNY
135
Jun-18
3.5
-200
MNT/US$
140
Dec-17
4.0
0
145
Jun-17
4.5
Dec-16
5.0
Gross international reserves (RHS, billion US$)
200
Jun-16
Current account balance (LHS, million US$)
400
Exchange rate: Tugrug (Spot rate, Index, Dec 31, 2015=100)
Dec-15
Current account balance and FX reserves
2,430
Dec-20
Sep-20
Jul-20
May-20
Mar-20
Jan-20
Nov-19
Sep-19
Jul-19
May-19
Mar-19
3
Jan-19
13%
Sources: BoM; World Bank staff es�mates.
13
XI
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Table ES.1.
Key macroeconomic indicators
2016
2017
2018
2019
2020e
2021f
2022f
Annual percent change unless indicated otherwise
Real GDP growth, at constant market prices
1.4
5.4
7.0
5.0
-5.2
4.3
5.4
Private Consumption
-2.2
5.4
12.4
9.9
2.0
3.6
4.5
Government Consumption
10.6
-1.8
-0.8
11.5
17.5
-5.1
1.6
0.5
35.6
21.3
23.5
-16.3
9.0
10.0
Exports, Goods and Services
13.8
14.8
24.0
9.1
-5.0
13.4
7.4
Imports, Goods and Services
12.7
24.8
30.9
22.3
-9.0
14.1
8.4
1.2
5.3
7.2
5.2
-5.2
4.3
5.4
6.2
1.8
4.5
8.4
10.8
5.0
6.0
-0.4
0.7
7.9
3.1
-11.0
6.3
5.4
1.1
7.7
4.7
5.8
-5.7
2.5
5.2
0.9
6.4
8.1
5.2
2.3
5.0
7.0
-6.3
-10.2
-16.8
-15.4
-3.3
-7.7
-8.3
7.6
24.5
17.4
21.1
9.2
11.8
13.2
1.1
12.7
16.3
16.5
12.5
14.0
15.0
Fiscal Balance (% of GDP)**
-15.3
-3.8
2.6
1.4
-9.5
-2.7
-1.9
Primary Balance (% of GDP)
-10.1
0.4
5.8
3.7
-6.9
-0.3
0.1
87.6
84.7
72.6
69.0
79.4
77.7
73.0
Gross Fixed Capital Formation
Real GDP growth, at constant factor prices
Agriculture
Industry (incl mining)
Services
Inflation (CPI, end-period)
Current account balance (% of GDP)
Financial and Capital account (% of GDP)
Net Foreign Direct Investment (% of GDP)*
Debt (% of GDP)***
* In 2016, net FDI number excluded the transactions of Oyu Tolgoi-2 project financing in May–June 2016.
** Development Bank of Mongolia (DBM) spending is excluded from fiscal balance and monitored separately.
***General government debt data exclude SOE debt and central bank liability from People’s Bank of China swap line.
XII
I. ECONOMIC PERFORMANCE
AND PROSPECTS
A. Recent Economic Developments
B. Outlook and Risks
2
23
1
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
I. ECONOMIC PERFORMANCE AND
PROSPECTS
A1. Output contracted sharply during the first nine
months of 2020
RECENT
ECONOMIC
DEVELOPMENTS
The COVID-19 crisis has triggered a global economic shock of
unprecedented magnitude, causing synchronized collapses in
economic activity across the world. In particular, economic conditions
in the East Asia and Pacific (EAP) region deteriorated sharply due to
the pandemic-related lockdowns. Although the Chinese economy
is recovering at a brisk pace, recovery in the rest of the region is
expected to be subdued and fragile as disruptions to economic
activity were more acute than expected. The pandemic has caused
a heavy toll of deaths and illness, plunged millions into poverty, and
may depress economic activity and incomes for a prolonged period.
Furthermore, the pandemic has exacerbated the risks associated with
debt accumulation as debt levels have reached historic highs and
financial market stress builds.
The COVID-19 health crisis quickly escalated into deep economic
turmoil in Mongolia, affecting businesses, households, and government
revenue. This manifested itself through four key channels: (i) the
government’s containment measures have had a direct and immediate
adverse impact on small businesses and household income, weighing
on already weakening domestic economic activity (see box I.1); (ii)
the mining sector has been hard hit by weaker Chinese demand,
compounded by self-imposed border closures, a drop in commodity
prices, and greater risk aversion of investors; (iii) the services sector
(including tourism and transportation), which accounts for about 40
percent of the Mongolian economy, was affected by the containment
measures; and (iv) unforeseen revenue shortfalls and increased
spending on health care and social protection further exacerbated
fiscal pressures.
2
ECONOMIC PERFORMANCE AND PROSPECTS
Box I.1.
The government’s measures to contain the COVID-19 pandemic
The Government of Mongolia, through the State Emergency Commission (SEC), which is tasked with handling emergencies at the national level, introduced throughout 2020 a series of restrictions to contain the risk of COVID-19.
These include:
•
Border closures: All travel (air, road, and railway) from or through China was banned since February 1, 2020.
Cross-border passenger transportation of all forms ceased starting March 10. Mongolia’s borders have remained
closed for passengers, with the exception of Mongolian nationals arriving through special chartered flights
organized by the government. Upon arrival, passengers are subject to a 21-day mandatory strict quarantine to
limit the risks of domestic contagion. Hygiene protocols were elevated on the trucks transporting consumer
items imported from Russia.
•
Suspension of exports: Exports of coal and crude oil were suspended during February 10–March 2, in an attempt to minimize the risk of infection of truck drivers over the Mongolia-China border. Although the official
suspension was lifted as scheduled, export did not return to its regular pace until August, when the government
introduced the Green Gate program, which aimed to accelerate truck transportation through improved customs
clearance and proper implementation of hygiene protocols.
•
Suspension of educational activities: All activities of schools, kindergartens, universities, vocational centers,
production centers, and training centers were suspended from January 27 to September 1. Online/TV schooling
was provided for students until September 21, when in-class education resumed.
•
Restriction of services and community activities: Bars, cafés, and restaurants were instructed during mid-February to July 2020 to close at 10:00 p.m. rather than the usual 4:00 a.m. In early May, nightclubs and karaoke bars
were banned from operating, and in early March, the government suspended community activities including
meetings, trainings, sport competitions, travel, arts, cultural activities, cinema, driving courses, and game center
activities. These restrictions have been gradually loosened since then.
•
Introduction of a strict lockdown when the first domestic contagion was recorded on November 11, 2020:
Ulaanbaatar and several other regions remained in strict lockdown between November 11 and December 14.
During this period, the sale of alcohol was prohibited, pedestrian and automobile movement in the city was
restricted to grocery, health care, and other essential services only, public transportation service was limited,
travel between regions was prohibited, and charter flights were suspended. During the lockdown, the authorities traced the domestic infections and conducted PCR (polymerase chain reaction) tests of a sample of households. On December 14, when the strict lockdown ended, a number of economic activities that could enforce
social distancing were allowed to reopen. Passenger travel between towns remains conditional on PCR testing.
In-class educational activities have been suspended since November 11, and TV schooling resumed.
•
After a temporary loosening, a strict lockdown was reintroduced in the city of Ulaanbaatar starting
December 14: An accelerating number of COVID-19 cases in the city triggered the authorities to introduce
a strict lockdown until January 11, 2021. Unlike in the preceding lockdown, delivery services were restricted
within the city. Due to consequences on economic activities, starting January 11, the strict lockdown has been
loosened step by step.
Source: Compiled from various government websites.
3
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
quarters of 2020 from 9.9 percent in the same period
Mongolia’s economy is facing one of its most severe
cinema, driving courses, and game center activities. These restrictions have been gradually loosened
in 2019. Household consumption growth slowed to 6.1
contractions triggered
by the outbreak and associated
since then.
percent
(y/y) contagion
during thiswas
period
from on
9.5November
percent one
precautionary
measures.
The
COVID-19
shock
came
at
 Introduction of a strict lockdown when the first
domestic
recorded
11,
year
ago,
as
COVID-19-related
restriction
measures
a time when Mongolia’s
economy
was
already
facing
2020: Ulaanbaatar and several other regions remained in strict lockdown between November
11 and
this period,
theofsale of
alcohol
was prohibited,
automobile
affected
private
spending onpedestrian
retail trade,and
travel,
leisure,
a slowdown -December
particularly14.in During
the second
half (H2)
movement
in
the
city
was
restricted
to
grocery,
health
care,
and
other
essential
services
only,
public
and recreational activities. The Household Response
2019 - mostly driven by weaker commodity prices and
transportation service was limited, travel between regions was prohibited, and charter flights were
Phone Survey indicates that the pandemic has led to
the deteriorating quality of locally produced copper, a
suspended. During the lockdown, the authorities traced the domestic infections and conducted PCR
deceleration
in 14,
labor
income,
particularly
key mineral export.
Hit
by
the
COVID-19
shock
through
(polymerase chain reaction) tests of a sample ofsignificant
households.
On December
when
the strict
lockdown
among
the
self-employed
and
household
both domesticended,
and external
channels,
Mongolia’s
real
a number of economic activities that could enforce social distancing were allowed tobusiness
reopen.
ownerson(see
II for
details).
However,
household
GDP contracted
by 7.3 travel
percent
(year-over-year
[y/y])conditional
Passenger
between
towns remains
PCRpart
testing.
In‐class
educational
activities
have
been
suspended
since
November
11,worst
and TV schooling
resumed.
consumption
and income were supported by, among
in the first nine
months
of 2020
(figure
I.1), its
 since
Afterthe
a temporary
strict lockdown
was reintroduced
in the city
of Ulaanbaatar
others,
the wage/pension
increase,
the write starting
off of
contraction
economicloosening,
transitionaperiod
in
December
14:
An
accelerating
number
of
COVID‐19
cases
in
the
city
triggered
the
authorities
to
pension loans, and COVID-19-related income support
early 1990s. Although the contraction was broadintroduce a strict lockdown until January 11, 2021. Unlike in the preceding lockdown, delivery services
measures. Meanwhile, government consumption
based, it was significantly felt in the mining sector
were restricted within the city. Due to consequences on economic activities, starting January 11, the
expanded by 11.7 percent, mainly reflecting COVID-19(-20.7 percent,strict
y/y).lockdown
Output has
in been
non-mining
loosenedindustry
step by step.
related spending.
fell by 3.7 percent (y/y), while services contracted by 7
Source:
Compiled
from various
government
websites.
percent
in the
same period.
Meanwhile,
the agriculture
Investment, especially in the private sector, plummeted,
sector was the key driver of growth, as it expanded
pulling contractions
down growthtriggered
on the by
demand
side. The
Mongolia’s
economy
is facing
one ofweather
its most severe
the outbreak
and
by 11.3
percent (y/y),
supported
by favorable
contribution
of
gross
capital
formation
to
GDP
growth
associated
precautionary
measures.
The
COVID‐19
shock
came
at
a
time
when
Mongolia’s
economy
was
conditions. The adverse impact of a weaker global
already facing a slowdown―particularly in the second
(H2) ofnegative
2019―mostly
driven bypoints)
weaker
turned half
significantly
(-14.3 percentage
economy was exacerbated by a sharp fall in domestic
commodity prices and the deteriorating quality of locally
produced copper, a2020,
key mineral
Hit by
during January–September
from +10export.
percentage
economic activities due to the authorities’ containment
the COVID‐19 shock through both domestic and external
channels,
Mongolia’s
real
GDP explained
contractedby
by a7.3
points
a
year
ago.
This
is
mainly
measures, including the exports ban.
percent (year‐over‐year [y/y]) in the first nine months
of 2020 (figure
I.1),including
its worstdeclining
contraction
since the
combination
of factors
commodity
economic
transition
period
in
early
1990s.
Although
the
contraction
was
broad‐based,
it
was
significantly
prices, weakening domestic demand, and deteriorating
On the demand side, although final consumption
felt moderated
in the mining
sector
(‐20.7 percent, y/y).
Outputinvestor
in non‐mining
industry
fellforeign
by 3.7 percent
(y/y), while
confidence.
In fact,
direct investment
growth
during
January–September
2020,
services acontracted
percent(figure
in theI.2).
same
period.(FDI)
Meanwhile,
the agriculture
was
the key
flows, which
account for sector
about 70
percent
of driver
the
it remained
key driverby
of7growth
Final
of
growth,
as
it
expanded
by
11.3
percent
(y/y),
supported
by
favorable
weather
conditions.
The
adverse
gross capital formation, fell by over 20 percent (y/y)
consumption grew by 7.1 percent (y/y) in the first three
impact of a weaker global economy was exacerbated by a sharp fall in domestic economic activities due
to the authorities’ containment measures, including the exports ban.
Figure I.1. Output contraction was mostly driven by
Figure I.2. Steady growth of private consumption was
theFigure
mining
and
services
sectors
not enough
to compensate
sharp drop
in investment
I.1. Output contraction was mostly driven by
Figure
I.2. Steady
growth of private
consumption
was
the mining and services sectors
not enough to compensate sharp drop in investment
Supply contribution to GDP growth, percentage points
Demand contribution to GDP growth, percentage points
Supply contribution to GDP growth, percentage points
15%
10%
Mining
Non-mining industry
Services
Agriculture
Demand contribution to GDP growth, percentage points
25%
5%
Gross capital formation
Net exports
15%
0%
5%
-5%
-5%
-10%
Sources: NSO; World Bank staff estimates.
Sources: NSO; World Bank staff estimates.
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
Q4-18
Q3-18
Q2-18
-25%
Q1-18
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
Q4-18
Q3-18
Q2-18
-15%
Q1-18
-15%
Household consumption
Public consumption
GDP growth
Sources: NSO; World Bank staff estimates.
Sources: NSO; World Bank staff estimates.
On the demand side, although final consumption growth moderated during January–September 2020,
it remained a key driver of growth (figure I.2). Final consumption grew by 7.1 percent (y/y) in the first
4
16
three quarters of 2020 from 9.9 percent in the same period
in 2019. PERFORMANCE
Household consumption
growth
ECONOMIC
AND PROSPECTS
slowed to 6.1 percent (y/y) during this period from 9.5 percent one year ago, as COVID‐19‐related
restriction measures affected private spending on retail trade, travel, leisure, and recreational activities.
The Household Response Phone Survey indicates that the pandemic has led to significant deceleration in 2
to US$1.2 billion during January–September. Moreover,
to boost exports through the Green Gate program.
labor income, particularly among the self‐employed and household business owners (see part II for
total
outstanding
loans
in the banking
sector, a and
key income
In addition,
Q3 2020,by,
goldamong
exportsothers,
reachedthe
their
details).
However,
household
consumption
were in
supported
source
of
financing
of
domestic
investment,
contracted
highest
peak
since
2008,
as
the
central
bank
provided
wage/pension increase, the writeoff of pension loans, and COVID‐19‐related income support measures.
by
over 5 percent
(y/y) amid consumption
the ongoing deterioration
soft percent,
loans to gold
miners
(0.3 percent
of GDP during
Meanwhile,
government
expanded by 11.7
mainly
reflecting
COVID‐19‐related
ofspending.
loan quality. Meanwhile, the accelerated execution
January-October).
of public investment projects was not sufficient to
Imports
contracted
Investment,
especially
the private sector, plummeted,
pullingalso
down
growth onsignificantly
the demandamid
side. weaker
The
offset
the slump
in privateininvestment.
demand andnegative
lower oil
prices.
As a net
contribution of gross capital formation to GDP growthdomestic
turned significantly
(‐14.3
percentage
Exports
hard in the first half
but from
recovered
importerpoints
of energy,
Mongolia
declining
points) were
duringhitJanuary–September
2020,
+10 percentage
a year
ago. Thisbenefited
is mainlyfrom
explained
quickly
(figure
I.3).
In
the
first
nine
months
of
2020,
global
oil
prices.
Real
imports
of
goods
and
by a combination of factors including declining commodity prices, weakening domestic demand,services
and
deteriorating
investor
confidence.
In fact,
directfell
investment
(FDI)(y/y)
flows,
which
account for about
exports
of goods
and services
contracted
by 8foreign
percent
by 8 percent
during
January-September
2020
percent to
(y/y)
to US$1.2 billion
percent
grossdecline
capitalsince
formation,
fellglobal
by over 20
in70real
terms,of
thethe
largest
the 2009
compared
an expansion
of 23.2during
percentJanuary–
a year ago
September.
totalsame
outstanding
the banking
a key
source
of financingisofsupported
domestic by,
financial
crisis.Moreover,
In fact, in the
period ofloans
2019,inreal
(figuresector,
I.4). The
import
compression
investment,
contracted
by
over
5
percent
(y/y)
amid
the
ongoing
deterioration
of
loan
quality.
Meanwhile,
exports expanded by 15.1 percent. The contraction was
among others, subdued purchase of capital goods
the accelerated
of public
investment
projects(mostly
was notreflecting
sufficientlower
to offset
the slump
in private
most
significant inexecution
coal and crude
oil (which
accounted
private
investment),
lower
investment.
for 45 percent of the total export in 2019) following
oil prices, and reduction in imported consumer goods
weaker
ban quickly
triggered
by COVID-19-related
precautionary
Exportsdemand
were hitfrom
hardChina
in theand
firstthe
halftemporary
but recovered
(figure
I.3). In the first nine
months ofmeasures
2020,
on
exports
February-March
contain the
of
(for
example,
the official
exports
of in
goods
and servicestocontracted
by risk
8 percent
in real
terms,cancellation
the largestofdecline
sincecelebration
the 2009 of
global financial
crisis.
In fact,
in the
real lunar
exports
by 15.1economic
percent. activity
The
COVID-19.
Moreover,
copper
exports
(24 same
percentperiod
of totallast year,
the 2020
newexpanded
year and reduced
contraction
was most
significant
in coal and
crude oil (which
accounted
forother
45 percent
of Meanwhile,
the total export
exports
in 2019)
contracted
significantly,
especially
in retail
trade and
services).
imports
2019)
weaker
from
and the of
temporary
bandeclined
on exports
in February–March
to
ininthe
firstfollowing
quarter (Q1)
duedemand
to a sharp
fallChina
in prices
services also
sharply,
partly due to weaker
contain
the
risk
of
COVID‐19.
Moreover,
copper
exports
(24
percent
of
total
exports
in
2019)
contracted
түүхий
эдийн
үнэ
өссөн,
цар
тахлаас
урьдчилан
сэргийлэх
арга
хэмжээ
суларсан,
Засгийн
газраас
as the COVID-19 shock suppressed global demand.
demand for transportation services (mainly triggered
significantly,
especially
in the
first
quarter
(Q1)indueхэрэгжүүлсэнтэй
to atravel
sharprestrictions
fall холбоотой
in prices
the 1Covid‐19
shock2020
экспортыг
сэргээх
“Ногоон
гарц”
хөтөлбөрийг
Үүний
However,
exports
recovered
quickly,
particularly
by
andasбайв.
limited
truck сацуу
activities),
suppressed
global demand.
exports 2008
recovered
in the third
quarter
(Q3), алт
оны 3 дугаар
улиралдHowever,
алтны экспорт
оноосquickly,
хойш particularly
оргилдоо хүрсэн
нь Төв
банкнаас
the third quarter (Q3), mainly driven by increasing
and reduction in overseas tourism and international
the
gradual
easing
of
COVID‐19
preventive
measures,
and
mainly
driven
by
increasing
commodity
prices,
олборлогч компаниудад хөнгөлөлттэй зээл (эхний 10 сард ДНБ‐ий 0.3 хувьтай тэнцэх) олгосонтой
commodity prices, the gradual easing of COVID-19
consultancy services (particularly
in the mining sector).
1
the government’s
холбоотой. initiative to boost exports through the Green Gate program. In addition, in Q3 2020,
preventive measures, and the government’s initiative
gold exports reached their highest peak since 2008, as the central bank provided soft loans to gold miners
Зураг I.3.
эхний
хагас жилд хүнд
Зураг I.4. Дотоодын эрэлт суларч, түлш шатахууны
(0.3 percent
ofЭкспорт
GDP during
January–October).
цохилтод
орсон
ч хурдацтай
үнэ
буурсан
нь импортод
нөлөөлөв
Figure
I.3. Exports
were
hit hard inсэргэв
H1 but quickly
Figure
I.4. Imports
were also
affected by subdued
Бүтээгдэхүүн,
улирлын
бодит
экспорт Figure
Бүтээгдэхүүн,
үйлчилгээний
улирлын
импорт
Figure
I.3. Exportsүйлчилгээний
were hit hard
in H1 but
quickly
I.4. Imports
were also
subdued
recovered
domestic
demand
andaffected
lower
oilbyбодит
prices
(жилийн өөрчлөлт)
recovered
(жилийн
өөрчлөлт)
domestic
demand
and lower oil prices
Quarterly
real exports
of goods
and services
Quarterly
real exports
of goods
and services
(y/y)(y/y)
19.6%
19.6%
9.0%
9.0%
imports
goods and
services (y/y)
Quarterly realQuarterly
imports real
of goods
andofservices
(y/y)
31.6%
16.3%
8.8%
16.3%
25.2%
8.8%
-5.8%
-5.8%
-2.7%
-2.7%
12.4%
25.2%
31.6%
12.4%
-36.1%
-36.1%
Q1-19 Q1-19
Q2-19 Q2-19
Q3-19 Q3-19
Q4-19 Q4-19
Q1-20 Q1-20
Q2-20 Q2-20
Q3-20 Q3-20
Source: NSO.
ЭхNSO.
сурвалж: ҮСХ.
Source:
1
2
19.9%
19.9%
-17.4%
-2.6% -2.6%
-5.2% -5.2%
-17.4%
Q1-19 Q1-19
Q2-19 Q2-19
Q3-19 Q3-19
Q4-19 Q4-19
Q1-20 Q1-20
Q2-20 Q2-20
Q3-20 Q3-20
Source:
NSO.
Эх
сурвалж:
Source:
NSO. ҮСХ.
The Дотоодын
Green Gate initiative
by theшатахууны
government has
helped
the gradual
recovery
of coal and copper
exports.
эрэлт introduced
суларч, түлш
үнэ
буурснаар
импорт
мэдэгдэхүйц
агшив.
Эрчим хүчний
цэвэр импортлогч улсын хувьд дэлхийн зах 17
зээлд нефтийн үнэ буурсан нь Монгол Улсад ашигтай
байв. Бүтээгдэхүүн, үйлчилгээний бодит импорт 2019 оны эхний 3 улиралд 23.2 хувиар өсөж байсан
бол 2020 оны эхний 3 улиралд жилийн 8 хувиар агшжээ (зураг I.4). Импортын агшилтад үндсэн
хөрөнгийн худалдан авалт багассан (хувийн хөрөнгө оруулалт буурсны илрэл), нефтийн үнэ буурсан,
хэрэглээний барааны импорт цар тахалтай холбоотойгоор (2020 оны цагаан сарыг тэмдэглэхгүй байх
The Green Gate initiative introduced by the government has helped the gradual recovery of coal and copper exports.
шийдвэр гарч жижиглэн худалдаа болон үйлчилгээний бусад салбарт идэвхжил суларсан) агшсан нь
тус тус нөлөөлжээ. Үйлчилгээний импорт мөн ялгаагүй буурсан нь тээврийн үйлчилгээний эрэлт
5
суларсан (зорчих хөдөлгөөн болон ачаа тээвэрт тавьсан хязгаарлалтаас шалтгаалан), гадаад аялал
жуулчлал болон гадаадын зөвлөх үйлчилгээ (ялангуяа уул уурхайн секторт) багассантай холбоотой
юм.
Уул уурхайн салбарын үйлдвэрлэл ялангуяа 2020 оны эхний хагаст огцом буурсан ч хурдацтай
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Mining sector output contracted sharply, especially in
Non-mining output also contracted notably, as the
Imports
Imports
also also
contracted
contracted
significantly
significantly
amidamid
weaker
weaker
domestic
domestic
demand
demand
and and
lower
lower
oil prices.
oil prices.
As aAsneta net
H1 2020, but recovered quickly. In H1 2020, production
services sector was significantly hit by COVID-19importer
importer
of energy,
of energy,
Mongolia
Mongolia
benefited
benefited
fromfrom
declining
declining
global
global
oil prices.
oil prices.
RealReal
imports
imports
of goods
of goods
and services
and services
of coal contracted by 49 percent (y/y), while its volume of
related precautionary measures. After recording
fell by
fell8by
percent
8 percent
(y/y)(y/y)
during
during
January–September
January–September
20202020
compared
compared
to antoexpansion
an expansion
of 23.2
of 23.2
percent
percent
a year
a year
exports contracted by 52.1 percent (y/y).3 Weak demand
growth of 6.7 percent (y/y) in 2019, non-mining GDP
ago ago
(figure
(figure
I.4). I.4).
The The
import
import
compression
compression
is supported
is supported
by, among
by, among
others,
others,
subdued
subdued
purchase
purchase
of capital
of capital
from China and the COVID-19-related precautionary
contracted by 3.7 percent (y/y) in the first nine months
goods
goods
(mostly
(mostly
reflecting
reflecting
lower
lower
private
private
investment),
investment),
lower
lower
oil prices,
oil prices,
and and
reduction
reduction
in imported
in imported
consumer
consumer
measures
of
the
authorities
largely
explain
the
weak
of measures
2020 (figure
I.6).
Thecancellation
services
sector,
mainly
goods
goods
triggered
triggered
by COVID‐19‐related
by COVID‐19‐related
precautionary
precautionary
measures
(for (for
example,
example,
cancellation
of the
of official
thetrade
official
4,5
performance.
Meanwhile,
crude
oil
production
was
and
transportation,
declined
significantly
(by
13
to
celebration
celebration
of the
of 2020
the 2020
lunarlunar
newnew
yearyear
and and
reduced
reduced
economic
economic
activity
activity
in retail
in retail
tradetrade
and and
other
other
services).
services).
down
by
about
70
percent
(y/y)
during
the
same
period.
25
percent),
reflecting
its
strong
link
with
the
mining
Meanwhile,
Meanwhile,
imports
imports
of services
of services
also also
declined
declined
sharply,
sharply,
partly
partly
due due
to weaker
to weaker
demand
demand
for transportation
for transportation
Copper
production
contracted
8 percent
in
H1 2020,
sector.
Mainly
explained
byand
reduced
production
of
services
services
(mainly
(mainly
triggered
triggered
bybytravel
by
travel
restrictions
restrictions
and and
limited
limited
truck
truck
activities),
activities),
and
reduction
reduction
in overseas
in overseas
reflecting
theand
declining
quality
ofconsultancy
copper services
fromservices
the (particularly
Oyu (particularly
textiles,
manufacturing
output contracted by 6.6
tourism
tourism
and
international
international
consultancy
in the
in
mining
the mining
sector).
sector).
Tolgoi mines and lower international prices.6 However,
percent (y/y) in the same period from 9.2 percent
Mining
Mining
sector
sector
output
output
contracted
sharply,
sharply,
especially
especially
in
H1
in 2020,
H1
2020,
but
recovered
recovered
quickly.
quickly.
In H1
In
2020,
H1 2020,
9
the output
contraction
ofcontracted
the mining
sector
decelerated
growth
a year
ago.but
Despite
the
accelerated
execution
production
production
of coal
of coal
contracted
contracted
by 49bypercent
49 percent
(y/y),(y/y),
whilewhile
its volume
its volume
of exports
of exports
contracted
contracted
by 52.1
by 52.1
percent
percent
to 5.23 percent
(y/y) in Q3 (figure I.5). This was mainly
of public investment projects and the resumption of
3
Weak
Weak
demand
demand
fromfrom
China
China
and and
the COVID‐19‐related
the COVID‐19‐related
precautionary
precautionary
measures
measures
of the
of authorities
the authorities
(y/y).(y/y).
driven by strong gold production following
a subsidized housing program by the BoM since April
4,5 4,5 higher
largely
largely
explain
explain
the weak
the weak
performance.
performance.
Meanwhile,
Meanwhile,
crude
crude
oil production
oil production
was was
down
down
by about
by about
70 percent
70 percent
prices, and the Bank of Mongolia (BoM)’s program
2019, the construction sector also contracted by 6.3
(y/y)(y/y)
during
during
the the
samesame
period.
period.
Copper
Copper
production
production
contracted
contracted
by
8
by
percent
8
percent
in
H1
in
2020,
H1
2020,
reflecting
reflecting
the the
to support gold production and exports.7, 8 Moreover,
percent (y/y) in the same period from
6
6expansion (8
declining
declining
quality
quality
of copper
of copper
fromfrom
the the
Oyu Oyu
Tolgoi
Tolgoi
mines
mines
and and
lower
lower
international
international
prices.
prices.
However,
However,
the the
coal production also recovered in the same period
percent) in 2019, with a fall in both residential and
output
output
contraction
contraction
of the
of mining
the mining
sector
sector
decelerated
decelerated
to 5.2
topercent
5.2 percent
(y/y)(y/y)
in Q3in(figure
Q3 (figure
I.5). I.5).
This This
was was
mainly
mainly
supported
by
government’s
efforts
to boost
coal
industrial
(the latter
mainly
due
toto
the to
driven
driven
by strong
by the
strong
gold
gold
production
production
following
following
higher
higher
prices,
prices,
and and
thebuilding
Bank
the Bank
ofactivity
Mongolia
of Mongolia
(BoM)’s
(BoM)’s
program
program
7,8 7,8
exports,
including
through
the
Green
Gate
initiative
slowdown
in
the
development
of
the
Oyu
Tolgoi
mine’s
Moreover,
Moreover,
coal coal
production
production
also also
recovered
recovered
in the
in same
the same
period
period
support
support
goldgold
production
production
and and
exports.
exports.
withsupported
China. by the
underground
project).
In the
contrast,
expansion
in the
supported
by government’s
the government’s
efforts
efforts
to boost
to boost
coal coal
exports,
exports,
including
including
through
through
Green
the Green
GateGate
initiative
initiative
withwith
China.
China.
Figure I.5. Mining output fell sharply in H1, but
Figure
Figure
I.5. Mining
I.5.
Mining
output
output
fell sharply
fell sharply
in H1,
inbut
H1, but
recovered
strongly
Figure I.6. The services sector explained most of
Figure
Figure
I.6.contraction
The
I.6. services
The services
sector
explained
explained
mostmost
of the
of the
the
insector
non-mining
output
contraction
contraction
in non‐mining
in non‐mining
output
output
recovered
recovered
strongly
strongly
Contributions
totomineral
output
(y/y,percentage
percentage
points)
Contributions
non-mineral
output
points)
Contributions
Contributions
to mineral
mineral
output
output
(y/y,
(y/y,
percentage
points)
points) Contributions
Contributions
to non‐mineral
totonon‐mineral
output
output
(y/y, (y/y,
percentage
(y/y,percentage
percentage
points)
points)
Sources:
Sources:
NSO;World
NSO;
World
World
Bank
Bank
staff
estimates.
staff estimates.
Sources:
NSO;
Bank
staff
estimates.
Q3-20
Q3-20
Q2-20
Q2-20
Q1-20
Q1-20
Q4-19
Q4-19
Q3-19
-10% -10%
Agriculture
Agriculture
ServicesServices
Net taxes
Net taxes
Non-mineral
Non-mineral
industries
industries
Non-mining
Non-mining
GDP growth
GDP growth
Q3-20
-5%
Q3-20
Q2-20
-5%
Q2-20
Q1-20
0%
Q1-20
Q4-19
0%
Q4-19
Q3-19
5%
Q3-19
Q2-19
Q3-19
Q2-19
Q2-19
Q1-19
Q1-19
Q4-18
Q1-18
-40% -40%
Gold Gold
Crude oil
Crude oil
Coal Coal
Q4-18
Q3-18
-30% -30%
Others Others
Iron oreIron ore
CopperCopper
Mining Mining
GDP growth
GDP growth
Q3-18
Q2-18
-20% -20%
Q2-18
Q1-18
-10% -10%
5%
Q2-19
Q1-19
0%
Q1-19
Q4-18
0%
Q4-18
Q3-18
10%
10%
Q3-18
Q2-18
10%
10%
Q2-18
Q1-18
20%
Q1-18
20%
Sources:
Sources:
NSO;NSO;
NSO;
World
World
Bank
Bank
staff
staff
estimates
Sources:
World
Bank
staffestimates
estimates.
Non‐mining
Non‐mining
output
output
also also
contracted
contracted
notably,
notably,
as the
as services
the services
sector
sector
was was
significantly
significantly
hit by
hitCOVID‐19‐
by COVID‐19‐
related
related
precautionary
precautionary
measures.
measures.
AfterAfter
recording
recording
growth
growth
of 6.7
of percent
6.7 percent
(y/y)(y/y)
in 2019,
in 2019,
non‐mining
non‐mining
GDPGDP
Coal3 exports
Coal exports
accounted
accounted
for 45for
percent
45 percent
of total
of total
mineral
mineral
exports
exports
in 2019.
in 2019.
As a4 part
As a of
part
theofprecautionary
the precautionary
measures,
measures,
the export
the export
ban during
ban during
February–March
February–March
contributed
contributed
to a sharp
to a sharp
fall infall
mineral
in mineral
output.
output.
5 In 2019,
5 In 2019,
coal production
coal production
and export
and export
grew grew
by 1.9bypercent
1.9 percent
and 2and
percent,
2 percent,
respectively,
respectively,
to reach
to reach
historically
historically
high levels
high levels
(that (that
is, is,
50.8
million
50.8
million
tons
and
tons
36.5
and
million
36.5
million
tons,
tons,
respectively).
respectively).
3
Coal exports accounted for 45 percent of total mineral exports in 2019.
64 The6 copper
Theof copper
export
unit price
unit
price
fell by
fellabout
by about
14.3
percent
14.3 February–March
percent
during
during
the contributed
H1
the2020
H1 2020
following
following
theincollapse
the
collapse
in global
in global
pricesprices
amid amid
the the
As a part
theexport
precautionary
measures,
the
export
ban during
to a sharp
fall
mineral
output.
5
In 2019,
production
and
export
1.9 commodity
percent market.
and 2 market.
percent, respectively, to reach historically high levels (that is, 50.8 million tons and 36.5
impact
impact
ofcoal
theof
COVID‐19
the COVID‐19
shock
shock
ongrew
the
onby
commodity
the
76 The 7copper export unit price fell by about 14.3 percent during the H1 2020 following the collapse in global prices amid the impact of the COVID-19
Gold Gold
production
production
grew grew
by 35by
percent
35 percent
(y/y) (y/y)
in theinfirst
thenine
first months
nine months
of 2020.
of 2020.
the commodity market.
8shock
8on
The Bank
of Mongolia
of Mongolia
has also
hasprovided
also provided
soft loans
soft loans
to gold
to mining
gold mining
companies,
companies,
whichwhich
may have
may have
also contributed
also contributed
to boosting
to boosting
gold gold
7 The Bank
Gold production grew by 35 percent (y/y) in the first nine months of 2020.
8
production.
The production.
Bank of Mongolia has also provided soft loans to gold mining companies, which may have also contributed to boosting gold production.
3
4
The contraction in the textile industry, which represents nearly 14 percent of manufacturing production, is mainly attributed to weakened business
activity, especially in the cashmere industry.
9
19 19
6
contracted
contracted
by 3.7
by 3.7
percent
percent
(y/y)
(y/y)
in the
in the
firstfirst
ninenine
months
months
of 2020
of 2020
(figure
(figure
I.6).I.6).
TheThe
services
services
sector,
sector,
mainly
mainly
trade
trade
andand
transportation,
transportation,
declined
declined
significantly
significantly
(by (by
13 to
13 25
to percent),
25 percent),
reflecting
reflecting
its strong
its strong
linklink
withwith
thethe
ECONOMIC
PERFORMANCE
AND
PROSPECTS
mining
mining
sector.
sector.
Mainly
Mainly
explained
explained
by reduced
by reduced
production
production
of textiles,
of
textiles,
manufacturing
manufacturing
output
output
contracted
contracted
by by
8
8
Despite
Despite
thethe
accelerated
accelerated
6.6 6.6
percent
percent
(y/y)
(y/y)
in the
in the
same
same
period
period
from
from
9.2 9.2
percent
percent
growth
growth
a year
a year
ago.ago.
execution
execution
of public
of public
investment
investment
projects
projects
andand
thethe
resumption
resumption
of aofsubsidized
a subsidized
housing
housing
program
program
by the
by the
BoM
BoM
since
since
April
April
2019,
2019,
the
the
construction
construction
sector
sector
also
also
contracted
contracted
by
6.3
by
6.3
percent
percent
(y/y)
(y/y)
in
the
in
the
same
same
period
period
from
from
agriculture sector accelerated to 11.3 percent during
have also contributed to low inflation as Mongolia is
expansion
expansion
(8 percent)
(8 percent)
in 2019,
in 2019,
withwith
a fall
a fall
in both
in both
residential
residential
andand
industrial
industrial
building
building
activity
activity
(the(the
latter
latter
January–September 2020, up from 8.4 percent in 2019,
a net oil importer. Moreover, the government decision
mainly
mainly
duedue
to the
to the
slowdown
slowdown
in the
in the
development
development
of the
of the
OyuOyu
Tolgoi
Tolgoi
mine’s
mine’s
underground
underground
project).
project).
