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

2

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)

3

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

Inflation targeting countrieshighlighted

Appreciation > 35 % 25 - 35 % 15 - 25 % 0 - 15 %Iceland Mongolia Kazakhstan Costa Rica Hong KongPoland Belarus Jamaica Thailand Trinidad and TobagoUkraine Norway Kenya Paraguay JapanZambia South Africa Uganda Peru LaosNew Zealand Swaziland Croatia Madagascar ChinaSouth Korea Pakistan Botswana Algeria AzerbaijanRussian Federation Gambia, The Latvia Georgia BoliviaUnited Kingdom Canada Macedonia TanzaniaSweden Indonesia Guinea-Bissau LibyaColombia Czech Republic Cape Verde SingaporeHungary Mauritius Bosnia & Herzegovina KuwaitAustralia Bhutan Bulgaria Sri LankaTurkey India Estonia HaitiMexico Nigeria Denmark GuatemalaChile Albania Lithuania Dominican RepublicRomania Armenia NicaraguaBrazil Israel Burundi

Philippines Sierra LeoneEthiopia RwandaUruguay EgyptArgentina AngolaSwitzerland BangladeshMoroccoKyrgyz RepublicMalaysia

Depreciation

Chile

4

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“

5

Monetary policy and IR: Trilemma vs. Quadrilemma

Mundell-Fleming’s impossible trinity

Policy choice:Closed financial markets

Policy choice:Give up monetary

independence

Policy choice:Floating exchange

ratePolicy goal:

Financial integration

Policy goal: Exchange rate

stability

Policy goal: Monetary

independence

New dimension:Accumulation ofinternational reservesimproves financial stability and allows forindependent monetarypolicy (Aizenman, 2011)

6

The role of monetary policy and ER regime

Comparable to Obstfeld et alt. (2008)Panel data analysis:

Sample: 123 countriesTime period: 1999 – 2009 (if data available)Data source: Worldbank, IMF, EIU

Extended with MP/ER arrangements and financial stabilityDummy variable for exchange rate regime (from

currency union to free float, 2 classifications)Dummy variable for monetary policy arrangementMonetary independenceFinancial stability measured by M2/GDP and banking

crisis dummy

7

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

0

0.2

0.4

0.6

0.8

1

1.2

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

0

0.05

0.1

0.15

0.2

0.25

0.3

Trade openess

Capital account openess

Reserves on GDP (right axis)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

0

0.05

0.1

0.15

0.2

0.25

0.3

M 2 on GDP

HM FI

Reserves on GDP (right axis)

8

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.

9

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.

10

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 like1) Relationship to fiscal policy and CB independence. 2) Stage of development of the financial system 3) Limited functioning of the standard transmission channels

11

Some evidence

• First hint: Central bank credibility – index from Meade and Crowe (2008)

• Still more work to be done: on-going reserach -> countries holding more reserves use them as the fist MP instrument

Number of obs = 81R-squared = 0.253Number of clusters (code) = 81

RobustCoeficient Std. Err. t P>|t|

Trade openess 0.538 0.258 2.08 0.041 0.024 1.052Capital account openess -0.269 0.073 -3.71 0.000 -0.414 -0.125Net oil export 0.033 0.029 1.12 0.268 -0.026 0.091HMFI 0.020 0.010 1.95 0.055 0.000 0.040CBI -0.769 0.462 -1.67 0.100 -1.688 0.150Constant 1.782 0.892 2 0.049 0.008 3.556

[95% Conf. Interval]

Note: author’s calculations. Cross-section for 2003.

