by eric m.p. chiu and thomas d. willett

The Interactions of Strength of The Interactions of Strength of Governments and Alternative Governments and Alternative

Exchange Rate Regimes in Avoiding Exchange Rate Regimes in Avoiding Currency CrisesCurrency Crises

ByBy

Eric M.P. Chiu and Thomas D. Eric M.P. Chiu and Thomas D. WillettWillett

National Chung-Hsing University National Chung-Hsing University Claremont Graduate UniversityClaremont Graduate University

Nov 18, 2006 Nov 18, 2006

IntroductionIntroduction

Under a world of high capital mobility, Under a world of high capital mobility, the Bretton Woods style adjustable the Bretton Woods style adjustable pegged regime (dead center) is known pegged regime (dead center) is known as the most crisis prone type of as the most crisis prone type of exchange rate arrangement due to the exchange rate arrangement due to the problem of “one-way speculative problem of “one-way speculative gamble”. gamble”.

This is also known as the “unstable This is also known as the “unstable middle” hypothesis.middle” hypothesis.

PuzzlesPuzzles

How far away from the middle How far away from the middle countries need to move to countries need to move to substantially reduce the frequency of substantially reduce the frequency of crises?crises?

Unstable Middle vs. Two Corners Unstable Middle vs. Two Corners HypothesisHypothesis

Some Responses Some Responses

Frankel (2004) has recently argued that Frankel (2004) has recently argued that we do not have a good economic theory we do not have a good economic theory for why the middle itself is unstable.for why the middle itself is unstable.

However, Willett (2006) suggest that However, Willett (2006) suggest that combining both standard economic combining both standard economic theory with political analysis of the theory with political analysis of the incentives to delay needed adjustment, incentives to delay needed adjustment, we can better understand why middle is we can better understand why middle is unstable. unstable.

Main PurposeMain Purpose

Both the issues of why the middle is Both the issues of why the middle is unstable and how far toward the unstable and how far toward the extremes of fixed or flexible exchange extremes of fixed or flexible exchange rates countries need to go to rates countries need to go to substantially reduce the likelihood of substantially reduce the likelihood of currency crises depends crucially on currency crises depends crucially on political factors, i.e. the strength of political factors, i.e. the strength of governments, as well as standard governments, as well as standard economic considerations.economic considerations.

Two InnovationsTwo Innovations

Use of IMF new Use of IMF new de factode facto exchange exchange rate regime classification as opposed rate regime classification as opposed to to de jurede jure classification classification

Focus on the interactions between Focus on the interactions between weak governments and alternative weak governments and alternative exchange rate regimes in influencing exchange rate regimes in influencing crisis probabilities. crisis probabilities.

Types of Weak Govt. (1)Types of Weak Govt. (1)

1.1. Politically unstable governmentsPolitically unstable governments

Political instability (e.g. frequent government turnovers, Political instability (e.g. frequent government turnovers, riots, strikes, and lack of strong political popularity) is riots, strikes, and lack of strong political popularity) is likely to force a government to give increased weight to likely to force a government to give increased weight to short run political considerations, thereby increasing short run political considerations, thereby increasing the propensity to postpone policies such as exchange the propensity to postpone policies such as exchange rate and macro economic policy adjustments, which rate and macro economic policy adjustments, which enhances the likelihood of crises.enhances the likelihood of crises.

International Country Risk GuideInternational Country Risk Guide (ICRG) (ICRG) defines defines government stability as government’s ability to carry government stability as government’s ability to carry out its declared program, and its ability to stay in office. out its declared program, and its ability to stay in office. The ICRG stability index ranges from 1 (the lowest level The ICRG stability index ranges from 1 (the lowest level of government strength) to 12 (the highest level). of government strength) to 12 (the highest level).

Types of Weak Govt. (2)Types of Weak Govt. (2)

2. 2. Politically divided governments (veto players)Politically divided governments (veto players)

Policymakers in divided governments in general face Policymakers in divided governments in general face collective action problems. In particular, a country with collective action problems. In particular, a country with many veto players will delay the changes in policy in many veto players will delay the changes in policy in responding to external shocks due to the difficulty in responding to external shocks due to the difficulty in rectifying agreements among policymakers.rectifying agreements among policymakers.