In In
reflecting relatively favorable weather conditions and
to reduce the price of coal briquettes also significantly
contrast,
contrast,
expansion
expansion
in the
in the
agriculture
agriculture
sector
sector
accelerated
accelerated
to 11.3
to 11.3
percent
percent
during
during
January–September
January–September
2020,
2020,
higher survival rates of livestock. Finally, net taxes
contributed to moderate inflation through end-2020.
up from
up from
8.4 8.4
percent
percent
in 2019,
in 2019,
reflecting
reflecting
relatively
relatively
favorable
favorable
weather
weather
conditions
conditions
andand
higher
higher
survival
survival
rates
rates
contracted
byFinally,
8.4Finally,
percent
(y/y)
amid
subdued
However,
food
pricedomestic
inflation
remained
high
at 8.5
of
livestock.
of livestock.
netnet
taxes
taxes
contracted
contracted
by domestic
8.4
by 8.4
percent
percent
(y/y)
(y/y)
amid
amid
subdued
subdued
domestic
demand
demand
and
and
import
import
demand
and import
compression
(mainly
a sharp
percent
atand
end-2020
(8.3 percentcapital
at capital
end-2019)
amid
compression
compression
(mainly
(mainly
a sharp
a sharp
fall fall
in
imports
in imports
of passenger
offall
passenger
carscars
and
mining‐sector‐related
mining‐sector‐related
goods).
goods).
in imports of passenger cars and mining-sector-related
the lockdowns and panic buying.
capital
goods).
A2.A2.
Inflation
Inflation
moderated
moderated
notably,
notably,
reflecting
reflecting
subdued
subdued
domestic
domestic
demand
demand
and
lower
lower
oilpolicy
prices
oil prices
With
subdued
inflation,
theand
monetary
rate was
Weakening
Weakening
domestic
domestic
demand
demand
largely
largely
contributed
contributed
to moderate
toreduced
moderate
inflation
in 2020.
inlow
2020.
Inflation
Inflation
moderated
moderated
to to
to ainflation
historic
to mitigate
the
economic
A2.
Inflation
moderated
notably,
reflecting
2.3 2.3
percent
percent
in November
in November
2020,
2020,
down
down
from
from
5.2 5.2
percent
percent
in 2019
in 2019
on the
the
on the
back
back
of muted
ofshock.
muted
domestic
domestic
demand
demand
impact
of
COVID-19
Reflecting
weaker
subdued
domestic
demand
and
lower andand
pressures
pressures
following
following
plummeting
plummeting
private
private
investment
investment
decelerating
decelerating
private
private
consumption
consumption
growth
growth
(figure
(figure
domestic
demand,
core
inflation moderated
to
0.2
oilI.7).
prices
I.7).
Supply
Supply
sideside
factors,
factors,
suchsuch
as lower
as lower
global
global
oil prices,
oil prices,
have
have
also
also
contributed
contributed
to
low
to
low
inflation
inflation
as
Mongolia
as
Mongolia
percent at end-2020 from 4.2 percent (y/y) at endis aisnet
a net
oil importer.
oil importer.
Moreover,
Moreover,
thethe
government
government
decision
decision
reduce
to reduce
the
price
price
of
coal
of coal
briquettes
briquettes
alsoalso
2019to
(figure
I.8).the
Moreover,
domestic
credit
contracted
Weakening domestic demand largely contributed to
significantly
significantly
contributed
contributed
to moderate
to moderate
inflation
inflation
through
through
end‐2020.
end‐2020.
However,
However,
food
food
price
price
inflation
inflation
remained
remained
in March as banks’ risk aversion toward new loans
moderate inflation in 2020. Inflation moderated to
highhigh
at 8.5
at 8.5
percent
percent
at end‐2020
at end‐2020
(8.3(8.3
percent
percent
at end‐2019)
at end‐2019)
amid
amid
thethe
lockdowns
lockdowns
andand
panic
panic
buying.
buying.
increased
amid
heightened
market
uncertainty
2.3 percent in December 2020, down from 5.2 percent
triggered
by
the
COVID-19
shock.
This
also
contributed
With
subdued
subdued
inflation,
inflation,
the
monetary
monetary
policy
policy
raterate
waswas
reduced
reduced
to ato
historic
a historic
lowlow
to mitigate
to mitigate
thethe
economic
economic
in With
2019
on the
back
ofthemuted
domestic
demand
to the demand,
falling
core
inflation
trend.
The authorities
impact
impact
of following
the
of the
COVID‐19
COVID‐19
shock.
shock.
Reflecting
Reflecting
weaker
weaker
domestic
domestic
demand,
corecore
inflation
inflation
moderated
moderated
to 0.2
to 0.2
pressures
plummeting
private
investment
consequently
cut
the
policy
rate
by
a
total
of
500
basis
percent
percent
at
end‐2020
at
end‐2020
from
from
4.2
4.2
percent
percent
(y/y)
(y/y)
at
end‐2019
at
end‐2019
(figure
(figure
I.8).
I.8).
Moreover,
Moreover,
domestic
domestic
credit
credit
contracted
contracted
and decelerating private consumption growth (figure
in
March
in
March
as
banks’
as
banks’
risk
risk
aversion
aversion
toward
toward
new
new
loans
loans
increased
increased
amid
amid
heightened
heightened
market
market
uncertainty
uncertainty
points
in
2020
to
6
percent,
a
historic
low.
I.7). Supply side factors, such as lower global oil prices,
triggered
triggered
by the
by the
COVID‐19
COVID‐19
shock.
shock.
ThisThis
alsoalso
contributed
contributed
to the
to the
falling
falling
corecore
inflation
inflation
trend.
trend.
TheThe
authorities
authorities
of 500
of 500
basis
basis
points
points
in 2020
in 2020
to 6topercent,
6 percent,
a historic
a historic
low.low.
consequently
consequently
cut cut
thethe
policy
policy
raterate
by abytotal
a total
Figure I.7. Inflation moderated amid lower oil
Figure I.8. …and compounded by the contraction
Figure
Figure
I.7.
Inflation
Inflation
moderated
moderated
amid
amid
lower
lower
oil prices
oil pricesFigure
Figure
I.8.
…and
…and
compounded
compounded
by the
by the
contraction
contraction
of of
prices
andI.7.
subdued
domestic
demand…
ofI.8.
domestic
credit
domestic
domestic
credit
credit
y/y change
y/y change
y/y change
10% 10%
10% 10%
8%
8%
6%
6%
4%
4%
2%
2%
0%
0%
0%
Fuel price:
Fuel price:
LHS LHS
-10% -10%
Domestic
Domestic
demand:
demand:
LHS LHS
-20% -20%
Q3-20
Q2-20
Q1-20
Q2-20
Q1-20
Q4-19
Q3-19
Q4-19
Q3-19
Q2-19
Q1-19
Q2-19
Q4-18
Q1-19
Q4-18
Q3-18
Q2-18
Q1-18
Q1-18
-30% -30%
Headline
Headline
inflation
inflation
(UB): RHS
(UB): RHS
Q2-18
Q3-18
0%
Core inflation
Core inflation
(y/y): RHS
(y/y): RHS
CreditCredit
growth
growth
(y/y): LHS
(y/y): LHS
PolicyPolicy
rate: RHS
rate: RHS
22% 22%
12% 12%
2%
2%
-8% -8%
12% 12%
10% 10%
Oct-18
Aug-18
Dec-18
Oct-18
Feb-19
Dec-18
Apr-19
Feb-19
Jun-19
Apr-19
Aug-19
Jun-19
Oct-19
Aug-19
Dec-19
Oct-19
Feb-20
Dec-19
Apr-20
Feb-20
Jun-20
Apr-20
Aug-20
Jun-20
Oct-20
Aug-20
Dec-20
Oct-20
20% 20%
Aug-18
12% 12%
Q3-20
30% 30%
y/y change
8%
8%
6%
6%
4%
4%
2%
2%
0%
0%
Dec-20
andand
subdued
subdued
domestic
domestic
demand…
demand…
y/y change
y/y change
Sources:
Sources:
NSONSO
Bulletin;
Bulletin;
World
World
BankBank
staffstaff
estimates.
estimates.
Sources:
Sources:
BoM;
BoM;
World
World
BankBank
staffstaff
estimates.
estimates.
Sources: NSO Bulletin; World Bank staff estimates.
Sources: BoM; World Bank staff estimates.
Note:
Note:
Domestic
Domestic
demand
demand
is defined
is defined
as the
as sum
the sum
of final
of final
Note:
Note:
RHS RHS
= right‐hand
=right-hand
right‐hand
side;
side;
LHS
LHS
= =left‐hand
= left‐hand
side.side.
Note:
RHS
=
side;
LHS
left-hand
side.
Note: Domestic demand is defined as the sum of final consumption
consumption
consumption
and and
investment
investment
fromfrom
national
national
accounts
accounts
data.data.
and investment from national accounts data. RHS = right-hand side;
RHS
=left-hand
right‐hand
= right‐hand
LHS LHS
= left‐hand
= left‐hand
side.side.
LHS =RHS
side.side;side;
8 The
8 The
contraction
contraction
in the
in textile
the textile
industry,
industry,
which
which
represents
represents
nearly
nearly
14 percent
14 percent
of manufacturing
of manufacturing
production,
production,
is mainly
is mainly
attributed
attributed
to to
weakened
weakened
business
business
activity,
activity,
especially
especially
in the
in cashmere
the cashmere
industry.
industry.
19 19
7
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
require relatively lower skilled labor compared to
A3. The COVID-19 shock affected the
sectors such as information technology (IT), finance,
structure and conditions of the labor
education, and health, and therefore workers in these
A3.
The COVID‐19 shock affected the structure and conditions of the labor market
market
fields had lower job security and limited opportunity
A3.
The
COVID‐19
shock
thelosses
structure
and
conditions
oflabor
the
labor
market
The
COVID‐19
pandemic
has
led
ininseveral
sectors
force participation
rate (LFPR)
to work
from and
home.
In contrast,
during the pandemic,
The
COVID-19
pandemic
hasaffected
led to
tojob
job
losses
marked
the
lowest
level
in
a
decade.
According
to
official
NSO
data,
at
end‐September
2020,
total
the
health
sector
saw
a
substantial
rise
in
employment.
several
sectors pandemic
and laborhas
force
The
COVID‐19
led participation
to job losses rate
in several sectors and labor force participation rate (LFPR)
Furthermore,
employment
in the
trade and
IT sectors
employment
bylevel
20,400
(1.7 percent,
y/y) to
relative
a year
ago.atWhile
sizable
COVID‐19‐related
(LFPR) marked
the lowest
decade.
According
marked
theincreased
lowest
level
in in
a adecade.
According
officialtoNSO
data,
end‐September
2020,
total
increased
during
this
period,
partly
explained
by the
relief
measures
to
firms
overall
might
have
contributed
to
this
outcome,
the
difference
in
level
of skills
to
official
NSO
data,
at
end-September
2020,
total
employment increased by 20,400 (1.7 percent, y/y) relative to a year ago. While sizable COVID‐19‐related
9
digital
transformation
of
economic
activities,
including
required
for different
sectors
may
explain
ups and downs
employment
across sectors.
employment
increased
by overall
20,400
(1.7
percent,
y/y)
relief
measures
to firms
might
havethe
contributed
to thisin
outcome,
the difference
in level In
of fact,
skills the
11
9a year‐on‐year
trade.
In
the
meantime,
the
labor
force
(employment
mining,
construction,
manufacturing,
agriculture,
and
entertainment
sectors
all
posted
relative
to
a
year
ago.
While
sizable
COVID-19required for different sectors may explain the ups and downs in employment across sectors. In fact, the
+(figure
unemployment)
decreased
by posted
1 percent
the same
relatedinrelief
to firmsasoverall
might have
decline
theirmeasures
employment
of September
2020
I.9) amid
the lockdowns
and
precautionary
mining,
construction,
manufacturing,
agriculture,
and
entertainment
sectors
all
a in
year‐on‐year
period,
and
the
number
of
those
out
of
the
labor
force
contributed
to
this
outcome, the
difference
in
level
of also
decline
in
employment
as
of September
2020
(figure
I.9) amidby
thethe
lockdowns
precautionary
measures
bytheir
the
authorities.
Moreover,
this
could
be explained
fact that and
the industrial
sectors
increased
by
4
percent.
This
indicates
that
finding
a
skills
required
for
different
sectors
may
explain
the
measures
by
the
authorities.
Moreover,
this
could
also
be
explained
by
the
fact
that
the
industrial
sectors
require relatively lower skilled labor compared to sectors such as information technology (IT), finance,
10
job
has
become
more
difficult
and
that
some
of
the
ups and downs
employment
across
sectors.
In fact,
require
relatively
lower and
skilled
labor
compared
to in
sectors
as information
(IT),and
finance,
education,
andinhealth,
therefore
workers
thesesuch
fields
had lower technology
job security
limited
unemployed
moved
out
of
the
labor
force.
the
mining,
construction,
manufacturing,
agriculture,
education,
and
health,
and
therefore
workers
in
these
fields
had
lower
job
security
and
limited
opportunity to work from home. In contrast, during the pandemic, the health sector saw a substantial rise
to work
from all
home.
In contrast,
the pandemic,
the health
sector saw a substantial
rise
and
entertainment
sectors
posted
a year-on-year
and IT sectors
this
in opportunity
employment.
Furthermore,
employment
induring
the trade
Unemployment
ratesincreased
moderatelyduring
increased
in period,
Q3 2020.partly
10
and IT sectors
increased
during
period,
partly the
in
employment.
Furthermore,
the tradeactivities,
decline
inbytheir
as employment
of September
2020
Inthis
the
meantime,
explained
theemployment
digital transformation
of in
economic
including
Despite the sharp
outputtrade.
contraction,
unemployment
10
In
the
meantime,
the
explained
by
the
digital
transformation
of
economic
activities,
including
trade.
(figure
I.9)
amid
the
lockdowns
and
precautionary
labor force (employment + unemployment) decreased
by 1were
percent
in thestable
same in
period,
and the
number
rates
relatively
H1 2020,
partly
labor
force
(employment
+
unemployment)
decreased
by
1
percent
in
the
same
period,
and
the
number
byof
thethe
authorities.
Moreover,
this could
of measures
those out
labor force
increased
by 4also
percent.
This indicates
that finding
job hasmeasures.
become12 more
supported
by the sizable
incomeasupport
of
out of
forcethe
increased
4 percent. This indicates that finding a job has become more
be those
explained
bythe
thelabor
fact that
industrialbysectors
difficult and that some of the unemployed moved out of the labor force.
difficult and that some of the unemployed moved out of the labor force.
Figure
TheCOVID‐19
COVID-19pandemic
pandemic has
FigureI.10.
I.10.…thereby
…thereby reversing
of of
Figure
I.9.I.9.The
has put
putsome
some
Figure
reversingdeclining
decliningtrends
trends
Figure I.9. The COVID‐19 pandemic has put some
Figure I.10. …thereby reversing declining trends of
jobs
at
risk...
theunemployment
unemployment rate
jobs
at
risk...
the
rate
jobs at risk...
the unemployment rate
Change
inin
employment
(Q3
2019,
y/y percent
percent
Change
in employment
(Q3 2020–Q3
Change
employment
(Q32020–Q3
2020–Q3
2019,2019,
y/y
change)
y/y percent change)
change)
Total
Total
Health
Health
Finance
Finance
InfoInfo
& communication
& communication
Education
Education
Trade
Trade
Transportation
Transportation
Manufacturing
Manufacturing
-1%
-1%
Construction
Construction
-2%
-2%
Agriculture
-2%
Agriculture
-2%
Public
admin/defense
-5%
Public
admin/defense
-5%
Mining
-5%
Mining
-5%
Water
& utilities
-6%
Water
& utilities
-6%
Administrative
-14%
Administrative
-14%
Household activities
-18%
Household
activities
-18%
Hospitality
-25%
Hospitality
-25%
Science
-34%
Science
-34%
Electricity
-35%
Electricity
-35%
Entertainment
-42%
Entertainment
-42%
1.7%
1.7%
17%
17%
11%
11%
10%
10%
6%
6%
Sources: NSO Bulletin; World Bank staff estimates.
Sources:
NSOBulletin;
Bulletin;
World
staff estimates.
Sources: NSO
World
Bank Bank
staff estimates.
45%
45%
38%
38%
Unemployment
rate
gender
Unemployment
rate by gender
Unemployment
rate
byby
gender
15%
15%
Unemployment rate
Unemployment rate
MaleMale
12%
12%
Female
Female
9%
9%
6%
6%
3%
3%
Q1-19
Q1-19
Q2-19
Q2-19
Q3-19
Q3-19
Q4-19
Q1-20
Q4-19
Q2-20
Q1-20
Q3-20
Q2-20
Q3-20
Sources: NSO Bulletin; World Bank staff estimates.
Sources:
NSO
Bulletin;
Bank
staff estimates.
Sources: NSO
Bulletin;
WorldWorld
Bank staff
estimates.
Unemployment rates moderately increased in Q3 2020. Despite the sharp output contraction,
Unemployment rates moderately increased in Q3 2020. Despite the sharp output contraction,
unemployment rates were relatively stable in H1 2020, partly supported by the sizable income support
unemployment
rates were relatively stable in H1 2020, partly supported by the sizable income support
11
However, unemployment moderately increased to 7.3 percent in Q3, up from 6.6 in H1 (figure
measures.
11
However,
unemployment
increased
7.3 percent
in Q3,
up from
6.6 in H1
measures.
12
I.10).
The rise in unemployment
wasmoderately
faster for men
than fortowomen,
as more
women
dropped
out(figure
of
12
I.10).
The
rise
in
unemployment
was
faster
for
men
than
for
women,
as
more
women
dropped
out
of
the labor force, thus reducing the number of women actively seeking jobs.
the labor force, thus reducing the number of women actively seeking jobs.
Measures include exemptions on tax, social security contributions, and use of the unemployment insurance fund to support firms that did not lay off
workers.
11
However, according to the latest Household Response Phone Survey by NSO and World Bank, the strict lockdown since mid-November 2020 may have
caused significant disruptions of employment in the private sectors (see Part II for details).
912 Measures include exemptions on tax, social security contributions, and use of the unemployment insurance fund to support
Measures include exemptions on tax, social security contributions, and use of the unemployment insurance fund to support firms that did not lay off
9 firms
workers.
that include
did not lay
off workers.
Measures
exemptions
on tax, social security contributions, and use of the unemployment insurance fund to support
10
10
However, according to the latest Household Response Phone Survey by NSO and World Bank, the strict lockdown since mid‐
firms
8 that did not lay off workers.
10 November 2020 may have caused significant disruptions of employment in the private sectors (see Part II for details).
However, according to the latest Household Response Phone Survey by NSO and World Bank, the strict lockdown since mid‐
11 Measures include exemptions on tax, social security contributions, and use of the unemployment insurance fund to support
November
2020 may have caused significant disruptions of employment in the private sectors (see Part II for details).
11 firms that did not lay off workers.
Measures
include exemptions on tax, social security contributions, and use of the unemployment insurance fund to support
12
were 92,600 unemployed people in September, up from 83,700 people in H1 2020.
firmsThere
that did
not lay off workers.
12
There were 92,600 unemployed people in September, up from 83,700 people in H1 2020.
ECONOMIC PERFORMANCE AND PROSPECTS
However, unemployment moderately increased to 7.3
percent in Q3, up from 6.6 in H1 (figure I.10).13 The rise
in unemployment was faster for men than for women,
as more women dropped out of the labor force, thus
reducing the number of women actively seeking jobs.
childcare responsibilities. This is more relevant to
women, who traditionally bear the responsibility of
caregiver. Also, the generous increase of social welfare
benefits coupled with other relief measures increased
the financial means of eligible households and hence
may
have
reduced impact
the need the
to look
for employment
Generous
income
support
islikely
likely
tohave
have
contributedto
tothe
the
moderate
pandemic
onlabor
labor
Generous
income
support
contributed
moderate
impact ofofthe
pandemic
on
Generous
income
support
is islikely
totohave
contributed
(figure
I.11).
Still,
family
support
remains
the
main
market
conditions
(see
Part
II
for
details).
A
moderate
rise
in
unemployment
and
shrinking
labor
force
market
conditionsimpact
(see Part
II for
details). on
A moderate
rise in unemployment and shrinking labor force
to the moderate
of the
pandemic
labor
source
of
income
assistance
for
people
currently
participationduring
duringtimes
times ofsevere
severeeconomic
economiccrisis
crisis oftenreflect
reflectthe
thefact
factthat
thatpeople
peoplebelieve
believeititwould
wouldbeout
be
participation
market conditions
(see Part of
II for details).
A moderate often
of
work.
In
2019,
about
85
percent
of
the
unemployed
hardertotofind
findemployment
employmentand
andthey
theystop
stoplooking
lookingfor
forjobs.
jobs.With
WithCOVID‐19
COVID‐19spreading
spreadingsosoeasily,
easily,people
peoplemay
may
harder
rise in unemployment and shrinking labor force
indicated
thatthe
financial
support
from
family members
havestopped
stoppedlooking
lookingfor
fora ajob
jobtotoreduce
reducethe
therisk
riskofofcontracting
contracting
the
virus.Closing
Closingkindergartens
kindergartens
and
have
virus.
and
participation during times of severe economic crisis
was
their
main
source
of
income.
This
share
declined
schools
may
have
also
discouraged
unemployed
parents
from
looking
for
a
job
due
to
increased
household
schools may have also discouraged unemployed parents from looking for a job due to increased household
often reflect the fact that people believe it would be
in Q2 2020
totraditionally
80 percent,bear
while
about
14 percent
of
andchildcare
childcareresponsibilities.
responsibilities.This
Thisisismore
morerelevant
relevanttotowomen,
women,
whotraditionally
bear
the
responsibility
and
who
the
responsibility
ofof
harder
to
find
employment
and
they
stop
looking
for
caregiver.Also,
Also,the
thegenerous
generousincrease
increaseofofsocial
socialwelfare
welfare
benefitscoupled
coupled
with
other
reliefmeasures
measures
the benefits
unemployed
reported
that
they mainly
rely
on cash
caregiver.
with
other
relief
jobs.
With the
COVID-19
spreading
easily,
people
may and
increased
thefinancial
financial
meansso
eligible
households
and
hence
may
have
reduced
theneed
need
lookfor
for
increased
means
ofofeligible
households
hence
may
have
reduced
the
toto
look
transfers
and
social
welfare
benefits
(figure
I.12).
have
stopped (figure
looking
for
aStill,
job
reduce
the risk
of
employment
(figureI.11).
I.11).
Still,to
family
support
remains
themain
mainsource
sourceofofincome
incomeassistance
assistancefor
forpeople
people
employment
family
support
remains
the
contracting
theofvirus.
Closing
kindergartens
and
schools
currentlyout
out
ofwork.
work.
2019,
about8585percent
percent
theunemployed
unemployedindicated
indicatedthat
thatfinancial
financialsupport
supportfrom
from
currently
InIn2019,
about
ofofthe
may
have
also
discouraged
unemployed
parents
from
family
members
was
their
main
source
of
income.
This
share
declined
in
Q2
2020
to
80
percent,
while
family members was their main source of income. This share declined in Q2 2020 to 80 percent, while
looking
for
a job ofdue
tounemployed
increased household
and
percent
ofthe
the
unemployed
reportedthat
thatthey
theymainly
mainlyrely
relyononcash
cashtransfers
transfersand
andsocial
socialwelfare
welfare
about1414
percent
reported
about
benefits(figure
(figureI.12).
I.12).
benefits
Figure I.11. Relevance of cash transfers for people
Figure I.12. For unemployed, main source of
FigureI.11.
I.11.Relevance
Relevanceofofcash
cashtransfers
transfersfor
forpeople
people
FigureI.12.
I.12.For
Forunemployed,
unemployed,main
mainsource
sourceofofincome
income
Figure
Figure
currently out of work increased in H1 2020
income support shifted in Q2 2020
currentlyout
outofofwork
workincreased
increasedininH1
H12020
2020
supportshifted
shiftedininQ2
Q22020
2020
currently
support
Shareofofpeople
people
reporting
cash
benefits/social
welfare
Share
reporting
cash
benefits/social
welfare
asas
Share
people
reporting
cash
benefits/social
welfare
as main
sourcesupport
of
income support
mainsource
sourceofofincome
income
support
main
15%
15%
Unemployed
Unemployed
Y/ychange
change
main
source
income
support
for
Y/y
ininmain
source
ofofincome
support
for
Y/y change
in main
source
of
income
support
for unemployed
people
unemployedpeople
people
unemployed
Out
labor
force
Out
of of
labor
force
13%
13%
4 4
Cash
benefits/social
welfare
Cash
benefits/social
welfare
2 2
9%9%
0 0
7%7%
-2 -2
-4 -4
5%5%
3%3%
Family
support
Family
support
Percentage points
Percentage points
11%
11%
6 6
Q1-19
Q1-19
Q2-19
Q2-19
Q3-19
Q3-19
Q4-19
Q4-19
Q1-20
Q1-20
-6 -6
Q2-20
Q2-20
Q1Q1
Q2Q2
Sources:NSO
NSO(LFS
(LFS2019,
2019,2020);
2020);World
WorldBank
Bankstaff
staffestimates.
estimates. Sources:
Sources:NSO
NSO(LFS
(LFS2019,
2019,2020);
2020);World
WorldBank
Bankstaff
staffestimates.
estimates.
Sources:
Sources: NSO (LFS 2019, 2020); World Bank staff estimates.
Sources: NSO (LFS 2019, 2020); World Bank staff estimates.
A4.The
Thebudget
budgetdeficit
deficitwidened
widenedsharply
sharplyinin2020
2020but
butisisexpected
expectedtotonarrow
narrowinin2021
2021
A4.
Thedecline
declineinineconomic
economicactivity
activityand
andforgone
forgonerevenue
revenuelinked
linkedtotoselected
selectedCOVID‐19
COVID‐19relief
reliefmeasures
measuresled
led
The
largeoverall
overallrevenue
revenueshortfall
shortfallinin2020.
2020.Total
Totalrevenue
revenuedeclined
declinedbyby1313percent
percent(y/y)
(y/y)inin2020,
2020,reflecting
reflecting
totoa alarge
1313
weakermineral
mineralrevenue,
revenue,subdued
subduedconsumption,
consumption,income
incomelosses,
losses,and
andtax
taxrelief
reliefmeasures
measures(figure
(figureI.13).
I.13).
weaker
Taxrevenue
revenuefell
fellbyby12.8
12.8percent
percent(y/y),
(y/y),while
whilenon‐tax
non‐taxrevenue
revenuecontracted
contractedbyby12.6
12.6percent
percent(y/y).
(y/y).Notably,
Notably,
Tax
the
corporate
income
tax,
social
security
contributions,
and
the
value‐added
tax,
which
together
the corporate income tax, social security contributions, and the value‐added tax, which together
accountedfor
for6161percent
percentofofoverall
overalltax
taxrevenue,
revenue,contracted
contractedbyby15.8
15.8percent
percent(y/y),
(y/y),19.6
19.6percent,
percent,and
and11.2
11.2
accounted
percent,respectively,
respectively,amid
amidthe
theCOVID‐19‐related
COVID‐19‐relatedrelief
reliefmeasures
measuresand
andthe
thefall
fallininmineral
mineralsector
sectorrevenue.
revenue.
percent,
Thepersonal
personalincome
incometax
taxfell
fellbyby7.2
7.2percent
percent(y/y),
(y/y),reflecting
reflectingtax
taxrelief
reliefand
andincome
incomelosses
lossesamid
amidthe
theCOVID‐
COVID‐
The
19‐relatedprecautionary
precautionarymeasures
measuresand
andmoderate
moderatelabor
labormarket
marketpressures.
pressures.Excise
Exciseand
andcustoms
customsduties
dutiesalso
also
19‐related
declined.
In
fact,
as
the
revenue
shortfall
had
already
reached
3.9
percent
of
projected
2020
GDP
by
July
declined. In fact, as the revenue shortfall had already reached 3.9 percent of projected 2020 GDP by July
2020,a aseries
seriesofofrevenue‐enhancing
revenue‐enhancingmeasures
measures(for
(forexample,
example,collection
collectionofoftax
taxarrears,
arrears,and
andtax
taxprepayment
prepayment
2020,
There were 92,600 unemployed people in September, up from 83,700 people in H1 2020.
frommajor
majorstate‐owned
state‐ownedenterprises)
enterprises)were
weresanctioned
sanctionedunder
underthe
the2020
2020supplementary
supplementarybudget.
budget.
from
13
9
fact,the
therevenue
revenueshortfall
shortfallhad
hadalready
alreadyreached
reached3.9
3.9percent
percentofofprojected
projected2020
2020GDP
GDPbybyJuly
July2020
2020when
whenthe
theauthorities
authoritieswere
were
InInfact,
consideringthe
the2020
2020supplementary
supplementarybudget.
budget.
considering
13 13
21
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
A4. The budget deficit widened sharply in
2020 but is expected to narrow in 2021
duties also declined. In fact, as the revenue shortfall had
already reached 3.9 percent of projected 2020 GDP by
July 2020, a series of revenue-enhancing measures (for
example, collection of tax arrears, and tax prepayment
from major state-owned enterprises) were sanctioned
under the 2020 supplementary budget.
The decline in economic activity and forgone revenue
linked to selected COVID-19 relief measures led to a
large overall revenue shortfall in 2020. Total revenue
declined by 13 percent (y/y) in 2020, reflecting weaker
mineral revenue, subdued consumption, income losses,
and tax relief measures (figure I.13).14 Tax revenue fell
by 12.8 percent (y/y), while non-tax revenue contracted
by 12.6 percent (y/y). Notably, the corporate income tax,
social security contributions, and the value-added tax,
which together accounted for 61 percent of overall tax
revenue, contracted by 15.8 percent (y/y), 19.6 percent,
and 11.2 percent, respectively, amid the COVID-19related relief measures and the fall in mineral sector
revenue. The personal income tax fell by 7.2 percent
(y/y), reflecting tax relief and income losses amid
the COVID-19-related precautionary measures and
moderate labor market pressures. Excise and customs
Meanwhile, measures to minimize the economic and
social impact of the COVID-19 crisis drove a surge in
spending. Total budget spending rose by 22.1 percent
(y/y) in 2020 following 24 percent growth in 2019
(figure I.14). Social protection and welfare spending
increased by 128.7 percent (y/y) in 2020 due to crisis
response measures (mainly the sharp increase in
benefits of the Child Money Program) (see box I.2).
Health spending increased by 27 percent (y/y) in the
same period. Meantime, capital spending execution
was stronger than in the previous years (8.3 percent),
reflecting the government’s efforts to support the
economy by boosting domestic demand.15
Figure
Figure
I.13.
Government
Government
revenue
revenue
has
declined
has
declined
across
acrossFigure
Figure
I.14. I.14.
…while
government
government
spending
spending
soared
soared driven
Figure
I.13.I.13.
Government
revenue
has
declined
Figure
I.14.…while
…while
government
soared
all
categories…
all
categories…
driven
driven
by
social
by
social
welfare
welfare
spending
spending
and
public
and
public
across all categories…
by social welfare spending and public investment
investment
investment
Budget
Budget
Budget
revenue,
revenue,
y/y
change
y/yrevenue,
change y/y change
Direct mineral
Direct mineral
revenuerevenue
CIT
Excise &Excise
Custom
& Custom
Other taxes
Other taxes
PIT
PIT
VAT
Non-Tax
Non-Tax
revenuerevenue
40%
Budget
spending, y/y change
Budget
Budget
spending,
spending,
y/y change
y/y change
34.2% 34.2%
40%
CIT
VAT
20%
InterestInterest
payment
payment
Sub & Transfers
Sub & Transfers
Capex Capex
Net Lending
Net Lending
Wages Wages
Total spending
Total spending
Total revenue
Total revenue
43.3% 43.3%
40%
27.1% 27.1%
Goods &
Goods
Services
& Services
40%
19.5% 19.5%
20%
23.9% 23.9%22.1% 22.1%
20%
20%
2.7%
0%
0%
-2.9% -2.9%
-20% -20%
2015
0%
-13.0% -13.0%
-2.1% -2.1%
2015 2016
2016 2017
2017 2018
2018 2019
2.7%
0%
-5.3% -5.3%
-20% -20%
20192020e 2020e
2015
2015 2016
-5.9% -5.9%
2016 2017
2017 2018
2018 2019
20192020e 2020e
Sources:
Sources:
MoF;World
MoF;
World
World
Bank
staff
estimates.
staff estimates.
Sources:
Sources:
MoF;MoF;
MoF;
World
World
Bank
Bank
staff
estimates.
staff
estimates.
Sources:
MoF;
Bank
staffBank
estimates.
Sources:
World
Bank
staff
estimates.
Note:
CIT==corporate
CIT
corporate
= corporate
income
income
tax;
tax;
= PIT
personal
=income
personal
income
tax;
Note: Note:
CIT
income
tax;
PIT =PIT
personal
tax; income
VAT
= tax;
VAT
=VAT
value‐added
= value‐added
tax. tax.
value-added
tax.
Meanwhile,
Meanwhile,
measures
measures
to minimize
to minimize
the economic
the economic
and and
social
social
impact
impact
of the
of COVID‐19
the COVID‐19
crisiscrisis
drove
drove
a surge
a surge
in spending.
in spending.
TotalTotal
budget
budget
spending
spending
roserose
by 22.1
by 22.1
percent
percent
(y/y)(y/y)
in 2020
in 2020
following
following
24 percent
24 percent
growth
growth
in 2019
in 2019
(figure
(figure
I.14).I.14).
Social
Social
protection
protection
and welfare
and welfare
spending
spending
increased
increased
by 128.7
by 128.7
percent
percent
(y/y)(y/y)
in 2020
in 2020
due due
to crisis
to crisis
response
response
measures
measures
(mainly
(mainly
the sharp
the sharp
increase
increase
in benefits
in benefits
of the
of Child
the Child
Money
Money
Program)
Program)
(see (see
box box
I.2). I.2).
Health
Health
spending
spending
increased
increased
by 27bypercent
27 percent
(y/y)(y/y)
in the
in same
the same
period.
period.
Meantime,
Meantime,
capital
capital
spending
spending
execution
execution
was was
stronger
stronger
thanthan
in the
in previous
the previous
yearsyears
(8.3 (8.3
percent),
percent),
reflecting
reflecting
the government’s
the government’s
efforts
efforts
to support
to support
the the
14
14 of projected 2020 GDP by July 2020 when the authorities were considering the 2020
In fact,
theby
revenue
had domestic
alreadydemand.
reached
3.914percent
economy
economy
boosting
by shortfall
boosting
domestic
demand.
supplementary budget.
15
In fact, the increased social transfers and higher health spending were partly compensated by government capital expenditure cuts worth 0.6
percentage
points
of deficit
GDPincreased
in theincreased
2020 supplementary
budget.
The
The
fiscal
fiscal
deficit
significantly
significantly
owing
owing
to revenue
to revenue
losses
losses
and and
spending
spending
needs
needs
to fight
to fight
the the
(figures
(figures
I.15 I.15
pandemic.
pandemic.
The budget
The budget
deficit
deficit
reached
reached
9.5 percent
9.5 percent
of GDP
of GDP
in 2020,
in 2020,
its highest
its highest
levellevel
sincesince
20162016
15
15
10 and
and
I.16).I.16).
The
three
The three
yearsyears
of fiscal
of fiscal
consolidation
consolidation
that that
helped
helped
to rebuild
to rebuild
sizable
sizable
buffers
buffers
also also
contributed
contributed
16
In 16
contrast
In contrast
to to
to the
togovernment’s
the government’s
efforts
efforts
to cope
to cope
withwith
the COVID‐19
the COVID‐19
shock
shock
in the
inearly
the early
months
months
of 2020.
of 2020.
whatwhat
was was
observed
observed
during
during
the 2015–16
the 2015–16
economic
economic
slowdown,
slowdown,
the government
the government
had had
no pressing
no pressing
needneed
to to
borrow
borrow
fromfrom
either
either
domestic
domestic
or international
or international
markets
markets
in the
in first
the first
five five
months
months
of 2020.
of 2020.
However,
However,
sincesince
JuneJune
2020,
2020,
government
government
requests
requests
for donor
for donor
financing
financing
havehave
intensified,
intensified,
including
including
additional
additional
budget
budget
support
support
ECONOMIC PERFORMANCE AND PROSPECTS
The fiscal deficit increased significantly owing to
revenue losses and spending needs to fight the
pandemic. The budget deficit reached 9.5 percent of
GDP in 2020, its highest level since 2016 (figures I.15
and I.16).16 The three years of fiscal consolidation that
helped to rebuild sizable buffers also contributed to the
government’s efforts to cope with the COVID-19 shock
in the early months of 2020.17 In contrast to what was
observed during the 2015 - 16 economic slowdown,
the government had no pressing need to borrow from
either domestic or international markets in the first five
months of 2020. However, since June 2020, government
requests for donor financing have intensified, including
additional budget support totaling US$550 million
from the International Monetary Fund (IMF), Asian
Development Bank (ADB), Asian Infrastructure
Investment Bank, and Japan, disbursed in H2 2020.
plans to bring back the fiscal deficit within 2 percent of
GDP (figure I.20). A projected rebound in revenues (3.4
percentage points of GDP) and substantial spending
cuts (4.6 percentage points of GDP) are estimated to
support the sharp improvement in the fiscal stance in
2021. The underlying assumptions of the 2021 budget
include, among others, strong economic recovery (7.2
percent in 2021), modernization/renovation of customs
and border points, digitalization of tax administration,
improved governance of state-owned enterprises, and
introduction of a new tax on livestock headcount (see
box I.3). It also considers a reduction of total spending
mainly reflecting the expiry of major COVID-19-related
relief/stimulus measures (except the Child Money
Program) and a moderate reduction of the capital
budget relative to the 2020 supplementary budget.