12

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)

13

Thank you for your attention

www.cnb.cz

Sona Benecka

sona.benecka@cnb.cz

14

Summary statistics

Table 1: Summary statistics Variable Observations Mean Std. Dev. Min Max

Reserves on GDP 1353 0.189 0.189 0.001 1.583Population (mil) 1353 46.329 157.117 0.250 1345.750GDP per capita 1353 11.606 15.916 0.086 117.955Trade openess 1353 0.933 0.564 0.190 4.381Capital account openess 1353 0.864 1.577 -1.844 2.478Oil exports 1353 0.673 2.266 0.000 19.030HIM 1305 0.764 0.109 0.000 0.954M2 to GDP 1353 0.788 0.818 0.067 6.639Banking crisis 1353 0.061 0.239 0.000 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.

15

Explanatory variables

General cross-country differences: population, GDP per capita, advanced countries dummy, share on net oil export

Trade openness – export+import/gdpFinancial 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 belowMonetary independence - Heritage monetary freedom index

Financial stability: M2/GDP and banking crisis dummy

iitititi PCMHI 23121100_

16

Traditional model and its extensions

Note: standard errors in parentheses, dependent variable: ln(IR/GDP)*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively

Pooled OLSFixed effects Pooled OLS

Fixed effects Pooled OLS

Fixed effects

Population -0.067 0.4750.049 0.441

GDP per capita -0.195*** 0.0740.052 0.084

Trade openess 0.579** 0.614*** 0.575*** 0.702*** 0.604*** 0.731***0.224 0.151 0.204 0.145 0.198 0.144

Capital account openess -0.071 -0.075 -0.019 0.0040.045 0.055 0.044 0.051

Net oil export 0.083*** 0.19*** 0.041** 0.194*** 0.048*** 0.19***0.020 0.056 0.016 0.062 0.017 0.063

Advanced country -1.154*** -1.696*** -0.858*** -1.457**dummy 0.240 0.565 0.242 0.601Interaction term -0.049** -0.048*

0.024 0.026Constant -1.555*** -3.184*** -1.725*** -1.696*** -1.688*** -1.621***

0.128 0.922 0.088 0.130 0.085 0.136

R-sq (overall/within) 0.218 0.076 0.315 0.144 0.329 0.159Obs 1353 1353 1353 1353 1353 1353

With interaction termIIII II

With advanced countryTraditional model

17

Exchange rate regime matters…

Pooled OLSFixed effects Pooled OLS

Fixed effects Pooled OLS

Fixed effects

Trade openess 0.504*** 0.874*** 0.509*** 0.878*** 0.696*** 0.826***0.163 0.156 0.162 0.155 0.187 0.154

CO interaction term -0.048* -0.066*** -0.046* -0.063*** -0.127*** -0.096***0.024 0.020 0.023 0.020 0.025 0.028

Net oil export 0.028* 0.212*** 0.027* 0.213*** 0.061*** 0.183***0.015 0.062 0.015 0.060 0.018 0.060

Regime 1 -1.39*** -1.405** -1.401*** -1.485** 0.059 -0.2420.301 0.554 0.298 0.587 0.395 0.248

Regime 2 0.475** 0.327* 0.471** 0.322 0.331 0.0080.219 0.196 0.216 0.198 0.358 0.180

Regime 3 0.493*** 0.043 0.495*** 0.065 0.511 -0.1140.157 0.136 0.157 0.128 0.378 0.171

Regime 4 0.402** 0.2750.163 0.218

Regime 5 0.192 -0.143 -0.938** -0.485**0.214 0.180 0.2* 0.054 0.370 0.196

Regime 6 0.071 0.022 0.113 0.068 0.492 -0.0290.235 0.121 0.500 0.256

Regime 7 0.183 0.0520.123 0.070

Constant -1.999*** -1.824*** -2.002*** -1.829*** -1.967*** -1.755***0.116 0.121 0.116 0.121 0.349 0.184

R-sq (overall/within) 0.472 0.191 0.470 0.185 0.352 0.150Obs 1230 1230 1230 1230 1137 1137

I II

Intermediate regimesIMF classificationReinhart and Rogoff coarse classification

III

Note: standard errors in parentheses, dependent variable: ln(IR/GDP)*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively

18

… more than monetary policy arrangement..

