Mezinárodní konference "Česká a světová ekonomika po
globální finanční krizi"
International reserves and the
financial crisis: monetary policy
matters
Sona Benecka, VŠFS, ČNB
25 Nov 2011
International reserves literature
Buffer stock - to fluctuations in external transaction (Heller,
1966)
Combined with inventory theoretic approach
(Frenkel and Jovanovic,1981)
Currency crisis – first and second generation models
(Krugman, 1979; Obstfeld, 1986)
IMF and international vulnerability
(Bussiere and Mulder, 1999)
Mercantilist motives – export promoting (Aizenman and Lee,
2007)
Financial globalization – protection of domestic credit
markets (Obstefeld, Shambaugh and Taylor, 2008)
2
Relevance: “fear of floating” or “fear of losing IR”
Crisis 2008 – 2009 – IR served as a warchest? (Obstfeld,
2008; Aizenman, 2010) – implications for economic policy
> 35 %
Iceland
Poland
Ukraine
Zambia
New Zealand
South Korea
Russian Federation
United Kingdom
Sweden
Colombia
Hungary
Australia
Turkey
Mexico
Chile
Chile
Romania
Brazil
Depreciation
25 - 35 %
15 - 25 %
Mongolia
Kazakhstan
Belarus
Jamaica
Norway
Kenya
South Africa
Uganda
Swaziland
Croatia
Pakistan
Botswana
Gambia, The
Latvia
Canada
Macedonia
Indonesia
Guinea-Bissau
Czech Republic Cape Verde
Mauritius
Bosnia & Herzegovina
Bhutan
Bulgaria
India
Estonia
Nigeria
Denmark
Albania
Lithuania
Armenia
Israel
Philippines
Ethiopia
Uruguay
Argentina
Switzerland
Morocco
Kyrgyz Republic
Malaysia
Appreciation
0 - 15 %
Costa Rica
Thailand
Paraguay
Peru
Madagascar
Algeria
Georgia
Tanzania
Libya
Singapore
Kuwait
Sri Lanka
Haiti
Guatemala
Dominican Republic
Nicaragua
Burundi
Sierra Leone
Rwanda
Egypt
Angola
Bangladesh
Hong Kong
Trinidad and Tobago
Japan
Laos
China
Azerbaijan
Bolivia
Inflation
targeting
countries
highlighted
3
Inflation targeting countries and the crises
• de Carvalho Filho (2011): „inflation targeting countries
lowered nominal and real interest rates more sharply than
other countries; were less likely to face deflation scares;
and had sharp real depreciations without a relative
deterioration in their risk assessment by markets“
4
Monetary policy and IR: Trilemma vs. Quadrilemma
Mundell-Fleming’s impossible trinity
Policy choice:
Closed financial markets
Policy goal:
Monetary
independence
Policy choice:
Floating exchange
rate
Policy goal:
Exchange rate
stability
New dimension:
Accumulation of
international
reserves
improves financial
stability and
allows for
independent
monetary
policy
(Aizenman, 2011)
Policy choice:
Give up monetary
independence
Policy goal:
Financial integration
5
The role of monetary policy and ER regime
Comparable to Obstfeld et alt. (2008)
Panel data analysis:
Sample: 123 countries
Time period: 1999 – 2009 (if data available)
Data source: Worldbank, IMF, EIU
Extended with MP/ER arrangements and financial stability
Dummy variable for exchange rate regime (from
currency union to free float, 2 classifications)
Dummy variable for monetary policy arrangement
Monetary independence
Financial stability measured by M2/GDP and banking
crisis dummy
6
Trends in explanatory variables
Globalization in trade and capital
Strong impact of financial crisis
No clear trend of growing ER flexibility
More countries with ER anchor and IT regime
1.2
0.3
1
0.3
0.9
1
0.25
0.8
0.2
0.25
0.8
0.7
0.2
0.6
0.4
0.1
Reserves on GDP (right axis)
0.05
09
08
20
07
20
06
20
05
20
04
20
03
20
02
0
01
0
20
09
08
20
07
20
06
20
05
20
04
20
03
20
02
20
01
20
20
20
00
0
99
0
HM FI
00
Reserves on GDP (right axis)
0.1
0.2
20
0.05
99
Cap ital account op eness
0.2
M 2 on GDP
0.3
20
0.1
19
Trade op eness
0.4
0.15
0.5
20
0.15
0.6
19
•
•
•
•
7
Summary of main results I
• Openness to trade and the development of the current
account is still a crucial for the determination of the
reserves. So country with export-oriented growth may be
sensitive to exchange rate, especially if not allowing for
free capital movement.