In addition, a substantial increase of accumulation
in the fiscal stabilization and future heritage funds,
similar to their levels in 2019, is also estimated under
the 2021 budget. Finally, after an increase in 2020, the
government expects that the debt-to-GDP ratio will
resume its downward trajectory in 2021- 22 based on
these fiscal policy assumptions.
After a surging deficit in 2020, the 2021 budget
plans to return to fiscal consolidation. The 2020
supplementary budget exhibited a widening of the
overall fiscal deficit from an initial target of 2.4 percent
of GDP to 9.9 percent of GDP. However, the 2021 budget
Figure I.15. The revenue shortfall was exacerbated
Figure I.16. …reversing the fiscal surplus trajectory
Figure I.15. The revenue shortfall was exacerbated by Figure I.16. …reversing the fiscal surplus trajectory
Figure
I.15.
The
revenue
shortfall
was
exacerbated
by
Figure
I.16.
…reversing
the fiscal
surplus
trajectory
Figure
I.15.
The
revenue
shortfall
was
exacerbated
by
Figure
I.16.
…reversing
the fiscal
surplus
trajectory
byhuge
hugespending
spending
thepast
pastthree
threeyears
years
……
ofofthe
spending
of past
the past
three
years
hugehuge
spending
… …
of the
three
years
Budget revenue
and
expenditures
Budget
revenue
and expenditures
Budget
revenue
and
expenditures
Budget
revenue
and
expenditures
Revenue (% of GDP)
Expenditures (% of GDP)
Revenue
(% of GDP)
Revenue
(% of GDP)
40
31
26
31
31
26
26
2015
2015 2015
32
24
Expenditures
(% of GDP)
Expenditures
(% of GDP)
40
40
24
24
2016
2016 2016
28
2017
2017 2017
32
32
28
28
31
28
31
31
28
28
2018
2018 2018
32
31
32
32
31
31
Overall and primary
balances
Overallbudget
and primary
budget balances
Overall
and primary
budget
balances
Overall
and
primary
budget
balances
Overall budget balance (% of GDP)
Primary budget balance (% of GDP)
37
37
37
28
28
28
-1.7
-1.7-4.0-1.7
-3.0
-4.0 -4.0
-3.0
-3.0
-3.8
-3.8
-3.8
-6.9
-6.9-9.5-6.9
-9.5 -9.5
-11.2
-11.2 -11.2
-15.3
-15.3 -15.3
2019
2020e
2019 2019 2020e 2020e
Sources: MoF; World Bank staff estimates.
balance
(% of GDP)Primary
Primary
balance
(% of GDP)
OverallOverall
budgetbudget
balance
(% of GDP)
budgetbudget
balance
(% of GDP)
5.8
5.8
5.8
3.7
2.6
3.7 1.4 3.7
2.6
0.3 2.6
0.2
1.4
1.4
0.3
0.2
0.3
0.2
2014
2015
2016
2017
2018
2019
2020e
2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 20192020e 2020e
Sources: MoF; World Bank staff estimates.
Sources: MoF; World Bank staff estimates.
Sources:
World
estimates.
Sources:
MoF;MoF;
World
BankBank
staff staff
estimates.
Sources: MoF; World Bank staff estimates.
Sources:
World
estimates.
Sources:
MoF;MoF;
World
BankBank
staff staff
estimates.
Box I.2. Government fiscal relief measures to alleviate the economic impact of the COVID‐19 pandemic
I.2. Government
measures
to alleviate
the economic
impact
of COVID‐19
the COVID‐19
pandemic
Box Box
I.2. Government
fiscalfiscal
reliefrelief
measures
to alleviate
the economic
impact
of the
pandemic
The government’s COVID‐19 relief package, totaling about MNT 3.6 trillion (over 9 percent of GDP), was rolled
government’s
COVID‐19
relief
package,
totaling
about
3.6 trillion
(over
9 percent
of GDP),
rolled
The The
government’s
COVID‐19
relief
package,
totaling
about
MNTMNT
3.6 focused
trillion
(over
9 percent
ofhouseholds
GDP),
was was
rolled
out
in three phases.
The
government
response
is primarily
on supporting
and firms
in three
phases.
The
government
response
is primarily
focused
on supporting
households
and
firms
out out
in
three
phases.
The
government
response
is
primarily
focused
on
supporting
households
and
firms
particularly affected by the economic downturn, and on small and medium‐sized enterprises (SMEs) to cushion
16
In particularly
fact, the 2020
budget
amendment
2020)
exhibits and
a widening
of the
overall
fiscal
deficit from
an initial
target
of (SMEs)
2.4 percent
GDP to 9.9
affected
by economic
the (August
economic
downturn,
and
on
small
and
medium‐sized
enterprises
toofcushion
particularly
affected
by
the
downturn,
on
small
and
medium‐sized
enterprises
(SMEs)
to
cushion
lossofof
income and avoid mass unemployment and bankruptcies. This includes over 3 percent of GDP in tax relief
percent
GDP.
loss
of
income
andfollowed
avoid
mass
unemployment
and
bankruptcies.
This
includes
over
3 percent
ofofGDP
inrelief
tax relief
loss
ofprudent
income
and
mass
and
bankruptcies.
This
includes
over
3to percent
of GDP
insizable
tax
17
The
fiscal
policy
byunemployment
the authorities
during
2017–19
created some
fiscal
space
and
ledspending
the accumulation
cash reserves
measures
and
6avoid
percent
of
GDP
in increased
social
transfers
and
higher
health
(figure
I.17).
measures
6 (over
percent
of GDP
in increased
social
transfers
higher
health
spending
(figure
of about
MNT
2.7 and
7 percent
of increased
GDP)
at end-2019.
measures
and
6trillion
percent
of
GDP
in
social
transfers
and and
higher
health
spending
(figure
I.17).I.17).
Figure I.17. COVID‐19 fiscal relief measures
Figure
COVID‐19
measures
Figure
I.17. I.17.
COVID‐19
fiscalfiscal
reliefrelief
measures
Tax relief measures (over 3% of GDP)
Tax relief
measures
of GDP)
Tax relief
measures
(over (over
3% of3%
GDP)
SSC exemptions
SSC exemptions
SSC exemptions
PIT exemptions
PIT exemptions
PIT exemptions
2
0.5
0.5
0.5
2
2
Spending measures (over 6% of GDP)
Spending
measures
of GDP)
Spending
measures
(over (over
6% of6%
GDP)
Increase in CMP
Increase
Increase
in CMPin CMP
Increase in health spending
0.7
Increase
in health
spending 0.7
0.7
Increase
in health
spending
Cash transfer to herders
0.5
Cash transfer
to herders 0.5
0.5
Cash transfer
to herders
4.4
11
4.4
4.4
28
26
26
24
28
28
28
31
31
28
-1.7 -1.7
-3.0
-4.0 -4.0
28
24
-3.0
-3.8
-3.8
-6.9
-9.5
-11.2 -11.2
-15.3 -15.3
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020e 2020e
Sources:
MoF;MoF;
World
BankBank
staff staff
estimates.
Sources:
World
estimates.
-6.9
-9.5
2014 20142015 20152016 20162017 20172018 20182019 20192020e 2020e
Sources:
MoF;MoF;
World
BankBank
staff staff
estimates.
Sources:
World
estimates.
Box I.2. Government fiscal relief measures to alleviate the economic impact of the COVID-19
pandemic
Box I.2.
fiscalfiscal
reliefrelief
measures
to alleviate
the economic
impact
of the
pandemic
BoxGovernment
I.2. Government
measures
to alleviate
the economic
impact
of COVID‐19
the COVID‐19
pandemic
TheThe
government’s
COVID-19
reliefrelief
package,
totaling
aboutabout
MNT MNT
3.6 trillion
(over(over
9 percent
of GDP),
was rolled
out in
government’s
COVID‐19
package,
totaling
3.6 trillion
9 percent
of GDP),
was was
rolled
The government’s
COVID‐19
relief
package,
totaling about
MNT
3.6 trillion
(over
9 percent
of GDP),
rolled
18
three
phases.
Thephases.
government
response
is primarily
focused
on supporting
households
and firms
particularly
affected
out
in
three
The
government
response
is
primarily
focused
on
supporting
households
and
firmsfirms
out in three phases. The government response is primarily focused on supporting households and
by the
economicaffected
downturn,
and economic
on small and
medium-sized
(SMEs) to cushion
loss of(SMEs)
incometoand
avoid
particularly
by the
downturn,
and and
on enterprises
small
and and
medium‐sized
enterprises
particularly affected
by the economic
downturn,
on small
medium‐sized
enterprises
(SMEs)cushion
to cushion
mass
unemployment
and
bankruptcies.
This
includes
over
3
percent
of
GDP
in
tax
relief
measures
and
6
percent
of
GDP
loss of
income
and avoid
massmass
unemployment
and bankruptcies.
This This
includes
overover
3 percent
of GDP
in taxinrelief
loss
of income
and avoid
unemployment
and bankruptcies.
includes
3 percent
of GDP
tax relief
in increased
social
transfers
and
higher
health spending
(figure I.17).
measures
and
6
percent
of
GDP
in
increased
social
transfers
and
higher
health
spending
(figure
I.17).
measures and 6 percent of GDP in increased social transfers and higher health spending (figure I.17).
Figure I.17. COVID-19 fiscal relief measures
Figure
I.17. I.17.
COVID‐19
fiscalfiscal
reliefrelief
measures
Figure
COVID‐19
measures
Tax relief
measures
(over(over
3% of
Tax relief
measures
3%GDP)
of3%
GDP)
Tax
relief measures
(over
of GDP)
Spending
measures
(over
GDP)
Spending
measures
(over 6%
6% of
of6%
GDP)
Spending
measures
(over
of GDP)
SSC exemptions
SSC exemptions
PIT exemptions
PIT exemptions
CIT exemptions
(turnover
< MNT1.5
CIT exemptions
(turnover
< MNT1.5 0.16
bn)
bn)
PIT/CITPIT/CIT
exemption
if rent has
been
exemption
if rent
has been0.07
lowered
lowered
2
0.5
Increase
in CMPin CMP
Increase
2
Increase
in health
spending
Increase
in health
spending
0.5
Wage subsidies
for employers
0.13
Wage subsidies
for employers
0.07
0.03
VAT exemption
(Medical
& Food)
0.02
VAT exemption
(Medical
& Food)
0.02
Increase
in govt's
fund fund
0.1
Increase
in emergency
govt's emergency
InterestInterest
subsidies
for cashmere
producers
0.07
subsidies
for cashmere
producers
Doubling
food stamp
allowance
0.04
Doubling
food stamp
allowance
4.4
0.7
Cash transfer
to herders
Cash transfer
to herders 0.5
Increase
in social
pension
0.15
Increase
inwelfare
social welfare
pension
0.16
Waiving
late payment
penalties
for
Waiving
late payment
penalties
for
0.03
PIT/SSCPIT/SSC
4.4
0.7
0.5
0.15
0.13
0.1
0.07
0.04
Sources:
MoF;MoF;
World
BankBank
staff staff
estimates.
Sources:
World
estimates.
Sources:
MoF;
World
Bank
staff
estimates.
Note:
In percent
of GDP.
CIT =CIT
corporate
income
tax; CMP
= Child
Money
Program;
PIT =PIT
personal
income
tax; SSC
social
Note:
In percent
of GDP.
= corporate
income
tax; CMP
= Child
Money
Program;
= personal
income
tax;=SSC
= social
contribution;
=VAT
value‐added
tax.CMP
Note:security
In percent
of contribution;
GDP. CIT VAT
= corporate
tax;
security
= income
value‐added
tax.= Child Money Program; PIT = personal income tax; SSC = social security
contribution; VAT = value-added tax.
Mongolia’s
fiscalfiscal
reliefrelief
measures
are among
the largest
in the
The optimal
size of
package
Mongolia’s
measures
are among
the largest
in region.
the region.
The optimal
sizeany
of support
any support
package
Mongolia’s
fiscal relief
arethe
among
the largest
inathe
region.
The
optimal
size(such
of
any
support
package
is
is contingent
on the
severity
of
outbreak
and and
a country’s
initialinitial
conditions
(such
as the
of the
is contingent
onmeasures
the severity
of
the outbreak
country’s
conditions
as state
the state
of health
the health
contingent
on
the
severity
of
the
outbreak
and
a
country’s
initial
conditions
(such
as
the
state
of
the
health
sector,
sector,
commodity
dependence,
fiscalfiscal
and monetary
space
and degree
of informality,
to name
a few).
WithWith
thesethese
sector,
commodity
dependence,
and monetary
space
and degree
of informality,
to name
a few).
commodity
dependence,
fiscal
and
monetary
space
and
degree
to name
few).average
With
these
caveats,
caveats,
Mongolia’s
support
package
in response
to the
isinformality,
relatively
higher
thanathan
the
size size
of
fiscal
caveats,
Mongolia’s
support
package
in
response
to crisis
the of
crisis
is relatively
higher
the
average
of fiscal
Mongolia’s
support
package
in
response
to
the
crisis
is
relatively
higher
than
the
average
size
of
fiscal
measures
measures
announced
to
date
in
developing
EAP,
estimated
at
around
5
percent
of
GDP
(figure
I.18).
Nearly
two‐two‐
measures announced to date in developing EAP, estimated at around 5 percent of GDP (figure I.18). Nearly
announced
date
in developing
EAP,
at
around
5 percent
GDP
I.18).
Nearly
two-thirds
these
thirds
oftothese
relief
measures
wereestimated
directed
at individuals
to mitigate
the(figure
impact
of income
loss
for
thirds
of these
relief
measures
were
directed
at individuals
to of
mitigate
the impact
of income
losshouseholds
for of
households
relief
measures
were
directed
at
individuals
to
mitigate
the
impact
of
income
loss
for
households
(figure
I.19).
Such
(figure
I.19).
Such
measures
were
broad‐based,
using
social
insurance
to
protect
formal
sector
workers
and
social
(figure I.19). Such measures were broad‐based, using social insurance to protect formal sector workers and
social
measures
were
broad-based,
using
social
insurance
to
protect
formal
sector
workers
and
social
assistance
to
support
assistance
to
support
the
poor
and
vulnerable.
assistance to support the poor and vulnerable.
the poor and vulnerable.
Figure I.18. Mongolia’s fiscal relief package is one of
Figure I.19. Income support and tax exemptions
FigureFigure
I.18. Mongolia’s
I.18. Mongolia’s
fiscal relief
fiscal relief
package
package
is oneis one
FigureFigure
I.19. Income
I.19. Income
support
support
and tax
and
exemptions
tax exemptions
the highest among EAP countries
dominated fiscal relief measures
of theof
highest
the highest
amongamong
EAP countries
EAP countries
dominated
fiscal
relief
fiscal
relief
measures
measures
23 dominated
23
10%
8%
8%
6%
4%
2%
0%
6%
4%
Quasi-fiscal
operations
Quasi-fiscal
operations
Additional
spendingspending
and revenue
Additional
and measures
revenue measures
2%
0%
MNG THA
MMR
MNGCHN
THAIDN
CHNPHL
IDNMYS
PHLKHM
MYSVNM
KHM
VNMLAO
MMR LAO
10%
10%
9%
9%
8%
8%
7%
7%
6%
5%
4%
3%
Percent of GDP
10%
Additional
Additional
health-related
health-related
spendingspending
Percent of GDP
12%
Percent of GDP
Percent of GDP
12%
6%
Firms - Revenue
Firms - Revenue
measuresmeasures
Firms - Additional
on support
revenue support
Firms - Additional
spendingspending
on revenue
Individuals
- Revenue- Revenue
measuresmeasures
Individuals
Individuals
- Additional
spendingspending
on income
Individuals
- Additional
onsupport
income support
5%
4%
3%
2%
2%
1%
1%
0%
0%
MNG
THA
MNG CHN
THA IDN
CHN PHL
IDN MYS
PHL KHM
MYS VNM
KHM MMR
VNM
MMR
Sources:
Sources:
MoF;
World
MoF;
World
Bank
2020b;
Bank
2020b;
World
Bank
Bankestimates.
staff estimates.
Sources:
MoF;
World
Bank
2020b;
World
BankWorld
staff staff
estimates.
Note: Data
Note:are
Data
as are
of September
as of September
12, 2020.
12, Data
2020.refer
Datato
refer
general
to general
government,
government,
exceptexcept
for Indonesia,
for Indonesia,
Malaysia,
Malaysia,
and the
and the
Note: Data are as of September 12, 2020. Data refer to general government, except for Indonesia, Malaysia, and the Philippines, which
Philippines,
Philippines,
which which
refer to
refer
central
to central
government
government
only. Income
only. Income
and revenue
and revenue
support
support
measures
measures
includeinclude
direct direct
transfer
transfer
refer to central government only. Income and revenue support measures include direct transfer payments; reduction or deferral of
payments;
payments;
reduction
reduction
or
deferral
or deferral
of payment
of payment
commitments;
foregone
revenue
revenue
from
tax
from
cuts,
taxcredits,
cuts,
credits,
and exemptions;
exemptions;
and
and
payment
commitments;
foregone
revenue
from
tax
cuts,commitments;
credits, foregone
and exemptions;
and
other
financial
assistance
toand
individuals
and firms.
other financial
other financial
assistance
assistance
to individuals
to individuals
and firms.
and firms.
Mongolia
Mongolia
has limited
has limited
headroom
headroom
to provide
to provide
further
further
fiscal fiscal
relief relief
(and to
(and
boost
to boost
economic
economic
recovery).
recovery).
In terms
In terms
of
of
government
government
debtofsustainability,
debt
compares
compares
unfavorably
unfavorably
tountil
other
to
other
countries.
debttheas
debt
a share
as a share
It includes
the
extension
some sustainability,
measuresMongolia
which Mongolia
are expected
to be
implemented
July
2021.countries.
But Government
it does Government
not include
government’s
recent
decisionof
onGDP
exempting
for about
households
and
ofaccounts
GDP utilities
accounts
forfees
about
for
70 percent
70 percent
atenterprises.
end‐2019,
at end‐2019,
compared
compared
to theto40the
percent
40 percent
average
average
for emerging
for emerging
markets
markets
18
12
and developing
and developing
economies
economies
(EMDEs).
(EMDEs).
Moreover,
Moreover,
banks’banks’
excessexcess
liquidity
liquidity
was estimated
was estimated
MNT MNT
7.7 trillion
7.7 trillion
in
in
November
November
2020, 2020,
of which
of which
centralcentral
bank bill
bank
holdings
bill holdings
by banks
by banks
was around
was around
MNT 5.4
MNT
trillion,
5.4 trillion,
indicating
indicating
sizablesizable
room room
for domestic
for domestic
debt issuance.
debt issuance.
Given Given
large external
large external
debt (over
debt 60
(over
percent
60 percent
of GDPofcompared
GDP compared
to theto
40the
percent
40 percent
EMDEEMDE
average),
average),
borrowing
borrowing
in foreign
in foreign
currency
currency
is still is
not
still
a favorable
not a favorable
option.
option.
Finally,Finally,
tapping
tapping
into the
into
Fiscal
the Fiscal
Stability
Stability
Fund Fund
declining
declining
coal prices.
coal prices.
could could
not provide
not provide
enough
enough
fiscal space
fiscal space
to mitigate
to mitigate
the impact
the impact
of theof
pandemic,
the pandemic,
considering
considering
In fact,
In the
fact,Fiscal
the Fiscal
Stability
Stability
Fund’sFund’s
liquid liquid
part ispart
estimated
is estimated
at MNT
at 150
MNTbillion
150 billion
(0.4 percent
(0.4 percent
of GDP)
of GDP)
as of as
end‐
of end‐
ECONOMIC PERFORMANCE AND PROSPECTS
Mongolia has limited headroom to provide further fiscal relief (and to boost economic recovery). In terms of
government debt sustainability, Mongolia compares unfavorably to other countries. Government debt as a share
of GDP accounts for about 70 percent at end-2019, compared to the 40 percent average for emerging markets and
developing economies (EMDEs). Moreover, banks’ excess liquidity was estimated MNT 7.7 trillion in November 2020,
of which central bank bill holdings by banks was around MNT 5.4 trillion, indicating sizable room for domestic debt
issuance. Given large external debt (over 60 percent of GDP compared to the 40 percent EMDE average), borrowing
in foreign currency is still not a favorable option. Finally, tapping into the Fiscal Stability Fund could not provide
enough fiscal space to mitigate the impact of the pandemic, considering declining coal prices. In fact, the Fiscal
Stability Fund’s liquid part is estimated at MNT 150 billion (0.4 percent of GDP) as of end-November.
Sources: MoF; World Bank 2020b; World Bank staff estimates.
The revenue projections in the 2021 budget are
moderately optimistic. At 7 percent, the growth
assumption in the 2021 budget appears ambitious
given the ongoing strict lockdown at the start of 2021.
It is, however, achievable, assuming a strong recovery of
mining exports and successful domestic containment
of COVID-19. While commodity price assumptions are
broadly in line with the projections of international
institutions, export projections may be optimistic. In
particular, the 2021 budget assumes that coal export
volumes will increase to 42 million tons next year, a
15 percent rise from the historically high level (36.6
million tons) achieved in 2019. To achieve this target,
the government plans to improve the capacity at the
border posts and accelerate digitalization to reduce red
tape. However, this is likely to be optimistic amid the
preventive public health measures still in place and
continued worries about the rise in infection rates in
major markets. Moreover, the budget assumes that tax
administration reforms (simplification, digitalization,
international taxation issues) will bring an additional
MNT 1.1 trillion in revenue (1.5 percentage points of
GDP), contributing to 44 percent of the total expected
revenue increase (figure I.21). However, the successful
and timely implementation of these measures may be
challenging in a context dominated by the pandemic.
Figure
I.20.I.20.
The The
deficit
widened
sharply
in 2020
revenue projections
projections in
in the
the2021
2021
Figure
deficit
widened
sharply
in 2020 but is Figure
Figure I.21.
I.21. The
The revenue
Figure
The deficit
widened
sharply
in 2020 but is Figurebudget
I.21.
The
revenue
projections
in the 2021
but isI.20.
expected
narrow
notably
2021
are
moderately
optimistic…
expected
toto
narrow
notably
in in
2021
budget
are
expected
to narrow
notably in 2021
budgetRevenue
are moderately
In percent
of GDP
to increaseoptimistic…
by 3.4 percentage points of GDP in
In percent of GDP
In percent of GDP
Overall balance
Overall balance
6%
6%
3%
3%
3%0%
1%
0%
-4%
-11%
-15%
2016
3%
-10%
2017
2018
2018
2019
1%
1%
-2%
-15%
2016
2017
1%
-4%
-11%
Revenue
to increase
3.4 percentage
points
of GDP
Revenue
to increase
by 3.4by
percentage
points
of GDP
in in 2021.
2021.
2021.
Primary balance
Primary balance
-7% -10%
-2%
-7%
2019
2020 Suppl 2021 Plan
2020 Suppl 2021 Plan
Sources: MoF; World Bank staff estimates.
Sources: MoF;
MoF; World
staff
estimates.
Sources:
WorldBank
Bank
staff
estimates.
Sources: MoF; World Bank staff estimates.
Sources:
World
Bank
staff
estimates.
Sources:
MoF;MoF;
World
Bank
staff
estimates.
The revenue projections in the 2021 budget are moderately optimistic. At 7 percent, the growth
The revenue
projections
in the
2021
budget
are moderately
At lockdown
7 percent,atthe
assumption
in the 2021
budget
appears
ambitious
given theoptimistic.
ongoing strict
the growth
start of 2021.
assumption
in
the
2021
budget
appears
ambitious
given
the
ongoing
strict
lockdown
at
the
start
of 2021.
It is, however, achievable, assuming a strong recovery of mining exports and successful
domestic
It is, however,
achievable,
assuming
a strong recovery
of mining are
exports
and
successful
containment
of COVID‐19.
While commodity
price assumptions
broadly
in line
with thedomestic
projections of
containment
of COVID‐19.
Whileexport
commodity
price assumptions
are broadly
in line with
projections
of
international
institutions,
projections
may be optimistic.
In particular,
thethe
2021
budget assumes
international
institutions,
export
projections
may
be
optimistic.
In
particular,
the
2021
budget
assumes
that coal export volumes will increase to 42 million tons next year, a 15 percent rise from the historically
that coal
will increase
to 42 million
tons
year,this
a 15
percent
from the historically
highexport
level volumes
(36.6 million
tons) achieved
in 2019.
To next
achieve
target,
therise
government
plans to improve
high level
(36.6
million
tons)
achieved
in
2019.
To
achieve
this
target,
the
government
plans to improve
the capacity at the border posts and accelerate digitalization to reduce red tape. However,
this is likely to
the capacity
at the border
posts
and accelerate
to reduce
tape.
this
is likelyabout
to 13
continued
worries
the
be optimistic
amid the
preventive
public digitalization
health measures
still inred
place
andHowever,
continued
worries
about
the
be optimistic
amid
the
preventive
public
health
measures
still
in
place
and
rise in infection rates in major markets. Moreover, the budget assumes that tax administration reforms
rise in (simplification,
infection rates digitalization,
in major markets.
Moreover,taxation
the budget
assumes
that an
tax additional
administration
international
issues)
will bring
MNTreforms
1.1 trillion in
(simplification,
digitalization,
international
taxation
issues)
will
bring
an
additional
MNT
1.1
trillion increase
in
revenue (1.5 percentage points of GDP), contributing to 44 percent of the total expected revenue
revenue
(1.5 percentage
points
ofsuccessful
GDP), contributing
to 44
percent of theof
total
expected
revenue
(figure
I.21). However,
the
and timely
implementation
these
measures
may increase
be challenging
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Box I.3. Summary of the 2021 budget
The 2021 budget is based on optimistic macroeconomic assumptions. It assumes (i) real economic growth of -1
percent in 2020 and 7.2 percent in 2021; (ii) strong demand for coal and relatively higher production of copper
concentrate; (iii) continuation of tax reforms in 2021; and (iv) inflation of 7 percent in 2021, in line with the monetary
policy guidelines. The revenue projections and corresponding expenditure plans are shown in table I.1.
Table I.1.
Mongolia: Improvements in the overall fiscal balance in 2021 (% of GDP)
2020 Supplementary
2021 Plan
Diff
27.7
31.1
3.4
2.6
3.2
0.6
22.9
25.5
2.6
2.3
2.5
0.2
37.7
33.0
-4.6
26.3
23.3
-3.0
6.9
5.7
-1.1
Revenues
Stabilization & Heritage Funds
Tax Revenues
Non-Tax Revenues
Expenditures
Recurrent spending
o.w. Wages and Salaries
Goods & Services
5.9
4.8
-1.2
13.5
12.8
-0.7
Capital spending
8.8
8.4
-0.4
Interest Payments
2.5
2.7
0.2
Overall balance
-9.9
-1.9
8.0
Primary balance
-7.4
0.8
8.2
Others (incl. Social Spending)
Source: MoF.
Key highlights of the 2021 budget:
• Return to a fiscal sustainability path after a substantial hike in the fiscal deficit in 2020 driven by a sharp revenue
shortfall and a rise in public spending to mitigate the impact of COVID-19 crisis.
• Fiscal improvements mainly supported by:
o Higher mineral revenue, reflecting the positive prospect in commodity prices and ambitious export targets.
o Stronger economic recovery leading to higher tax revenue under existing and new policies.
o Rolling back (expiry) of COVID-19-related spending measures and other recurrent spending, and rationalization
of capital expenditures to compensate for the substantial increase in social spending (mainly the Child Money
Program) planned in H1 2021.
o Improvement in the overall balance of over US$1 billion (8 percentage points of GDP) and a primary deficit of
over US$1.1 billion (8.2 percentage points) compared with the 2020 supplementary budget.
• Ambitious but achievable growth assumptions depending on recovery in mining exports.
• Revenue projections are predicated on successive implementation of tax administration reforms (simplification,
digitalization, international taxation issues including introduction of transfer pricing and renovation of customs
capacity).
• Assuming successful containment of the pandemic, recurrent spending related to COVID-19 measures are
planned to be scaled down.
• No growth assumed in the size of the civil service, the wage bill, or pensions.
• Partial extension of top-up on benefits of the Child Money Program entails sizable fiscal burden (about 2.2
percent of GDP).
14
ECONOMIC PERFORMANCE AND PROSPECTS
• Capital expenditure allocation (8.4 percent of GDP) slightly declined from 2020 supplementary budget - largely to
complete ongoing projects. It remains higher than in the pre-COVID years (which were significantly expansionary).
• Interestingly, many projects that were included in the 2020 budget for reconstruction have been scaled down for
renovation, with substantial cost savings (these include the state drama theater, state opera house, and national
library). However, there is room for further rationalization and reprioritization of the current public investment
program. The capital expenditure execution rate has generally averaged about 80 percent over the past three
years.
• Commitment to budget credibility as overall budget envelope is consistent with the 2020 Medium-Term Fiscal
Framework.
Sources: MoF; 2020 budget document; World Bank staff illustrations.
A5. External pressures considerably
eased following notable current account
adjustment
pressures were reduced thanks to a remarkable current
account adjustment. Lower FDI (which contracted by
about 30 percent [y/y] in 2020) and the private sector
external debt payment (US$500 million in May 2020)
accounted for the narrower financial account surplus
Despite lower capital inflows and large private sector
despite official sector support from development
debt repayments, external pressures eased considerably
partners including ADB, IMF, AIIB, the World Bank and
amid exports recovery and imports compression.
Japan.19 In contrast, weak domestic demand and the
In 2020, Mongolia’s balance of payments recorded
17
from
development
partners
including
ADB,
IMF, aAIIB,quick
the World
and Japan.
In contrast,
weak
recoveryBank
of exports
have resulted
in a remarkable
a surplus
of US$787
millionpartners
(figure
I.22).
Despite
from
development
including
ADB, IMF, AIIB, the World Bank and Japan.17 In contrast, weak
domestic
demand
and
the
quick
recovery
of
exports
have
resulted
in
a
remarkable
current
account
current account adjustment.
narrower domestic
surplus of
the financial
externalof exports
demand
and the account,
quick recovery
have resulted in a remarkable current account
adjustment.
adjustment.
FigureI.22.
I.22.Current
Current account adjustment
adjustment was
was
Figure
I.23. Current
account
surplus
in recent
months
Figure
I.23. Current
account
surplus
in recent
months
Figure I.22. account
Current account adjustment
was FigureFigure
I.23. Current
account
surplus
in recent
monthsisis
enough
to
ease
external
pressures
is
unprecedented
in
Mongolia’s
recent
history
enough to ease external pressures
unprecedented in Mongolia’s recent history
unprecedented in Mongolia’s recent history
Monthly
current
account
balance
(million
US$,
3 mma)
Monthly
current
account
balance
(million
US$,
3 mma)
Monthly
current
account
balance
(million
US$,
3 mma)
Trade Balance
Trade Balance
CA (mn US$) CA (mn US$)
FA & KA (mnFAUS$)
& KA (mn US$)BoP (mn US$)
BoP (mn US$)
Note: CA = current account; KA = capital account; FA = financial
financialand
account;
and BOP
= Balance of payments.
account;
BOP = Balance
of payments.
Oct-20
Dec-20
Dec-20
Aug-20
Oct-20
Apr-20
Jun-20
2017
Sources: BoM;
World2018
Bank staff2019
estimates.2020
Source: BoM.
Note:
CA
=
current
account;
KA
=
3 BoM.
mma = three‐month moving average.
Sources: BoM; World Bank staff estimates.capital account; FA =Source:Note:
BoM.
Source:
Sources: BoM; World Bank staff estimates.
= Balance
of payments.
Note: CA =financial
current account;
account;and
KA BOP
= capital
account;
FA =
Note: 3 mma = three‐month moving average.
Jun-20
Aug-20
Feb-20
Apr-20
Dec-19
Feb-20
Oct-19
Aug-19
Dec-19
Oct-19
2020
Apr-19
2019
-400
Aug-19
Jun-19
2018
-400
-300
Feb-19
2017
-300
(2,162)
-200
Jun-19
2016
(2,162)
-200
Apr-19
2016
(2,207)
(2,207)
-100
0
-100
Oct-18
-3,000
(1,155)
(433)
100
Dec-18
(1,155)
(433)
0
Income
Balance
Income
Balance
Current
Account
Current
Account
Feb-19
-2,000
(142)
100
786.9
786.9
Dec-18
(700)
200
Jun-18
-1,000
(700)
453
(142)
300
200
Aug-18
-3,000
(18)
400
300
1,220
1,220
453
400
Apr-18
-2,000
0
2,615
2,065
Oct-18
-1,000
(18)
2,065
681
1,000
681
1,000
1,460
1,460
2,615
2,615
Feb-18
Jun-18
2,000
2,000
0
2,615
3,000
Feb-18
3,000
Current
Transfers
Current
Transfers
ServicesServices
Aug-18
External accounts (million US$)
Apr-18
enough to ease external pressures
External accounts
External(million
accountsUS$)
(million US$)
Note: 3 mma = three-month moving average.
Improvement in the trade balance drove the current account adjustment. The current account deficit
narrowed
to US$433
million in
2020the
from
US$2.1account
billion inadjustment.
2019. In fact,The
the current
current account
Improvement
in the
trade balance
drove
current
accountposted
deficit a
of US$530
million
duringfrom
May–December,
which
is unprecedented
the past account
decade (figure
I.23).
narrowedsurplus
to US$433
million
in 2020
US$2.1 billion
in 2019.
In fact, theincurrent
posted
a
Import
compression
supported
by
weaker
domestic
demand
and
lower
oil
prices
contributed
to
the
surplus of US$530 million during May–December, which is unprecedented in the past decade (figure I.23).
current account
adjustment,
coupleddomestic
with the demand
relatively and
quicklower
recovery
of exports
(figures I.24
and
Import compression
supported
by weaker
oil prices
contributed
to the
18,19,20
Moreover,
lowermillion
profits
repatriation
decliningdidservice
(for
example,
travel
The recentI.25).
sovereign bond
issuance (US$600
in late
September) by and
the government
not havepayments
a sizable direct
impact
on the country’s
current
account
adjustment,
coupled
with the relatively
quick
recovery
of exports (figures
I.24 and
external position
as the proceeds
used truck
mainly activities)
to pay off existing
debts.
contrast, it had
significant
market expectations
alsopublic
played
anInimportant
role
in theimplications
improvedoncurrent
account
restrictions
and were
limited
18,19,20
Moreover,
profitsandrepatriation
and declining service payments (for example, travel
I.25).
regarding immediate
pressure of lower
external liquidity
exchange rate depreciation.
balance. Furthermore, the BoM’s gold purchase, which reached a historically high level of 23 metric ton
restrictions
and limited
trucksupported
activities)
played
an important
role
21 in the improved current account
in 2020,
significantly
thealso
export
recovery
(figure I.24).
15
balance. Furthermore, the BoM’s gold purchase, which reached a historically high level of 23 metric ton
in 2020, significantly supported the export recovery (figure I.24).21
19
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Improvement in the trade balance drove the current
account adjustment. The current account deficit
narrowed to US$433 million in 2020 from US$2.1 billion
in 2019. In fact, the current account posted a surplus
of US$530 million during May–December, which is
unprecedented in the past decade (figure I.23). Import
compression supported by weaker domestic demand
and lower oil prices contributed to the current account
adjustment, coupled with the relatively quick recovery
of exports (figures I.24 and I.25).20, 21, 22 Moreover, lower
profits repatriation and declining service payments (for
example, travel restrictions and limited truck activities)
also played an important role in the improved current
account balance. Furthermore, the BoM’s gold purchase,
which reached a historically high level of 23 metric ton
in 2020, significantly supported the export recovery
(figure I.24).23
Current account adjustment, specifically a surge in
gold purchases by the BoM, led to a strong recovery
in reserves after a significant drop during January–
May. Due to the sharp drop in exports, the current
account deficit widened in H1 2020 compounded by
declining capital inflows (mainly FDI) and large private
sector external debt repayments, resulting in a drain
on foreign exchange reserves (figure I.26). However,
reserves recovered significantly in H2 2020 amid the
current account adjustment, disbursement from some
donors, and extensive gold purchases by the BoM. In
fact, gross international reserves reached a historically
high level of US$4.5 billion (equivalent to over eight
months of imports) at end-2020, up from US$4.3
billion in 2019.
Figure I.24. Exports were hit hard in H1, but have
Figure I.25. Import compression has largely been
Figure
I.24.
Exports
were hit
hard
H1, in
but
have
I.25.I.25.
Import
compression
hashas
largely
been
recovered
quickly
driven
by lower
fuel
and capital
goods
imports
Figure
I.24. Exports
were
hitinhard
H1,
but have Figure
Figure
Import
compression
largely
been
recovered
quickly
driven
by
lower
fuel
and
capital
goods
imports
recovered quickly
driven by lower fuel and capital goods imports
-10%
Dec-20
Nov-20
Dec-20
Oct-20
Nov-20
Sep-20
Oct-20
Aug-20
Sep-20
Jul-20
Jun-20
Jun-20
May-20
Sources: BoM; World Bank staff estimates.
Jul-20
Aug-20
Apr-20
Mar-20
May-20
Apr-20
Jan-20
Mar-20
Feb-20
Dec-19
Oct-19
Nov-19
-20%
Feb-20
Sources: NSO; BoM; World Bank staff estimates.