Note: standard errors in parentheses, *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively

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 targeting0.126 Inflation targeting -0.321**0.148 0.156

Fund-supported or other monetary program -0.023 Monetary aggregate targeting-0.1950.152 0.133

Exchange rate anchor 0.035 Fund-supported or other monetary program -0.345**0.288 0.141

Other 0.321** Exchange rate anchor -0.2860.156 0.245

Monetary union -1.824*** Monetary union -2.145***0.250 0.259

Constant -1.861*** -1.54***

R-sq (overall/within) 0.535 0.535Obs 984 984

Compared to otherCompared to inflation targeting

19

… while financial stability is difficult to measure.

Note: standard errors in parentheses, *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively

Pooled OLSFixed effects Pooled OLS

Fixed effects

Trade openess 0.464*** 0.787*** 0.506*** 0.803***0.158 0.165 0.160 0.173

CO interaction term -0.061*** -0.074*** -0.069*** -0.074***0.023 0.020 0.023 0.020

Net oil export 0.035** 0.216*** 0.04** 0.193***0.016 0.054 0.018 0.057

M2 on GDP 0.225** 0.35** 0.136 0.276*0.101 0.143 0.108 0.157

Banking crisis -0.336*** -0.359*** -0.29** -0.336***0.116 0.072 0.119 0.073

Regime 1 -1.528*** -1.457** -1.47*** -1.455**0.333 0.569 0.325 0.574

Regime 2 0.47** 0.179 0.436** 0.1830.202 0.155 0.216 0.142

Regime 3 0.446*** 0.026 0.401** 0.0000.154 0.120 0.159 0.129

Regime 4-7 0.245** 0.027 0.295** 0.0430.116 0.071 0.119 0.074

HMFI 1.206** 0.495*0.492 0.270

Constant -1.823*** -1.575*** -2.787*** -1.988***0.143 0.139 0.431 0.278

R-sq (overall/within) 0.492 0.235 0.509 0.238Obs 1230 1230 1182 1182

With monetary independence

III

Financial stability

20

Appendix:IR/GDP ranking

1 Syrian Arab Republic 131.91 Singapore 93.08 Singapore 92.63 Libya 99.082 Botswana 106.17 Botswana 89.86 Libya 89.79 Saudi Arabia 92.853 Singapore 93.27 Syrian Arab Republic 84.11 Hong Kong 69.89 Singapore 90.104 Bhutan 73.68 Libya 72.10 Botswana 61.52 Hong Kong 84.815 Lesotho 63.79 Bhutan 69.97 Syrian Arab Republic 60.74 Algeria 83.776 Hong Kong 58.94 Hong Kong 68.32 Bhutan 58.07 Lebanon 67.637 Malta 45.75 Lesotho 63.63 Algeria 55.02 Botswana 67.328 Lebanon 44.71 Malta 52.19 Lebanon 54.43 Bhutan 61.459 Malaysia 38.65 Guinea-Bissau 50.44 Malaysia 50.68 Lesotho 53.46

10 Guyana 38.61 Yemen, Rep. 44.54 Saudi Arabia 49.13 China 43.11: : : : : : : : :

113 Dominican Republic 3.20 Bangladesh 3.54 Portugal 1.82 Italy 1.61114 Germany 2.85 Angola 3.29 United Kingdom 1.69 Slovenia 1.60115 France 2.72 Haiti 2.54 Germany 1.62 Netherlands 1.31116 Belarus 2.42 Germany 2.54 Italy 1.44 Germany 1.19117 Netherlands 2.40 Italy 2.35 Netherlands 1.41 France 1.18118 Pakistan 2.40 United Kingdom 2.33 France 1.29 Spain 0.78119 United Kingdom 2.22 Netherlands 2.18 Spain 0.86 Luxembourg 0.58120 Italy 1.87 France 1.95 Luxembourg 0.64 Portugal 0.52121 Zambia 1.45 Dominican Republic 1.76 United States 0.43 United States 0.46122 United States 0.65 Luxembourg 0.67 Ireland 0.39 Ireland 0.33123 Luxembourg 0.37 United States 0.64 Greece 0.21 Greece 0.10