• Opening capital account was a very dynamic process in
1990’s, while after 2000 it slowed down. If we account for
the effect of wealth, this improves the estimate.
• Oil exporters have substantially higher reserves; the
income from oil export may well be transferred to reserves
or CB react more on ER movements to stabilize oil
revenues.
8
Summary of main results II
• As for exchange rate arrangements, we find inverted-U
relationship, with free floating and fixed arrangements
holding most reserves.
• As for monetary policy regimes, the results are rather
weak. The sign for inflation targeting countries is
negative, but insignificant.
• Finally, the financial stability plays an important role.
When the banking crises starts, the reserves are
eventually used. But the measurement of the financial
system vulnerability is difficult.
9
A proposal for the new framework
• The current framework is still not able to describe fully
underlying forces behind huge accumulation of reserves.
• One possible explanation: failing monetary policy, non
availability of other policy instruments/channels.
• The choice of monetary policy mix may be driven by
specific conditions of emerging economies like
1) Relationship to fiscal policy and CB independence.
2) Stage of development of the financial system
3) Limited functioning of the standard transmission
channels
10
Some evidence
• First hint: Central bank credibility – index from Meade and
Crowe (2008)
Number of obs = 81
R-squared =
Number of clusters (code) = 81
Trade openess
Capital account openess
Net oil export
HMFI
CBI
Constant
0.253
Coeficient
0.538
-0.269
0.033
0.020
-0.769
1.782
Robust
Std. Err.
0.258
0.073
0.029
0.010
0.462
0.892
t
2.08
-3.71
1.12
1.95
-1.67
2
P>|t|
0.041
0.000
0.268
0.055
0.100
0.049
[95% Conf. Interval]
0.024
1.052
-0.414
-0.125
-0.026
0.091
0.000
0.040
-1.688
0.150
0.008
3.556
Note: author’s calculations. Cross-section for 2003.
• Still more work to be done: on-going reserach ->
countries holding more reserves use them as the fist MP
instrument
11
Economic policy implications
• Accumulation of reserves as a war chest against the
crisis does not have to be the most effective way..
• Optimal level of reserves to be doubted (dominance of
non linear relationship between variables, country specific
structural weaknesses and peculiarities of the individual
financial markets) ->
develop stress testing for balance of payment
(in 2012)
12
Thank you for your attention
www.cnb.cz
Sona Benecka
sona.benecka@cnb.cz
13
Summary statistics
Table 1: Summary statistics
Variable
Reserves on GDP
Population (mil)
GDP per capita
Trade openess
Capital account openess
Oil exports
HIM
M2 to GDP
Banking crisis
Observations
1353
1353
1353
1353
1353
1353
1305
1353
1353
Mean
0.189
46.329
11.606
0.933
0.864
0.673
0.764
0.788
0.061
Std. Dev.
0.189
157.117
15.916
0.564
1.577
2.266
0.109
0.818
0.239
Min
0.001
0.250
0.086
0.190
-1.844
0.000
0.000
0.067
0.000
Max
1.583
1345.750
117.955
4.381
2.478
19.030
0.954
6.639
1.000
Source: author’s calculation from World Development Indicators (Worldbank), IFS IMF (April 2011), Economic Intelligence
Unit (for several data missing), Heritage Foundation website and Laeven and Valencia (2010) database.