-15%
Jan-20
-20%
Industrial
& Intermediate
Industrial
& Intermediate
FuelsFuels
TotalTotal
imports
growth
imports
growth
Dec-19
Dec-20
Oct-20
Nov-20
Sep-20
Dec-20
Jul-20
Aug-20
Nov-20
Jan-20
Apr-20
-10%
-15%
Feb-20
May-20
Dec-19
Mar-20
Jan-20
Oct-19
Feb-20
Nov-19
Dec-19
Sep-19
Nov-19
Aug-19
Jun-19
Oct-19
Jul-19
Sep-19
Jul-19
Aug-19
Total exports growth
-50%Total exports growth
Jun-19
-50%
Others
-5%
Sep-19
-40%
Crude oil
-5%
Oct-19
Crude oil
-40%Others
0%
Nov-19
-30%
0%
Jul-19
-30%
Coal
Coal
5%
Aug-19
-20%
Copper
5%
Sep-19
Gold
Copper
-20%
10%
Jul-19
-10%Gold
10%
Consumption
Consumption
CapitalCapital
goodsgoods
Others Others
Jun-19
Aug-19
-10%
Jun-20
0%
Oct-20
0%
Sep-20
10%
Apr-20
Jul-20
10%
May-20
Aug-20
20%
Mar-20
Jun-20
20%
Contribution
to growth
(y/y, percentage
points)
Contribution
to
growth
(y/y,
percentage
points)
Contribution
to growth
(y/y,
percentage
points)
Jun-19
Contribution
to (y/y,
growth
(y/y, percentage
points)
Contribution
to growth
percentage
points)
Contribution
to growth
(y/y, percentage
points)
Sources: NSO;
NSO; BoM;
World
Bank
staffstaff
estimates.
Sources: BoM; World Bank staff estimates.
Sources:
World
Bank
estimates.
Note:BoM;
Coal, copper
and gold
accounted
for 75 percent of Sources: BoM; World Bank staff estimates.
Note:
Coal,
copper
and
gold
accounted
for
75
percent
of
total
Note: Coal,
copper
gold accounted
total
exportand
proceeds
in 2020. for 75 percent of
export
proceeds
in 2020.in 2020.
total
export
proceeds
Current account adjustment, specifically a surge in gold purchases by the BoM, led to a strong recovery
Currentinaccount
adjustment,
specifically
surgeJanuary–May.
in gold purchases
bythe
thesharp
BoM,drop
led to
strongthe
recovery
reserves
after a significant
drop aduring
Due to
in a
exports,
current
in reserves
after
a significant
drop
during
January–May.
Due tocapital
the sharp
drop
in exports,
current
account
deficit
widened in
H1 2020
compounded
by declining
inflows
(mainly
FDI) andthe
large
private
accountsector
deficitexternal
widened
in H1
2020 compounded
capitalexchange
inflows (mainly
andI.26).
largeHowever,
private
debt
repayments,
resulting inbya declining
drain on foreign
reservesFDI)
(figure
sector external
repayments,
resulting
a drain
on the
foreign
exchange
reserves
(figuredisbursement
I.26). However,
reservesdebt
recovered
significantly
in H2in2020
amid
current
account
adjustment,
from
donors,significantly
and extensive
purchases
thecurrent
BoM. Inaccount
fact, gross
international
reserves reached
reservessome
recovered
in gold
H2 2020
amidbythe
adjustment,
disbursement
from a
historically
level ofgold
US$4.5
billion (equivalent
to over
eightgross
months
of imports)reserves
at end‐2020,
up from
some
donors,
andhigh
extensive
purchases
by the BoM.
In fact,
international
reached
a
Imports were also severely affected by friction at main border ports with Russia and China. Since the first domestic contagion of the virus, all
US$4.3
in
historically
highbillion
level
of2019.
US$4.5
billion
to anover
eightcongestion
monthsof of
imports)
end‐2020,
up
from
transportation
through
the main
borders
were
ceased, (equivalent
and there has been
increasing
merchandise
andat
traffic
on the other
side
of the
border. Without customs clearance, these items are not recorded as imports, despite having already been paid for. Since the friction is not expected to be
US$4.3
billion
inI.26.
2019.
resolved soon,Figure
the imports
are
to be recorded
in late
January or
February
FXlikely
reserves
recovered
strongly
after
a 2021.
Figure I.27. …and the exchange rate stabilized in H2
20
The government’s efforts to boost exports by accelerating coal transportation at the key border posts with China have also supported the recovery of
sharp fall in H1, supported by eased current
after a moderate depreciation in the first half
exports.
Figure I.26. FX reserves recovered strongly after a Figure I.27. …and the exchange rate stabilized in H2
22
account
adjustment
and
gold
purchases…
Exports declined by 45.3 percent (y/y) in the first four months of 2020, but contraction eased significantly to 0.6 percent by December 2020 amid
supportedmeasures,
by eased
current
sharp fallofinsome
H1,precautionary
after commodity
a moderate
depreciation
in theand
first
halfin gold exports.
easing/expiryGross
recovery
in Chinese
prices
(mainly(Spot
copper
prices),
a surge
international reserves
(GIR)
(billion
US$) demand andExchange
rate:
Tugrug
rate,
Index, Dec
31, 2015=100)
23 account adjustment and gold purchases…
To support gold
5.0 mining, the BoM provided soft loans of MNT 110 billion (US$42 million) to gold miners under the “Gold-2” program.
21
Gross international
reserves (GIR) (billion US$)
4.5
16 5.0
4.0
4.0
3.0
4.5
3.5
3.0
2.5
3.5
2.5
2.0
1.5
145
MNT/US$
Exchange
rate: Tugrug
(Spot rate, Index, Dec 31, 2015=100)
140
145
135
135
125
140
130
130
120
125
120
115
110
MNT/CNY
MNT/US$
MNT/CNY
Depreciation
Depreciation
-15%
-20%
-20%
Dec-20
Dec-20
Oct-20
Nov-20
Sep-20
Jul-20
Oct-20
Aug-20
Nov-20
Sep-20
Jul-20
May-20
Aug-20
Jun-20
May-20
Mar-20
Jun-20
Apr-20
Mar-20
Jan-20
Apr-20
Feb-20
Jan-20
Nov-19
Feb-20
Dec-19
ECONOMIC PERFORMANCE AND PROSPECTS
Oct-19
Aug-19
Nov-19
Sep-19
Dec-19
Oct-19
Jul-19
-15%
Jul-19
Total exports
Totalgrowth
exports growth
-10%
Aug-19
Jun-19
Sep-19
Jul-19
-50%
-10%
Jun-19
-50%
Others Others
Dec-20
-40%
Coal
Crude oilCrude oil
Nov-20
-40%
Coal
Aug-19
Jun-19
Sep-19
Jul-19
Oct-19
Aug-19
Nov-19
Sep-19
Dec-19
Oct-19
Jan-20
Nov-19
Feb-20
Dec-19
Mar-20
Jan-20
Apr-20
Feb-20
May-20
Mar-20
Jun-20
Apr-20
Jul-20
May-20
Aug-20
Jun-20
Sep-20
Jul-20
Oct-20
Aug-20
Nov-20
Sep-20
Dec-20
Oct-20
-30%
Jun-19
-30%
Sources:
Sources:
NSO; BoM;
NSO; World
BoM; World
Bank staff
Bankestimates.
staff estimates.
Sources:
Sources:
BoM; World
BoM; World
Bank staff
Bankestimates.
staff estimates.
Note: Coal,
Note:copper
Coal, copper
and gold
andaccounted
gold accounted
for 75 for
percent
75 percent
of
of
Thetotal
tugrug
depreciated
moderately
against the US
the intervention of the BoM, which continued to sell
export
total export
proceeds
proceeds
in 2020.
in 2020.
dollar in 2020 supported by foreign exchange (FX)
foreign exchange on the domestic market. In fact, BoM’s
interventions.
Inaccount
nominal
terms, the
tugrug
depreciated
gross
exchange
direct
Current
Current
account
adjustment,
adjustment,
specifically
specifically
a surge
a surge
in gold
in
purchases
goldforeign
purchases
by
the
byBoM,
theinterventions
BoM,
led toled
a strong
to(excluding
a strong
recovery
recovery
reserves
in reserves
after
after
a the
significant
aU.S.
significant
drop
during
during
January–May.
January–May.
Due to
Due
theto
sharp
thelarge
sharp
dropmining
drop
in exports,
incompanies)
exports,
the current
the
current
byin4.2
percent
against
dollar
anddrop
by 11.2
percent
FX purchases
from
reached
account
account
deficit
deficit
widened
widened
in
H1
in
2020
H1
2020
compounded
compounded
by
declining
by
declining
capital
capital
inflows
inflows
(mainly
(mainly
FDI)
and
FDI)
large
and
large
private
private
against the Chinese RMB in 2020 (figure I.27). The
US$2.63 billion in 2020, close to the US$2.87 billion
sector
sector
external
external
debt
repayments,
debt
repayments,
resulting
resulting
in
a
drain
in
a
drain
on
foreign
on
foreign
exchange
exchange
reserves
reserves
(figure
(figure
I.26).
I.26).
However,
However,
depreciation of the tugrug was smaller in 2020 relative
in 2019 (figure I.29). Nonetheless, with moderate
reserves
reserves
recovered
recovered
significantly
significantly
in
H2
in
2020
H2
2020
amid
amid
the
current
the current
account
account
adjustment,
adjustment,
disbursement
disbursement
from from
to the exchange rates of Russia and Kazakhstan (figure
inflation,
the real
effective
exchange
rate depreciated
some
some
donors,
donors,
and
extensive
and
extensive
gold
purchases
gold
purchases
by
the
by
BoM.
the
BoM.
In
fact,
In
gross
fact,
gross
international
international
reserves
reserves
reached
reached
a
a
I.28). Such moderate depreciation was supported by
by over 3 percent (y/y) by November 2020.
historically
historically
high level
high level
of US$4.5
of US$4.5
billionbillion
(equivalent
(equivalent
to over
to seven
over seven
months
months
of imports)
of imports)
at end‐2020,
at end‐2020,
up from
up from
US$4.3
US$4.3
billionbillion
in 2019.
in 2019.
Figure I.26. FX reserves recovered strongly after
Figure I.27. …and the exchange rate stabilized
aFigure
sharpFigure
fall in
H1,
supported
by
eased
current
in
H2…and
after…and
a moderate
depreciation
ininthe
I.26.
FX
I.26.
reserves
FX
reserves
recovered
recovered
strongly
strongly
after aafterFigure
a Figure
I.27.
I.27.
the
exchange
the exchange
rate stabilized
rate stabilized
H2 in H2
account
adjustment
and
gold
first
supported
by purchases…
eased
by eased
current
current after aafter
sharpsharp
fall
infall
H1,insupported
H1,
moderate
ahalf
moderate
depreciation
depreciation
in theinfirst
thehalf
first half
account
account
adjustment
adjustment
and gold
andpurchases…
gold purchases…
Gross international reserves (GIR) (billion US$)
Gross international
Gross international
reserves
reserves
(GIR) (billion
(GIR) (billion
US$) US$)
5.0
5.0
4.5
4.5
4.0
4.0
3.5
3.5
3.0
3.0
2.5
2.5
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
0.0
Exchange rate: Tugrug (Spot rate, Index, Dec 31, 2015=100)
Exchange
Exchange
rate: Tugrug
rate: Tugrug
(Spot rate,
(SpotIndex,
rate, Index,
Dec 31,Dec
2015=100)
31, 2015=100)
145
145
135
135
140
140
130
MNT/CNY
MNT/CNY
Depreciation
Depreciation
130
125
125
120
120
115
115
110
110
105
105
100
95
MNT/US$MNT/US$
100
95
Sep-20
Dec-20
Jun-16
Dec-15
Sep-16
Mar-16
Dec-16
Jun-16
Mar-17
Sep-16
Jun-17
Dec-16
Sep-17
Mar-17
Dec-17
Jun-17
Mar-18
Sep-17
Jun-18
Dec-17
Sep-18
Mar-18
Dec-18
Jun-18
Mar-19
Sep-18
Jun-19
Dec-18
Sep-19
Mar-19
Dec-19
Jun-19
Mar-20
Sep-19
Jun-20
Dec-19
Sep-20
Mar-20
Dec-20
Jun-20
Dec-15
Mar-16
Sep-20
Dec-20
Dec-20
Jun-20
Jun-20
Dec-19
Sep-20
Mar-20
Dec-19
Jun-19
Mar-20
Sep-19
Jun-19
Dec-18
Sep-19
Mar-19
Dec-18
Jun-18
Mar-19
Sep-18
Jun-18
Dec-17
Sep-18
Mar-18
Dec-17
Jun-17
Mar-18
Sep-17
Sep-17
Mar-17
Jun-17
Dec-16
Dec-16
Mar-17
supported by the intervention of the BoM, which continued to sell foreign exchange on the domestic
market.
In fact,byBoM’s
gross foreign
exchange
interventions
direct
FX purchases
from large
supported
the intervention
of the
BoM, which
continued (excluding
to sell foreign
exchange
on the domestic
Source:
Source:
BoM.
BoM.
Source:
Source:
BoM.
BoM.
mining
companies)
reached
US$2.63
billion
in
2020,
close
to
the
US$2.87
billion
in
2019
(figure
I.29).
market. In fact, BoM’s gross foreign exchange interventions
Source:
Source: BoM.(excluding direct FX purchases from large
Note:BoM.
FX
Note:
= foreign
FX = foreign
exchange.
exchange.
mining
companies)
reached
US$2.63the
billion
in 2020, close
to therate
US$2.87
billion in
I.29).
Nonetheless,
with
moderate
inflation,
real effective
exchange
depreciated
by2019
over (figure
3 percent
(y/y)
Note:
FX = foreign
exchange.
Nonetheless,
with moderate inflation, the real effective exchange rate depreciated by over 3 percent (y/y)
by November
2020.
Theby
tugrug
The
tugrug
depreciated
depreciated
moderately
against
against
the US
thedollar
US dollar
in 2020
in 2020
supported
supported
by foreign
by foreign
exchange
exchange
(FX) (FX)
November
2020. moderately
interventions.
interventions.
In nominal
In nominal
terms,
terms,
the tugrug
the tugrug
depreciated
depreciated
by 4.2bypercent
4.2 percent
against
against
the U.S.
thedollar
U.S. dollar
and by
and
11.2
by 11.2
FigureI.28.
I.28.The
Thetugrug
tugrugdepreciation
depreciation was
was moderate
moderate
Figure
I.29.
…supported
by
FX
interventionsby
bythe
the
Figure
Figure
I.29.
…supported
by
FX
interventions
percent
percent
against
against
the
Chinese
the
Chinese
RMB
RMB
in
2020
in
2020
(figure
(figure
I.27).
I.27).
The
depreciation
The
depreciation
of
the
of
tugrug
the
tugrug
was
smaller
was
smaller
in
2020
in
2020
Figure
I.28.
The
tugrug
depreciation
was
moderate
Figure
I.29.
…supported
by
FX
interventions
by
the
compared
to
Mongolia’s
structural
peers...
BoM,
particularly
in
the
first
half
of
2020
compared to Mongolia’s structural peers...
BoM, particularly in the first half of 2020
relative
relative
to
the
to
exchange
the
exchange
rates
rates
of
Russia
of
Russia
and
Kazakhstan
and
Kazakhstan
(figure
(figure
I.28).
I.28).
Such
Such
moderate
moderate
depreciation
depreciation
was
was
compared to Mongolia’s structural peers...
BoM, particularly in the first half of 2020
Nominal
exchange
rate
perUS$
US$(y/y
(y/y change,
change, end-2020)
Nominal
exchange
rate
per
end‐2020)
Nominal exchange rate per US$ (y/y change, end‐2020)
Russia
Kazakhstan
19.2%
Russia
10.3%
Kazakhstan
South Africa
4.8%
South Africa
19.2%
10.3%
4.2%4.2%
Botswana
Botswana
Indonesia
Indonesia
1.5
1.5
Japan Japan-5.0% -5.0%
China
-6.2%
-6.2%
Euro -8.2%
Euro -8.2%
Sources: https://www.x‐rates.com/; BoM; World Bank staff
Sources: https://www.x-rates.com/;
BoM; World
Bank
staff estimates.
Sources:
https://www.x‐rates.com/;
BoM;
World
Bank staff
estimates.
estimates.
MNT/USD (eop): RHS
2490
2490
2.5
2.5
0.9%0.9%
-1.7% -1.7%
MNT/USD (eop): RHS
3
22
11
0.5
0.5
0
0
3100
28503100
2850
2900
2734
TheBoM's
BoM's net
net sales
(bn(bn
US$):
LHSLHS
The
sales of
offoreign
foreignexchange
exchange
US$):
3
1.2%1.2%
Chile Chile -3.9% -3.9%
China
The BoM’s net FX sales and MNT/US$
3.5
28 28
3.5
4.8%
Mongolia
Mongolia
Malaysia
Malaysia
BoM’s and
net FX
sales and MNT/US$
The BoM’s netThe
FX sales
MNT/US$
1.9
1.9
11
1.8
1.8
1888
1888
1659
1659
1996
1996
2012
2427
2427
1.61.6
2.872.87
2700
2300 2300
2100 2100
1900 1900
1.2
1700 1700
1500 1500
0.1
0.1
2013
2013
2014
2014
2015
2015
2700
2500 2500
2.63 2.63
1.5 1.5
1.2
1392
1392
2012
2900
26432734
2643
2016
2016
2017
2018
2017
2019
2018
2020
2019
1300
2020
1300
Sources: BoM; World Bank staff estimates.
Sources:BoM;
BoM; World
staffstaff
estimates.
Sources:
WorldBank
Bank
estimates.
Note: The BoM’s gross FX sales exclude its direct FX purchases
Note:The
TheBoM’s
BoM’s gross
FXFX
sales
exclude
its direct
FX purchases
from
Note:
gross
sales
exclude
itsindirect
purchases
from large mining companies, which started
June FX
2018.
eop
large
mining
companies,
which started
in started
June 2018.ineop
= end-offrom
large
mining
companies,
which
June
2018. eop
= end‐of‐period;
RHS
=
right‐hand
side;
LHS
=
left‐hand
side.
period; RHS = right-hand side; LHS = left-hand side.
= end‐of‐period; RHS = right‐hand side; LHS = left‐hand side.
A6. Monetary conditions have eased, but risks in the banking sector are building as asset
A6. Monetary
conditions have eased, but risks in the banking sector are building as asset
quality deteriorates
quality
deteriorates
17
Prior to the onset of the COVID‐19 pandemic, monetary policy focused on addressing unsustainable
well within
the BoM’sunsustainable
target of 8
macroprudential
measures.
As inflation
Priorcredit
to thegrowth
onsetthrough
of the COVID‐19
pandemic,
monetary
policywas
focused
on addressing
in 2018–19,
BoM focused onmeasures.
addressing As
unsustainable
credit
growth
(particularly
inflation was
well
within
the BoM’shousehold
target of 8
creditpercent
growth
through the
macroprudential
loans)
and
external
imbalances
with
a
mix
of
contractionary
monetary
and
macroprudential
policy
percent in 2018–19,
the BoM focused on addressing unsustainable credit growth (particularly household
24
measures.
In fact, the rapid credit expansion in 2017–18 was channeled mainly to households, and
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
A6. Monetary conditions have eased, but
risks in the banking sector are building as
asset quality deteriorates
Prior to the onset of the COVID-19 pandemic,
monetary policy focused on addressing unsustainable
credit growth through macroprudential measures.
As inflation was well within the BoM’s target of 8
percent in 2018–19, the BoM focused on addressing
unsustainable credit growth (particularly household
loans) and external imbalances with a mix of
contractionary monetary and macroprudential policy
measures.24 In fact, the rapid credit expansion in
2017–18 was channeled mainly to households, and
consequently, the household debt-to-income ratio was
estimated to have reached as high as about 70 percent
at end-2018, up from an average of 39 percent in 2012.
As a result of macroprudential measures, broad money
growth and domestic credit growth fell from 23 percent
and 26.5 percent, respectively, in December 2018, to 7
percent and 5.1 percent in December 2019 (figure I.30).
medium term. The BoM has also been trying to nudge
banks to use their excess liquidity to support economic
activities by making it relatively unattractive for banks
in the short run to passively deposit funds with the
central bank in the form of central bank bills. Moreover,
the central bank reduced the reserve requirement ratio,
and introduced a longer-term liquidity instrument to
further encourage banks to lend their excess liquidity.
In addition, the BoM reengaged with the government’s
subsidized mortgage program, introduced a freeze
on mortgage loan repayments, engaged in several
asset purchasing programs, and provided soft loans to
banks to support non-mineral export industries and
SMEs. In total, these measures are estimated to cost
around 3 percent of GDP, while the effective cost of
other regulatory measures could not be estimated
(see box I.4).
The impact of the monetary policy easing was
mitigated by a credit contraction amid the pandemic.
Broad money growth accelerated to 16 percent (y/y) in
December, from its recent low of 1.6 percent in April
2020. However, domestic credit growth remained in
In 2020, the monetary policy stance shifted toward
negative territory while banking sector excess reserves
mitigating the economic impact of the pandemic.
continued to increase gradually (figure I.31). The
Since March
2020,
theexcess
BoM lowered
its policy
rate fourthe BoM
banks
to lend
their
liquidity.
In addition,
reengaged with the government’s subsidized
overall economic contraction, rising nonperforming
times
by
a
cumulative
500
basis
points
to
6
percent,
mortgage program, introduced a freeze on mortgage loan repayments, engaged in several asset
loans, and risk aversion due to heightened uncertainty
a historical low
(figure I.30).
The goal was
reduce
purchasing
programs,
and provided
softtoloans
to banks
to support non‐mineral export industries and
made banks
reluctant
to lend
and the
companies
reluctant
marketIn
interest
boost domestic
demand intothe
SMEs.
total,rates
theseand
measures
are estimated
cost around
3 percent
of GDP,
while
effective
cost of
other regulatory measures could not be estimated (see box I.4).
Sources:
BoM;World
World
Bank
estimates.
Sources: BoM;
Bank
staffstaff
estimates.
Note:
RHS==right-hand
right‐hand
side;
= left‐hand
Note: RHS
side;
LHSLHS
= left-hand
side. side.
Sep‐20
Dec‐20
Jun‐20
0%
Dec‐19
5%
‐10%
Mar‐20
10%
‐5%
Jun‐19
15%
0%
Sep‐19
20%
5%
Dec‐18
0%
25%
10%
Mar‐19
Dec-20
Sep-20
Jun-20
Mar-20
Dec-19
Sep-19
Jun-19
Mar-19
Dec-18
Sep-18
-10%
30%
Dec‐17
5%
0%
35%
15%
Mar‐18
10%
40%
20%
Jun‐17
10%
25%
Sep‐17
20%
Excess reserves to deposit ratio (%): RHS
Domestic credit growth (y/y): LHS
30%
15%
Mar‐17
M2 growth (y/y): LHS
Bank loan growth (y/y): LHS
Policy rate: RHS
30%
Domestic
creditexcess
and banks
excess reserves
Domestic credit
and banks
reserves
Jun‐18
Money domestic
supply, domestic
and policy
Money supply,
credit,credit,
and policy
rate rate
Figure I.31. However, banks have been reluctant to
Figure
I.31.
However,
banks
haveexcess
been reserves
reluctant to
lend
despite
having
sizable
lend despite having sizable excess reserves
Sep‐18
Figure I.30. The monetary policy rate was lowered
Figure
I.30. The low
monetary
policy
rate
was lowered
to a historical
to revive
credit
growth
to a historical low to revive credit growth
Sources:
BoM;
staffestimates.
estimates.
Sources:
BoM;World
World Bank
Bank staff
Note:Note:
RHSRHS
= right‐hand
LHS==left-hand
left‐hand
side.
= right-handside;
side; LHS
side.
The impact of the monetary policy easing was curtailed by a credit contraction amid the pandemic.
Broad money growth accelerated to 16 percent (y/y) in December, from its recent low of 1.6 percent in
These2020.
include macroprudential
measures aimed
at limiting
the debt-to-income
individual borrowers
from aswhile
high as 100
to 60 percent,
April
However, domestic
credit
growth
remainedratio
in aofnegative
trajectory
thepercent
banking
sector
reducing the maturity on non-mortgage household loans, and raising the risk weight on unhedged foreign currency borrowing.
excess reserves continued to increase gradually (figure I.31). Interestingly, the overall economic
contraction,
rising nonperforming loans, and risk aversion due to heightened uncertainty largely explained
18
the persistence of credit contraction, despite some support from monetary policy easing. This provides
the BoM the justification to pursue banking sector clean up to prevent a long balance sheet stagnation.
24
Box I.4. The Bank of Mongolia’s measures to mitigate the impact of COVID‐19
ECONOMIC PERFORMANCE AND PROSPECTS
Box I.4.
The Bank of Mongolia’s measures to mitigate the impact of COVID-19
The Monetary Policy Committee (MPC) of the Bank of Mongolia (BoM) met six times since the start of the COVID-19
pandemic in February 2020. Several decisions were taken by the MPC aimed at boosting credit growth, relieving the
debt burden, and supporting liquidity of the banking system. These include:
•
Reducing the policy rate sequentially from 11 percent to 6 percent, over meetings held in March, April,
September, and November 2020. As the inflation outlook remained within the central bank’s target, reduction
of the policy rate was intended to relieve the financing costs of banks, support financial intermediation, and
stimulate domestic demand.
•
Relaxing the condition of repo financing instruments to support liquidity of the banks. The MPC narrowed the
interest rate corridor by 200 basis points, which effectively reduced the interest rate on the short-term repo
instrument. In September, the maturity of the longer-term repo instrument was temporarily extended from 90
days to 180 days and its interest rate reduced from 16 percent to 11 percent. Consequently, banks could borrow
from the BoM at a lower rate and for a longer term.
•
Releasing more liquidity to the banking system by reducing the required reserve ratio on domestic currency
liabilities by 4.5 percentage points to 6 percent in March. As a result, an estimated MNT 730 billion was
released to the market.
•
Promoting incentives to reduce interest rates on FX deposits and discourage deposit dollarization by reducing
remunerationa provided to banks by the amount equivalent to their FX deposits and interest-bearing FX current
accounts. In addition to applying higher reserve requirements on FX liabilities, this measure was intended to
support the stability of the financial system by addressing the growing currency mismatch.
•
Allowing the restructuring and extension of the maturity of consumer loans of troubled borrowers for up to
12 months and later extending the deadline to the end of the year. These measures are intended to reduce
monthly payments of troubled borrowers and support private consumption.b
•
Purchasing assets and providing concessional loans. The BoM purchased municipal bonds to support its
mortgage program (MNT 100 billion) targeting civil servants at the COVID-19 frontline; provided repo loans to
banks to indirectly support loans for non-mineral exports and SMEs (MNT 230 billion), and directly provided
concessional funding for gold companies under the “Gold-2” program (MNT 110 billion).
Under its supervisory function, the BoM made temporary changes to its regulations, effective until the end of 2020.
These include:
•
Loosening the asset classification regulation starting in March so that borrowers’ credit history is not affected.
Consumer and mortgage loans that are in arrears for less than 90 days will be considered normal (the regular
cutoff is 15 days), those in arrears for 91 to 120 days will be considered past due (the regular cutoff is 90 days),
and those that missed payments for over 121 days would be considered nonperforming.
•
Reducing the liquidity ratio for banks from 25 percent to 20 percent, so that banks could reduce their liquid
assets and create room for issuing loans.
•
Encouraging banks to reduce their transaction fees and removing FX deposits from the insurance coverage to
discourage deposit dollarization.
19
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Under the framework of a Parliamentary resolution to support the economy amid COVID-19, passed on April 29, the
BoM took the following measures:
•
Allowing the freezing of payments of the subsidized mortgage program and extending its maturity for up to
six months (later extended by eight more months). The subsidized mortgage borrowers were given a one-time
option to restructure their loans without any interest accrual on their balance starting May 1. As of June 19,
38,270 borrowers had restructured their loans and delayed payments of MNT 121 billion MNT. In November, the
freeze period was extended by eight more months and is expected to delay payments of MNT 310 billion.
•
Continuing to finance the subsidized mortgage program. As agreed under the IMF Extended Fund Facility
program and the World Bank’s Economic Management Support Operation series, BoM financing of the subsidized
mortgage program ended on January 1, 2020. However, the Law on Pandemic Preparedness and Response of
April 2020 reauthorized BoM’s financing of the program, which currently amounts to about MNT 245 billion.
Source: BoM.
Note: a. The BoM provides some remuneration to banks for their assets held at the central bank in accordance with the reserve requirement.
b. The option to restructure is usually not restricted by the BoM. However, loans issued before January 1, 2019, were not capped by the ceiling of
60 percent set on the debt-service-to-income ratio and a 30-month term limit. Restructuring these loans would have violated either one of these
restrictions. The BoM therefore provided a one-time pardon on the term limit of 30 months to reduce the debt burden of households.
to invest – explaining the limited impact of monetary
policy easing on credit growth. A thorough clean-up
of bank balance sheets post crisis may be needed to
encourage fresh lending activity and thus support the
recovery.
rapidly, weakening income of households and lower
profitability of the corporates have curtailed their
potential to borrow, as well. According to the NSO’s
survey, 64.2 percent of firms reported an income loss
over 50 percent due to the COVID-19 shock. Corporate
loan issuance has been declining in all sectors and
The credit contraction was prolonged as consumers
seems most severe in key sectors such as construction,
and small businesses were severely hit by the COVID-19
trade, transportation, manufacturing, and mining (figure
shock. Domestic credit contracted by about 5 percent in
I.32). In addition to tighter conditions and weakening
2020,
marking
a contraction
ofseems
10 consecutive
months.
declining
in
all
sectors
and
most
severe
in
key
sectors
such
asasconstruction,
trade,
transportation,
the
decelerating
preference
of households
for
declining in all sectors and seems most severe in keyincome,
sectors
such
construction,
trade,
transportation,
While
banks
have
tightened
their
loan
issuance
to
manufacturing,
tototighter
conditions
and
weakening
income,
the
durable
goods
such as cars
may
have contributed
manufacturing,and
andmining
mining(figure
(figureI.32).
I.32).InInaddition
addition
tighter
conditions
and
weakening
income,to
the
corporates
and preference
households as
quality deteriorated
decelerating
households
for
such
asascars
have
declining
loan
issuance
I.33).
decelerating
preferenceofofloan
households
fordurable
durablegoods
goods
such
carsmay
may(figure
havecontributed
contributedtotodeclining
declining
Sources: BoM; World Bank staff estimates.
Sources:
Sources:BoM;
BoM;World
WorldBank
Bankstaff
staffestimates.
estimates.
-30%
-30%
Dec-20
Dec-20
Dec-18
Dec-18
Feb-19
Feb-19
Apr-19
Apr-19
Jun-19
Jun-19
Aug-19
Aug-19
Oct-19
Oct-19
Dec-19
Dec-19
Feb-20
Feb-20
Apr-20
Apr-20
Jun-20
Jun-20
Aug-20
Aug-20
Oct-20
Oct-20
Dec-20
Dec-20
-30%
-30%
Oct-20
Oct-20
-20%
-20%
-10%
-10%
Aug-20
Aug-20
0%0%
-10%
-10%
10%
10%
Jun-20
Jun-20
10%
10%
Apr-20
Apr-20
20%
20%
30%
30%
Feb-20
Feb-20
30%
30%
Dec-19
Dec-19
40%
40%
Salary
and
pension
backed
Salary
and
pension
backed
Deposit
backed
loans
Deposit
backed
loans
Credit
card
Credit
card
Others
Others
Entrepreneurs
and
SMEs
Entrepreneurs
and
SMEs
Household
loan
Household
loan
50%
50%
Oct-19
Oct-19
50%
50%
Agriculture
Agriculture
Mining
Mining
Manufacturing
Manufacturing
Construction
Construction
Trade
Trade
Transportation
Transportation
Other
Other
Corporate
loans
Corporate
loans
Aug-19
Aug-19
60%
60%
Jun-19
Jun-19
70%
70%
Individual
loans
issuance
(a 12-month
rolling
sum,
y/y)
Individual
loans
(a(a12‐month
rolling
sum,
y/y)
Individual
loansissuance
issuance
12‐month
rolling
sum,
y/y)
Apr-19
Apr-19
Corporate
loans
issuance
(a12‐month
12-month
rolling
sum,
y/y)
Corporate
loans
issuance
(a(a
y/y)
Corporate
loans
issuance
12‐monthrolling
rollingsum,
sum,
y/y)
Figure I.33. Banks have also tightened new loan
Figure
I.33.
have
tightened
loan
Figure
I.33.Banks
Banks
havealso
also
tightenednew
new
loan
issuance
to
individuals,
entrepreneurs,
and
SMEs
issuance
issuancetotoindividuals,
individuals,entrepreneurs,
entrepreneurs,and
andSMEs
SMEs
Feb-19
Feb-19
Figure I.32. Corporate loans issuance has been
Figure
Corporate
loans
FigureI.32.
I.32.
Corporate
loansissuance
issuancehas
hasbeen
been
declining
across
sectors
declining
decliningacross
acrosssectors
sectors
Dec-18
Dec-18
loan
loanissuance
issuance(figure
(figureI.33).
I.33).
Sources: BoM; World Bank staff estimates.
Sources:
Sources:BoM;
BoM;World
WorldBank
Bankstaff
staffestimates
estimates
Asset
Assetquality
qualityofofthe
thebanking
bankingsystem
systemhas
hasdeteriorated
deterioratednotably,
notably,reflecting
reflectingthe
theimpact
impactofofthe
thepandemic.
pandemic.
20
The
Thenonperforming
nonperformingloans
loans(NPLs)
(NPLs)ofofcommercial
commercialbanks
banksreached
reachedMNT
MNT22trillion
trillionbybyDecember,
December,a a1010percent
percent
increase
increaserelative
relativetotoend‐2019.
end‐2019.The
TheNPL
NPLratio
ratio(nonperforming
(nonperformingloans
loanstotototal
totaloutstanding
outstandingloans)
loans)increased
increased
toto11.7
11.7percent
percentininDecember
Decemberfrom
from10.1
10.1percent
percentininDecember
December2019
2019(figure
(figureI.34).
I.34).Past‐due
Past‐dueloans
loanshave
havebeen
been
increasing
increasingmore
morerapidly.
rapidly.The
Theamount
amountofofpast‐due
past‐dueloans
loansreached
reachedabout
aboutMNT
MNT1.3
1.3trillion
trillionfrom
fromMNT
MNT816
816
loans
jumped
to
7.4
percent
in
December
billion
in
December
2019.
The
ratio
of
past‐due
loans
to
total
billion in December 2019. The ratio of past‐due loans to total loans jumped to 7.4 percent in December
ECONOMIC PERFORMANCE AND PROSPECTS
Asset quality of the banking system has deteriorated
notably, reflecting the impact of the pandemic.
The nonperforming loans (NPLs) of commercial
banks reached MNT 2 trillion by December, a 10
percent increase relative to end-2019. The NPL ratio
(nonperforming loans to total outstanding loans)
increased to 11.7 percent in December from 10.1
percent in December 2019 (figure I.34). Past-due loans
have been increasing more rapidly. The amount of pastdue loans reached about MNT 1.3 trillion from MNT
816 billion in December 2019. The ratio of past-due
loans to total loans jumped to 7.4 percent in December
from 4.5 percent at end-2019. Problematic loans (NPLs
and past-due loans) are likely to rise further once
forbearance on identification of these loans expires
as planned by July 2021. According to the BoM, as of
September 2020, over 20 percent of total loans in
the banking sector were affected by the pandemic,
and additional loans may become problematic once
regulatory forbearance is scaled back. Across sectors,
the mining sector claimed the highest proportion of
loans affected by the COVID-19 shock (46 percent),
followed by construction (38 percent), trade (35
percent), and real estate (26 percent) (figure I.35).
The adequacy of loan loss provisions (LLP) for both
corporate and individual loans is uncertain.25 As of
December 2020, LLP for corporate loans stood at MNT
1.2 billion. This covers over 80 percent of NPLs and
around half of the value of problematic loans (NPLs
+ past due loans), (figure I.36). The LLP coverage
of problematic loans for the mining, construction,
manufacturing, and trade sectors ranged between 33
and 77 percent, while these sectors combined account
for about 70 percent of total problematic loans.
Meanwhile, 51 percent of the value of problematic
loans issued to individuals is currently covered by
provisions (figure I.37). The weakest provisioned loans
are car loans.
Figure I.34. Loan quality has deteriorated
notably…
Figure I.34. Loan quality has deteriorated notably…
Figure I.35. …mainly in the mining, construction, and
trade
sectors
Figure
I.35. …mainly in the mining, construction,
Figure I.34. Loan quality has deteriorated
NPLs and past‐due loans in percent to outstanding loans
NPLsnotably…
and past-due loans in percent to outstanding loans
12%
NPLs and past‐due loans in percent to outstanding loans
12%
Outstanding NPLs and past-due loans in Dec 2019
500
400
400
NPLs
300
300
6%
200
4%
100
100
Nov-20
Sep-20
Nov-20
Jul-20
Sep-20
Jul-20
May-20
Jan-20
May-20
Mar-20
Mar-20
Jan-20
Nov-19
Jul-19
Sep-19
Nov-19
May-19
Sep-19
200
May-19
Jan-19
Mar-19
Jan-19
4%
New
NPLs and past-due
loans
since Decloans
2019 in Dec 2019
Outstanding
NPLs and
past-due
500
Past-due loans
NPLs
8%
6%
700 Increase
Increase
of problematic
loans
sector
(in(inbillions
MNT)
of problematic
loans
by
sector
billions
MNT)
Newby
NPLs
and past-due
loansofof
since
Dec 2019
600
Past-due loans
10%
8%
Figure I.35. …mainly in the mining, construction, and
Increase
of problematic
and trade
sectors loans by sector (in billions of MNT)
trade sectors
700
600
Mar-19
Jul-19
10%
The banking system remains liquid. The liquidity ratio
(liquid assets to total assets) has been trending up
since June 2020 and reached 40.6 percent in December
2020, its highest in the past two years (figure I.38).