1999 2002 2005 2008

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Ranking IR in bill. USD

1 Japan 286 916.1 Japan 461 185.6 Japan 834 274.9 China 1 949 260.02 China 157 727.9 China 291 127.8 China 821 513.9 Japan 1 009 364.83 Hong Kong 96 236.0 South Korea 121 345.2 Korea, Rep. 210 317.2 Saudi Arabia 442 249.54 Singapore 77 047.1 Hong Kong 111 896.0 Russia 175 891.4 Russia 411 749.65 Korea, Rep. 73 987.3 Singapore 82 221.2 Saudi Arabia 155 028.9 India 247 418.96 Germany 61 038.8 United States 67 962.3 India 131 924.3 Korea, Rep. 201 144.57 United States 60 499.6 India 67 665.5 Hong Kong 124 244.0 Brazil 192 843.68 France 39 701.5 Germany 51 170.6 Singapore 116 171.8 Hong Kong 182 469.09 Switzerland 36 321.0 Mexico 50 594.4 Mexico 74 054.1 Singapore 174 192.7

10 Brazil 35 279.3 Russia 44 053.6 Malaysia 69 858.0 Algeria 143 243.0: : : : : : : : :

113 Gambia 111.2 Luxembourg 151.7 Laos 234.3 Guyana 355.9114 Laos 101.2 Maldives 133.1 Maldives 186.3 Greece 343.8115 Luxembourg 77.4 Belize 114.5 Cape Verde 174.0 Luxembourg 334.6116 Belize 71.3 Gambia 106.9 Sierra Leone 170.5 Burundi 265.7117 Djibouti 70.6 Guinea-Bissau 102.7 Tajikistan 168.2 Tajikistan 242.0118 Tajikistan 55.2 Tajikistan 89.5 Haiti 133.1 Maldives 240.6119 Burundi 48.0 Sierra Leone 84.7 Burundi 100.1 Sierra Leone 220.2120 Zambia 45.4 Haiti 81.7 Gambia 98.3 Djibouti 175.5121 Cape Verde 42.6 Cape Verde 79.8 Djibouti 89.3 Belize 166.2122 Sierra Leone 39.5 Djibouti 73.7 Guinea-Bissau 79.8 Guinea-Bissau 124.6123 Guinea-Bissau 35.3 Burundi 58.8 Belize 71.4 Gambia 116.5

1999 2002 2005 2008

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GDP per capita vs Advanced countries dummy

1 Luxembourg 49 219 Luxembourg 50 605 Luxembourg 80 959 Luxembourg 117 9552 Switzerland 37 565 Norway 42 293 Norway 65 324 Norway 94 5683 Norway 35 660 Switzerland 38 247 Iceland 54 935 Qatar 86 4364 Japan 34 495 United States 36 797 Switzerland 50 083 Switzerland 65 6995 United States 33 332 Denmark 32 354 Qatar 48 609 Denmark 62 0366 Denmark 32 702 Ireland 31 178 Ireland 48 466 Ireland 60 1787 Iceland 31 505 Iceland 30 928 Denmark 47 577 United Arab Emirates 58 2728 Sweden 29 220 Japan 30 745 United States 42 534 Kuwait 54 2609 Austria 26 359 Qatar 28 288 Sweden 41 066 Netherlands 53 076

