Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
A Possible Macro-Prudential Approach: Case of Mongolia
Nomun Bukh-Ochir *
The recent financial crisis has required implementing specific macro
approach of financial regulation and supervision. Thus, macro-prudential
policy recently attracted considerable attention among global central banks.
In 2008, dramatic fall occurred in the loan growth of Mongolian banks and
whole economy was slowed down because of large banking sector.
Therefore this paper provides an investigation of Mongolian financial
systemic risk using macro-prudential frame and the way to avoid financial
systemic risk.
Dynamic provision was determined as a countercyclical macro-prudential tool
to avoid systemic risk. Procyclicality, cross-sectional systemic risk analysis,
and financial soundness indicators proposed that Mongolian financial system
is at credit risk because of large banking sector. After financial crisis,
although provision was 389.64 billion tugriks in January of 2010, dynamic
provision was calculated as 62.64 billion tugriks that confirmed dynamic
provision is countercyclical capital buffering tool. The impulse response
analysis of FAVAR, considered commodity price shock and domestic
economy shock, appears to be significant to adopt dynamic provision as a
macro-prudential tool.
JEL Codes: E44, E47, E58, E61, G28, G32
1. Introduction
Recent financial crisis has highlighted financial stability policy that is counterbalanced
systemic risk rather than micro-prudential policy. In other words, macro-prudential policy is
provided to weaken the financial imbalances and accumulated systemic risk. Board of IMF
investigated macro-prudential tools’ implementations and significance from overall countries
experiences (Lim and et al, 2011). However only limited research and analytical tools was
available to inform decisions on a macro-prudential policy framework, macro-prudential tools
implication was successfully in Spain, Peru, USA, Chile, and Euro area countries.
In Mongolia, excess demand boom increases risk of sudden reversal and emergence of
financial excesses and vulnerabilities in banking sector through export channel, fiscal
channel, and credit channel (Maino and et al, 2012). The focus of our paper is determining
the accumulating risk, proposing dynamic provision as a macro-prudential tool, and its
impulse response to commodity market shock and domestic economy shock.
*Nomun Bukh-Ochir, Department of Financial Management, Institute of Finance and Economics, Mongolia.
Email : nomun.b@ife.edu.mn
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
In the paper, we draw accumulated risk perspective to procyclicality, cross-sectional systemic
risk, and financial soundness indicators. Factor augmented VAR model’s impulse response
function illustrates us dynamic provision’s significance to commodity price shock and
domestic economy shock. Principal component analysis provides us to get commodity price
factor and domestic economy factor from large set of data.
Dynamic provision is convenient counter cyclical capital buffering tool to avoid systemic risk in
Mongolia. In particular, dynamic provision was 62.64 billion tugriks as we calculated but
actual provision was 389.64 billion tugriks in January of 2010. We obtain a result that both
commodity price shock and domestic economy shock affect dynamic provision in a month
which was taken out from the impulse response function of FAVAR model.
2. Economic overview
Mongolia is at a juncture of loosening fiscal policy conductive to credit exuberance and
inflation. Excess demand boom increases risk of sudden reversal and emergence of financial
excesses and vulnerabilities in the banking sector.
Macro-prudential tools and regulations may complement but not substitute the need to
contain systemic risk through fiscal policy.
2.1. Procyclicality
Figure 1 Copper price and Export
Figure 2 GDP and Export
Figure 1 illustrates high correlation of export and copper price. In the figure 2 we can see
GDP growth is high correlated with copper price. The cause of economic growth can be
explained by increasing of commodity price. On the other word, these correlations are
expressing Mongolian economy is at procyclical risk.
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Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
2.2. Cross-sectional systemic risk
Figure 3 Interbank connectedness
Figure 4 Domestic and Foreign currency loan
Deep inter-connectedness of banks is high level of cross-sectional risk (Figure 3). Increasing
dollarization negatively influences the domestic economy (Figure 4).
2.3. Financial soundness indicators
We calculated some of financial soundness indicators which are capital adequacy ratio (tier 1
capital and risk weighted assets ratio), non-performing loan and total loan ratio, liquidity ratio,
and leverage ratio.
Figure 5 Financial soundness indicators /Core set/
Increasing capital adequacy and financial leverage, decreasing NPL ratio and liquidity ratio
were sounding good economy condition until 4th quarter of 2008 but then financial crisis
occurred (Figure 5). CAR and leverage decreased, NPL ratio and liquidity increased when
crisis occurs.
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Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Mongolian macro economy indicators and financial indicators are procyclicality. Interbank
connectedness leads us to cross-sectional systemic risk. Therefore we need a policy that
loosens systemic risk when economy falls.
Otherwise, central bank policy that reduces institutional risk by monetary policy instrument is
not enough to neutralize systemic risk. That’s why Bank of Mongolia need to implement
macro-prudential policy.
3. Dynamic provisioning
Total loan growth increased to 71 percent and actual provision rate decreased to 3 percent
before crisis in October of 2008. When economic fall happens, loan of loose standard altered
to non-performing loan. In particular, total loan growth was 1.6 percent and systemic provision
rate increased to 7 percent in May of 2009. Credit risk led banking sector to systemic risk.