Bank reserves stood at 15.9 percent of total deposits
in December 2020, above the reserve requirement
ratios (15 percent for FX deposits and 6.5 percent for
MNT deposits). However, this is a reduction from 25.6
percent in April 2020 mainly due to a steady increase
in FX deposits (denominator) until September 2020.26
Sources: BoM; World Bank staff estimates.
Sources:
BoM;Bank
Worldstaff
Bankestimates.
staff estimates.
Sources: BoM;
World
00
Mining
Mining
Construction
Construction
Trade
Trade
Real estate
Agriculture
Real estate
Agriculture
Sources: BoM; World Bank staff estimates.
Sources:BoM;
BoM; World
estimates.
Sources:
WorldBank
Bankstaff
staff
estimates.
There are limited provisions for pandemic‐related loan losses, as loan loss provisions (LLP) remain low
There are
limited provisions for pandemic‐related
loan losses, as loan loss provisions (LLP) remain low
23
As of December 2020, LLP for corporate loans stood at MNT
for both corporate and individual loans.
23
of December
LLP for
stood at MNT
for both1.2
corporate
and individual
billion. Although
this coversloans.
over 80 As
percent
of NPLs, it 2020,
is equivalent
to corporate
only half ofloans
the problematic
1.2 billion.
Although
this
covers
over
80
percent
of
NPLs,
it
is
equivalent
to
only
half
of
the
problematic
loans (NPLs + past‐due loans) (figure I.36). The LLP share of problematic loans for the mining, construction,
loans (NPLs
+ past‐dueand
loans)
(figure
I.36).
The between
LLP share33ofand
problematic
the mining,
construction,
manufacturing,
trade
sectors
ranged
77 percent,loans
whilefor
these
sectors combined
The provision
coverage
ratio is used
determineofhow
banks
are protected from
possible
losses on nonperforming
credits.
account
for
about
70 to
percent
total
problematic
loans.
Meanwhile,
only 51
percent
of the
problematic
manufacturing,
and
trade
sectors
ranged
between
33
and
77
percent,
while
these
sectors
combined
The consistent increase in the FX deposits since March 2020 was reversed in October 2020. From a peak of 31 percent in September 2020, the FX
loans
issued
to
individuals
is
currently
covered
by
provisions
(figure
I.37).
The
weakest
provisioned
loans
deposit - total
ratio
25.7 percent
in December
2020, its levelloans.
in March–April
2020.
account
fordeposit
about
70reached
percent
of total
problematic
Meanwhile,
only 51 percent of the problematic
are car loans.
loans issued to individuals is currently covered by provisions (figure I.37). The weakest provisioned loans
21
are car loans.
Figure I.36. Provisions to loans of risky sectors seem Figure I.37. Banks should also take hefty charges as
25
26
low
Sectoral
assessment
corporate
loans, sectors
Decemberseem
2020
Figure I.36.
Provisions
toofloans
of risky
low
Problematic loans (% of total loans in each sector)
the COVID‐19 impact intensifies
Household
and SME
loans,also
December
2020 charges as
Figure
I.37.loans
Banks
should
take hefty
the80%COVID‐19 impact intensifies
69%
1.2
1.2billion.
billion.Although
Althoughthis
thiscovers
coversover
over80
80percent
percentof
ofNPLs,
NPLs,ititisisequivalent
equivalentto
toonly
onlyhalf
halfof
ofthe
theproblematic
problematic
loans
loans(NPLs
(NPLs++past‐due
past‐dueloans)
loans)(figure
(figureI.36).
I.36).The
TheLLP
LLPshare
shareof
ofproblematic
problematicloans
loansfor
forthe
themining,
mining,construction,
construction,
manufacturing,
manufacturing, and
and trade
trade sectors
sectors ranged
ranged between
between 33
33 and
and 77
77 percent,
percent, while
while these
these sectors
sectors combined
combined
account
account
for
forabout
about
70
70percent
percent
of
oftotal
total
problematic
loans.
loans.Meanwhile,
Meanwhile,only
only51
51percent
percentof
ofthe
theproblematic
problematic
MONGOLIA
ECONOMIC
UPDATE
Fromproblematic
Relief to Recovery
loans
loansissued
issuedto
toindividuals
individualsisiscurrently
currentlycovered
coveredby
byprovisions
provisions(figure
(figureI.37).
I.37).The
Theweakest
weakestprovisioned
provisionedloans
loans
are
arecar
carloans.
loans.
Figure
I.36.
Provisionsto
toloans
loansofof
ofrisky
risky
sectors
Figure
I.37.
Banks
should
also
takehefty
heftycharges
chargesas
Figure
Figure
I.36.
I.36.
Provisions
Provisions
to
loans
riskysectors
sectorsseem
seem Figure
Figure
I.37.
I.37.
Banks
Banks
should
should
also
also
take
take
hefty
charges
as
seem
low
as
the
COVID-19
impact
intensifies
low
low
the
theCOVID‐19
COVID‐19impact
impactintensifies
intensifies
Sectoral
Sectoral
assessment
assessment
ofofcorporate
loans,December
December
2020
2020
Sectoral
assessment
ofcorporate
corporateloans,
loans,
December
2020
100%
100%
87%
87%
60%
60%
Problematic
Problematicloans
loans(%
(%ofoftotal
totalloans
loansinineach
eachsector)
sector)
80%
80%
LLP
LLP(%
(%ofofproblematic
problematicloans
loansinineach
eachsector)
sector)
70%
70%
77%
77%
80%
80%
50%
50%
20%
20%
68%
68%
52%
52%
31%
31%
56%
56%
51%
51%
44%
44%
50%
50%
48%
48%
40%
40%
40%
40%
33%
33%
32%
32%
19%
19%
Problematic
Problematicloans
loans(%
(%ofoftotal
totalloans
loansinineach
eachcategory)
category)
30%
30%
49%
49%
33%
33%
0%
0%
69%
69%
62%
62%
60%
60%
54%
54%
40%
40%
33%
33%
Household
Household
loans
loansand
and
SME
SME
loans,
loans,
December
December
2020
2020
Household
loans
and
SME loans,
December
2020
LLP
LLP(%
(%ofofproblematic
problematicloans
loansinineach
eachcategory)
category)
20%
20%
13%
13%
10%
10%
0%
0%
14%
14%
9%
9%
9%
9%
Total
Total
Others
Others
15%
15%
7%
7%
Creditcard
card
Credit
Salary&&
Carloans
loans
Salary
Car
pension
pension
backedloans
loans
backed
Sources:
Sources:BoM;
BoM;World
WorldBank
Bankstaff
staffestimates.
estimates.
Sources: BoM; World Bank staff estimates.
Note:
Note:Problematic
Problematicloans
loans==NPLs
NPLs++past‐due
past‐dueloans.
loans.
Note: Problematic loans = NPLs + past-due loans.
The
Thebanking
bankingsystem
systemseems
seemsto
toremain
remainliquid.
liquid.The
Theliquidity
liquidityratio
ratio(liquid
(liquidassets
assetsto
tototal
totalassets)
assets)has
hasbeen
been
However, the risk of currency mismatch remains high in
mounting external pressures, particularly in the first half
trending
trendingup
upsince
sinceJune
June2020
2020and
andreached
reached40.6
40.6percent
percentininDecember
December2020,
2020,its
itshighest
highestininthe
thepast
pasttwo
twoyears
years
the banking system. The share of foreign liabilities in
of the year. Deposit dollarization has declined somewhat
(figure
(figureI.38).
I.38).Bank
Bankreserves
reservesstood
stoodatat15.9
15.9percent
percentof
oftotal
totaldeposits
depositsininDecember
December2020,
2020,above
abovethe
thereserve
reserve
the banking system is almost triple the size of foreign
in recent months amid an improving current account
requirement
requirementratios
ratios(15
(15percent
percentfor
forFX
FXdeposits
depositsand
and6.5
6.5percent
percentfor
forMNT
MNTdeposits).
deposits).However,
However,this
thisisisaa
assets, which exposes banks to high risks of currency
balance and sequential policy measures by the BoM,
mismatch. In fact, FX deposits reached 31 percent of
including setting higher reserve requirements on FX
total deposits in September 2020, the highest rate in
deposits and removing its insurance coverage in case
2323The
Theprovision
provisioncoverage
coverageratio
ratioisisused
totodetermine
determinehow
howbanks
banksare
areprotected
from
frompossible
possiblelosses
losseson
onnonperforming
nonperformingcredits.
credits.
two
years,
while
FX loans
wereused
9 percent
of total
loans
of protected
bank failures
(see
box I.4).
Nevertheless,
the large
gap
(figure I.39). Credit risk associated with exchange rate 33
33between deposit dollarization and credit dollarization
fluctuation is now relatively moderate as banks have
in times of an uncertain external environment exposes
significantly tightened their condition for FX loans
banking system balance sheets to significant fluctuations
over the past few years. In contrast, households and
in the exchange rate.
reduction
25.6 percent
2020following
mainly due to a steady increase in FX deposits (denominator)
corporates from
have ramped
up theirinFXApril
deposits
reduction from 24
25.6 percent in April 2020 mainly due to a steady increase in FX deposits (denominator)
until September
2020.
reduction
from 25.6
percent
in April 2020 mainly due to a steady increase in FX deposits (denominator)
24
until
September
2020.
24
until
September
2020.
Figure I.38. The liquidity of the banking system
Figure I.39. …however, the banking system remains
Figure I.38.
TheI.38.
liquidity
of the of
banking
system
I.39.I.39.
…however,
the banking
system
Figure
The liquidity
the banking
system Figure
Figure
…however,
banking
system remains
remains
has remained
steady...
vulnerable
to risk of the
currency
mismatch
Figure
I.38. The
liquidity of the banking system vulnerable
Figure
I.39.
…however,
the banking
system remains
has remained
steady...
to risk
of of
currency
mismatch
has remained
steady...
vulnerable
to
risk
currency
mismatch
has remained
steady...
Liquid assets/total
asset (%) asset (%)
Liquid assets/total
13%
Sources: BoM; World Bank staff estimates.
Oct-20
Oct-20
Oct-20
Dec-20
Dec-20
Dec-20
Aug-20
Aug-20
Aug-20
Apr-20
Apr-20
Sources: BoM; World Bank staff estimates.
Jun-20
Jun-20
Jun-20
Feb-20
Feb-20
Apr-20
Feb-20
Oct-19
Oct-19
Dec-19
Dec-19
Oct-19
Dec-19
Jun-19
Jun-19
Aug-19
Aug-19
Apr-19
Apr-19
Jun-19
Aug-19
Feb-19
Feb-19
Apr-19
Dec-18
Dec-18
Feb-19
Oct-18
Aug-18
Aug-18
Dec-18
Oct-18
Oct-18
8%
8%
Jun-18
8%
Aug-18
Jun-18
Jun-18
Oct-20
Oct-20
Dec-20
Dec-20
Aug-20
Aug-20
Dec-20
Jun-20
Jun-20
Sources: BoM; World Bank staff estimates.
Sources:
BoM;
World
Bank
staff estimates.
Sources: BoM;
World
Bank
staff
estimates.
Oct-20
Apr-20
Apr-20
Aug-20
Feb-20
Feb-20
Jun-20
Dec-19
Dec-19
14%
14%
18%
18%
13% 13%
Apr-20
14%
18%
Oct-19
Oct-19
19%
19%
23%
Feb-20
19%
MNT/USD: RHS
23% 23%
Aug-19
Aug-19
Dec-19
24%
24%
24%
FX loans/total
MNT/USD:
MNT/USD:
RHSRHSloans: LHS
28% 28%
28%
Jun-19
Jun-19
Oct-19
29%
29%
Bank reserves/deposits (%)
Jun-19
Feb-19
Feb-19
29%
Apr-19
34%
34%
Feb-19
34%
33% vulnerable
FX deposit/total
LHS
toFX risk
of deposits:
currency
mismatch
33%
deposit/total
deposits:
LHS
33%
FX loans/total
loans:
LHSLHS LHS
deposit/total
deposits:
FX loans/total
loans:
Liquid
assets/total
(%)
Bank reserves/deposits
(%) asset(%)
Bank reserves/deposits
39%
39%
Aug-19
Apr-19
Apr-19
39%
2,830
2,830
2,830
2,780
2,780
2,780
2,730
2,730
2,730
2,680
2,680
2,680
2,630
2,630
2,630
2,580
2,580
2,580
2,530
2,530
2,530
2,480
2,480
2,480
2,430
2,430
2,430
Sources:
World
staff
estimates.
Note:BoM;
FXBoM;
deposits
ofBank
firms
and
households are considered
Sources:
World
Bank
staff
estimates.
Sources:
World Bank
staff estimates.
Note:
FXBoM;
deposits
of
firms
andhouseholds
households
are considered
considered
for
banks,
FXand
loans
are
assets of are
banks.
Note:liabilities
FX deposits
of while
firms
Note: FX deposits
of firms
and
households
are considered
liabilities
for banks,
while
FX
loans are side.
assets
of banks.liabilities
RHS =for
right‐hand
side;
LHS
= left‐hand
liabilities
banks,
while
FX
loans
are
assets
of
banks.
for banks,
while FXside;
loansLHS
are=assets
of banks.
RHS
= right‐hand
left‐hand
side.
RHS =RHS
right‐hand
side;
LHS
= =left‐hand
side.
= right-hand
side;
LHS
left-hand side.
However, risk of currency mismatch remains high in the banking system. The share of foreign liabilities
However,
risk ofsystem
currency
mismatch
remains
high
in
the banking
system.
The share
of foreign
in
the banking
is almost
triple
the
size
foreign
assets,
which The
exposes
banks
to highliabilities
risks of
22
However,
risk
of currency
mismatch
remains
high
inofthe
banking
system.
share
of foreign
liabilities
in the banking system is almost triple the size of foreign assets, which exposes banks to high risks of
currency mismatch. In fact, FX deposits reached 31 percent of total deposits in September 2020, the
in the banking
system
is almost
triple
the size
of foreign
assets,ofwhich
exposesinbanks
to high
risksthe
of
currency
mismatch.
In fact,
FX FX
deposits
reached
31 percent
total (figure
deposits
2020,
highest rate
in two years,
while
loans were
9 percent
of total loans
I.39). September
Credit risk associated
currencyhighest
mismatch.
fact, FX while
depositsloans
reached
percent
of total
deposits
in September
2020, the
rate inIntwo
were 31
9 percent
of total
loans
(figure
I.39).
Credittightened
risk associated
with exchange
rateyears,
fluctuation FX
is now relatively
moderate
as banks
have significantly
their
highest rate
in
two
years,
while
FX
loans
were
9
percent
of
total
loans
(figure
I.39).
Credit
risk
associated
with
exchange
rate
fluctuation
is
now
relatively
moderate
as
banks
have
significantly
tightened
their
condition for FX loans over the past few years. In contrast, households and corporates have ramped
up
ECONOMIC PERFORMANCE AND PROSPECTS
B. Outlook and Risks
OUTLOOK AND
RISKS
The Mongolian economy is expected to recover moderately from the
pandemic, as the latest outbreak has added considerable uncertainty.
Mongolia is expected to have experienced its first recession in a decade
in 2020 as real GDP is estimated to contract by 5.2 percent (table I.2).27
Mongolia trails the Philippines, Thailand, and Malaysia, which are the
other economies projected to be most impacted in the EAP region
(box I.6). The mining and services sectors, particularly, are expected to
be severely hit by weak external demand and COVID-19 containment
measures. However, real GDP growth is projected to accelerate to about
5 percent in 2021-22, supported by a renewed drive of investment in
the mining sector (compounded by higher-grade ore and increased
production of gold) despite delay in the production schedule of Oyu
Tolgoi’s underground development.28 Private investment backed by
FDI and domestic credit (mainly corporate loans) will remain a key
contributor to growth in 2021-22, especially in mining, manufacturing,
and transport services. Private consumption will also support growth in
the medium term.
Monetary policy is expected to be tightened in the medium term as
inflation and external sector pressures re-emerge. Inflation moderated
in 2020 driven by weak domestic demand, lower imports, and negative
credit growth. However, it will pick up gradually in 2021–22, while
exceeding the BoM’s medium-term target as economic activity
recovers.29 Moreover, relatively higher fiscal spending in 2020 compared
to the previous two years and the expected recovery of domestic credit
could generate inflationary pressures in 2021.30 Our base case is built
on the continued commitment of the monetary authorities to price
stability keeping inflation within the central bank’s target, which would
eventually help lower inflation expectations. Interventions in the foreign
exchange market are expected to be limited to smoothing excessive
volatility, allowing more flexibility in exchange rate movements, and
rebuilding international reserves. Further policy rate cuts are unlikely
as the external environment remains uncertain and the central bank’s
policy rate is already at a historical low (6 percent). In addition, the
reserve requirement ratio stands at 6.5 percent, its lowest level since
the 2008–09 global financial crisis, leaving little room for decreasing it
further to induce liquidity into the financial system. Recently introduced
monetary policy tools such as long-term repo transactions (which has
availed MNT 230 billion to banks in Q4 2020 and up to MNT 250 billion
Our estimate of real GDP growth for 2020 contrasts squarely with overoptimistic growth assumptions of the 2021 budget, which considered a 1 percent
contraction in 2020 and 7.2 percent growth in 2021 (see box I.3).
28
This increase in the gold production outlook is the result of initiatives implemented by Oyu Tolgoi that have brought the higher-grade gold-bearing
ore from the South West pit forward into 2020 and 2021. The plan also allows for copper production growth of 315 percent from 2022 to 2028 as well
as gold production growth of 140 percent in the same time frame.
29
Through the approval of 2021 monetary policy guidelines, the BoM reduced its inflation target rate for 2021–23 to 6 percent, with a +/-2-percentagepoint band.
30
IMF 2012.
27
23
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Private Consumption
After a riseGovernment
in 2020, the
government debt-to-GDP ratio
Consumption
is expected
to
decline
again
in the outer years with
Gross Fixed Capital Formation
favorable Exports,
debt dynamics
in
part
driven by a cyclical
Goods and Services
recovery. Imports,
Before Goods
the and
COVID-19
outbreak, broadly
Services
prudent Real
fiscalGDP
management
in 2017–19 led to a sharp
growth, at constant factor prices
reduction in government debt, giving the government
Agriculture
some room to craft a fiscal response. The combination of
Industry (incl mining)
increased spending and an expected decline in revenue
Services
collection is estimated to widen the fiscal deficit
Inflation (CPI, end‐period)
considerably and lead to an increase in government
Current account balance (% of GDP)
debt. The three phases of stimulus packages combined
Financial and Capital account (% of GDP)
Net Foreign Direct Investment (% of GDP)*
‐2.2
5.4
12.4
9.9
7.6
24.5
17.4
1.1
12.7
16.3
2022f
2021f
2019
2020f
2018
2017
2016
2015
2014
2013
2012
amount to approximately over 9 percent of GDP, which
was financed mainly by external concessional lending
and a drawdown of the government’s deposits in the
Further loan forbearance by the BoM could lead to
sovereign wealth fund. With a sizable revenue shortfall
unintended effects including on economic growth in the
and fiscal relief measures, government debt is estimated
medium term. As indicated earlier, the asset quality of
to have risen in 2020 before declining gradually starting
several banks has been threatened amid diminishing
from 2021. However, Mongolia’s debt ratio remains high
corporate
earningsto over
thetopast
few months.
In
are projected
decline
2 percent
of GDP during
2021–23 from 2.6 percent of GDP in 2020 and 2.3
among comparators (figure I.40).
addition,
theinforbearance
measures could be masking
percent
2019.31
a significant amount of problematic loans as discussed
Figure I.40. The government debt-to-GDP ratio
After
rise in 2020,
government
above.
By aSeptember
2020,the
over
20 percentdebt‐to‐GDP
of the
Figure I.40. The government debt‐to‐GDP ratio is
ratiosector
is expected
to had
decline
in theimpacted
outer years is estimated to have risen in 2020 in many
banking
loan book
beenagain
reportedly
estimated to have risen in 2020 in many selected
selected
peers
with favorable
debt
dynamics
in reforms
part driven
by COVID-19.
Therefore,
advancing
bank
wouldby a peers
cyclical
recovery.
Before
the
COVID‐19
outbreak,
Government
debt (in percent
GDP) of GDP)
Government
debt (inofpercent
be critical to support growth in the medium term as
broadly prudent fiscal management in 2017–19 led to 100
Chile
several banks, especially those exposed to sectora sharp reduction in government debt, giving the
China
80
distressed loans, lower earnings, and insufficient capital,
government some room to craft a fiscal response. The
may be vulnerable.
Kazakhstan
combination of increased spending and an expected
60
Malaysia
revenueand
collection
estimated to widen
The decline
2021 inbudget
the is
medium-term
fiscal the
40
fiscal deficit
considerably
and lead
to an increase
framework
for 2021
- 23 are broadly
consistent
with in
Mongolia
government
debt.
The
three
phases
of
stimulus
fiscal consolidation and the debt reduction objective.
20
Peru
combined
amount to Fiscal
approximately
over 9
The packages
government’s
Medium-Term
Framework
Philippines
0
percent
of GDP,
which
projects
an overall
budget
deficitwas
of 1.5financed
percent ofmainly
GDP, by
Russia
externalinconcessional
lendingunder
and aless
drawdown
of the
on average,
2021-23. However,
optimistic
government’s deposits in the sovereign wealth fund. Sources:
Sources:
IMF
2020;
World
Bank
staff
estimates.
IMF 2020; World Bank staff estimates.
revenue projections, we project that the overall
With a sizable revenue shortfall and fiscal relief
fiscal deficit would average about 1.9 percent of GDP
measures, government debt is estimated to have risen in 2020 before declining gradually starting from
during
2021-23.
Financial
support
2021.
However,
Mongolia’s
debtfrom
ratio multilateral
remains high among
Riskscomparators (figure I.40).
and bilateral donors would be necessary to ensure
sustainable financing of the deficit. Interest
payments,
Table I.2.
Key macroeconomic
There is aindicators
large band of uncertainty around the baseline
reflecting projected concessional financing, are projected 2016forecast,
2017 with
2018
2019 2020e
2021f risks.
2022fIn the
both upside
and downside
Annual
percent
change
unless
indicated
otherwise
to decline to 2 percent of GDP during 2021–23 from 2.6
near term, the biggest risk is the inability to contain
Real
GDP
at constant
market
1.4
5.4
7.0
5.0
‐5.2
4.3
5.4
percent of
GDP
ingrowth,
2020 and
2.3 percent
inprices
2019.33
the latest outbreak, resulting in a prolonged lockdown.
2011
is expected in Q1 2021) could put further pressure on
the domestic FX market amid weak FX inflows.31, 32
2.0
3.6
4.5
21.1
9.2
11.8
13.2
16.5
12.5
14.0
15.0
This would take a significant toll on public health and
10.6
‐1.8
‐0.8
11.5
17.5
‐5.1
1.6
the economy in the coming months. Other risks to the
0.5
35.6
21.3
23.5
‐16.3
9.0
10.0
growth outlook include the impact of further waves
13.8
14.8
24.0
9.1
‐5.0
13.4
7.4
of the COVID-19 global pandemic on commodity
12.7
24.8
30.9
22.3
‐9.0
14.1
8.4
prices (especially coal and copper), a relaxation of
1.2
5.3
7.2
5.2
‐5.2
4.3
5.4
the government’s commitment to reforms after the
6.2
1.8
4.5
8.4
10.8
5.0
6.0
COVID-19 pandemic, weather-related shocks (drought/
‐0.4
0.7
7.9
3.1
‐11.0
6.3
5.4
floods, a harsh winter), and limited progress on banking
1.1
7.7
4.7
5.8
‐5.7
2.5
5.2
sector reforms (box I.5). A downside scenario of the
0.9
6.4
8.1
5.2
2.3
5.0
7.0
outlook could materialize if the impact of COVID-19
‐6.3
‐10.2
‐16.8
‐15.4
‐3.3
‐7.7
‐8.3
persists in advanced economies exacerbated by trade
The recent renewal of the border bottleneck with China following the domestic contagion of the COVID-19 in Mongolia is an additional external
sector pressure.
fact, coking
prices in China recently soared to a four-year
after Mongolia’s
of‐2.7
the COVID-19
FiscalInBalance
(% coal
of GDP)**
‐15.3 high‐3.8
2.6 first local
1.4 transmission
‐9.5
‐1.9 by midNovember 2020 resulted in emergency measures. These measures have slowed operations at the border crossings. Some traders have recently continued
Primary Balance (% of GDP)
‐10.1
0.4
5.8
3.7
‐6.9
‐0.3
0.1
to lift Mongolian coal prices after noting firm coking coal demand from Chinese end-users.
32
The Monetary
decided on December 18th that up to MNT
be provided
exporters
and
PublicPolicy
DebtCommittee
(% of GDP)***
87.6 250 billion
84.7 in funding
72.6 would
69.0
79.4 to non-mining
77.7
73.0
SMEs in Q1 2021.
*In
2016,
the
net
FDI
number
excluded
the
transactions
of
Oyu
Tolgoi‐2
project
financing
in
May–June
2016.
33
One key feature of the government’s debt management strategy is to substitute expensive domestic debt with concessional borrowing and foreign debt
** Development
of Mongoliaterms,
(DBM)resulting
spendinginisaexcluded
fromdecline
fiscal balance
and payments
monitoredinseparately.
obtained through
refinancingBank
on preferential
considerable
in interest
2017-18.
31
24
31 One key feature of the government’s debt management strategy is to substitute expensive domestic debt with concessional
borrowing and foreign debt obtained through refinancing on preferential terms, resulting in a considerable decline in interest
payments in 2017–18.
36
ECONOMIC PERFORMANCE AND PROSPECTS
Table I.2.
Key macroeconomic indicators
2016 2017 2018 2019 2020e 2021f 2022f
Annual percent change unless indicated otherwise
Real GDP growth, at constant market prices
Private Consumption
Government Consumption
Gross Fixed Capital Formation
Exports, Goods and Services
Imports, Goods and Services
Real GDP growth, at constant factor prices
Agriculture
Industry (incl mining)
Services
Inflation (CPI, end-period)
Current account balance (% of GDP)
Financial and Capital account (% of GDP)
Net Foreign Direct Investment (% of GDP)*
Fiscal Balance (% of GDP)**
Primary Balance (% of GDP)
Public Debt (% of GDP)***
1.4
-2.2
10.6
0.5
13.8
12.7
1.2
6.2
-0.4
1.1
0.9
-6.3
7.6
1.1
-15.3
-10.1
87.6
5.4
5.4
-1.8
35.6
14.8
24.8
5.3
1.8
0.7
7.7
6.4
-10.2
24.5
12.7
-3.8
0.4
84.7
7.0
12.4
-0.8
21.3
24.0
30.9
7.2
4.5
7.9
4.7
8.1
-16.8
17.4
16.3
2.6
5.8
72.6
5.0
9.9
11.5
23.5
9.1
22.3
5.2
8.4
3.1
5.8
5.2
-15.4
21.1
16.5
1.4
3.7
69.0
-5.2
2.0
17.5
-16.3
-5.0
-9.0
-5.2
10.8
-11.0
-5.7
2.3
-3.3
9.2
12.5
-9.5
-6.9
79.4
4.3
3.6
-5.1
9.0
13.4
14.1
4.3
5.0
6.3
2.5
5.0
-7.7
11.8
14.0
-2.7
-0.3
77.7
5.4
4.5
1.6
10.0
7.4
8.4
5.4
6.0
5.4
5.2
7.0
-8.3
13.2
15.0
-1.9
0.1
73.0
*In 2016, the net FDI number excluded the transactions of Oyu Tolgoi-2 project financing in May–June 2016.
** Development Bank of Mongolia (DBM) spending is excluded from fiscal balance and monitored separately.
***General government debt data exclude SOE debt and the central bank liability from the People’s Bank of China swap line.
uncertainty between the United States and China. These
events could severely cripple global demand, the price
of key export commodities (particularly copper), and
financial markets. Additionally, weather-related shocks
(including potential risk of the dzud34) could affect
non-mining exports (for example, meat and cashmere)
and thus adversely impact the income of poor and
vulnerable herders. Finally, the failure to gradually
return to fiscal discipline, as foreseen in the 2021
budget, could precipitate a deterioration in investor and
consumer confidence and derail the incipient recovery.
Inadequate recapitalization of the banking sector could
exacerbate these risks and furthermore affect planned
official sector support. On a positive note, the Financial
Action Task Force removed Mongolia from the list of
countries with inadequate protection against money
laundering and terrorist financing, commonly referred to
as the “grey list.” This would positively affect FDI inflows
and boost the credibility of the financial sector.
A shrinking fiscal and monetary space could pose
challenges to the Mongolian economy if the COVID-19
pandemic continues throughout 2021. Mongolia has
used its available monetary and fiscal space to offset the
negative economic impacts of the COVID-19 pandemic.
However, with the Bank of Mongolia’s policy rate now
at a historically low level, monetary policy space is
limited to stimulate the economy if the pandemic
persists. In addition, other monetary policy tools such
as quantitative easing measures (including the recent
introduction of a long-term repo instrument) could
decrease the BoM’s space for further liquidity support.
After a sharp rise in 2020 largely driven by the COVID-19
response package, government debt is expected to
remain elevated and thus erode the existing fiscal space.
Therefore, rebuilding fiscal buffers is a key priority in the
medium term.
External financing pressures could reemerge in the
medium term. Although exports are expected to
recover notably in 2021–22, an expected renewed
drive in imports of investment-related merchandise and
services will likely keep the current account in the red
in the coming years. Unless further external financing
is timely and successfully mobilized, a higher current
account deficit could easily translate into a deficit in
Dzud “is a Mongolian term for a severe winter in which large number of livestock die, primarily due to starvation due to being unable to graze, in other
cases directly from the cold” (https://en.wikipedia.org/wiki/Zud_(Mongolia).
34
25
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Box I.5. Medium-term Banking Sector Strengthening Program for 2020–2023
On January 29, 2020, the Economic Standing Committee of the Parliament passed a resolution that authorized the Bank
of Mongolia to implement the Medium-Term Banking Sector Strengthening Program for 2020–23. The program has five
main objectives with detailed actions and expected outcomes:
1. To reduce ownership concentration of the banking sector and improve its governance, the BoM shall, among others,
require banks to change their form from limited liability companies (LLCs) to joint stock companies (JSCs), limit
the sum of shares with voting rights and offer some shares to the public, and make necessary changes in the legal
framework to ensure the rights of the minority stakeholders. As a result, banks’ shareholding structure would be
more diversified, and bank funding sources could be improved with public participation and oversight.
2. To continue enhancing the banking supervision and regulatory instruments to international standards, the BoM
shall introduce prudential ratios conforming with the Basel standards, establish a legal framework for risk-based
supervision, and collaborate with relevant authorities for effective enforcement. An expected outcome is a flexible
risk-based banking supervision regulatory environment.
5. To provide specialized banking licenses with requirements tailored to their operations and business
3. To successfully
complete
the International
Fund
(IMF)
Extended
Fundspecialized
Facility Program,
the
BoM shall
thespecialized
BoM
shall build
anMonetary
effective
legal requirements
framework
to issue
licenses,
support
5. models,
To provide
banking
licenses with
tailored
to their banking
operations
and business
ensure that introduction
banks raise their
additional
capital
in full
fromand
legitimate
sources,
take necessary
actions
on banks
of
FinTech
to
the
banking
sector,
modify
the
supervisory
methodology
accordingly.
models, the BoM shall build an effective legal framework to issue specialized banking licenses, support
that failed to
meet the capital
requirement,
and make
an effort
to reachthe
ansupervisory
agreement with
the IMF to
complete
introduction
of FinTech
to the banking
sector,
and modify
methodology
accordingly.
BoM; minutes
of the
Economic
Standing
Committeeofmeeting
on January
29, will
2020.be improved, and long-term
theSources:
sixth review.
As a result,
the
resilience
and soundness
the banking
system
economic
growth
will beofsustained.
BoM; minutes
the Economic Standing Committee meeting on January 29, 2020.
ASources:
shrinking
fiscal and
monetary
space could pose challenges to the Mongolian economy if the COVID‐
4. To enhance the effectiveness of Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT), the BoM
19
pandemic
continues
throughout
2021.
Mongolia
has used to
its the
available
monetary
and fiscal
to
A shrinking fiscal and monetary space
could
pose challenges
Mongolian
economy
if thespace
COVID‐
shall enhance the AML/CFT regulatory framework for banks and the effectiveness of its supervision with relevant
offset
the
negative
economic
impacts
of
the
COVID‐19
pandemic.
However,
with
the
Bank
of
Mongolia’s
19 pandemic continues throughout 2021. Mongolia has used its available monetary and fiscal space to
authorities, support correspondent banking relationships of banks, and improve requirements and supervision of
policy
rate
now at a economic
historicallyimpacts
low level,
monetary
policy
space is limited
to stimulate
the economy
if the
offset
the negative
of the
COVID‐19
pandemic.
However,
with the Bank
of Mongolia’s
bank shareholders and their paid-in capital.
pandemic
persists.
In addition,
policy space
tools issuch
as to
quantitative
easing
measures
policy
rate now
at a historically
lowother
level,monetary
monetary policy
limited
stimulate the
economy
if the
5. To(including
provide specialized
banking
licenses with
tailored
to their operations
and business
models,space
the for
recent
of a requirements
long‐term
instrument)
decrease
theeasing
BoM’s
pandemic the
persists.
Inintroduction
addition, other
monetaryrepo
policy
tools suchcould
as quantitative
measures
BoM
shall liquidity
build an effective
legal
framework
torise
issueinspecialized
banking
licenses,
support
introduction
of FinTech
further
support.
After
a sharp
2020
largely
driven
by
the
COVID‐19
response
package,
(including
the recent
introduction
of a long‐term
repo
instrument)
could
decrease
the
BoM’s space
for
to the banking sector, and modify the supervisory methodology accordingly.
government
debtsupport.
is expected
remainrise
elevated
thus driven
erode by
thethe
existing
fiscalresponse
space. Therefore,
further liquidity
Aftertoa sharp
in 2020and
largely
COVID‐19
package,
rebuilding
fiscal
buffers
is
a
key
priority
in
the
medium
term.
government
debt
is
expected
to
remain
elevated
and
thus
erode
the
existing
fiscal
space.
Therefore,
Sources: BoM; minutes of the Economic Standing Committee meeting on January 29, 2020.
rebuilding
fiscal buffers
is a key
priority
in the medium term.
reemerge
External financing
pressures
could
I.41. The size of external bonds maturing during
the balance
payments.
Despite,
the extension
of swap
in of
the
medium
term.
Although
exports
are Figure
reemerge
External
financing
pressures
could
Figure I.41. The size of external bonds maturing
2022–24
is significant
expected
to
recover
notably
in
2021–22,
an
Figure
I.41.
The size ofisexternal
bonds maturing during
lines within
the
People’s
Bank
of
China
and
successful
the medium term. Although exports are
during
2022–24
significant
Payment
schedule
of key sovereign
bonds (million US$)
2022–24
is
significant
expected
renewed
drive
in
imports
of
refinancing
of immediate
payments
of US$570
million,
expected
to recover
notably
in 2021–22,
an
schedule
of key of
sovereign
bondsbonds
(million
US$)
Payment
schedule
key sovereign
(million
O/W
refinanced
through
the "Nomad"
bond
(US$600
mn) US$)
merchandise
a total ofinvestment‐related
US$2.1 billion
in sovereign
external
debtand
is
expected
renewed
drive
in imports
of Payment
Government
international
bonds
35
services
will
likely
keep
the
current
account
in
O/W refinanced through the "Nomad" bond (US$600 mn)
and
still due investment‐related
during 2021–24 (figuremerchandise
I.41). In addition,
the
red
in
the
coming
years.
Unless
further
Government international bonds
services
will
likely
keep
the
current
account
in
delayed implementation of ongoing reforms (including
external
financing
is timely
and
successfully
the
red
in
the
coming
years.
Unless
further
fiscal consolidation and the banking sector) and a
200
mobilized,
a higheris current
account
deficit
external
financing
and
successfully
less effective
response
to the timely
pandemic
could
affect
could easilya translate
into aaccount
deficit in
the
200
mobilized,
higher
current
deficit
Mongolia’s sovereign ratings and reduce the odds of
balanceeasily
of payments.
the extension
could
translateDespite,
into a deficit
in the
800
refinancing
favorable
conditions.
Although
of under
swap lines
with the
People’s
Bankextension
of gross
China
balance
of payments.
Despite, the
370
600
600
reserves reached
a
historically
high
level
of
US$4.5
800
andswap
successful
immediate
of
lines withrefinancing
the People’sofBank
of China
370
600
600
billion (over
months
ofrefinancing
imports)
end-2020,
and
payments
of US$570
million,ata total
of US$2.1
andeight
successful
of immediate
130
it is expected
toinremain
at that
level adebt
intotal
theisofmedium
billion
sovereign
external
still
due
payments
of US$570
million,
US$2.1
33
130
2021
2022
2023
2024
term, it is billion
still below
100
percent
of
the
IMF’s
Assessing
In
addition,
during
2021–24
(figure
I.41).
in sovereign external debt is still due
Sources:
MoF;
BoM;
World
Bank
staff
estimates.