14
Explanatory variables
General cross-country differences: population, GDP per capita,
advanced countries dummy, share on net oil export
Trade openness – export+import/gdp
Financial openness – Chinn-Ito capital market openness index
Monetary policy arrangements – de facto classification by IMF:
inflation targeting (1), monetary aggregate targeting (2), IMF
support (3), other (4), ER anchor (5), monetary union (6)
Exchange rate regime – see below
Monetary independence - Heritage monetary freedom index
HI _ M i  100    1 it   2 it 1   3 it  2  PC i
Financial stability: M2/GDP and banking crisis dummy
15
Traditional model and its extensions
Population
GDP per capita
Trade openess
Capital account openess
Net oil export
Advanced country
dummy
Interaction term
Constant
R-sq (overall/within)
Obs
I
II
III
Traditional model
With advanced country With interaction term
Fixed
Fixed
Fixed
Pooled OLS
effects
Pooled OLS
effects
Pooled OLS
effects
-0.067
0.475
0.049
0.441
-0.195***
0.074
0.052
0.084
0.579**
0.614***
0.575***
0.702***
0.604***
0.731***
0.224
0.151
0.204
0.145
0.198
0.144
-0.071
-0.075
-0.019
0.004
0.045
0.055
0.044
0.051
0.083***
0.19***
0.041**
0.194***
0.048***
0.19***
0.020
0.056
0.016
0.062
0.017
0.063
-1.154*** -1.696*** -0.858***
-1.457**
0.240
0.565
0.242
0.601
-0.049**
-0.048*
0.024
0.026
-1.555*** -3.184*** -1.725*** -1.696*** -1.688*** -1.621***
0.128
0.922
0.088
0.130
0.085
0.136
0.218
1353
0.076
1353
0.315
1353
0.144
1353
0.329
1353
0.159
1353
Note: standard errors in parentheses, dependent variable: ln(IR/GDP)
*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively
16
Exchange rate regime matters…
I
Trade openess
CO interaction term
Net oil export
Regime 1
Regime 2
Regime 3
Regime 4
Regime 5
Regime 6
Regime 7
Constant
R-sq (overall/within)
Obs
III
Reinhart and Rogoff
IMF classification
Intermediate regimes
coarse classification
Fixed
Fixed
Fixed
Pooled OLS
effects
Pooled OLS
effects
Pooled OLS
effects
0.504***
0.874***
0.509***
0.878***
0.696***
0.826***
0.163
0.156
0.162
0.155
0.187
0.154
-0.048*
-0.066***
-0.046*
-0.063*** -0.127*** -0.096***
0.024
0.020
0.023
0.020
0.025
0.028
0.028*
0.212***
0.027*
0.213***
0.061***
0.183***
0.015
0.062
0.015
0.060
0.018
0.060
-1.39***
-1.405**
-1.401***
-1.485**
0.059
-0.242
0.301
0.554
0.298
0.587
0.395
0.248
0.475**
0.327*
0.471**
0.322
0.331
0.008
0.219
0.196
0.216
0.198
0.358
0.180
0.493***
0.043
0.495***
0.065
0.511
-0.114
0.157
0.136
0.157
0.128
0.378
0.171
0.402**
0.275
0.163
0.218
0.192
-0.143
-0.938**
-0.485**
0.214
0.180
0.2*
0.054
0.370
0.196
0.071
0.022
0.113
0.068
0.492
-0.029
0.235
0.121
0.500
0.256
0.183
0.052
0.123
0.070
-1.999*** -1.824*** -2.002*** -1.829*** -1.967*** -1.755***
0.116
0.121
0.116
0.121
0.349
0.184
0.472
1230
II
0.191
1230
0.470
1230
0.185
1230
0.352
1137
0.150
1137
Note: standard errors in parentheses, dependent variable: ln(IR/GDP)
*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively
17
… more than monetary policy arrangement..
Compared to inflation targeting
Compared to other
Trade openess
0.573*** Trade openess
0.573***
0.166
0.166
CO interaction term
-0.043* CO interaction term
-0.043*
0.024
0.024
Net oil export
0.034** Net oil export
0.034**
0.014
0.014
Monetary aggregate targeting
0.126
Inflation targeting
-0.321**
0.148
0.156
Fund-supported or other monetary
-0.023 program
Monetary aggregate targeting
-0.195
0.152
0.133
Exchange rate anchor
0.035
Fund-supported or other monetary
-0.345** program
0.288
0.141
Other
0.321** Exchange rate anchor
-0.286
0.156
0.245
Monetary union
-1.824*** Monetary union
-2.145***
0.250
0.259
Constant
-1.861***
-1.54***
R-sq (overall/within)
Obs
0.535
984
0.535
984
Note: standard errors in parentheses,
*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively
18
… while financial stability is difficult to measure.