In January of 2010 even actual provision was 389.6 billion tugriks, dynamic provision was
62.2 billion tugriks as we calculated. It provides us avoiding from provision boom in economic
falling period by dynamic provision (Figure 6).
Figure 6 Dynamic provision and Actual provision
In October of 2008 total loan growth increased to 70 percent but it decreased to 3.6 percent
in August of 2010. Total loan was 5.5 trillion tugriks in December of 2010 under actual
provision but it was 5.4 trillion tugriks under dynamic provision (Figure 7)
4
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Figure 7 Total loans and Loan growth path (Under dynamic provision and actual provision)
We approved that dynamic provision limits loan growth. It is suitable tool to accept as a
macro-prudential tool because it could construct countercyclical capital buffer.
3.1. FAVAR estimation
In this section we will investigate dynamic provision’s impulse response to commodity price
shock and domestic economy shock using factor augmented VAR model. Restriction of
FAVAR was structural decomposition that commodity price shock affects to both domestic
economy and dynamic provision, domestic economy shock doesn’t affect to commodity price
and it affects dynamic provision. Dynamic provision neither affects to commodity price and
domestic economy. Therefor we obtain commodity price factor F1 and domestic economy
factor F2 using principal component analysis.
We constructed the FAVAR model as follows:
(1)
(2)
(3)
3.1.1. Impulse response function analysis
Impulse response function illustrates us both commodity price shock and domestic economy
shock affect dynamic provision in a month. Next month it becomes clear purely.
5
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
6
8
5
6
4
3
4
2
2
1
0
0
-1
-2
-2
-3
-4
1
2
3
4
5
6
7
8
9
10
Figure 8 Response of Dynamic provision to commodity price shock
1
2
3
4
5
6
7
8
9
10
Figure 9 Response of Dynamic provision to domestic economy
shock
4. Conclusion
Macro-prudential policy aims to provide systemic stability in wide range.
Procyclicality was determined as copper price growth and export growth correlation, export
growth and GDP growth correlation. Cross-sectional risk was determined as interbank
connectedness and dollarization. Financial soundness indicators are expressing economic
growth which leads credit growth that is faced to systemic risk.
Dynamic provision is counter cyclical capital buffer. In January of 2010 dynamic provision was
62.2 billion tugriks as we calculated but actual provision was 389.6 billion tugriks.
Further, we need to calculate LTV ratio and use a stress test for estimating its implication.
References
Bank of Mongolia. (2012). Monthly bulletin. Ulaanbaatar: BoM.
Dashdorj, S & Dulamzaya, B. (2010). Macro economy and Financial market linkage: Case of
Mongolia. Ulaanbaatar: IFE.
De Bandt, O., & Hartmann, P. (2000). Systemic Risk: A Survey. ECB Working Paper No. 35.
De Bandt, O., Hartmann, P., & Peydro, J. L. (2009). Systemic risk: An update. Oxford
Handbook of Banking, Oxford University Press.
De Nicolo', G., & Lucchetta, M. (2009). Systemic Risk and the Macroeconomy. IMF.
Galati, G., & Moessner, R. (2011). Macroprudential policy - a literature review. Monetary and
Economic Department: BIS Working Papers No 337.
Maino, R., Imam, P., & Ojima, Y. (2012). Mongolia: Macroprudential Policy Implementation.
Monetary and Capital Markets Department: IMF.
Maino, R., Patrick, I., & Yasuhisa, O. (2012). Mongolia: Macroprudential Policy
Implementation. IMF.
National Statistical Organization. (1995-2011). Statistical Year Book. Ulaanbaatar: Admon
press.
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Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Saurina, J. (2009a). Loan loss provisions in Spain. A working macroprudential tool. Bank of
Spain Financial Stability review No. 17, p. 11-26.
Saurina, J. (2009b). Dynamic Provisioning. The experience of Spain. The World Bank: Crisis
Response. Public Policy for the Private Sector. Note Nomber 7.
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Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Appendixes
Appendix 1 Financial soundness indicators /Encouraged set/
Appendix 2 Actual provision and Actual
provision rate
Appendix 3 Total loans, actual
provision, actual provision rate, and
non-performing loan ratio
Appendix 4 Actual provision, nonperforming loan, and Actual provision
and NPL ratio
Appendix 5 Actual provision and
Dynamic provision
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Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
1
-0.391
(0.122)
1
-1.238
(1.166)
-3.239
(1.087)
Appendix 6 FAVAR estimation
9
1
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Response to Structural One S.D. Innovations ± 2 S.E.