33 100 and
2021 BoM; World
2022Bank staff estimates.
2023
2024
delayed
implementation
of ongoing
reforms
Reserve Adequacy
metric
(a (figure
ratio between
150
Sources: MoF;
In addition,
during 2021–24
I.41).
36
(including
fiscal
consolidation
and
the
percent isdelayed
considered
adequate).
implementation
of ongoing reforms Sources: MoF; BoM; World Bank staff estimates.
banking sector)
a less effectiveand
response
(including
fiscalandconsolidation
the to the pandemic could affect Mongolia’s sovereign ratings
35
and
reduce
the
odds
of
refinancing
under
favorable
conditions.
Although
gross
The People’s
Bank of China
swap and
line with
the BoM
was renewed
for another
Also, no large
repayments
the
public reserves
debtsovereign
are due reached
until ratings
2022, a
banking
sector)
a less
effective
response
tothree
theyears.
pandemic
could
affect ofMongolia’s
partly thanks historically
to a successful issuance
of a US$600
million billion
international
bondseven
in September
2020 of
(with
a maturity at
of 5.5
years with a and
5.1 percent
coupon).
This to
high
level
of
US$4.5
(over
months
imports)
end‐2020,
it
is
expected
and reduce the odds of refinancing under favorable conditions. Although gross reserves reached
a
issuance (i) helped reaffirm market sentiment toward Mongolia; (ii) helped repurchase three-fourths of a US$500 million bond due in 2021, and one-fifth of a
remain
at
that
level
in
the
medium
term,
it
is
still
below
100
percent
of
the
IMF’s
Assessing
Reserve
US$1.0 billionhistorically
bond due in 2022;
andlevel
(iii) contributed
to interest
savings
of approximately
US$27 of
million
per year, at
according
to the government.
high
of US$4.5
billion
(over
seven months
imports)
end‐2020,
and it is expected to
36
34 and is used to assess the
The assessing
reserve adequacy
metric
reflects
potential 100
balance-of-payments
liquidity
needs in adverse
circumstances
Adequacy
(a ratio
between
and 150
is considered
adequate).
remain
at metric
that level
in
the
medium
term,
it ispercent
stillFXbelow
100
percent
of the IMF’s
Assessing Reserve
adequacy of FX reserves against potential FX liquidity drains (see IMF 2016).
34
Adequacy metric (a ratio between
100
and
150
percent
is
considered
adequate).
a
Box I.6. Global and regional outlook and risks
26
Box I.6. Global and regional outlook and risksa
33
The People’s Bank of China swap line with the BoM was renewed for another three years. Also, no large repayments of the
ECONOMIC PERFORMANCE AND PROSPECTS
Box I.6. Global and regional outlook and risksa
The massive shock triggered by the COVID-19 pandemic and shutdown measures to contain it have plunged the
global economy into a severe contractionb (figure I.42). In advanced economies, precautionary social distancing and
stringent lockdowns in response to surging COVID-19 cases triggered an unprecedented collapse in the demand
and supply of services in mid-2020, and the ensuing recovery has been dampened by a substantial resurgence of
COVID-19 cases. The health and economic crisis triggered by COVID-19 caused emerging markets and developing
economies (EMDE) output to shrink by an estimated 2.6 percent in 2020 - the worst rate since at least 1960.
Excluding the recovery in China, the contraction in EMDE output in 2020 is estimated to have been 5 percent,
reflecting recessions in over 80 percent of EMDEs-a higher share than during the global financial crisis, when
activity shrank in about a third of EMDEs. The severity of the shock to EMDEs was uneven, depending on the
intensity of pandemic-related domestic disruptions and the spillovers from the global recession. The worst-hit
economies were those with extended periods of lockdowns combined with large domestic outbreaks or domestic
policy uncertainty, and those that rely heavily on tourism and travel.
Global economic output is expected to expand by 4 percent in 2021 but remain below pre-pandemic projections
by more than 5 percent. This outlook is predicated on proper pandemic management and effective vaccination
limiting the community spread of COVID-19 in many countries, and on continued monetary policy accommodation
accompanied by diminishing fiscal support. Global growth is projected to moderate to 3.8 percent in 2022, weighed
down by the pandemic’s lasting damage to potential growth. Although aggregate EMDE growth is envisioned to
firm to 5 percent in 2021 and to moderate to 4.2 percent in 2022, the improvement largely reflects China’s expected
rebound. Absent China, the recovery across EMDEs is anticipated to be far more muted, averaging 3.5 percent in
2021–22, as the pandemic’s lingering effects continue to weigh on consumption and investment. Despite the
recovery, aggregate EMDE output in 2022 is expected to remain 6 percent below its pre-pandemic projection. The
pandemic is expected to leave lasting scars on productivity, including through its effect on the accumulation of
physical and human capital, which will exacerbate the downward trend in potential growth.
Figure I.42. Real GDP growth (percent)
Figure I.43. World commodity price forecast
(Index=nominal U.S. dollars, 2016=100)
Crude Oil
Coking Coal
Copper
Gold
World
Advanced economies
Emerging market and developing countries
Sources: World Bank 2021; Consensus forecast.
Sources: World Bank 2021; Consensus forecast.
Investment in EMDEs collapsed in 2020, following a decade of persistent weakness. Some recovery of investment
growth is expected to expand in 2021 but will not be sufficient to offset the 2020 loss. Based on the experience
of past epidemics, investment is likely to remain weak for several years following the COVID-19 pandemic. A
supportive policy environment will be key to laying the groundwork for an investment rebound in EMDEs. The
COVID-19 shock has triggered a surge in debt levels and has exacerbated debt-related risks in EMDEs, where even
before the pandemic, a rapid debt buildup had raised concerns about debt sustainability and the possibility of
financial crisis.
27
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Most commodity prices rebounded in the second half of 2020; however, the pickup in oil prices lagged the broader
recovery in commodity prices due to the prolonged impact of the pandemic on global oil demand. Oil prices are
forecast to remain close to current levels and average US$44 per barrel in 2021 before rising to US$50 per barrel in
2022. The main risk to this forecast relates to the evolution of the pandemic, with oil demand particularly susceptible
to lockdown measures and reduced mobility; however, positive vaccine news has reduced this risk somewhat. Base
metal prices were, on net, broadly flat in 2020, as sharp falls in the first half of the year were followed by a strong
recovery in the second half due to rising demand from China. Prices are expected to increase 5 percent in 2021
alongside the expected rebound in global demand (figure I.43). Agricultural prices rose 4 percent in 2020, largely
driven by supply shortfalls and stronger-than-expected demand in edible oils and meals. Some regions experienced
localized food price spikes, and a decline in household incomes, particularly among the poorest populations, has
increased the risk of food insecurity. Agricultural prices are forecast to see a further modest increase in 2021.
After a sharp slowdown to 0.9 percent in 2020,
output in East Asia and Pacific (EAP) is projected to
expand 7.4 percent in 2021, to a level still around
3 percent below pre-pandemic projections (figure
I.44). Growth in China is projected to accelerate
to 7.9 percent this year, reflecting the release of
pent-up demand and a quicker-than-expected
resumption of production and exports. Growth
is expected to slow to 5.2 percent in 2022, well
below its pre-pandemic potential rate, leaving
output about 2 percent below pre-pandemic
projections. In the rest of the region, the recovery
is expected to be more protracted. Following last
year’s contraction, output in the region excluding
China is expected to expand by 4.9 percent in
2021 and 5.2 percent in 2022, to a level around
7.5 percent below pre-pandemic projections, with
significant cross-country variations.
Figure I.44. East Asia and Pacific country forecasts
Real GDP growth (at market prices, y/y)
Source: World Bank 2021.
While global growth is projected to recover in 2021, it will be weaker if a protracted pandemic requires an extension
of control measures, the COVID-19 vaccine procurement and distribution are delayed, and a prolonged disruption to
economic activity exacerbates financial stress resulting in a widespread financial and debt crises. For instance, fiscal
measures have replaced a proportion of lost incomes and mitigated default risk, loan guarantees have helped keep
businesses afloat, and liquidity provision by central banks has kept the financial system functional. However, if the
impact of the pandemic continues to grow, financial crises may follow, resulting in a collapse in lending, a longer
global recession, and a slower recovery. Even if the global financial system avoids a crisis, the debt accumulated in
response to the pandemic may weigh on growth in the longer run.
Sources: World Bank 2020b; 2021.
Note: a. This box draws heavily on World Bank (2021). b. World Bank 2021.
28
PERFORMANCE AND PROSPECTS
II. COVID -19 IMPACTS
ON HOUSEHOLDS IN
MONGOLIA
A. Channels of COVID-19 Shocks to Households
32
B. Impacts on Employment and Labor Income
C. Impacts on Non-labor Income
34
40
D. Potential Impacts on Poverty
E. Potential Mitigation Impacts of Policy Responses
41
45
29
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
II. COVID -19 IMPACTS ON
HOUSEHOLDS IN MONGOLIA 37
A. Channels of COVID-19 Shocks to
Households
some businesses remain closed and other containment
measures continue as of end-January 2021.38
Mongolia went into nationwide lockdown for the
second time on November 12, 2020. At the beginning
of the COVID-19 outbreak, the Government of Mongolia
took early and decisive measures to prevent the
inflow of COVID-19, including closures of its borders
and all schools (figure II.1). As confirmed cases grew
globally, greater travel restriction measures have been
imposed: the Trans-Siberian Railway and all inbound
international flights were suspended and the border
with Russia was closed. The government also canceled
Mongolia’s national Lunar New Year celebrations
and restricted travels in Ulaanbaatar and all 21
aimags (provinces). As these prompt containment and
mobility restriction measures appeared to have been
effective in preventing the local spread of COVID-19
in Mongolia, the government gradually lifted strict
measures from May 31 and schools reopened on
September 1, 2020. However, in mid-November, after
the first locally transmitted cases were verified, the
government imposed a strict nationwide lockdown,
and while strict containment measures were lifted,
Despite fewer confirmed cases in Mongolia than in
neighboring countries, the household-level shocks
caused by COVID-19 may be long-lasting and
disproportionally affect the poor and vulnerable. The
poor and vulnerable generally have limited resources
to protect themselves and are therefore likely to be
most exposed to the negative impacts of many shocks.
COVID-19-related shocks are no exception, and given
their breadth and persistence, they have the potential
to threaten the sustainability of poverty reduction
efforts. While the poverty rate in Mongolia declined
during 2016–18, the speed of poverty reduction has
slowed, and much of the population is still clustered
just above the national poverty line. When a shock hits,
these vulnerable households can easily fall back into
poverty while the poor can sink into deeper poverty.
37
38
COVID-19-related shocks may lead to adverse effects
on various dimensions of household well-being
through various transmission channels. Figure II.2
illustrates how the effects of COVID-19 are transmitted
at the household and individual level. The impact of
This chapter was prepared by Ikuko Uochi (Economist) and Lydia Kim (Consultant) of the Poverty and Equity Global Practice at the World Bank.
As of January 31, 2021, 1,779 cases were confirmed (https://coronavirus.jhu.edu/region/mongolia).
30
also canceled Mongolia’s national Lunar New Year celebrations and restricted travels in Ulaanbaatar and
all 21 aimags (provinces). As these prompt containment and mobility restriction measures appeared to
have been effective in preventing the local spread of COVID‐19 in Mongolia, the government gradually
lifted strict measures from May 31 and schools reopened on September 1, 2020. However, in mid‐
COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
November, after the first locally transmitted cases were verified, the government imposed a strict
nationwide lockdown, and while strict containment measures were lifted, some businesses remain closed
and other containment measures continue as of end‐January 2021.36
Figure II.1. Authorities tightened containment measures as the number of COVID-19 cases increased
Figure II.1. Authorities tightened containment measures as the number of COVID‐19 cases increased
Stringency
of government
measures
containCOVID‐19
COVID-19 and
COVID-19
cases
Stringency
of government
measures
totocontain
andconfirmed
confirmed
COVID‐19
cases
60
New COVID-19 cases
Stringency index
100
80
70
40
60
30
50
Stringency index
New COVID-19 cases
90
50
40
20
30
20
10
10
their breadth
and persistence, they have the potential to threaten the sustainability of poverty
reduction
0
0
efforts. While the poverty rate in Mongolia declined during 2016–18, the speed of poverty reduction has
slowed, and much of the population is still clustered just above the national poverty line. When a shock
Source:
Oxford
University (OxCGRT).
hits,
these
vulnerable
households can easily fall back into poverty while the poor can sink into deeper
Source:
Oxford
Note:
TheUniversity
stringency(OxCGRT).
index measures the stringency of government containment measures, including school and workplace
poverty.
Note: The stringency index measures the stringency of government containment measures, including school and workplace closings and
closings and restrictions on gatherings in response to COVID‐19. Higher values indicate more stringent measures.
restrictions on gatherings in response to COVID-19. Higher values indicate more stringent measures.
COVID‐19‐related shocks may lead to adverse effects on various dimensions of household well‐being
Despite various
fewer confirmed
caseschannels.
in Mongolia
than
neighboring
the
shocks
through
transmission
Figure
II.2inillustrates
howcountries,
the effects
ofhousehold‐level
COVID‐19 are transmitted
COVID-19
can
be divided
into
serviceaffect
delivery
disruptions
in health,
education,
by COVID‐19
be economic
long‐lasting
andsocial
disproportionally
poor
and
vulnerable.
The
poor
atcaused
the household
andmay
individual
level. and
The
impact
oftoCOVID‐19
can the
be divided
into
economic
and
social
impacts.
The
economic
impact
is
further
divided
into
and
social
protection.
This
section
of
the
report
will
and vulnerable
generallyimpact
have limited
resources
to protect
themselves
are therefore
likely
be most
impacts.
The economic
is further
divided
into labor
income, and
non‐labor
income,
andtoprice
shocks
labor
income,
income,
and of
price
shocks
on COVID‐19‐related
primarily
focusinfections
on theare
economic
aspects
of COVID-19
exposed
tonon-labor
the negative
impacts
many
shocks.
shocks
exception,
and
given are
on
consumption.
Given
the
relatively
limited
number
of COVID‐19
inno
Mongolia,
households
consumption.
relatively
of shocks.
shocks
the household
and explore
the
more likelyGiven
to bethe
impacted
by limited
indirectnumber
economic
Theatsocial
impacts oflevel
the pandemic
arehow
mainly
COVID-19
infections
in
Mongolia,
households
are
more
impacts
of
COVID-19
are
translated
from
aggregate
related
to service delivery disruptions in health, education, and social protection. This section of the report
35
This chapter was prepared by Ikuko Uochi (Economist) and Lydia Kim (Consultant) of the Poverty and Equity Global Practice at
will
primarily
the economic
COVID‐19
shocks
at the household
level and
likely
toWorld
be impacted
byon
indirect
economicaspects
shocks. of
The
shocks
to households
and individuals
andexplore
estimatehow
the
the
Bank.focus
36
As
of January
2021,
1,779are
cases
weremainly
confirmed
(https://coronavirus.jhu.edu/region/mongolia).
the
impacts
of31,
COVID‐19
translated
from
aggregate
shocks to
households
and individuals
and estimate
social
impacts
the
pandemic
are
related
potential
effects
of COVID-19
on the poverty
rate.
the potential effects of COVID‐19 on the poverty rate.
41
Figure II.2. Transmission
channels
of COVID-19
impactsoftoCOVID‐19
households
Figure
II.2. Transmission
channels
impacts to households
Labor income
Economic
impact
Direct:
lost earnings to
illness
Indirect:
earnings/employment shocks
Remittance
COVID-19
Shocks on
households
Non-labor income
Public transfers
Price changes and
goods’ shortage
Household Coping Strategies:
• Reduced total
food/education/health
consumption
• Household labor/entering
work force
• Use saving, borrowing
• Selling assets
• Risk pooling
• Government assistance and
other aids, etc.
Consumption
Out of pocket
cost of health care
Social impact
Service disruption
Sources: Modified based on World Bank (2020a).
Sources: Modified based on World Bank (2020a).
B.
Impacts on Employment and Labor Income
31
The COVID‐19 Household Phone Response Survey (HRPS) shows that the pandemic caused significant
37
disruptions in employment (box II.1). Almost 19 percent of workers who had been working pre‐crisis38
had stopped working by the end of May 2020, with two‐thirds out of work due to COVID‐19‐related issues
such as mandated business closures, quarantine, or other reasons caused by mobility restrictions.
Between June and September, some recovery in employment was visible, as nearly half of those who had
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
B. Impacts on Employment and Labor
Income
The COVID-19 Household Phone Response Survey
(HRPS) shows that the pandemic caused significant
disruptions in employment (box II.1).39 Almost 19
percent of workers who had been working pre-crisis40
had stopped working by the end of May 2020, with
two-thirds out of work due to COVID-19-related issues
such as mandated business closures, quarantine, or
other reasons caused by mobility restrictions. Between
June and September, some recovery in employment
was visible, as nearly half of those who had been out
of work by late May had returned to work by early
September. However, with the rise in COVID-19 cases
in early November and stricter containment measures,
the share of individuals working pre-crisis who were no
longer working rose to 51 percent by early December
2020 (figure II.3).
Box II.1. Mongolia COVID-19 Household Response Phone Survey
To explore transmission channels of COVID-19 shocks to households, the analysis in this report uses data from three
rounds of the Mongolia COVID-19 Household Response Phone Survey (HRPS). The HRPS was jointly implemented
by the National Statistics Office of Mongolia (NSO) and the World Bank with the aim of monitoring the economic
and social impacts of the pandemic at the household level. The HRPS drew a subsample of 2,000 households from
the nationally representative 2018 Household Socio-Economic Survey (HSES) and aimed to monitor and collect
information from the same households across multiple rounds. The first round took place from May 22 to 29, 2020;
the second from August 31 to September 7, 2020; and the third from December 3 to 15, 2020. The second lockdown
occurred in mid-November to December 2020, which overlaps with the reference period for the third round of
the HRPS. Comparison of the third-round results to other rounds in the HRPS or to any other surveys would be
sensitive considering the timing and intensity of the containment measures. As the HRPS was phone-based, the
sample is representative of households that have access to a telephone. Out of 16,454 households sampled in
the 2018 HSES, 95.1 percent had a valid working phone number. Sampling weights were constructed to ensure
unbiased estimates from the sample,a and the sample distribution of the HRPS is similar to that of the 2018 HSES
on key household characteristics such as location, education level of household head, and poverty status. The HRPS
questionnaire covers a range of topics, including knowledge and behavior associated with COVID-19, employment,
family business, herders’ livelihood, income, access to food and basic services, methods of coping with the crisis,
and safety nets.
Table II.1.
Overview of HRPS Rounds 1–3
Round 1
Round 2
Round 3
Data collection period
May 22 to 29, 2020
Implementation method
Computer-assisted telephone interviewing (CATI)
Number of respondents
1,333 households
1,212 households
1,147 households
Response rate
66.7 percent (out of
2,000 households
sub-sampled from
2018 HSES)
90.9 percent (out of 1,333
households interviewed in
Round 1)
94.6 percent (out of 1,212
households interviewed in
Round 2)
August 31 to September 7,
2020
December 3 to 15, 2020
Sources: HPRS Rounds 1, 2, and 3; https://www.worldbank.org/en/country/mongolia/brief/monitoring-covid-19-impacts-on-households-in-mongolia.
Note: a. Himelein 2014.
Respondents who “stopped working” in the HRPS refers to those who did not work for permanent or temporary reasons during the week preceding the
survey, while they had worked in previous rounds or pre-pandemic. Please note that the definition of “stopped working” in the HRPS is different from the
definition of unemployment in the Labor Force Survey, which refers to a person who is actively looking for a job during the last 30 days preceding the
survey and is ready to start to work but is unable to find work.
39
40
In the HRPS, pre-crisis and pre-pandemic are defined as before January 27, 2020.
32
COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
While the majority of these shocks to employment
appear to have been temporary, poorer workers were
more likely to face long-term job losses. About 6 out
of 10 respondents to the HRPS who stopped working
between June and December 2020 indicated that they
had a job to return to once stringent containment
measures have been lifted. Although this likelihood is
similar across the welfare distribution, poorer workers
have been significantly more likely to face long-term
unemployment: Among those who were working prepandemic, 21 percent of workers in the bottom 40 of
the welfare distribution had stopped working by June
and continued to be unemployed by December, while
just 11 percent of those in the top 60 had.
Although the employment impacts of the crisis have
extended across most economic sectors, industry,
tourism, hospitality, transportation, and trade have
been particularly affected.41 Shares of those who
stopped working by December 2020 among the
industry sectors - namely, manufacturing, utilities,
construction, and mining - reached 70 percent (figure
II.4). In particular, the construction and manufacturing
sectors were heavily affected by the lockdown that
occurred in mid-November to December 2020, which
overlaps with the reference frame for the third round
of the HRPS. As many construction sites and factories
reopened once mobility restrictions eased, disruptions
in employment in the industry sector are likely to
be temporary: nearly two out of three of those who
stopped working in the industry sector reported they
have a job to return to. Private service sectors such as
accommodation, restaurants, and transportation, as
well as retail trade and other services (for example,
personal services and recreation/entertainment),
have also faced sizable employment shocks. While a
Figure
More
than
of workers
who
worked
Figure
II.3.II.3.
More
than
halfhalf
of workers
who
worked
pre‐
pre-pandemic
stopped
working
by
the
second
pandemic
stopped
working
the second
Figure II.3.
More than
half by
of workers
wholockdown
worked pre‐
pandemic stopped working by the second lockdown
lockdown
FigureII.4.
II.4.Large
Largeshares
sharesofofworkers
workersininthe
the industry
Figure
and
private
services
sectors
faced
employment
industry
private
sectors
Figure
II.4.and
Large
sharesservices
of workers
in thefaced
industry
and private
services sectors faced
disruptions
employment
disruptions
Employment status change for those working pre‐pandemic
Employment
Employmentstatus
statuschange
changefor
forthose
thoseworking
workingpre-pandemic
pre‐pandemic
employment
disruptions
Share of workers
who stopped working between
of workers
who stopped
working
between
ShareShare
of workers
who
working
between
Jan
and
Decstopped
2020, by
subsector
Jan and Dec 2020, by subsector
Jan and Dec 2020, by subsector
Private sector services
Private sector services
40
Industry
Industry
43
Other services
Other services
36
Retail
trade
Retail
trade
40
43
0
72
72
70
70
66
66
26 60
26
Agriculture11 1122 22 32
0
30
30
Public
admin,
education,
Public
admin,
education,
20 20 15 1535
health
health
Agriculture
27
27
36
34 34
32
32
60
35
32
50
50
percent of respondents working pre-crisis
100
100
percent of respondents working pre-crisis
not working but have a job to return to
not working but have a job to return to
not working and don't have a job to return to
not working and don't have a job to return to
Sources:
HRPS
Rounds
1 and
3; World
Bank Bank
staff estimates.
Sources:
HRPS
Rounds
1 and
3; World
staff estimates.
Note: Industry includes mining, manufacturing, utilities, and
Sources:
HRPS includes
Rounds mining,
1 and 3;
World Bankutilities,
staff estimates.
Note:
Industry
includes
mining,
manufacturing,
utilities,
construction;
private
sector
services
include accommodation
Note: Industry
manufacturing,
and construction;
private
sector
services
include
accommodation
and food
services,and
and
food
services,
communication,
finance,
real
estate
and
construction;
private
sector
services
include
accommodation
communication, finance, real estate and transportation. Other services include
other
service
activities;
arts,
entertainment,
and
recreation;
activities of households as employers; and activities of extraterritorial organizations.
transportation.
Other communication,
services include other
service
activities;
and food services,
finance,
real
estate and
arts,
entertainment,
andservices
recreation;
activities
households
transportation.
Other
include
otherofservice
activities;
as
employers;
and activities
extraterritorial
organizations.
arts,
entertainment,
and of
recreation;
activities
of households
41
These sectors are referred to as “affected sectors,” and workers engaged in these sectors are referred to as “affected workers” in this report.
as employers; and activities of extraterritorial organizations.
Although the employment impacts of the crisis have extended across most economic sectors, industry,
39
33
tourism,the
hospitality,
transportation,
particularly
Sharessectors,
of thoseindustry,
who
Although
employment
impacts ofand
the trade
crisis have
have been
extended
across affected.
most economic
39
stopped
working bytransportation,
December 2020
among
industry
sectors―namely,
manufacturing,
tourism,
hospitality,
and
tradethe
have
been particularly
affected.
Shares ofutilities,
those who
construction,
and
mining―reached
70
percent
(figure
II.4).
In
particular,
the
construction utilities,
and
stopped working by December 2020 among the industry sectors―namely, manufacturing,
manufacturing sectors were heavily affected by the lockdown that occurred in mid‐November to
construction, and mining―reached 70 percent (figure II.4). In particular, the construction and
December 2020, which overlaps with the reference frame for the third round of the HRPS. As many
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
large share of those working in these service sectors
had stopped working between January and December
2020, these employment disruptions likely happened
during the strict second lockdown, and more than
half of those out of work have a job to return to.42 In
contrast, workers employed in the agriculture, public
administration, health, and education sectors are by far
less affected. Even under the second lockdown, only
about one-third of those were out of work. However,
once farmers and herders lose a job, they are less likely
to be able to return to the same job even after the
lockdown is lifted.
decline of carried passengers, and another nationwide
lockdown from November 2020 halted the steady
recovery of passenger railway use that began over
the summer. Travel restrictions critically impacted
tourism-related sectors (such as accommodations
and restaurants), retail businesses, transportation,
and other services (such as personal services and
recreation). The number of tourists entering Mongolia
more than halved in the first quarter of 2020 compared
to the same period of 2019. It further declined to less
than 10,000 people during the peak tourist season
in the second and third quarters (figure II.7). As 70
percent of tourists came to the country during the
second and third quarters in recent years, a prolonged
decline in tourism flows worsened the impact on the
tourism sector.
Two out of three workers who stopped working between January and December 2020 were employed in
the aforementioned affected sectors. In 2019, about
half of workers in Mongolia (48 percent of the employed
population or 557,000 people) were engaged in the
COVID-19-related mobility restrictions and disruptions
affected sectors (figure II.5). However, among workers
also decreased domestic private consumption in
who experienced job losses between the 40onset of
transportation, retail, hospitality, and other services,
out the
of crisis
workand
have
a
job
to
return
to.
In
contrast,
workers employed in the agriculture, public
December 2020, almost 1.4 times this
including personal services and recreation. Figure II.8
administration,
health,
and education
sectors
are3 by exhibits
far less Google
affected.
Even data,
underwhich
the second
share was from
the affected
sectors. Overall,
nearly
mobility
indicate lockdown,
how
onlyinabout
one‐third
of
those
were
out
of
work.
However,
once
farmers
and
herders
lose
a job,tothey
10 workers who faced disruptions were employed in
busy certain types of locations are compared
a are
less industries,
likely to be
to in
return
to the same job even after
the lockdown
lifted.
andable
6 in 10
services.
five-week
period fromisearly
January to February 2020.
The
data
show
a
significant
decline2020
in thewere
number
of
TwoTourism-related
out of three workers
whowere
stopped
working
January and December
employed
service sectors
severely
hit duebetween
trips to retail and recreation places, grocery stores,
in the
aforementioned
sectors. As
In shown
2019, about half of workers in Mongolia (48 percent of the
to early
and prolongedaffected
travel restrictions.
and transportation stations during February to April
employed
population
or
557,000
people)
were
in the affected sectors (figure II.5). However,
in figure II.6, the first lockdown, during which theengaged
and again during November to December 2020. In
among
workersofwho
experienced
between the onset of the crisis and December 2020, almost
Government
Mongolia
suspendedjob
alllosses
international
particular, a sharp drop in visits to these places is visible
1.4 times
was
fromand
theclosed
affected
sectors. Overall,
nearly 3 in 10 workers who faced disruptions
flights,this
roadshare
and rail
travel,
nonessential
in the last week of February and in mid-November,
February resulted
a significant
werebusinesses
employedlast
in industries,
and 6 in
in 10
in services. when the government restricted nonessential travel
Figure
II.5. Share
of workers
Figure II.5. Share of workers
in affected
sectors
in 2019 in affected sectors in 2019
8
0
6
10
Manufacturing
Construction
Mining
Utilities
Retail trade
Transportation
Other services
Accommodations, restaurants
Not affected
5
3
20
14
30
5
4
40
3
52
50
60
70
80
90
100
Percent of employed workers
Sources:
NSO; LFS 2019; World Bank staff estimates.
Sources: NSO; LFS 2019; World Bank staff estimates.
Tourism‐related service sectors were severely hit due to early and prolonged travel restrictions. As
While more than 60 percent of those working in services sectors including accommodation and restaurants, retail trade, transportation, professional or
first
lockdown,
during
which
Mongolia
suspended
all
shown
in activities,
figurerealII.6,
technical
estate,the
finance,
insurance,
information, and
communication
had the
stoppedGovernment
working by Decemberof
2020,
previous rounds
of the HRPS
show that job losses were relatively small in these sectors until September 2020, before lockdown measures were put in place.
international flights, road and rail travel, and closed nonessential businesses last February resulted in a
34
significant
decline of carried passengers, and another nationwide lockdown from November 2020 halted
the steady recovery of passenger railway use that began over the summer. Travel restrictions critically
impacted tourism‐related sectors (such as accommodations and restaurants), retail businesses,
transportation, and other services (such as personal services and recreation). The number of tourists
42
COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
declined during the first and second lockdowns
400
300
400
261
200
132150
150
261
229
142
132
98
142
99
98
99
200
Sources:
World
Bank
staff
estimates.
Sources:
NSO;
World
Bank staff estimates.
Sources:
NSO;NSO;
World
Bank
staff
estimates.
Number
of Number
passengers
includes
domestic
international
travel.
Note:
of passengers
includes
bothand
domestic
andtravel.
international
travel.
Note:Note:
Number
of
passengers
includes
bothboth
domestic
and
international
300
10
Q3-20
Q2-20
Q1-20
Q3-19
Q2-20
7
142
132
150
261
Q2-19
Q1-20
Q1-19
Q4-19
229
Q4-18
Q3-19
250
10
7
Q3-18
Q2-19
0
Q4-19
Q3-20
50
300
Q2-18
Q1-19
Railway
Sep-20
Flight
0
200
0
Nov-20
500
0
229
250
100
Figure
number of 75tourists in 2020 was
100The
70 II.7.
70 75
considerably
lower
than in previous
years
36
36
50
100
May-19
Jan-19
Jul-19
Mar-19
Sep-19
May-19
Nov-19
Jul-19
Jan-20
Sep-19
Mar-20
Nov-19
May-20
Jan-20
Jul-20
Mar-20
Sep-20
May-20
Nov-20
Jul-20
600
Jan-19
Number of carried passengers (thousands)
200 II.6. The
Figure
200 number of carried passengers in 2020
declined
during
the first and second lockdowns
100
250
Q3-18
300
300
Q1-18
Q4-18
400
Railway
Number of tourists (thousands)
Railway
Flight
Q2-18
Flight
500
Q1-18
500
considerably lower than in previous years
300
Number of tourists (thousands)
600
Number of tourists (thousands)
600
Mar-19 Number of carried passengers (thousands)
Number of carried passengers (thousands)
Figure II.6. The number of carried passengers in
Figure II.7. The number of tourists in 2020 was
Figure II.6.Figure
The number
carried of
passengers
in 2020 in 2020Figure II.7.Figure
The number
tourists intourists
2020 was
II.6. Theofnumber
carried passengers
II.7. Theofnumber
in 2020 was
2020
declined
during
the
first
and
second
lockdowns
considerably
lower than of
in previous
years
declined during the first and second lockdowns
considerably lower than in previous years
99
98
Q3-20
Q2-20
Q1-20
Q4-19
Q3-19
Q2-19
Q1-19
Q4-18
Q3-18
Q2-18
Q1-18
Nov-20
Jul-20
Sep-20
May-20
Mar-20
Jan-20
Nov-19
Sep-19
Jul-19
May-19
Mar-19
-20
Percentage change from baseline
Percentage change from baseline
Jan-19
200
mobility
and disruptions
also(figure
decreased
domestic
private
in
COVID‐19‐related
mobility closures.
restrictions
and disruptions
also100
decreased
private consumption
inpolicy
75consumption
and COVID‐19‐related
ordered
business
and restrictions
school
Despite
II.9,
b). Without
appropriate
70paneldomestic
transportation,
retail, hospitality,
and otherand
services,
includingincluding
personal personal
services and
recreation.
Figure
transportation,
retail,
hospitality,
other
services,
services
and
recreation.
Figure
36
an increase
in mobility between April and November,
responses50 and aid, these small firms are likely to face
100
II.8 exhibits
which
indicate
busyhow
certain
of locations
are compared
to a 7 10to a
II.8Google
exhibitsmobility
Google data,
mobility
data,
which how
indicate
busytypes
certain
types of locations
are compared
COVID-19-related
disruptions
have
continued
having
a
significant
operating
constraints
as
their
access to
five‐week
period
from
early
January
to
February
2020.
The
data
show
a
significant
decline
in
the
number
0
five‐week
period
from
early
January
to
February
2020.
The
data
show
a
significant
decline
in
the
number
0
detrimental
effect
on
livelihoods
- particularly
during
finance
is relatively
limited,
and their
employers
of trips toof
retail
recreation
places,
grocery
and
transportation
stations during
February
to April
tripsand
to retail
and recreation
places,stores,
grocery
stores,
and transportation
stations
during
February
to Aprilmight
and again
during
November
to December
particular,
a sharp
inoff
visits
tointhese
is visible
and
again
during
November
to December
2020. In particular,
alay
sharp
drop
visitsplaces
toorthese
places
is visiblehours.
the second
lockdown
in November
2020
-2020.
in theInretail,
have
todrop
employees
reduce
working
in the last
of Bank
February
and
mid‐November,
when the
government
restricted
nonessential
travel travel
inweek
the
last
week
of estimates.
February
and in mid‐November,
when
the government
nonessential
Sources:
NSO;
World
staff
hospitality,
personal
services,
andinrecreation
sectors,
Wage
workers
in therestricted
trade and
hospitality
sectors
and ordered
and includes
school
closures.
Despite
increase
mobility
April andApril
November,
and business
ordered
business
and
school
closures.
Despite
an in
increase
in between
mobility between
and November,
Note:
Number
of
passengers
both
domestic
and an
international
travel.
which
are concentrated
in urbanhave
areas.
are also effect
less likely
to be given employee benefits
COVID‐19‐related
disruptions
continued
having a having
detrimental
oneffect
livelihoods―particularly
COVID‐19‐related
disruptions
have continued
a detrimental
on livelihoods―particularly
such
as
social
insurance
and
paid
leave
during the
second
lockdown
in November
2020―in
thealso
retail,
personal
services,
and (figure
during
the
second restrictions
lockdown
inand
November
2020―in
thehospitality,
retail, domestic
hospitality,
personal
services,
and
COVID‐19‐related
mobility
disruptions
decreased
private
consumption
in II.9,
The recreation
affected sectors,
servicewhich
sectors
are characterized
by
are
concentrated
in
urban
areas.
Moreover,
workers
the affected
sectors
recreation
sectors,
which are
concentrated
in urbanpanel
areas.c).personal
transportation,
retail,
hospitality,
and
other services,
services
andinrecreation.
Figure
relatively
high informality
and low
skill levels, including
generally
have
lower
levels
of
education
compared
II.8Figure
exhibits
Google
mobility
data,
which
indicate
how
busy
certain
types
of
locations
are
compared
to
a
II.8.Figure
The mobility
people of
to people
get certain
services
significantly
affected by
government
II.8.
Theofmobility
get
certainwas
services
was significantly
affected
by government
rendering workers
in these
sectors
moretovulnerable
to
others
working
in
sectors
characterized
by
greater
five‐week
period
from
early
January
to
February
2020.
The
data
show
a
significant
decline
in
the
number
restrictions
restrictions
to of
negative
shocks.
Over half
of workers
trips 3‐day
toemployment
retail
andaverage
recreation
places,
grocery
stores,
and
transportation
during
February
to April real
moving
Mongolia’s
mobility
data
at specific
locations
change
from
the
baseline)
formality,
such
asstations
public
administration,
education,
3‐day
movingofaverage
of Mongolia’s
mobility
data
at
specific (%
locations
(%
change
from the
baseline)
in and
retail
trade
and November
transportation
are self-employed
again
torecreation
December
2020. In particular,
a sharp
drop in visits
to these
places is
visible
Retail &
100 during
Retail & recreation
estate,
and finance.
Workplace
closures
and
business
100
pharmacy
Grocery
& pharmacy and in when the government restricted nonessential travel
(figure
panel ofa).February
In Grocery
the &and
trade
sector
in theII.9,
last
in mid‐November,
80 week 80
disruptions
endanger
their
business
continuity,
Transit stations Transit stations
theand
accommodation
and
sector,Despite
where,an increase
ordered
business
andrestaurant
school closures.
in mobility
April and November,
60
60
and without
job between
security, low-skilled
and informal
COVID‐19‐related
continued
having a detrimental effect on livelihoods―particularly
40 44 percent
respectively,
and 70 have
percent
of workers
40 disruptions
workers face a higher risk of losing their job and labor
second
lockdown
November 2020―in
the retail, hospitality, personal services, and
20
20
areduring
paid the
employees,
more
than inthree-quarters
are
income sources.
recreation
which
are
concentrated
in
urban
areas.