I
Trade openess
CO interaction term
Net oil export
M2 on GDP
Banking crisis
Regime 1
Regime 2
Regime 3
Regime 4-7
HMFI
Constant
R-sq (overall/within)
Obs
II
With monetary
Financial stability
independence
Fixed
Fixed
Pooled OLS
effects
Pooled OLS
effects
0.464***
0.787***
0.506***
0.803***
0.158
0.165
0.160
0.173
-0.061*** -0.074*** -0.069*** -0.074***
0.023
0.020
0.023
0.020
0.035**
0.216***
0.04**
0.193***
0.016
0.054
0.018
0.057
0.225**
0.35**
0.136
0.276*
0.101
0.143
0.108
0.157
-0.336*** -0.359***
-0.29**
-0.336***
0.116
0.072
0.119
0.073
-1.528***
-1.457**
-1.47***
-1.455**
0.333
0.569
0.325
0.574
0.47**
0.179
0.436**
0.183
0.202
0.155
0.216
0.142
0.446***
0.026
0.401**
0.000
0.154
0.120
0.159
0.129
0.245**
0.027
0.295**
0.043
0.116
0.071
0.119
0.074
1.206**
0.495*
0.492
0.270
-1.823*** -1.575*** -2.787*** -1.988***
0.143
0.139
0.431
0.278
0.492
1230
0.235
1230
0.509
1182
0.238
1182
Note: standard errors in parentheses,
*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively
19
Appendix:IR/GDP ranking
1
2
3
4
5
6
7
8
9
10
:
113
114
115
116
117
118
119
120
121
122
123
1999
Syrian Arab Republic
Botswana
Singapore
Bhutan
Lesotho
Hong Kong
Malta
Lebanon
Malaysia
Guyana
:
Dominican Republic
Germany
France
Belarus
Netherlands
Pakistan
United Kingdom
Italy
Zambia
United States
Luxembourg
131.91
106.17
93.27
73.68
63.79
58.94
45.75
44.71
38.65
38.61
:
3.20
2.85
2.72
2.42
2.40
2.40
2.22
1.87
1.45
0.65
0.37
2002
Singapore
Botswana
Syrian Arab Republic
Libya
Bhutan
Hong Kong
Lesotho
Malta
Guinea-Bissau
Yemen, Rep.
:
Bangladesh
Angola
Haiti
Germany
Italy
United Kingdom
Netherlands
France
Dominican Republic
Luxembourg
United States
93.08
89.86
84.11
72.10
69.97
68.32
63.63
52.19
50.44
44.54
:
3.54
3.29
2.54
2.54
2.35
2.33
2.18
1.95
1.76
0.67
0.64
2005
Singapore
Libya
Hong Kong
Botswana
Syrian Arab Republic
Bhutan
Algeria
Lebanon
Malaysia
Saudi Arabia
:
Portugal
United Kingdom
Germany
Italy
Netherlands
France
Spain
Luxembourg
United States
Ireland
Greece
2008
92.63
89.79
69.89
61.52
60.74
58.07
55.02
54.43
50.68
49.13
:
1.82
1.69
1.62
1.44
1.41
1.29
0.86
0.64
0.43
0.39
0.21
Libya
Saudi Arabia
Singapore
Hong Kong
Algeria
Lebanon
Botswana
Bhutan
Lesotho
China
:
Italy
Slovenia
Netherlands
Germany
France
Spain
Luxembourg
Portugal
United States
Ireland
Greece
99.08
92.85
90.10
84.81
83.77
67.63
67.32
61.45
53.46
43.11
:
1.61
1.60
1.31
1.19
1.18
0.78
0.58
0.52
0.46
0.33
0.10
20
Ranking IR in bill. USD
1
2
3
4
5
6
7
8
9
10
:
113
114
115
116
117
118
119
120
121
122
123
1999
Japan
286 916.1
China
157 727.9
Hong Kong
96 236.0
Singapore
77 047.1
Korea, Rep.