A dummy variable that takes the value of one when the A dummy variable that takes the value of one when the chief executive’s party controls the legislature, that is, a chief executive’s party controls the legislature, that is, a unified government. (Becks, 2003) unified government. (Becks, 2003)

Veto Player Approach: using “Checks” from DPI. It counts Veto Player Approach: using “Checks” from DPI. It counts the number of veto players, actors whose approval is the number of veto players, actors whose approval is necessary for a shift in policy from the status quo. The necessary for a shift in policy from the status quo. The higher the score, the greater is the policy constraints.higher the score, the greater is the policy constraints.

HypothesesHypotheses

HH11: other things being equal, the more unstable : other things being equal, the more unstable

and the more divided is a nation’s government; and the more divided is a nation’s government; the higher is the probability of currency crises the higher is the probability of currency crises under any type of exchange rate regime.under any type of exchange rate regime.

HH22: other things being equal, the effects of : other things being equal, the effects of

weak governments on the likelihood of crises weak governments on the likelihood of crises will be stronger, the stickier is the exchange will be stronger, the stickier is the exchange rate regime. rate regime.

Sample & DataSample & Data

The data set comprises annual The data set comprises annual observations from 1990 to 2003 on 90 observations from 1990 to 2003 on 90 countries, including 21 industrial countries, countries, including 21 industrial countries, 42 emerging markets economies, and 27 42 emerging markets economies, and 27 low-income developing countries.low-income developing countries.

International Country Risk Guide (ICRG); International Country Risk Guide (ICRG); Database of Political Institutions (DPI); Database of Political Institutions (DPI); International Financial Statistics (IFS); International Financial Statistics (IFS); World Development Indicators (WDI)World Development Indicators (WDI)

MethodologyMethodology

A probit panel model is used.A probit panel model is used. Interaction dummies between Interaction dummies between

political variables and exchange rate political variables and exchange rate regimes are included.regimes are included.

A one-year lag is used for all A one-year lag is used for all independent variables to avoid the independent variables to avoid the endogeneity problem. endogeneity problem.

The ModelThe Model

A probit panel model is defined as:A probit panel model is defined as:

ti,ti,k,k

5

1kmt,i,jt,i,j

5

1jti,

ti,

ti,ti, εXβδα

P1

Plny

ERGERG mm

5

1

)(,,,,,

,,

5

1,

1

1),,|1(

jtijj

tik ERxtititititi

e

ERGxCCprobPwhere

List of VariablesList of Variables

Y: Crisis dummiesY: Crisis dummies G: Political variables including political G: Political variables including political

instability and divided government instability and divided government ER: a six-way classification based on BOR’s ER: a six-way classification based on BOR’s

exchange rate regimesexchange rate regimes X: control variables including: X: control variables including:

Lending boomLending boom M2/ReserveM2/Reserve Current Account/GDPCurrent Account/GDP Real Effective Exchange Rate IndexReal Effective Exchange Rate Index Election datesElection dates

Empirical ResultsEmpirical Results

(1) (2) (3)

Stability Unified Checks

STAB t-1-0.1582***

(0.0698)- -

Unified t-1 --0.5506***

(0.2862)-

Checks t-1 - -0.1021**(0.0463)