0 sectors,
0
working for small firms with fewer than 50 employees
-20
Figure II.8. The mobility of people to get certain services was significantly affected by government
restrictions
-60
-60
3-day average
moving average
of Mongolia’s
mobility
at specificlocations
locations (%
(% change
change from
baseline)
3‐day
moving
of Mongolia’s
mobility
datadata
at specific
fromthethe
baseline)
-80
-80
-40
-40
Figure II.8.
The mobility
of people to get certain services was significantly affected by government restrictions
100
Feb-20
Mar-20
Feb-20
Apr-20
May-20
Mar-20
Apr-20
Retail & recreation
Jun-20
May-20
Jul-20
Jun-20
Aug-20
Jul-20
Sep-20
Aug-20
Oct-20
Sep-20
Nov-20
Oct-20
Dec-20
Nov-20
Dec-20
Percentage change from baseline
Sources: Google
Community
Mobility
Report
(as of
December
2020). 30, 2020).
Sources:
Google Community
Mobility
Report
(as of 30,
December
Grocery & pharmacy
80 baseline is the median value for the corresponding day of the week during the five‐week period Jan 3–Feb 6, 2020.
Note: The
Note: The baseline isTransit
the median
stations value for the corresponding day of the week during the five‐week period Jan 3–Feb 6, 2020.
60
The affected
service sectors
characterized
by relatively
high informality
and low and
skill low
levels,
service are
sectors
are characterized
by relatively
high informality
skill levels,
40 The affected
rendering
workers
in
these
sectors
more
vulnerable
to
negative
employment
shocks.
Over
half
of half of
rendering
workers
in
these
sectors
more
vulnerable
to
negative
employment
shocks.
Over
20
0
46
-20
46
-40
-60
-80
Feb-20
Mar-20
Apr-20
May-20
Jun-20
Jul-20
Aug-20
Sep-20
Oct-20
Nov-20
Dec-20
Sources: Google Community Mobility Report (as of December 30, 2020).
Sources: Google Community Mobility Report (as of December 30, 2020).
Note: The baseline is the median value for the corresponding day of the week during the five‐week period Jan 3–Feb 6, 2020.
Note: The baseline is the median value for the corresponding day of the week during the five-week period Jan 3–Feb 6, 2020.
The affected service sectors are characterized by relatively high informality and low skill levels,
rendering workers in these sectors more vulnerable to negative employment shocks. Over half of
46
35
(figure II.9, panel b). Without appropriate policy responses and aid, these small firms are likely to face
significant operating constraints as their access to finance is relatively limited, and their employers might
have to lay off employees or reduce working hours. Wage workers in the trade and hospitality sectors are
also less likely to be given employee benefits such as social insurance and paid leave (figure II.9, panel c).
MONGOLIAworkers
ECONOMIC
Reliefgenerally
to Recovery
Moreover,
in theUPDATE
affectedFrom
sectors
have lower levels of education compared to others
working in sectors characterized by greater formality, such as public administration, education, real
estate, and finance. Workplace closures and business disruptions endanger their business continuity, and
without job security, low‐skilled and informal workers face a higher risk of losing their job and labor
Figure sources.
II.9. Lower-skilled individuals working in the informal sectors are most vulnerable
income
Panel A.
Panel
B.
Figure II.9. Lower‐skilled
individuals working in the
informal
sectors are most vulnerable Panel C.
Type of employment
Panel A. Type of employment
Trade
44
Hotels,
restaurants
Transportation
All non-farm
sectors
55
70
30
21 19
29
sizesize
of wage
workers
PanelEnterprise
B. Enterprise
of wage
workers
58
41
Trade
43
Hotels, restaurants
38
Transportation
28
All non-farm
sectors
33
53
9 31
16
24
8
61
40
44
workers
with
social
insurance
PanelWage
C. Wage
workers
with
social
insurance
Trade
Hotels, restaurants
71
63
Transportation
88
All non-farm
sectors
86
de and transportation are self‐employed (figure
In the trade sector and
0 20II.9,
40 panel
60 80a).
100
0 20 40 60 80 100
0 20 40 60 80 100
on and restaurant sector, where, respectively,
and 70 percent of workers
wage(public) 44 percent
wage(private)
less than 10
10-50
50 and more
, more than three‐quarters are working
for
small
firms
with
fewer
than
50
employees
self-employed
Others
). Without appropriate policy responses and aid, these small firms are likely to face
Sources:
NSO;relatively
HSES 2018;
LFS 2018; their
Worldemployers
Bank staffmight
estimates.
g constraints as their accessSources:
to finance
NSO;isHSES
2018; limited,
LFS 2018;and
World Bank
staff estimates.
oyees or reduce working hours. Wage workers in the trade and hospitality sectors are
given employee benefits such as social insurance and paid leave (figure II.9, panel c).
Despite
considerable
negative
impacts
on employment
2020. Among businesses that were still operating over
Despite
considerable
negative
impacts
in the affected sectors generally
have
lower levels
of education
compared
to on
others
Figure
II.10.period,
Non‐farm
business
were hit severely
particular
theadministration,
pandemic
has
led the
to real
even
this
income
lossesowners
were significant,
particularly
particular
sectors,
characterized by greaterinemployment
formality,
suchsectors,
asinpublic
education,
Reduction in household income between December 2019 and
Workplace closures and business
disruptions
endanger
theirin
business
continuity,
and
pandemic
has led
to even
more
widespread
more
widespread
reductions
labor
income. Nearly
during
the
second
lockdown,
in
which
more
than half
December 2020
y, low‐skilled and informalreductions
workers face
higherincome.
risk of losing
their
job and
labor
inalabor
Nearly
6 out
of 10
Percent of households with specified source of
income
Percent of households with specified source of
income
6 out of 10 households in Mongolia engaged in labor 100of non-farm businesses experienced a 60 percent loss
households a indecrease
Mongolia
engaged
in this
laborsource
experienced
in income
from
or more in income compared 87to the same time in the
illed individuals working in the
informal sectors
are
most vulnerable
experienced
a
decrease
in
income
from
this
compared to the samePanel
period
of previous year (figure 80previous year.
mployment
Panel B. Enterprise size of wage workers
C. Wage workers with social insurance
68
source
compared
to
the
same businesses
period of were
II.10). Households with non-farm
previous
year
(figure II.10). Trade
Households
with
nonagricultural sectors have been more
57
55
71
Trade
43
33
most likely
to24be affected, with
almost
9 out of 10 60Although
non‐farm businesses were most likely to be
likely
to
experience
employment shocks, disruptions
70
30
participating
suffering
in income
restaurantsreductions
Hotels, restaurants
63
38
53 households
8
affected,
with
almostHotels,
9 out
of 10 participating
in
supply
chains
and
36 contractions in external demand
from this source. According to the Household Response 40
9
58
households
reductions in 88income
Transportation
9 31
61 suffering Transportation
for livestock products have led to significant earnings
Phone
Survey
(HRPS),
by Juneto2020,
more than 40
from this
source.
According
the Household
All non-farm
41
28
All
non-farm
losses among rural herders. Most herders and farmers
16 40
44
86 businesses
20
sectors
percent
of households
operating
sectors non-farm
Response
Phone Survey
(HRPS),
by June
2020,
continued to work in the initial months of the pandemic,
40 60 80 100
0 20than
40 60 40
80had
100
pre-pandemic
temporarily
or permanently
closed
0 20 operating
40 60 80 100
more
percent
of households
wage(private)
less than 10
10-50
50 and more
with very few reporting that they stopped working from
0
their
business,businesses
and closurespre‐pandemic
continued into December
non‐farm
had
Others
Total labor
Non-farm
Agriculture
January
to June. Wages
However, employment
disruptions in
income
business
temporarily or permanently closed their
18; LFS 2018; World Bank staff estimates.
have increased since then: By December
Figure II.10.and
Non-farm
business
owners were
business,
closures
continued
intohit Sources:agriculture
NSO, HRPS Round 3; World Bank staff estimates.
2020,
a
third
of individuals who had been working
severely
Note: The sample is restricted to households with the specified
ble negative impacts onDecember 2020. Among businesses that were
Figure
II.10.
Non‐farm
business
owners
were
hit
severely
in
agriculture
pandemic
were no longer
categorythe
for the
last 12 months.
overin this
period,
income
losses source of income for eachbefore
particular sectors, thestill operating
household
income
between
ReductionReduction
in household
income
between
December
2019 and
o even more widespreadwere
working. In addition, two out of three households
significant,
particularly
during
the
December 2019
and December
2020
December
2020
income. Nearly 6 out of 10
100
engaged in agricultural activities experienced a
87
ngolia engaged in labor
significant decline in agricultural income in 2020
ease in income from this
80
47
68
(figure II.10). Many herders depend on the harvest
to the same period of
re II.10). Households with
57
of cashmere, which is the most lucrative livestock
60
es were most likely to be
product. However, contractions in the global demand
st 9 out of 10 participating
36
40
for cashmere that have coincided with the peak season
ng reductions in income
ccording to the Household
for harvesting cashmere has resulted in significant
20
rvey (HRPS), by June 2020,
negative impacts on herders’ cash income. Negative
nt of households operating
income shocks to rural herders are particularly
0
ses pre‐pandemic had
Total labor
Wages
Non-farm
Agriculture
income
business
ermanently closed their
detrimental because income growth among this group
osures continued into Sources:
NSO,
HRPS
was the biggest driver of the recent poverty reduction
Sources:
NSO,
HRPSRound
Round3;3;World
WorldBank
Bankstaff
staff estimates.
estimates.
mong businesses that were Note:
Note:
sample
is restricted
to households
with
specified
TheThe
sample
is restricted
to households
with
thethe
specified
(between 2016 and 2018).
this period, income losses source of income for each category for the last 12 months.
particularly during the
source of income for each category for the last 12 months.
36
47
COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
While poor workers were more likely to experience
employment losses43 during the first half of 2020, both
employment and income losses were felt similarly
across the welfare distribution during the second
lockdown. Although poor households are more likely
to work in agriculture - which was less affected by the
pandemic in terms of employment losses compared
to other sectors - engagement in low-skilled jobs in
the above-mentioned affected sectors, particularly
manufacturing, utilities, mining, and personal services,
is also high among poorer workers. Generally, about
two in three workers in the bottom 20 percent of the
welfare distribution are employed in low-skilled jobs.44
Workers at the top of the welfare distribution are more
likely to have formal job protection or skilled jobs in
services that may be more amenable to working from
home such as professions in public administration,
finance, and other professional jobs. Indeed, workers
at the bottom of the welfare distribution, namely the
bottom 20 percent, were significantly more likely
to face job losses between January and June 2020,
when mobility restrictions were still low and business
closures were not mandated by the government
(figure II.11, panel A). However, disruptions in
employment were more widespread across the
distribution between June and December 2020,
particularly during the second lockdown, when most
businesses were ordered to close.
Given high participation among the wealthy in retail
trade and non-farm businesses, mandated closures had
a significant impact on employment among the top
quintiles in the latter half of 2020. While the wealthy
may have been less vulnerable to job losses during
the first half of 2020, income losses were generally
felt across the welfare distribution throughout the
year, and more than half of households in all welfare
quintiles faced income losses in 2020 (figure II.11,
panel B). Lower external and internal demand, business
closures, and reduced work hours have resulted in
lower wages and/or business profits throughout the
distribution. The HRPS data indicate that, generally,
the wealthy suffered greater percentage and absolute
losses than poorer households, although the marginal
effect per tugrug on well-being is likely to be higher
for poorer households. This implies that the economic
contraction in 2020 has so far had a widespread impact
across the welfare distribution.
Figure II.11. Employment and income losses across welfare distribution
Figure
II.11.II.11.
Employment
and income
losses
across
welfare
distribution
Figure
Employment
and income
losses
across
welfare
distribution
70
40
30
20
10
0
60
Percent of workers
Percent of workers
50
Jan - Jun
2020
Jun - Dec
Jan
- Jun 2020
Jun2020
- Dec 2020
70
60
Panel
B. Income
lossloss
between
Dec
2019
and
Panel
B.B.
Income
between
Dec
2019
andDec
Dec2020
20202020
Panel
Income
loss
between
Dec
2019
and
Dec
50
36
40
30
19
20
27
19
27
15
25
36
31
25
15
12
13
12
13
10
0
Q1 (poorest)
Q2
Q1 (poorest)
Q2
Q3
Q3
Q4
31
29
9
9
29
Q5
Q4
Q5
(wealthiest)
(wealthiest)
80
60
40
20
0
Percent of households with labor income
80
Percent of households with labor income
80
Panel
A.A.Stopped
working
due to
todue
COVID‐19
Panel
Stopped
working
due
COVID-19
Panel
A. Stopped
working
to COVID‐19
80
58
60
69
58
54
54
54
54
69
53
53
40
20
0
Q1
Q1 Q2
(poorest)
(poorest)
Q2 Q3
Q3 Q4
Q4 Q5
Q5
(wealthiest)
(wealthiest)
Sources:
NSO;
HRPS
2020
Rounds
and
World
Bank
staff estimates.
Sources:
NSO;
HRPS
2020
13;and
3; World
Bank
staff estimates.
Sources:
NSO;
HRPS
2020
Rounds
1 Rounds
and13;
World
Bank
staff
estimates.
Note:The
Thesample
sample
in panel
A is restricted
to respondents
were
the same
across
rounds
1A and
Panel
Astopped
usesA those
who
Note:
The in
sample
A istorestricted
to who
respondents
whoacross
were
the same
across
rounds
and
3.
Panel
uses
those
Note:
panel
Ainispanel
restricted
respondents
werewho
the same
rounds
1 and
3. Panel
uses13.
those
who
working
duewho
stopped
working
due
to
COVID‐19‐related
such such
asquarantine,
workplace
and
school
closures,
quarantine,
and stay‐at‐home
stopped
working
due
toasCOVID‐19‐related
reasons
as workplace
and school
closures,
quarantine,
and
stay‐at‐home
to
COVID-19-related
reasons
such
workplace andreasons
school
closures,
and
stay-at-home
orders
under
the
government’s
containment
ordersorders
underunder
the government’s
containment
measures.
measures.
the government’s
containment
measures.
44
of respondents working pre-crisis
43
of respondents working pre-crisis
Geographically,
urban
households
havehave
beenbeen
Geographically,
urban
households
Figure
II.12.II.12.
Urban
workers
werewere
moremore
likelylikely
to stop
Figure
Urban
workers
to stop
moremore
likelylikely
to face
the economic
repercussions
of ofworking in 2020
to face
the economic
repercussions
working in 2020
COVID‐19.
Employment
in the
highly
affected
COVID‐19.
Employment
in the
highly
affected
50
50
sectors
is concentrated
in urban
areas:
82 percent
sectors
is concentrated
in urban
areas:
82 percent
Employment losses include temporary work disruptions under nationwide lockdowns due to COVID-19.
40
40
of
working
in these
sectors
live live
in urban
of the
those
in these
sectors
in urban
NSOthose
and
Worldworking
Bank 2020;
World
Bank
2018.
40
40
36
36
areas,
mainly
Ulaanbaatar,
which
is significantly
areas,
mainly
Ulaanbaatar,
which
is significantly
37
higher
thanthan
the overall
shareshare
(62 percent)
among
higher
the overall
(62 percent)
among
30
30
all workers.
Those
livingliving
in Ulaanbaatar
or Aimag
all workers.
Those
in Ulaanbaatar
or Aimag
centers
werewere
at least
1.9 and
moremore
likelylikely
centers
at least
1.9 3.9
andtimes
3.9 times
18
18
20
20
to stop
working
between
January
and and
December
to stop
working
between
January
December
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Also, under the COVID-19 pandemic, unemployed
and inactive individuals face further difficulties in
searching for a job, leading to a greater likelihood
of sinking into deeper poverty. Even without the
COVID-19 pandemic, poverty headcount rates for
unemployed and economically inactive individuals
were significantly higher compared to the employed or
retiree population. The poor and near-poor, who have
low levels of human capital, are less likely to be able
to meet labor market needs and often face difficulties
in finding a job. Being unemployed or economically
inactive means no labor income, translating into lower
consumption and a higher chance of staying in poverty.
The COVID-19 pandemic can exacerbate the already
devastating situation and high poverty rates for this
segment of the population.
Figure II.12. Urban workers were more likely to
ban households have been
Figure II.12. Urban workers were more likely to stop
he economic repercussions of
stopworking
working
in 2020
in 2020
ment in the highly affected
50
ted in urban areas: 82 percent
40
n these sectors live in urban
40
36
nbaatar, which is significantly
rall share (62 percent) among
30
iving in Ulaanbaatar or Aimag
t 1.9 and 3.9 times more likely
18
20
tween January and December
9
ving in Soum centers and the
10
ectively (figure II.12). In
rkers residing in urban areas
0
Ulaanbaatar
Aimag center
Soum center
Countryside
be engaged in informal, part‐
inesses in the affected sectors
Sources:
NSO;
HRPS
2020
Round
3;
World
staff
Sources: NSO; HRPS 2020 Round 3; World Bank staffBank
estimates.
ed to a higher risk of job losses estimates.
Note: Ulaanbaatar
and aimag
centers
are are
considered
urban.
Note: Ulaanbaatar
and aimag
centers
considered
urban.
counterparts.
C. Impacts on Non-labor Income
Percent of households with labor income
Geographically, urban households have been
more likely to face the economic repercussions of
COVID-19. Employment in the highly affected sectors
is concentrated in urban areas: 82 percent of those
working
in these
sectorsdistribution
live in urban areas, mainly
Figure II.11. Employment and
income losses
across welfare
ed working due to COVID‐19
Panel B. Income loss between Dec 2019 and Dec 2020
Ulaanbaatar,
which is significantly higher than the
80
un 2020
Jun - Dec 2020
69 all workers. Those
overall share (62 percent) among
58
54
living in Ulaanbaatar
centers53 were at least
60
54 or Aimag
1.9
and
3.9
times
more
likely
to
stop
working between
36
40
31
29
January and December 2020 than those living in Soum
25
centers and
20 the countryside, respectively (figure II.12).
13
12
9
In particular, poor workers residing in urban areas
0
are more likely
to beQ2 engaged
inQ4 informal,
part-time,
Q1
Q3
Q5
Q2
Q3
Q4
Q5
(poorest)
(wealthiest)
(wealthiest)
and small businesses in the affected sectors and are
20 Rounds 1 and 3; World Bank staff estimates.
thus
to across
a higher
jobAlosses
than
anel A is restricted to respondents
whoexposed
were the same
rounds risk
1 and of
3. Panel
uses those
who their
to COVID‐19‐related reasons such
as workplace
and school closures, quarantine, and stay‐at‐home
wealthier
counterparts.
Percent of respondents working pre-crisis
Percent of respondents working
pre-crisis
nment’s containment measures.
g impacts across various sectors, the pandemic has affected similarly women and
e likelihood of being out of
work.
to men,
women
are more
likely sectors,
to work the
Due
to Compared
far-reaching
impacts
across
various
ch as education, health, personal services, and hospitality, while men are more likely
pandemic has affected similarly women and men in
sectors such as construction and mining. As the economic impacts of COVID‐19 have
termssectors,
of the both
likelihood
being
out of
work.
Compared
ss multiple industry and service
womenof
and
men have
faced
job losses.
ests that female‐headed households
have beenare
similarly
to experience
to men, women
morelikely
likely
to work income
in service
ed households.
sectors such as education, health, personal services,
VID‐19 pandemic, unemployed and inactive individuals face further difficulties in
and hospitality, while men are more likely to work
, leading to a greater likelihood of sinking into deeper poverty. Even without the
sectors
such as construction
andwere
mining.
, poverty headcount ratesin
for industry
unemployed
and economically
inactive individuals
compared to the employed
or
retiree
population.
The
poor
and
near‐poor,
who
have
As the economic impacts of COVID-19 have been
capital, are less likely to be able to meet labor market needs and often face difficulties
extensive across multiple industry and service sectors,
g unemployed or economically inactive means no labor income, translating into lower
both women and men have faced job losses. The HRPS
also 49
suggests that female-headed households have
been similarly likely to experience income losses as
male-headed households.
38
Remittances are a critical income source for recipient
households, but their inflows are expected to fall
during the COVID-19 pandemic. According to the 2018
HSES, 18 percent of households received some sort of
private remittance in the last 12 months prior to the
survey. In Mongolia, most remittances are domestic
transfers: only 2 percent of households received private
transfers from abroad. By consumption levels, wealthier
households are more likely to receive remittances, with
24 percent of households in the wealthiest quintile
receiving remittances, while only about 14 percent
of the bottom 40 percent of households receiving
them (figure II.13). However, as shown in figure II.14,
regardless of household welfare level, remittances are
a critical income source for all remittance-receiving
households, accounting for one-quarter to one-third of
their total household income. The COVID-19 disruptions
can significantly affect the employment status of
migrant workers, and, thus, inflow of remittances. The
impact might be long-lasting if businesses where
migrant workers are engaged do not improve quickly.
For the poor and vulnerable recipient households that
heavily rely on remittances and have little savings or
assets to buffer themselves, the remittance impacts
will compound their existing vulnerabilities.
Other
Other non‐labor
non‐labor income,
income, notably
notably public
public transfers,
transfers, represents
represents an
an important
important share
share of
of household
household income
income
for
forthe
thepoor.
poor.Although
Althoughlabor
laborincome
incomeaccounts
accountsfor
formore
morethan
than60
60percent
percentof
ofhousehold
householdincome
incomefor
forthe
thepoor,
poor,
one‐third
one‐third of
of their
their income
income comes
comes from
from social
social transfers
transfers such
such as
as child
child money,
money, other
other social
social protection
protection
COVID -3),
19
ON HOUSEHOLDS
IN MONGOLIA
programs,
programs,and
andpensions.
pensions.4343According
Accordingto
tothe
theHRPS
HRPS(Round
(Round
3),IMPACTS
only
only33percent
percent
of
ofsocial
socialassistance
assistance
recipients
recipients
have
havefaced
faceddisruptions
disruptions in
inreceiving
receivinggovernment
governmentassistance
assistance under
under the
thepandemic.
pandemic.
Figure
FigureII.13.
II.13.Percent
Percentof
ofhouseholds
householdsreceiving
receivingaa
Figure II.13.
Percent of households receiving a
remittance,
remittance,
2018
2018
remittance, 2018
Figure
FigureII.14.
II.14.Share
Shareof
ofremittance
remittanceto
tototal
totalhousehold
household
Figure(among
II.14. Share
of remittance
toreceived
total
household
income
income
(among
households
households
that
that
received
aa
income (among households that received a remittance)
remittance)
remittance)
40%
40%
35%
35%
25
25
30%
30%
20
20
25%
25%
15
15
10
10
55
00
Average
Average shares
shares of
of remittance
remittance to
to total
total
household
household income
income
Percent
Percent of
of households
households receiving
receiving
remittance
remittance
30
30
14.3
14.3
Q1
Q1
14.2
14.2
Q2
Q2
15.5
15.5
Q3
Q3
18.3
18.3
Q4
Q4
24.0
24.0
20%
20%
15%
15%
10%
10%
Q5
Q5
Income
Incomedistribution
distributionfrom
fromlowest
lowestto
tohighest
highest
30%
30%
26%
26%
27%
27%
27%
27%
Q2
Q2
Q3
Q3
Q4
Q4
33%
33%
5%
5%
0%
0%
Q1
Q1
Q5
Q5
Income
Incomedistribution
distributionfrom
fromlowest
lowestto
tohighest
highest
Sources: NSO, HSES 2018; World Bank staff estimates.
Sources:
Sources:
NSO,
NSO,
HSES
HSES
2018;
2018;
World
World
Bank
Bankstaff
staffestimates.
estimates.
Note: Error
bars
in figures
show
95 percent
confidence
intervals.
Note:
Note:Error
Errorbars
barsin
infigures
figuresshow
show95
95percent
percentconfidence
confidenceintervals.
intervals.
Other non-labor income, notably public transfers,
in 2020 for the baseline scenario and a 50 percent
represents an important share of household income
decline for all quarters in 2020 for the lower-case
D.
D.
Potential
Potential Impacts
Impacts on
on Poverty
Poverty
for the poor. Although labor income accounts for more
scenario. The employment-output elasticities used as
This
This
section
section
assesses
assesses
the
thepotential
potential
impacts
impacts
of
ofthe
theCOVID‐19
COVID‐19
pandemic
on
onthe
thenational
national
poverty
povertybased
headcount
headcount
than
60 percent
of household
income
for the
poor,
inputs pandemic
into the simulation
are calculated
on
44
one-third
of their income
comes fromsimulation
social transfers
information
of sectoral
GDP growth
and employment
rate
rate
by
by adapting
adapting
aa macro‐micro
macro‐micro
simulation
model.
model.44
The
The ADePT
ADePT
macro‐micro
macro‐micro
simulation
simulation
combines
combines
such as child money,
other social
programs,
changes
between
and 2018,
and the survey
population
macroeconomic
macroeconomic
projections
projections
and
andprotection
household
household
welfare
welfare and
and
profile
profile
from
from2010
the
the latest
latest
household
household
survey4545 and
and
45
and pensions. According to the HRPS (Round 3), only
growth forecasts are based on the latest UN World
Population Prospects (2019).
43
43 3 percent of social assistance recipients have faced
NSO
NSOand
andWorld
WorldBank
Bank2020.
2020.
44
44 disruptions in receiving government assistance under
The
Themicrosimulation
microsimulationmodel
modelused
usedin
inthis
thisreport
reportisisoutlined
outlinedin
inOlivieri
Olivieriet
etal.
al.(2014).
(2014).
The simulation results suggest that without mitigation
45
45 HSES
HSESpandemic.
2018.
2018.
the
measures there would be an increase of 5.9 to 7.9
50
50
percentage points in the national poverty rate in 2020,
D. Potential Impacts on Poverty
compared to the pre-COVID forecast. This is equivalent
This section assesses the potential impacts of
to adding approximately 195,000 to 260,000 people
the COVID-19 pandemic on the national poverty
into poverty (figures II.15 and II.16). Even without the
headcount rate by adapting a macro-micro simulation
COVID-19 pandemic, the recent increasing food prices
46
model. The ADePT macro-micro simulation combines
placed great stress on poorer households, slowing
macroeconomic projections and household welfare
the speed of poverty reduction between 2019 and
and profile from the latest household survey47 and then
2020 under the pre-COVID case.48 With deteriorating
incorporates microsimulation assumptions related to
economic forecasts under the COVID-19 pandemic,
the labor market, non-labor income, and price changes
the poverty rate would go up to 31.7 and 33.6 percent
to project distributional and poverty effects of these
in the baseline and lower case, respectively, meaning
assumptions. Table II.2. summarizes GDP and price
that over 1 million people in Mongolia would be under
projections for three scenarios: (i) pre-COVID case
the poverty line. The impacts of COVID-19 would last
(business as usual), (ii) baseline case, and (iii) lower
beyond the current pandemic and will not be easily
case. The baseline and lower-case scenarios also
recovered. With the projected slower-paced recovery,
incorporate adverse remittance flow in the simulation,
the baseline case simulation results suggest that
with assuming a 50 percent decline for two quarters
poverty rate of 2022 would not go back to the level
NSO and World Bank 2020.
The microsimulation model used in this report is outlined in Olivieri et al. (2014).
HSES 2018.
48
The poverty line in the simulation was adjusted by the difference in food and non-food inflation rates. Since the ratio of food consumption to total
consumption in the poverty line is 51 percent, which is significantly higher than the ratio of food items in the CPI basket (26 percent), higher food price
inflation relative to non-food inflation would shift the poverty line upward, pushing more people under the poverty line.
45
46
47
39
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Table II.2.
GDP growth and inflation assumptionsа
(1) Pre-COVID Case (business as usual)
2018
2019 F
2020 E
2021 E
2022 E
Agriculture
4.5%
4.5%
4.4%
4.4%
5.0%
Industry including mining
7.9%
3.4%
3.1%
5.6%
5.7%
Services
4.7%
6.8%
6.2%
6.2%
6.7%
Total
7.2%
5.8%
5.3%
5.6%
5.8%
2018
2019
2020 E
2021 E
2022 E
Agriculture
4.5%
8.4%
10.8%
5.0%
6.0%
Industry including mining
7.9%
3.1%
-11.0%
6.3%
5.4%
Services
4.7%
5.8%
-5.1%
2.9%
5.2%
Total
7.2%
5.2%
-5.2%
4.3%
5.4%
2018
2019
2020 E
2021 E
2022 E
Agriculture
4.5%
8.4%
9.4%
4.0%
5.0%
Industry including mining
7.9%
3.1%
-12.2%
2.9%
3.9%
Services
4.7%
5.8%
-7.9%
1.6%
3.0%
Total
7.2%
5.2%
-7.1%
2.4%
3.5%
2018
2019
2020 E
2021 E
2022 E
Total CPI
8.1%
5.2%
7.0%
8.0%
8.5%
Food CPI
9.1%
8.3%
11.0%
9.0%
8.6%
Non-Food CPI
7.8%
4.2%
5.6%
7.6%
8.5%
2018
2019
2020 E
2021 E
2022 E
Total CPI
8.1%
5.2%
2.3%
5.0%
7.0%
Food CPI
9.1%
8.3%
8.5%
8.0%
8.2%
Non-Food CPI
7.8%
4.2%
0.1%
4.0%
6.6%
(2) Baseline Case
(3) Lower Case
Inflation (YoY) for pre-COVID case
Inflation (YoY) for Baseline and lower cases
Note: a. The pre-COVID case was based on forecasts from the Mongolia Economic Update (as of January 2020), whose 2019 GDP was a forecast
since the final 2019 GDP figure was not published at that time. Baseline and lower cases are the latest World Bank forecasts provided as of
January 18, 2021.
40
pandemic
pandemic
and
and
will
will
not
not
bebe
easily
easily
recovered.
recovered.
With
With
the
the
projected
projected
slower‐paced
slower‐paced
recovery,
recovery,
the
the
baseline
baseline
case
case
simulation
simulation
results
results
suggest
suggest
that
that
poverty
poverty
rate
rate
ofof
2022
2022
would
would
not
not
gogo
back
back
toto
the
the
level
level
ofof
2018,
2018,
and
and
nearly
nearly
11
million
million
people
people
would
would
remain
remain
inin
poverty.
poverty.
Given
Given
the
the
limited
limited
share
share
ofof
remittance‐receiving
remittance‐receiving
households,
households,
the
the
overall
overall
impacts
impacts
ofof
remittances
remittances
are
are
relatively
relatively
limited.
limited.
Without
Without
adverse
adverse
impacts
impacts
inin
remittances,
remittances,
the
the
poverty
poverty
-19 IMPACTS
COVID
ON
HOUSEHOLDS
IN MONGOLIA
rates
rates
are
are
projected
projected
toto
increase
increase
byby
5.5
5.5
toto
6.4
6.4
percentage
percentage
points
points
inin
the
the
baseline
baseline
and
and
lower‐case
lower‐case
scenarios,
scenarios,
respectively.
respectively.
Figure
II.15.
Projected
poverty
rates
Figure
Figure
II.15.
II.15.
Projected
Projected
poverty
poverty
rates
rates
33.633.6
34 34
32.832.8
32 32
30 30
28 28
26 26
31.731.7
28.428.4
24 24
26.926.9
31.331.3
1,000
1,000
30.530.5
25.825.8
24.124.1
22.322.3
2018
2018
(actual)
(actual)
2019E
2019E
Pre-covid
Pre-covid
2020F
2020F
1,098
1,098
2021F
2021F
Baseline
Baseline
1,084
1,084
1,100
1,100
28.728.7
22 22
20 20
1,200
1,200
Number of poor (thousands)
Number of poor (thousands)
National Poverty headcount rate (%)
National Poverty headcount rate (%)
36 36
Figure
II.16.
Projected
number
poor
people
Figure
Figure
II.16.
II.16.
Projected
Projected
number
number
ofofof
poor
poor
people
people
Lower
Lower
case
case
1,007
1,007
900900
800800
905905
871871
841841
2018
2018 2019E
2019E
(actual)
(actual)
Pre-covid
Pre-covid
959959
796796
700700
600600
2022F
2022F
1,035
1,035
1,046
1,046
2020F
2020F
2021F
2021F
Baseline
Baseline
746746
2022F
2022F
Lower
Lower
case
case
Source:
World
Bank
staff
estimates
(ADePT
simulation).
Source:
World
Bank
staff
estimates
(ADePT
simulation).
Source:
Source:
World
World
Bank
Bank
staff
staff
estimates
estimates
(ADePT
(ADePT
simulation).
simulation).
Source:
Source:
World
World
Bank
Bank
staff
staff
estimates
estimates
(ADePT
(ADePT
simulation).
simulation).
Note:
Impacts
of
mitigation
responses
by the byby
Note:
Impacts
ofofCOVID-19-related
mitigation
responses
by the
Note:
Note:
Impacts
Impacts
ofCOVID-19-related
of
COVID‐19‐related
COVID‐19‐related
mitigation
mitigation
responses
responses
thethe Note:
Note:
Impacts
Impacts
of
COVID‐19‐related
COVID‐19‐related
mitigation
mitigation
responses
responses
byby
government
were
not
in the
projection.
government
were notwere
included
innot
theincluded
poverty
projection.
government
government
were
were
notincluded
not
included
included
in poverty
in
thethe
poverty
poverty
projection.
projection.
the
thegovernment
government
werenot
included
in inthethepoverty
poverty
projection.
projection.
among the poorest population group that would
of 2018, and nearly 1 million people would remain in
expect a consumption decline by 18 percent between
poverty. Given the limited share of remittance-receiving
The
The
welfare
welfare
impact
impact
onon
the
the
poor,
poor,
particularly
particularly
among
among
the
the
“new
“new
poor,”
would
would
be
significantly
significantly
higher
higher
than
than
2018
and poor,”
2020
under
thebelower-case
scenario
(figure
households,
the
overall
impacts
of remittances
that
that
observed
observed
in
in
the
the
rest
rest
of
of
the
the
population.
population.
The
The
COVID‐19
COVID‐19
economic
economic
impacts
impacts
would
would
affect
affect
households
households
II.17).
As
a
result,
the
depth
and
severity
of
poverty
are relatively limited. Without adverse impacts in
across
across
allall
income
income
classes,
classes,
but
but
the
the
relative
relative
welfare
welfare
impact,
impact,
with
with
the
the
absence
absence
ofof
effective
effective
mitigation
policies,
policies,
would
worsen,
with an
increase
ofmitigation
3.4 percentage
remittances,
the poverty
rates
are
projected
to
increase
isby
ishighest
highest
among
the
thepoorest
poorest
population
group
group
that
thatwould
wouldexpect
a consumption
a consumption
decline
decline
byby18points
18percent
percent
points
inexpect
the poverty
gap, and 1.9
percentage
in
5.5
to among
6.4
percentage
pointspopulation
in
the baseline
and
between
between
2018
2018
and
and
2020
2020
under
under
the
the
lower‐case
lower‐case
scenario
scenario
(figure
(figure
II.17).
II.17).
As
As
a
result,
a
result,
the
the
depth
depth
and
and
severity
severity
the poverty severity index. Among the poor population,
lower-case scenarios, respectively.
ofof
poverty
poverty
would
would
worsen,
worsen,
with
with
anan
increase
increase
ofof
3.4
3.4
percentage
percentage
points
inin
the
the
poverty
poverty
gap,
gap,
and
and
1.9
1.9
percentage
notablypoints
the
“new
poor,”
who became
poor
inpercentage
2020
due
The
welfare
impact
on
the
poor,
particularly
among
points
pointsininthe
thepoverty
povertyseverity
severityindex.
index.Among
Amongthe
thepoor
poor
population,
population,
notably
notably
the
the“new
“newpoor,”
poor,”
who
became
became
to
the COVID-19
economic
shocks,
wouldwho
be
severely
the
“new
poor,”
would
be
significantly
higher
than that
poor
poor
inin2020
2020due
duetoto
the
the
COVID‐19
COVID‐19
economic
economic
shocks,
shocks,
would
wouldbe
beseverely
severely
affected.
affected.
Theirwelfare
welfare
would
would
affected.
Their
welfare
would Their
decline
significantly
observed
in the rest of
the population.
The be
COVID-19
decline
decline
significantly
significantly
because
because
they
they
would
would
be
forced
forced
toto
decrease
decrease
their
their
per
per
capita
capita
consumption
consumption
by
by
27
27
to
to
3131
because they would be forced to decrease their per
economic
impacts
would
affect
households
across
all
percent
percent
from
from
2018
2018
toto
2020
2020
inin
real
real
terms
terms
(figure
(figure
II.18).
II.18).
capita consumption by 27 to 31 percent from 2018 to
income classes, but the relative welfare impact, with
2020 in real terms (figure II.18).
the absence of effective mitigation policies, is highest
Figure
Figure
II.17.
II.17.
Consumption
growth
growthincidence
incidence
incidence
(%
Figure
II.17.Consumption
Consumption growth
(%(%
change
change
change
of
per
per capita
capita
consumption
consumption
from
from
2018
2018 to
to
of perof
capita
consumption
from 2018
to 2020)
2020)
2020)
Figure
Figure
II.18.
II.18.
Average
Average
welfare
welfare
loss
from
2018
toto2020
2020 by
by
Figure
II.18.