73 987.3
Germany
61 038.8
United States
60 499.6
France
39 701.5
Switzerland
36 321.0
Brazil
35 279.3
:
:
Gambia
111.2
Laos
101.2
Luxembourg
77.4
Belize
71.3
Djibouti
70.6
Tajikistan
55.2
Burundi
48.0
Zambia
45.4
Cape Verde
42.6
Sierra Leone
39.5
Guinea-Bissau
35.3
2002
Japan
461 185.6
China
291 127.8
South Korea
121 345.2
Hong Kong
111 896.0
Singapore
82 221.2
United States
67 962.3
India
67 665.5
Germany
51 170.6
Mexico
50 594.4
Russia
44 053.6
:
:
Luxembourg
151.7
Maldives
133.1
Belize
114.5
Gambia
106.9
Guinea-Bissau
102.7
Tajikistan
89.5
Sierra Leone
84.7
Haiti
81.7
Cape Verde
79.8
Djibouti
73.7
Burundi
58.8
2005
Japan
834 274.9
China
821 513.9
Korea, Rep.
210 317.2
Russia
175 891.4
Saudi Arabia
155 028.9
India
131 924.3
Hong Kong
124 244.0
Singapore
116 171.8
Mexico
74 054.1
Malaysia
69 858.0
:
:
Laos
234.3
Maldives
186.3
Cape Verde
174.0
Sierra Leone
170.5
Tajikistan
168.2
Haiti
133.1
Burundi
100.1
Gambia
98.3
Djibouti
89.3
Guinea-Bissau
79.8
Belize
71.4
2008
China
1 949 260.0
Japan
1 009 364.8
Saudi Arabia
442 249.5
Russia
411 749.6
India
247 418.9
Korea, Rep.
201 144.5
Brazil
192 843.6
Hong Kong
182 469.0
Singapore
174 192.7
Algeria
143 243.0
:
:
Guyana
355.9
Greece
343.8
Luxembourg
334.6
Burundi
265.7
Tajikistan
242.0
Maldives
240.6
Sierra Leone
220.2
Djibouti
175.5
Belize
166.2
Guinea-Bissau
124.6
Gambia
116.5
21
GDP per capita vs Advanced countries dummy
1
2
3
4
5
6
7
8
9
10
:
113
114
115
116
117
118
119
120
121
122
123
1999
Luxembourg
Switzerland
Norway
Japan
United States
Denmark
Iceland
Sweden
Austria
Germany
:
:
Tanzania
Nigeria
Laos
Rwanda
Kyrgyz Republic
Uganda
Madagascar
Tajikistan
Sierra Leone
Burundi
Ethiopia
Advanced countries
49 219
37 565
35 660
34 495
33 332
32 702
31 505
29 220
26 359
26 114
300
285
275
259
257
253
251
178
162
127
123
28
2002
Luxembourg
Norway
Switzerland
United States
Denmark
Ireland
Iceland
Japan
Qatar
Sweden
:
:
Bangladesh
Kyrgyz Republic
Tanzania
Madagascar
Gambia, The
Uganda
Sierra Leone
Tajikistan
Rwanda
Ethiopia
Burundi
29
50 605
42 293
38 247
36 797
32 354
31 178
30 928
30 745
28 288
28 122
326
322
309
272
266
237
206
194
192
113
93
2005
Luxembourg
Norway
Iceland
Switzerland
Qatar
Ireland
Denmark
United States
Sweden
Netherlands
:
:
Guinea-Bissau
Bangladesh
Tanzania
Tajikistan
Uganda
Gambia
Rwanda
Madagascar
Sierra Leone
Ethiopia
Burundi
29
80 959
65 324
54 935
50 083
48 609
48 466
47 577
42 534
41 066
39 122
401
394
373
354
314
302
287
286
243
165
108
2008
Luxembourg
Norway
Qatar
Switzerland
Denmark
Ireland
United Arab Emirates
Kuwait
Netherlands
Iceland
:
Haiti
Guinea-Bissau
Tanzania
Bangladesh
Gambia, The
Madagascar
Rwanda
Uganda
Sierra Leone
Ethiopia
Burundi
117 955
94 568
86 436
65 699
62 036
60 178
58 272
54 260
53 076
52 932
:
649
538
502
497
495
493
483
456
352
321
145
31
22
IT is a way out?