No. of obs. 710 582 649

Prob > Chi-Square 0.0000 0.0000 0.0000

Pseudo R2 0.1523 0.0795 0.1390

Log-Likelihood -153.1022 -196.3370 -119.8105

Table 2c. Probability of Crises for Stable Government with Different Crawls

Hard pegs Adjustable Forward Crawls

Backward Crawls

Managed Floats

Independent Floats

STAB = 1 0.0789 0.2709 0.0025 0.1242 0.1485 0.0015 STAB = 2 0.0190 0.2211 0.0046 0.1001 0.1330 0.0019 STAB = 3 0.0031 0.1770 0.0082 0.0797 0.1185 0.0024 STAB = 4 0.0003 0.1390 0.0141 0.0625 0.1052 0.0030 STAB = 5 0.0000 0.1069 0.0233 0.0484 0.0931 0.0038 STAB = 6 0.0000 0.0805 0.0373 0.0370 0.0820 0.0047 STAB = 7 0.0000 0.0594 0.0574 0.0278 0.0719 0.0058 STAB = 8 0.0000 0.0429 0.0852 0.0207 0.0628 0.0072 STAB = 9 0.0000 0.0303 0.1220 0.0151 0.0546 0.0088 STAB = 10 0.0000 0.0209 0.1688 0.0109 0.0473 0.0108 STAB = 11 0.0000 0.0142 0.2257 0.0078 0.0408 0.0131 STAB = 12 0.0000 0.0094 0.2622 0.0054 0.0350 0.0159

F igu re 2. P rob ab i l i ty o f C rises for S tab le G ov t. u n d er D iff eren t C raw ls

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1 2 3 4 5 6 7 8 9 10 11 12

S t a b l e G o v 't

Prob

of C

rises

hard

adjust

forw ard craw ls

backw ard craw ls

mgd fl oat

fl oat

N o te: C r aw l i n g P eg s: th e cu r r en cy i s ad ju sted p er i o d i ca l l y v i s -à -v i s a si n g le cu r r en cy o r a b ask et i n sm a l l am o u n ts a t a fi x ed r a te o r i n r esp o n se to ch an g es i n sel ecti v e q u an ti ta ti v e i n d i ca to r s (p ast i n fl ati o n d iff er en ti a l s w i th m a jo r tr ad in g p ar tn er s, d iff er en ti a l s b etw een th e ta r g eted o r p r o jected i n fl ati o n w i th m a jo r tr ad in g p ar tn er s, etc) . C r aw l i n g B an d s: th e cu r r en cy i s m a in ta in ed w i th in fl u ctu ati o n o f a t l east 1 p er cen t a r o u n d a f o r m a l o r a d e f acto cen tr a l r a te, w h i ch i s ad ju sted p er i o d i ca l l y i n sm a l l am o u n ts a t a fi x ed r a te.

T ab l e 2d . P ro b ab i l i ty o f C r i ses f o r D i v i d ed G o v ern m en t (4)

H ar d p eg s

A d j u stabl e F or w ar d C r aw l s

B ackw ar d C r aw l s

M an ag ed F l oats

I n d ep en d en t F l oats

U n i fi ed = 1 0 .0 1 0 4 0 .0 4 2 4 0 .1 3 1 7 0 .0 3 1 7 0 .0 5 1 9 0 .0 1 4 5

D i v i d ed = 0 0 .0 3 9 0 0 .1 5 0 5 0 .0 7 9 7 0 .0 6 8 7 0 .1 2 7 2 0 .0 4 4 1

F i g u re 4.

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0 1

D iv ided G ov ernm ent

Prob

of C

rises

hardpegs

adjustable

forw ard craw ls

back w ard craw ls

m anaged fl oats

fl oats

Hard pegs AdjustableForward Crawls

Backward Crawls

Managed Floats

Independent Floats

Checks = 1 0.0003 0.0967 0.2706 0.0271 0.0968 0.0238

Checks = 2 0.0017 0.1088 0.2530 0.0455 0.1026 0.0313

Checks = 3 0.0069 0.1220 0.2360 0.0728 0.1086 0.0407

Checks = 4 0.0224 0.1362 0.2197 0.1111 0.1148 0.0522

Checks = 5 0.0605 0.1515 0.2040 0.1619 0.1213 0.0662

Checks = 6 0.1365 0.1680 0.1890 0.2060 0.128 0.0829

Checks = 7 0.1855 0.2605 0.1747 0.2424 0.135 0.1026

0

0.05

0.1

0.15

0.2

0.25

0.3

Pro

b of

Crise

s Hard pegs

Adjustable

Forward Crawls

Backward Crawls

Managed Floats

Independent Floats

Main FindingsMain Findings

1.1. As we expected, As we expected, weak political institutions - weak political institutions - particularly characterized by unstable particularly characterized by unstable governments and divided governments - governments and divided governments - increase the likelihood of currency crises increase the likelihood of currency crises under any type of exchange rate regime. under any type of exchange rate regime.