Average
welfareloss
lossfrom
from2018
2018to
poverty
poverty
status
2020status
by poverty status
-5
-5
-10
-10
pre-covid
pre-covid
baseline
baseline
lower
lower
richest
richest
9
9
8
8
7
7
6
6
5
5
4
4
3
3
-20
-20
2
2
-15
-15
5252
Average
Average welfare
welfare loss
loss from
from 2018
2018 to
to
2020
2020
00
poorest
poorest
Percent
Percent change
change from
from 2018
2018
55
baseline
baseline
0%
0%
-5%
-5%
-6%
-6%
-10%
-10%
lower
lower
-4%
-4%
-7%
-7%
-15%
-15%
-7%
-7%
-20%
-20%
-25%
-25%
-30%
-30%
-27%
-27%
-31%
-31%
-35%
-35%
new
newpoor
poor
already
alreadypoor
poor
rest
restof
ofpopoulation
popoulation
Source:
Source:
World
Bank
Bank
staff
staff
estimates
estimates
(ADePT
(ADePT
simulation).
simulation).
Source:World
World Bank
staff
estimates
(ADePT
simulation).
Note:
Note:
Impacts
Impacts of
of COVID‐19‐related
COVID‐19‐related mitigation
mitigation responses
responses by
by the
the government
government were
were not
not included
included in
in the
the poverty
poverty projection.
projection.
Note: Impacts of COVID-19-related mitigation responses by the government were not included in the poverty projection. Consumption in 2018
Consumption
Consumption
in
in
2018
2018
was
was
adjusted
adjusted
to
to
2020
2020
price
price
levels.
levels.
New
New
poor
poor
are
are
those
those
who
who
were
were
not
not
poor
poor
before
before
the
the
COVID‐19
COVID‐19
pandemic
pandemic
was adjusted to 2020 price levels. New poor are those who were not poor before the COVID-19 pandemic but became poor during the pandemic.
poorpoor
are those
whothe
werepandemic.
already poorAlready
pre-COVID.
but
butAlready
became
became
poor
during
during
the
pandemic.
Already
poor
poor are
are those
those who
who were
were already
already poor
poor pre‐COVID.
pre‐COVID.
41
Urban
Urban households
households are
are more
more likely
likely to
to be
be adversely
adversely affected
affected than
than those
those in
in rural
rural areas.
areas. While
While the
the simulated
simulated
poverty
poverty rate
rate for
for 2020
2020 in
in the
the countryside
countryside remains
remains at
at the
the same
same level
level from
from the
the pre‐COVID
pre‐COVID to
to the
the lower‐case
lower‐case
scenario,
scenario, itit would
would significantly
significantly increase
increase in
in other
other locations
locations of
of the
the nation
nation (figure
(figure II.19).
II.19). In
In particular,
particular, poverty
poverty
incidence
incidence in
in the
the Aimag
Aimag centers
centers would
would reach
reach the
the highest
highest levels,
levels, rising
rising from
from 28
28 percent
percent in
in the
the pre‐COVID
pre‐COVID
0
Average welfare loss from 2018 to
2020
Percent change from 2018
5
-5
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
-10
-15
baseline
0%
-5%
-6%
-10%
lower
-4%
-7%
-15%
-7%
-20%
-25%
richest
9
8
7
6
5
4
3
2
poorest
-30%
-27%
Urban -20
households are more likely to be adversely
Nearly two-thirds
of “new poor” attributable to the
-31%
-35%
affected than those in rural areas. While the simulated
COVID-19 shocks are from the services
sectors. While
poverty rate for 2020 in the countryside remains
the COVID-19newshocks
have
affected
a
wide
range of
poor
already poor
rest of popoulation
pre-covid
baseline
lower
at the same level from the pre-COVID to the lowereconomic activities, the intensity of the impacts was
Source:
World Bank
staff estimates
(ADePT
simulation).
case
scenario,
it would
significantly
increase
in other
not the same across the sectors. Figure II.21 shows the
Note: Impacts of COVID‐19‐related mitigation responses by the government were not included in the poverty projection.
locations of the nation (figure II.19). In particular,
distribution of the “new poor” and “already poor” who
Consumption in 2018 was adjusted to 2020 price levels. New poor are those who were not poor before the COVID‐19 pandemic
poverty
incidence
in the
centers
would
reach
livealready
under poor
the poverty
line in the pre-COVID
but became
poor during
theAimag
pandemic.
Already
poor
are thosealready
who were
pre‐COVID.
the highest levels, rising from 28 percent in the prescenario by employment sectors. Before the COVID-19
COVID households
case to 38 percent
in thelikely
lower-case
scenario. affected
outbreak,than
the share
poorareas.
was relatively
uniform
Urban
are more
to be adversely
thoseofintherural
While the
simulated
Indeed,
nearly
three-quarters
of
the
“new
poor,”
who
across
all
sectors,
but
the
projected
economic
poverty rate for 2020 in the countryside remains at the same level from the pre‐COVID to the lower‐case
fell under it
the
poverty
line due to the
COVID-19
contraction
pushes
more
service
workers into
scenario,
would
significantly
increase
in shocks,
other locations
of theclearly
nation
(figure
II.19).
In particular,
poverty
are
from
either
the
capital
city
or
Aimag
centers
(figure
poverty.
In
turn,
as
the
limited
aggregate
impacts
incidence in the Aimag centers would reach the highest levels, rising from 28 percent in the pre‐COVID
II.20) As a result, under the lower-case scenario, more
are projected in the agriculture sector under the
case
to 38 percent in the lower‐case scenario. Indeed,
nearly three‐quarters of the “new poor,” who fell
than 200,000 people in urban areas would be newly
COVID-19 scenarios, only 6 percent of the new poor
under the poverty line due to the COVID‐19 shocks, are from either the capital city or Aimag centers (figure
added to the existing poor, while 74,000 people fell
in the baseline and lower-case scenario are linked to
II.20) As a result, under the lower‐case scenario, more than 200,000 people in urban areas would be newly
into poverty in rural areas.
agriculture.
added to the existing poor, while 74,000 people fell into poverty in rural areas.
Poverty headcount rate (%)
Figure II.19. Poverty headcount byFigure
location
II.19. Poverty headcount by location
40
38
36
33
35
30
30
29
26
25
29
26
35
32
32
34
30
23
28
20
30
30
28
33
26
2018
2020 pre covid
Ulaanbaatar
2020 base
Aimag center
Soum center
2020 lower
Countryside
National
Source:
Bank
estimates
simulation).
Source: World
World Bank
staffstaff
estimates
(ADePT(ADePT
simulation).
Note:
COVID‐19‐related
mitigation
by thewere
government
included
in the poverty projections.
Note:Impacts
Impacts ofof
COVID-19-related
mitigation
responsesresponses
by the government
not includedwere
in the not
poverty
projections.
10
22
19 19 19
20
7
10
0
Ulaanbaatar
0
18 19 19
19
Ulaanbaatar
Aimag
center
7
18
7
7
Aimag center
center Soum
center Countryside
Soum
Countryside
20
10
53
0
Distribution of the poor (% of total poor)
20
Distribution of the poor (% of total poor)
Distribution of the poor (% of total poor)
Distribution of the poor (% of total poor)
Nearly
of “new
to the
COVID‐19
shocks
are by
from
the services
Figuretwo‐thirds
II.20. Distribution
of thepoor”
poor byattributable
location
Figure
II.21.
Distribution
of the poor
economic
sector sectors.
Figure II.20.Figure
Distribution
of the poor
by poor
location
FigureII.21.
II.21.
Distribution
of poor
the poor
by economic
II.20.
Distribution
the
by
location
Distribution
of the
by economic
While
the COVID‐19
shocks
haveofaffected
a wide
rangeFigure
of economic
activities,
the
intensity
ofsector
the impacts
sector
60
70
66
was not the same across theAlready
sectors.
distribution
of the “new poor”
and “already
poor (2020Figure
pre-covid) II.21 shows the Already
poor (2020 pre-covid)
64
60
70
66
Already poor (2020 pre-covid)
64
Already poor (2020
pre-covid)
poor” who already
poverty
scenario
by
employment
sectors.
Before
Newthe
poor (2020
baseline) line in the pre‐COVID
49 49 live under
New
poor
(2020
baseline)
60
50
New poor (2020 baseline)
49 49
New
poor
(2020
baseline)
60
New
poor
(2020
lower)
the COVID‐19
outbreak,
theNew
share
of lower)
the poor was relatively uniform across all sectors, but the projected
50
poor (2020
41
New poor (2020 lower)
New poor (2020 lower)
50
41
economic
40 contraction clearly pushes more service workers
50 into poverty. In turn, as the limited aggregate
40
38
impacts are projected in the agriculture sector under
of the new
40 the COVID‐19 scenarios, only 6 percent
38
34 40
34
30
30
25
30
24
agriculture.
poor in the baseline
and
lower‐case
scenario
are
linked
to
30
28
28
25 24
22
28
30
28
30
20
10
6
6 6
0
AgricultureAgriculture
6
Industry Industry
Services
Services
Source:
World
Bank(ADePT
staff(ADePT
estimates
(ADePT simulation).Source: World
Source:Bank
World
Bank
staff estimates
(ADePT
simulation).
Source:
Bank
staffstaff
estimates
simulation).
Source:World
World
Bank
estimates
simulation).
staff
estimates
(ADePT
simulation).
Note:
Impacts of COVID‐19‐related
mitigation
responses
by Impacts
Note: Impacts
of COVID‐19‐related
mitigation
responses
Note:Impacts
Impacts
COVID‐19‐related
mitigation
responses
by
Note:
of COVID‐19‐related
mitigation
responses
by by
Note:
of of
COVID-19-related
mitigation
responses
by the government
were not included
in the poverty projections.
the government were not included in the poverty
the government were not included in the poverty
the government were not included in the poverty
the government were not included in the poverty
projections
projections.
projections
42
E.
projections.
E.
Potential Mitigation Impacts of Policy Responses
Potential Mitigation Impacts of Policy Responses
There is an immediate need to increase the resilience of the poor (including “new poor”) and vulnerable
There is an households
immediate that
needare
to severely
increaseaffected
the resilience
poor (including
“newshocks.
poor”)The
andGovernment
vulnerable of
under of
thethe
ongoing
and prolonged
householdsMongolia
that areresponded
severely quickly
affected
under
the
ongoing
and
prolonged
shocks.
The
Government
of
and implemented a series of measures to mitigate negative welfare impacts
COVID -19 IMPACTS ON HOUSEHOLDS IN MONGOLIA
(4) Orphan children,
under age 18
188,000
288,000
May 1–Dec
31, 2020
14,219
The Child Money Program (CMP) is the largest social
E. Potential Mitigation Impacts
of Policy
(5) Single
parent w/4+
188,000
288,000
May 1–Dec
12
program
and covers
90 percent
(4)under
Orphanage
children,
188,000
288,000
May
1–Dec
Responses
children
18 protection
31,more
2020than 14,219
(4) Orphan children,
188,000
288,000
May 1–Dec
14,219
under age 18
31, 2020
of the poor in Mongolia.51 The
CMP provides 20,000
under age 18
31, 2020
3There
Children
age 16need
in need
Children
under
age 16
188,000
288,000
May
1–Dec
10,243
is an under
immediate
to increase
the
(5)resilience
Single parent w/4+
188,000
288,000age 18)
May per
1–Dec
12 covers
tugrug
per child (under
month and
for permanent care
in needchildren
of Single
permanent
31,
2020
(5)
parent
w/4+
188,000
288,000
May
1–Dec
12
under age 18
31, 2020
of the poor (including “new poor”) and vulnerable
2018,
18 percent of all children. As of31,
2020 about 92 percent
care children under age 80
households
that
are
severely
affected
under
the
3
Children
under
age
16
in
need
Children
under
age
16
188,000
288,000
May
1–Dec
of
the
poor
population
lives
in
households
with
CMP
4 Food Stamp Program
(1) Poor HHs: Adults
16,000
32,000
May 1, 2020– 10,243
118,748
42
42
30
20
20
10
9
9
8
8
richest
richest
richest
7
7
9
0
40
0
6
10
0
6
0
58
60
20
8
10
58
40
30
5
20
50
40
5
30
58 65
42
7
40
65
60
50
4
6 4
50
80
71
65 71
70
60
5 3 3
60
4 2 2
70
sources, 2018
100 100
73
80
70
3
poorest
poorest
80
% of population in households receiving CMP
% of population in households receiving CMP
90
households
receiving CMP, 2018
96
96
92
100
92
96
86
86
100
8392
90
83
86
77
90
83 77
73
80
73
7771
2
100
poorest
% of population in households receiving CMP
3 for
Children
undercare
age 16 in need
16
188,000
288,000
May
1–Dec
10,243
permanent
inChildren
need ofunder
permanent
31, 2020
ongoing and
prolonged
shocks.
The(2)Government
of agebenefits
wealthy households
for permanent care
inHHs:
needChildren
of permanent
31, 2020
Poor
8,000(figure II.22).
16,000 As less
May
1–Nov
123,189
care
Mongolia responded
quickly
and implemented
a series
care
have more32,000
children,May
the
poor are 118,748
more likely
4 Food Stamp
Program
(1)
Poor
HHs: Adultstend to16,000
2020–
1,1,2020
4to Food
Stampnegative
Program welfare impacts
(1) Poor HHs: Adults
16,000
32,000
May 1, 2020–
118,748
of measures
mitigate
Sources:
https://www.legalinfo.mn/law/details/15358?lawid=15358,
http://hudulmur‐halamj.gov.mn/.
to receive
higher levels
benefits compared
to
(2) Poorunder
HHs: Children
8,000
16,000 of CMP
May 1–Nov
123,189
(2)
Poor
HHs:
Children
8,000
16,000
May
1–Nov
123,189
1,
2020
the COVID-19 pandemic, which include allowance
better-off households. The CMP1,accounts
for 10 percent
2020
Sources: https://www.legalinfo.mn/law/details/15358?lawid=15358, http://hudulmur‐halamj.gov.mn/.
increases
in
the Child
Money(CMP)
Program,
foodlargest
stamps,social
of protection
household
income
for and
the bottom
percent
The
Child Money
Program
is the
program
covers 20
more
thanof90
Sources:
https://www.legalinfo.mn/law/details/15358?lawid=15358,
http://hudulmur‐halamj.gov.mn/.
49 welfare benefits
and
other
employment
and
social
households
(figure
II.23).
percent ofThe
theChild
poorMoney
in Mongolia.
The CMP
20,000
tugrug per
childand
(under
agemore
18) than
per month
Program (CMP)
is theprovides
largest social
protection
program
covers
90
49
(table
II.3).The
InChild
this
section,
using
the (CMP)
microsimulation
49As
Money
Program
is
the
largest
social
protection
program
and
covers
more
90 in
and
covers
80
percent
of
all
children.
of
2018,
about
92
percent
of
the
poor
population
lives
percent of the poor in Mongolia. 49The CMP provides 20,000 tugrug per child (under age 18) perthan
month
percent
of
the
poor
in
Mongolia.
The
CMP
provides
20,000
tugrug
per
child
(under
age
18)
per
month
results,
the
potential
mitigation
impacts
of
these
policy
households
with
CMP80benefits
II.22). As
wealthy
havepopulation
more children,
and
covers
percent (figure
of all children.
As less
of 2018,
abouthouseholds
92 percent tend
of thetopoor
lives in the
50 of 2018, about 92 percent of the poor population lives in
and
covers with
80 welfare
percent
of all
children.
responses
on household
will
be(figure
examined.
households
CMP benefits
II.22).
As benefits
less wealthy
households
tend to havehouseholds.
more children,
theCMP
poor
are more
likely to
receive
higher
levels
of As
CMP
compared
to better‐off
The
households
with
CMP
benefitshigher
(figurelevels
II.22).ofAs
lessbenefits
wealthycompared
households
tend to have
more children,
the
poor
are
more
likely
to receive
CMP
toof
better‐off
households.
The
CMP
accounts for
10
percent
of
household
income
for
the
bottom
20
percent
households
(figure
II.23).
poor are for
more
likely
to receive
higher income
levels offor
CMP
benefits
compared
toofbetter‐off
households.
The CMP
accounts
10
percent
of
household
the
bottom
20
percent
households
(figure
II.23).
Figure II.22.
Share
of10population
in income for the Figure
II.23.
Shares of
of CMP and other
household
accounts
forpopulation
percent living
ofliving
household
bottom
20 percent
(figure
II.23).
Figureincome
II.23. Shares
of2018
CMPhouseholds
and other household
income
Figure
II.22.
Share
of
in
households
receiving
CMP,
2018
sources,
Figure II.23. Shares of CMP and other household income
Figure II.22. Share of population living in
2018
sources,
2018
householdshouseholds
receiving
CMP,
Figure II.23.
Figure II.22.receiving
Share of CMP,
population
2018 living in
sources,
2018Shares of CMP and other household income
100
80
80
60
60
40
40
20
20
0
0
5 5
15 155
8
10
5
13
815
108
510
135
13
44
44 44
Q1
Q1
wage
Q1
child
wagemoney
wagecapital
child money
child money
capital
33
88
3
8
11
11
311
3
88
3
158
33
1010
3
111110
5511
665
156
15
15
15
15
50
Q2
Q2
Q2
farm
7
7
37 3
143 14
114 1
9
1 9
149
116 1
8 8
1
138
13
13
14
52
52
49
Q3
Q4
Q5
52
52
5050
3 3
5 5
3
165 16
Q3
Q3
pension
farm
farm
remittances
pension
pension
remittances
5252
14
49 49
Q4 business
Q4
Q5
Q5
other
public transfers
business
business
other
public transfers
other public transfers
Sources: NSO; 2018 HSES; World Bank staff estimates.
Sources:
Bank staff estimates.
capital NSO; 2018 HSES; World
remittances
Sources: NSO; 2018 HSES; World Bank staff estimates.
Sources: NSO; 2018 HSES; World Bank staff estimates.
Sources:
NSO;
2018
HSES;World
Bank
estimates.
Sources: NSO;
2018
HSES;
World
Bank Bank
staffprovided
estimates.
Sources:
NSO;
2018
HSES;
World
staff estimates.
Sources:
NSO;
2018
HSES;
Bankstaff
staff
estimates.
Additional
CMP
benefits
by the government
would
mitigate
theWorld
COVID‐19
welfare
loss for the
Additional
CMP benefits
provided
the government
would
mitigate
the COVID‐19
welfare
for the
poor.
In response
to COVID‐19,
theby
government
expanded
CMP’s
monthly
benefit level
fromloss
20,000
to
poor.
response
to
COVID‐19,
the government
government
CMP’s
monthly
benefit
level
from
tothe
Additional100,000
CMPInbenefits
provided
bymonths
the
thewhich
COVID‐19
welfare
loss
tugrug
per
child
for 15
from April expanded
1,would
2020 tomitigate
July 1, 2021,
is equivalent
to20,000
a costfor
of
50child for 15 months from April 1, 2020 to July 1, 2021, which is equivalent to a cost of
100,000
tugrug
per
additional
CMP benefits
would increase
per capitabenefit
consumption
the poorest
3.0 percent
GDP. 50The the
poor. In response
toofCOVID‐19,
government
expanded
CMP’s monthly
leveloffrom
20,000 to
The additional
benefits
would increase
per
capita consumption
of the
3.0 percentgroup
of GDP.
population
by 30,000
tugrugfrom
onCMP
average,
accounting
38 percent
of is
their
average
per
capita
100,000 tugrug
per child
for
15
months
April
1,
2020
to for
July361,to2021,
which
equivalent
topoorest
a cost of
population50group
byII.24).
30,000
tugrug
on
average, accounting
for
36 to
38 percent
of theirwelfare
averagelosses
per capita
consumption
(figure
The
CMP
compensation
amount
would
completely
mitigate
due
additional
CMP
would
increase
per
capita consumption
of the poorest
3.0 percentconsumption
of GDP. The
(figure
II.24).
CMP benefits
compensation
amount
would
completely
mitigate
due
to the COVID‐19
shocks
for The
the bottom
40 (figure II.25).
In the
lower‐case
scenario,
for welfare
example,losses
without
populationtogroup
by 30,000
tugrug
on bottom
average,
accounting
for
36 to
38 percent
of their
average without
per capita
the
COVID‐19
shocks
for
the
40
(figure
II.25).
In
the
lower‐case
scenario,
for
example,
effective mitigation measures, the poorest group’s consumption would decline by nearly 20 percent from
consumption
(figure
II.24).
The
CMPlevel,
compensation
amount
would
completely
mitigate
losses
effective
mitigation
measures,
the poorest
consumption
wouldtheir
decline
by nearlywelfare
20
percent
from
the
pre‐COVID
consumption
but withgroup’s
additional
CMP
benefits,
consumption
is projected
todue
the
pre‐COVID
consumption
level,
but
with
additional
CMP
benefits,
their
consumption
is
projected
to
to the COVID‐19
shocks
for the
(figureCMP
II.25).
In theare
lower‐case
scenario,
forCOVID‐19
example,
without
expand by
11 percent.
Bybottom
contrast,40
additional
benefits
not sufficient
to recover
welfare
expand
by
11
percent.
By
contrast,
additional
CMP
benefits
are
not
sufficient
to
recover
COVID‐19
welfare
effective mitigation
measures,
losses for the
top 50. the poorest group’s consumption would decline by nearly 20 percent from
lossesconsumption
for the top 50. level, but with additional CMP benefits, their consumption is projected to
the pre‐COVID
expand by4911 percent. By contrast, additional CMP benefits are not sufficient to recover COVID‐19 welfare
Based on household‐level data (population weighted) from HSES 2018.
49
losses for 50the
top
Based
on50.
household‐level
datafigure
(population
GDP
is based
on nominal 2019
(Source:weighted)
NSO). from HSES 2018.
As of November
23,is2020.
benefit
amount
for children in the Food Stamp Program decreased from MNT 16,000 to the original
50 GDP
basedThe
on monthly
nominalincreased
2019 figure
(Source:
NSO).
benefit amount of MNT 8,000 from November 1, 2020. While the extension of additional benefits for the adult Food Stamp Program was not announced,
55
the program continued at least until the end of 2020. In addition to these social protection
measures, the Government of Mongolia has implemented other
55
49 COVID-19-related responses, including exemptions of social security contributions, utility payment, and personal income tax.
Based
on
household‐level
data
(population
weighted)
from
HSES
2018.
50
Due to the difficulties identifying “children (under age 16) in need for permanent care” in HSES, the response impact of “children for permanent care”
50
GDP
is based in
onthis
nominal
is
not examined
analysis.2019 figure (Source: NSO).
51
Based on household-level data (population weighted) from HSES 2018.
49
55
43
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Table II.3.
Government responses to COVID-19 (Social protection-related measures)
Program
Eligibility criteria
Original benefit
size (monthly,
MNT)
Increased
amount
(MNT)
1
Child Money Program
(CMP)
Children age 0–18
20,000
2
Social Welfare Pension
(goes for the following
groups):
(1) Seniors (not eligible
for SI pension), F55+/
M60+
Time frame to
apply
Number of
beneficiaries
100,000
Apr 1, 2020–
July 1, 2021
1,144,630
188,000
288,000
May 1–Dec
31, 2020
3,140
(2) Dwarf individual age
16+
188,000
288,000
May 1–Dec
31, 2020
106
(3) Disabled persons age
16+
188,000
288,000
May 1–Dec
31, 2020
36,486
(4) Orphan children,
under age 18
188,000
288,000
May 1–Dec
31, 2020
14,219
(5) Single parent w/4+
children under age 18
188,000
288,000
May 1–Dec
31, 2020
12
3
Children under age 16 in
need for permanent care
Children under age 16 in
need of permanent care
188,000
288,000
May 1–Dec
31, 2020
10,243
4
Food Stamp Program
(1) Poor HHs: Adults
16,000
32,000
May 1, 2020–
118,748
(2) Poor HHs: Children
8,000
16,000
May 1–Nov 1,
2020
123,189
Sources: https://www.legalinfo.mn/law/details/15358?lawid=15358, http://hudulmur-halamj.gov.mn/.
Additional CMP benefits provided by the government
would mitigate the COVID-19 welfare loss for the poor.
In response to COVID-19, the government expanded
CMP’s monthly benefit level from 20,000 to 100,000
tugrug per child for 15 months from April 1, 2020 to
July 1, 2021, which is equivalent to a cost of 3.0 percent
of GDP.52 The additional CMP benefits would increase
per capita consumption of the poorest population
group by 30,000 tugrug on average, accounting for 36
to 38 percent of their average per capita consumption
(figure II.24). The CMP compensation amount would
completely mitigate welfare losses due to the
COVID-19 shocks for the bottom 40 (figure II.25). In
the lower-case scenario, for example, without effective
mitigation measures, the poorest group’s consumption
would decline by nearly 20 percent from the pre-COVID
consumption level, but with additional CMP benefits,
their consumption is projected to expand by 11 percent.
By contrast, additional CMP benefits are not sufficient
to recover COVID-19 welfare losses for the top 50.
52
GDP is based on nominal 2019 figure (Source: NSO).
44
As a result, with the government’s mitigation measures,
poverty is expected to fall below the pre-COVID level in
both the baseline and lower-case scenarios. As shown
in figure II.26, taking into account the additional
CMP benefits, the 2020 simulated poverty rate for
the baseline and lower-case scenarios would drop to
22.3 and 23.9 percent, respectively. While additional
allowances on the social welfare pension and Food
Stamp Program would have little effect on overall
poverty given their limited coverage of the poor, those
interventions to reach different vulnerable groups
are critical. By combining these policy responses, the
simulation results suggest that potential welfare loss
among poor households would be eliminated and
poverty rates return to below the pre-COVID level.
Baseline
35
Lower
30
20
15
Figure
II.24.
benefits
asasshare
ofofper
Figure
II.24.
CMP
additional
benefits
as
share
of
Figure
II.24.CMP
CMPadditional
additional
benefits
share
per
aa
a
capita
consumption,
2020
per
capita
consumption,
2020
10
capita consumption,
2020
Lower + CMP
15
5
0
25
25 World Bank staff estimates (AdePT simulation).
Source:
Note:
20 a. CMP recipients are based on information from the HSES
20
2018.
15
15
richest
9
8
7
Lower + CMP
Lower + CMP
6
5
4
3
Baseline + CMP
Baseline + CMP
2
richest
15
15
poorest
-10
20-15
20
9
8
7
Baseline
Lower
Baseline
Lower
6
5
4
3
2
poorest
% change from the uncompensated case
% change from the uncompensated case
Baseline + CMP
Figure
II.25.
Welfare
additional
Figure
II.25.
Welfarechanges
changes
with
CMP
Figure
II.25.
Welfare
changeswith
withCMP
CMPadditional
additional
-5 compared
benefits
to
pre‐COVID
case,
2020
benefits
compared
to
pre-COVID
case,
2020
benefits compared to pre‐COVID case, 2020
40 5
40
30
30
20
COVID -19 IMPACTS
ON HOUSEHOLDS IN MONGOLIA
10
25
35 0
35
% change from the 2020 pre-COVID case
% change from the 2020 pre-COVID case % change from the 2020 pre-COVID case
% change from the uncompensated case
40
10
10
Source: World Bank staff estimates (AdePT simulation).
5
0
5
0
richest
richest
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
poorest
poorest
richest
richest
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
poorest
poorest
-5
As a result,
with the government’s mitigation measures, poverty
is expected to fall below the pre‐COVID
10
-5
10
level in
both the baseline and lower‐case scenarios. As -10
shown
in figure II.26, taking into account the
5
-10
5
additional CMP benefits, the 2020 simulated poverty rate for
the
baseline
and lower‐case scenarios would
-15
0
-15
0
drop to 22.3 and 23.9 percent, respectively. While additional allowances on the social welfare pension
and Food Stamp Program would have little effect on overall poverty given their limited coverage of the
poor,
those
interventions
to (AdePT
reach simulation).
different vulnerableSource:
groups
areBank
critical.
By combining
these policy
Source:
World
Bank
staff
estimates
World
staff
(AdePT
Source:
World
Bank
staff
estimates
(AdePT
simulation).
Source:
World
Bank
staffestimates
estimates
(AdePTsimulation).
simulation).
Source:
World
Bank
staff
estimates
(AdePT
simulation).
Source:
World
Bank
staff
estimates
(AdePT
simulation).
responses,
the
simulation
results
suggest
that
potential
welfare
loss
among
poor
households
would be
Note:
Note:a.a.CMP
CMPrecipients
recipientsare
arebased
basedononinformation
informationfrom
fromthe
theHSES
HSES
Note:
a.
CMP
recipients
are
based
on
information
from
the
HSES
2018.
eliminated
and
poverty
rates
return
to
below
the
pre‐COVID
level.
2018.
2018.
Figure
II.26. Povertymitigation
headcountmeasures,
rates with and
without
policy responses,
2020 the pre‐COVID
As
government’s
poverty
isisexpected
Asaaresult,
result,
with
the
government’s
mitigation
poverty
expected
fallbelow
below the pre‐COVID
Figurewith
II.26.the
Poverty
headcount rates
with and measures,
without policy
responses,
2020a totofall
level
levelininboth
boththe
thebaseline
baselineand
andlower‐case
lower‐casescenarios.
scenarios.As
Asshown
shownininfigure
figureII.26,
II.26,taking
takinginto
intoaccount
accountthe
the
additional
CMP
benefits,
the
2020
simulated
poverty
rate
for
the
baseline
and
lower‐case
scenarios
would
40
additional CMP benefits, the 2020 simulated poverty rate for the baseline
and lower‐case
scenarios would
33.6
33.4
33.4
31.7
31.5 additional allowances on the social welfare pension
31.5 While
drop
and
23.9
percent,
respectively.
droptoto22.3
22.3
and
23.9
percent,
respectively.
While
additional
allowances
on
the
social
welfare
pension
30
25.8
23.9
and
Food
Stamp
Program
would
have
little
effect
on
overall
poverty
given
their
limited
coverage
23.4
and Food Stamp Program would 22.3
have little effect on 21.7
overall poverty given their limited coverageofofthe
the
poor,
those
interventions
to
reach
different
vulnerable
20
poor, those
interventions to reach different vulnerablegroups
groupsare
arecritical.
critical.By
Bycombining
combiningthese
thesepolicy
policy
responses,
the
responses,
thesimulation
simulationresults
resultssuggest
suggestthat
thatpotential
potentialwelfare
welfareloss
lossamong
amongpoor
poorhouseholds
householdswould
wouldbe
be
10
eliminated
and
poverty
rates
return
to
below
the
pre‐COVID
level.
eliminated and poverty rates return to below the pre‐COVID level.
31.7
31.7
31.5
31.5
31.5
31.5
33.4
33.4
Lower + FSP
Lower + SWP
33.6
33.6
Lower + CMP
Lower
Base + All SP
responses
Base + FSP
Base + SWP
Base
Base + CMP
40
40
a
Figure
FigureII.26.
II.26.Poverty
Povertyheadcount
headcountrates
rateswith
withand
andwithout
withoutpolicy
policyresponses,
responses,2020
2020a
pre-COVID
0
33.4
33.4
2020 poverty rates (%)
2020 poverty rates (%)
Source:World
World Bank staff estimates (ADePT simulation);
Source:
30
25.8 Bank staff estimates (ADePT simulation);
30
25.8
23.9
23.9
Note:
beneficiary and
pre-COVID
allowance
level information
of each
is based
on the is
HSES
2018.
22.3allowance
Note:
a. a.AllAllbeneficiary
and
pre‐COVID
level information
of each
program
based
on the HSES 2018.
21.7program
22.3
21.7
= ChildMoney
Money Program;
FSPFSP
= Food
StampStamp
Program;
SWP = Social
Welfare
Pension.
CMPCMP
Program;
=
Food
Program;
SWP
=
Social
Welfare
Pension.
20= Child
20
Lower + All SP
responses
2020 poverty rates (%)
a
23.4
23.4
10
10
Lower + All SP
Lower
+ All SP
responses
responses
Lower + FSP
Lower + FSP
Lower + SWP
Lower + SWP
Lower + CMP
Lower + CMP
Lower
Lower
Base + All SP
Base
+ All SP
responses
responses
Base + FSP
Base + FSP
Base + SWP
Base + SWP
Base + CMP
Base + CMP
Base
Base
pre-COVID
pre-COVID
The HRPS results also suggested that COVID‐19‐related government assistance has generally been
0
0 in mitigating negative economic impacts of the pandemic for beneficiary households,
helpful
particularly the poor. Among households receiving any type of government assistance, 35 percent
expressed that the aid completely made up for the negative repercussions of the crisis, while another 57
percent said that it partially offset impacts (figure II.27). These numbers are largely driven by the ability
Source:
Source:World
WorldBank
Bankstaff
staffestimates
estimates(ADePT
(ADePTsimulation);
simulation);
Note:
a.
All
beneficiary
and
pre‐COVID
56 ofofeach
Note: a. All beneficiary and pre‐COVIDallowance
allowancelevel
levelinformation
information
eachprogram
programisisbased
basedononthe
theHSES
HSES2018.
2018.
CMP
CMP= =Child
ChildMoney
MoneyProgram;
Program;FSP
FSP= =Food
FoodStamp
StampProgram;
Program;SWP
SWP= =Social
SocialWelfare
WelfarePension.
Pension.
The
TheHRPS
HRPSresults
resultsalso
alsosuggested
suggestedthat
thatCOVID‐19‐related
COVID‐19‐relatedgovernment
governmentassistance
assistancehas
hasgenerally
generallybeen
been
helpful
helpful inin mitigating
mitigating negative
negative economic
economic impacts
impacts ofof the
the pandemic
pandemic for
for beneficiary
beneficiary households,
households,
particularly
particularlythe
thepoor.
poor.Among
Amonghouseholds
householdsreceiving
receivingany
anytype
typeofofgovernment
governmentassistance,
assistance,35
35percent
percent
expressed
57
expressedthat
thatthe
theaid
aidcompletely
completelymade
madeup
upfor
forthe
thenegative
negativerepercussions
repercussionsofofthe
thecrisis,
crisis,while
whileanother
another
45 57
percent
said
that
it
partially
offset
impacts
(figure
II.27).
These
numbers
are
largely
driven
by
the
ability
percent said that it partially offset impacts (figure II.27). These numbers are largely driven by the ability
56
56
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
The HRPS results also suggested that COVID-19related government assistance has generally been
helpful in mitigating negative economic impacts of
the pandemic for beneficiary households, particularly
the poor. Among households receiving any type of
government assistance, 35 percent expressed that the
aid completely made up for the negative repercussions
of the crisis, while another 57 percent said that it
partially offset impacts (figure II.27). These numbers are
largely driven by the ability of the CMP to partially or
fully offset the negative income shocks that households
have experienced since the crisis began. While most of
both poor and non-poor CMP recipients expressed that
the transfers were beneficial, poor recipients were 6
percent more likely to indicate that the aid completely
or partially mitigated the effects of the crisis.
COVID-19-related disruptions have been ongoing and
might have escalated since the government imposed
the second lockdown measures in mid-November, and
the actual impacts on household welfare need to be
closely monitored. The estimated potential impacts
on poverty in this report are based on the latest
available macroeconomic forecasts, distributional
and price assumptions. Once the macroeconomic
forecasts and other model assumptions are revised,
the microsimulation results need to be updated
accordingly.
Figure II.27. Perception of usefulness of government assistance
Percent of beneficiary households
Any government
assistance
35
Child Money
Program
Other Direct
Cash Transfers
37
18
Source: World Bank staff estimates (HRPS Round 2).
46
57
6
3 4
56
60
8
14
Completely mitigated
Partially mitigated
Has not mitigated
Not affected by COVID-19
REFERENCES
References
Himelein, K. 2014. “Weight Calculations for Panel Surveys with Subsampling and Split-off Tracking.”
Statistics and Public Policy 1 (1). Taylor & Francis Online, December 23. https://www.tandfonline.
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IMF (International Monetary Fund). 2012. “Inflation Dynamics in Mongolia: Understanding the Roller
Coaster.” International Monetary Fund, Washington, DC.
_____. “2016. Guidance note on the assessment of reserve Adequacy and related considerations”
https://www.imf.org/external/np/pp/eng/2016/060316.pdf
_____.. 2020. World Economic Outlook, October 2020: A Long and Difficult Ascent. Washington DC: International
Monetary Fund.
National Statistics Office of Mongolia and World Bank. 2020. Mongolia Poverty Update 2018
(English). Washington, DC: World Bank Group. http://documents.worldbank.org/curated/
en/532121589213323583/Mongolia-Poverty-Update-2018.
_____. 2020. “Results of Mongolia COVID-19 household Response phone survey (Round 1).” Ulaanbaatar.
_____. 2020. “Results of Mongolia COVID-19 household Response phone survey (Round 2).” Ulaanbaatar.
_____. 2021. “Results of Mongolia COVID-19 household Response phone survey (Round 3).” Ulaanbaatar.
Olivieri S., S. Radyakin, S. Kolenikov, M. Lokshin, A. Narayan, and C. Sánchez-Páramo. 2014. “Simulating
Distributional Impacts of Macro-dynamics: Theory and Practical Applications.” World Bank
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World Bank. 2020a. World Bank East Asia and Pacific Economic Update, April 2020: East Asia and Pacific in
the Time of COVID-19. Washington, DC: World Bank. https://openknowledge.worldbank.org/
handle/10986/33477.
_____. 2020b. World Bank East Asia and Pacific Economic Update, October 2020: From Containment to Recovery.
Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/34497.
_____. 2021. Global Economic Prospects, January 2021. Washington, DC: World Bank. https://openknowledge.
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47
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
MONGOLIA ECONOMIC UPDATE From Relief to Recovery
Address: Floor 5, MCS Plaza, 4 Seoul Street, 14250 Ulaanbaatar, Mongolia
Tel: +(976)7007 8200 • Web: www.worldbank.org/mongolia
Facebook: World Bank Mongolia
50