Response of D(F1) to Shock1
Response of D(F1) to Shock2
Response of D(F1) to Shock3
1.5
1.5
1.5
1.0
1.0
1.0
0.5
0.5
0.5
0.0
0.0
0.0
-0.5
-0.5
-0.5
-1.0
-1.0
1
2
3
4
5
6
7
8
9
10
-1.0
1
2
Response of D(D(F2)) to Shock1
3
4
5
6
7
8
9
10
1
Response of D(D(F2)) to Shock2
2
2
1
1
1
0
0
0
-1
-1
-1
-2
-2
2
3
4
5
6
7
8
9
10
Response of D(DY_PRO) to Shock1
2
3
4
5
6
7
8
9
10
1
Response of D(DY_PRO) to Shock2
12
8
8
8
4
4
4
0
0
0
-4
2
3
4
5
6
7
8
9
10
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
Response of D(DY_PRO) to Shock3
12
1
4
-2
1
12
-4
3
Response of D(D(F2)) to Shock3
2
1
2
-4
1
2
3
4
5
6
7
8
9
10
Appendix 7 Impulse response function
10
1
2
3
4
5
6
7
8
9
10
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
№
1
Industrial
production
Industrial production
2
Mining and quarrying
3
Manufacturing
4
Electricity, thermal energy
and water supply
5
Real sector
Industrial production
End of the
period
End of the
period
End of the
period
Current
prices
Current
prices
Current
prices
End of the
period
Current
prices
End of the
period
End of the
period
End of the
period
Constant
prices
Constant
prices
Constant
prices
nso.mn
ip1
nso.mn
ip2
nso.mn
ip3
nso.mn
ip4
nso.mn
rp1
nso.mn
rp2
nso.mn
rp3
6
Mining and quarrying
7
Manufacturing
8
Electricity, thermal energy
and water supply
End of the
period
Constant
prices
nso.mn
rp4
USD/MNT
End of the
period
Tugrik
against
USD
BoM
e1
10
CNY/MNT
End of the
period
Tugrik
against
CNY
BoM
e2
11
EUR/MNT
End of the
period
Tugrik
against
EUR
BoM
e3
12
RUB/MNT
End of the
period
Tugrik
against
RUB
BoM
e4
Weighted average rate
End of the
period
average of
7 day
CBBR
BoM
i1
7-day
CBBR
BoM
i2
CBBR
BoM
i3
CBBR
BoM
i4
BoM
i5
BoM
i6
BoM
i7
BoM
i8
BoM
m1
BoM
m2
9
13
Exchange rates
Хүүний түвшин
14
Policy rate
15
1 week
16
12 weeks
17
Interbank loans rate
Banks loan rates (Domestic
currency)
Banks loan rates (Foreign
currency)
18
19
Effective rate
20
21
22
Money survey
M0
(Reserve Money)
M1
(Narrow Money)
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
11
in annual
percent
in annual
percent
in annual
percent
in annual
percent
Million
tugriks
Million
tugriks
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
Quasi money
23
M2
(Broad Money)
DMB reserves (Bank
reserves)
24
25
26
Total loans outstanding
27
Loans to Private sector
28
Price indexes
Overall CPI
29
Food CPI
30
Alcoholic beverages
31
Clothing
32
Housing
33
Furnishing
34
Health
35
Transport
36
Communication
37
Recreation
38
Education
39
Restaurant and Hotel
40
Miscellianeous
41
Inflation
42
Fiscal
Revenue & Grant
43
Current revenue
44
Tax revenue
45
Non-tax revenue
46
Capital revenue
47
Grant
48
Expenditure
49
Current expenditure
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
2005 он 12
сар = 100
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
12
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
BoM
m3
BoM
m4
BoM
m5
BoM
m6
BoM
m7
index
BoM
p1
index
BoM
p2
index
BoM
p3
index
BoM
p4
index
BoM
p5
index
BoM
p6
index
BoM
p7
index
BoM
p8
index
BoM
p9
index
BoM
p10
index
BoM
p11
index
BoM
p12
index
BoM
p13
BoM
p14
nso.mn
g1
nso.mn
g2
nso.mn
g3
nso.mn
g4
nso.mn
g5
nso.mn
g6
nso.mn
g7
nso.mn
g8
Year-onyear
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
Proceedings of 24th International Business Research Conference
12 - 13 December 2013, Planet Hollywood, Las Vegas, USA, ISBN: 978-1-922069-37-5
50
Capital expenditure
51
net credit
52
Primary balance
53
Overall balance
54
Trade balance
Export
55
Copper concentrate
56
Gold
57
Coal
58
Zinc
59
Crude oil
60
Goat cashmere
61
Ironstone
62
Molybdenum
63
Goat dehaired cashmere
64
Spar
65
Import
66
Export price index
67
Import price index
68
Trade term
Cumulative
basis
Cumulative
basis
Cumulative
basis
Cumulative
basis
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
End of the
period
Appendix 8 Data
13
Million
tugriks
Million
tugriks
Million
tugriks
Million
tugriks
nso.mn
g9
nso.mn
g10
nso.mn
g11
nso.mn
g12
dollar
BoM
x1
dollar
Bloomberg
x2
dollar
Bloomberg
x3
dollar
Bloomberg
x4
dollar
Bloomberg
x5
dollar
Bloomberg
x6
dollar
Bloomberg
x7
dollar
Bloomberg
x8
dollar
Bloomberg
x9
dollar
Bloomberg
x10
dollar
Bloomberg
x11
dollar
nso.mn
x12
index
BoM
x13
index
BoM
x14
index
BoM
x15