2.2. More specifically, we find weak political More specifically, we find weak political institutions combined with adjustable institutions combined with adjustable pegged exchange rate system represent pegged exchange rate system represent the highest probability of currency crises, the highest probability of currency crises, as compared with other types of exchange as compared with other types of exchange rate regimes. rate regimes.

Table 1. Probit Panel Estimation of Currency Crisis Models for All Countries

(1) (2) (3) (4) Stability Unified Stability Unified

STAB t-1 -0.1690*** (0.0678)

- -0.1582** (0.0696)

-

Unified t-1 - -0.5710** (0.3003)

- -0.5506** (0.2862)

ELEC t-1 -0.0974 (0.1924)

-0.2858 (0.2139)

-0.1379 (0.1924)

-0.2887 (0.2146)

Adjustable parities (constant)

-1.5443** (0.7647)

-2.4424*** (0.4803)

-1.7312** (0.7907)

-2.6124*** (0.4727)

Hard pegs t-1 -1.1916 (1.5831)

-0.5914 (0.3949)

-0.2984 (1.5650)

-0.5902 (0.3928)

Crawls t-1 -1.6916* (0.9937)

-0.2740 (0.1953)

- -

Forward Crawls t-1 - - -2.2662** (0.9734)

-0.2345 (0.2147)

Backward Crawls t-1 - - 0.9220

(1.9718) -0.3128 (0.3254)

Managed Floats t-1 -0.6206 (0.6317)

-0.4555** (0.2215)

-0.5208 (0.6608)

-0.4542** (0.2201)

Independent Floats t-1 -2.6936*** (0.6484)

-0.5360* (0.3250)

-2.5955*** (0.6687)

-0.5328* (0.3252)

S1 -0.5089* (0.2775)

- -0.5038* (0.2699)

-

S3 0.2471** (0.1248)

0.4763 (0.4231)

0.3393** (0.1185)

0.8392* (0.4971)

S4 0.0982

(0.0885) 1.0556** (0.4326)

-0.1338 (0.2789)

0.1793 (0.5088)

S5 0.2429*** (0.0784)

0.0943 (0.5796)

0.0883 (0.0906)

1.0374** (0.4174)

S6 - - 0.2332*** (0.0806)

0.0712 (0.5710)

M2/ Reserve t-1 0.0239*** (0.0075)

-0.0026 (0.0008)

0.0250*** (0.0075)

-0.0025 (0.0075)

Lending boom t-1 0.0032** (0.0017)

0.0007*** (0.0001)

0.0031* (0.0017)

0.0007*** (0.0002)

CA (% of GDP) t-1 -0.0021*** (0.0005)

-0.0025** (0.0001)

-0.0021*** (0.0005)

-0.0003** (0.0001)

REER t-1 0.0115*** (0.0041)

0.0154*** (0.0044)

0.0122*** (0.0041)

0.0171*** (0.0043)