• Missing empirical evidence
• Optimal vs. Real behaviour
Ranking IT countries - Reserves on GDP
1999
2002
Czech Republic
0.213 Czech Republic
Israel
0.204 Thailand
Chile
0.200 Chile
Korea, Rep.
0.166 Israel
Poland
0.157 Korea, Rep.
Colombia
0.093 Philippines
New Zealand
0.077 Norway
Mexico
0.066 Peru
Brazil
0.060 Hungary
Sweden
0.058 Poland
Australia
0.054 Colombia
Canada
0.043 Mexico
United Kingdom
0.022 New Zealand
Brazil
Sweden
South Africa
Australia
Canada
Iceland
United Kingdom
0.313
0.300
0.228
0.213
0.211
0.174
0.167
0.164
0.156
0.145
0.109
0.078
0.076
0.074
0.068
0.053
0.052
0.050
0.049
0.023
2005
Thailand
Korea, Rep.
Slovak Republic
Czech Republic
Israel
Romania
Peru
Hungary
Philippines
Norway
Chile
Poland
Indonesia
Colombia
Mexico
New Zealand
South Africa
Iceland
Brazil
Australia
Sweden
Canada
United Kingdom
0.287
0.249
0.243
0.235
0.209
0.201
0.171
0.168
0.161
0.156
0.143
0.134
0.116
0.101
0.087
0.080
0.075
0.064
0.060
0.060
0.060
0.029
0.017
2008
Thailand
Peru
Hungary
Korea, Rep.
Israel
Iceland
Uruguay
Philippines
Romania
Albania
Czech Republic
Chile
Brazil
Guatemala
Norway
Poland
South Africa
Indonesia
Colombia
Turkey
New Zealand
Mexico
Sweden
Australia
Canada
United Kingdom
0.399
0.234
0.218
0.216
0.210
0.209
0.204
0.199
0.184
0.179
0.170
0.135
0.117
0.114
0.113
0.112
0.111
0.097
0.097
0.096
0.094
0.087
0.053
0.030
0.029
0.017
23
Capital account openess (KAOPEN)
24
Exchange rate regimes
De facto classification – for IR (Choi, Baek)
IMF (from 1997)
Reinhart and Rogoff (2004)
Data available: 1997-2008
1
Exchange arrangement with no separate legal tender
2
Currency board arrangement
3
4
1
No separate legal tender; Pre announced peg or currency board
arrangement; Pre announced horizontal band that is narrower
than or equal to +/-2%; De facto peg
2
Pre announced crawling peg and crawling band, that is narrower than
or equal to +/-2%; De facto crawling peg and band that is
narrower than or equal to +/-2%
3
Pre announced crawling band that is wider than or equal to +/-2%; De
facto crawling band that is narrower than or equal to +/-5%;
Moving band that is narrower than or equal to +/-2%; Managed
floating
4
Freely floating
5
Freely falling
6
Dual market in which parallel market data is missing.
Conventional pegged arrangement
Pegged exchange rate within horizontal bands
5
Crawling peg
6
Crawling band
7
Managed floating with no predetermined path for the exchange rate
8
Data available: 1960 - 2007
Independently floating
25
ER regimes (IMF)
100%
Independently floating
90%
80%
M anaged floating with no predetermined
path for the exchange rate
70%
Crawling band
60%
Crawling peg
50%
Pegged exchange rate within horizontal bands
40%
30%
Conventional pegged arrangement
20%
Currency board arrangement
10%
0%
1999 2000 2001
2002 2003 2004 2005
2006 2007 2008
Exchange arrangement with no separate legal
tender
26
Monetary arrangements
100%
M onetary union
90%
80%
Other
70%
60%
IM F support
50%
M onetary aggregate
40%
30%
Exchange rate
anchor
20%
10%
Inflation targeting
0%
2001
2002
2003
2004
2005
2006
2007
2008
27