10 Germany 26 114 Sweden 28 122 Netherlands 39 122 Iceland 52 932: : : : : : : : :

113 Tanzania 300 Bangladesh 326 Guinea-Bissau 401 Haiti 649114 Nigeria 285 Kyrgyz Republic 322 Bangladesh 394 Guinea-Bissau 538115 Laos 275 Tanzania 309 Tanzania 373 Tanzania 502116 Rwanda 259 Madagascar 272 Tajikistan 354 Bangladesh 497117 Kyrgyz Republic 257 Gambia, The 266 Uganda 314 Gambia, The 495118 Uganda 253 Uganda 237 Gambia 302 Madagascar 493119 Madagascar 251 Sierra Leone 206 Rwanda 287 Rwanda 483120 Tajikistan 178 Tajikistan 194 Madagascar 286 Uganda 456121 Sierra Leone 162 Rwanda 192 Sierra Leone 243 Sierra Leone 352122 Burundi 127 Ethiopia 113 Ethiopia 165 Ethiopia 321123 Ethiopia 123 Burundi 93 Burundi 108 Burundi 145

Advanced countries 28 2929 31

1999 2002 2005 2008

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IT is a way out?

• Missing empirical evidence• Optimal vs. Real behaviour

Ranking IT countries - Reserves on GDP

Czech Republic 0.213 Czech Republic 0.313 Thailand 0.287 Thailand 0.399Israel 0.204 Thailand 0.300 Korea, Rep. 0.249 Peru 0.234Chile 0.200 Chile 0.228 Slovak Republic 0.243 Hungary 0.218Korea, Rep. 0.166 Israel 0.213 Czech Republic 0.235 Korea, Rep. 0.216Poland 0.157 Korea, Rep. 0.211 Israel 0.209 Israel 0.210Colombia 0.093 Philippines 0.174 Romania 0.201 Iceland 0.209New Zealand 0.077 Norway 0.167 Peru 0.171 Uruguay 0.204Mexico 0.066 Peru 0.164 Hungary 0.168 Philippines 0.199Brazil 0.060 Hungary 0.156 Philippines 0.161 Romania 0.184Sweden 0.058 Poland 0.145 Norway 0.156 Albania 0.179Australia 0.054 Colombia 0.109 Chile 0.143 Czech Republic 0.170Canada 0.043 Mexico 0.078 Poland 0.134 Chile 0.135United Kingdom 0.022 New Zealand 0.076 Indonesia 0.116 Brazil 0.117

Brazil 0.074 Colombia 0.101 Guatemala 0.114Sweden 0.068 Mexico 0.087 Norway 0.113South Africa 0.053 New Zealand 0.080 Poland 0.112Australia 0.052 South Africa 0.075 South Africa 0.111Canada 0.050 Iceland 0.064 Indonesia 0.097Iceland 0.049 Brazil 0.060 Colombia 0.097United Kingdom 0.023 Australia 0.060 Turkey 0.096

Sweden 0.060 New Zealand 0.094Canada 0.029 Mexico 0.087United Kingdom 0.017 Sweden 0.053

Australia 0.030Canada 0.029United Kingdom 0.017

1999 2002 2005 2008

24

Capital account openess (KAOPEN)

25

Exchange rate regimes

De facto classification – for IR (Choi, Baek)

IMF (from 1997) Reinhart and Rogoff (2004)

1 Exchange arrangement with no separate legal tender

2 Currency board arrangement

3 Conventional pegged arrangement

4 Pegged exchange rate within horizontal bands

5 Crawling peg

6 Crawling band

7 Managed floating with no predetermined path for the exchange rate

8 Independently floating

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.

Data available: 1960 - 2007Data available: 1997-2008

26

ER regimes (IMF)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Independently floating

Managed floating with no predeterminedpath for the exchange rate

Crawling band

Crawling peg

Pegged exchange rate within horizontal bands

Conventional pegged arrangement

Currency board arrangement

Exchange arrangement with no separate legaltender

27

Monetary arrangements

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2001 2002 2003 2004 2005 2006 2007 2008

Monetary union

Other

IMF support

Monetary aggregate

Exchange rateanchor

Inflation targeting