No. of obs. 710 582 710 582

Wald Chi-Square Test 285.11 66.97 439.19 78.43

Prob > Chi-Square 0.0000 0.0000 0.0000 0.0000

Pseudo R2 0.1349 0.0760 0.1523 0.0795

Log-Likelihood -151.9669 -195.7708 -148.9002 -195.0301

Table 2a. Probability of Crises for Stable Government

Hard pegs Adjustable Crawls Managed

Floats Independent

Floats STAB = 1 0.1343 0.3424 0.0321 0.1766 0.0021 STAB = 2 0.0317 0.2590 0.0326 0.1422 0.0022 STAB = 3 0.0056 0.2074 0.0387 0.1269 0.0027 STAB = 4 0.0008 0.1806 0.0530 0.1270 0.0042 STAB = 5 0.0001 0.1243 0.0537 0.0998 0.0042 STAB = 6 0.0000 0.0930 0.0628 0.0879 0.0053 STAB = 7 0.0000 0.0679 0.0730 0.0772 0.0065 STAB = 8 0.0000 0.0560 0.0961 0.0773 0.0097 STAB = 9 0.0000 0.0336 0.0972 0.0587 0.0097 STAB = 10 0.0000 0.0228 0.1113 0.0508 0.0118 STAB = 11 0.0000 0.0151 0.1269 0.0489 0.0143 STAB = 12 0.0000 0.0117 0.1606 0.0439 0.0205

Figu re 1. P rob ab i l i ty of C rises for S tab le G ov t.

0 . 0 0

0 . 0 5

0 . 1 0

0 . 1 5

0 . 2 0

0 . 2 5

0 . 3 0

0 . 3 5

0 . 4 0

1 4 8 1 2

Prob

of

Cris

es

h a r d

a d j u s t

c r a w l

m g d fl o a t

fl o a t

N o te: th er e ar e to ta l 185 o b ser v ati o n s fo r cr aw l in g p eg / b an d r eg im es, b u t o n ly 14 o b ser v ati o n s en d ed u p w i th cu r r en cy cr i ses. T h ese i n clu d e B r az i l (1999), C h i l e (1999), C o lo m b i a (1995), E cu ad o r (1999), I n d o n esia (1997), I sr ael (1998), M ex i co (1994), P o r tu g a l (1991), R u ssi a (1998), S r i L an k a (1994), T u r k ey (1994, 2001), U r u g u ay (2002), an d V en ez u ela (1994).

Investigating the anomaly of Investigating the anomaly of

CrawlsCrawls Dividing crawling regimes into forward-Dividing crawling regimes into forward-

looking crawls and backward-looking crawls.looking crawls and backward-looking crawls. Hypo: Forward looking crawls tend to be Hypo: Forward looking crawls tend to be

associated with efforts at exchange rate associated with efforts at exchange rate based stabilization (ERBS) policy, which based stabilization (ERBS) policy, which require a strong government to implement require a strong government to implement it. This will make crises more likely than it. This will make crises more likely than backward looking crawls.backward looking crawls.

ci22==1 & crawlL=1

Country Year StabL Div Checks ER regime in previous year

Brazil 1999 10.17 0 6 7

Chile 1999 10.33 0 4 8

Colombia 1995 6.17 0 2 8

Ecuador 1999 9.75 0 4 8

Indonesia 1997 9.25 1 1 10

Israel 1998 7.17 0 3 8

Mexico 1994 7 1 2 8

Portugal 1991 6.67 0 2 8

Russia 1998 9.83 5 7

Sri Lanka 1998 9.83 1 5 10

Turkey 1994 6.33 0 3 9

Turkey 2001 9.67 0 6 7

Uruguay 2002 10.75 0 2 8

Venezuela 1994 4 0 5 9

T a b l e 2b . P r o b a b i l i ty o f C r i se s f o r D i v i d e d G o v e r n m e n t

H ar d p eg s A d j u s t ab l e C r aw l s M an ag ed

F l oa t s I n d ep en d en t

F l oa t s U n i fi e d = 1 0 .0 1 0 1 0 .0 4 1 6 0 .0 6 2 9 0 .0 5 2 9 0 .0 1 4 8

D i v i d e d = 0 0 .0 3 9 7 0 .1 2 2 7 0 .0 7 5 5 0 .1 0 8 6 0 .0 4 4 7

F i g u r e 2 .

0

0 .0 2

0 .0 4

0 .0 6

0 .0 8

0 .1

0 .1 2

0 .1 4

0 1

D i v i d ed G o v ern m en t

Prob

of C

rises

H ard p eg s

A d j u stab l e

C raw l s

M an ag ed F l o ats

I n d ep en d en t F l o ats

Justify the Anomaly of CrawlsJustify the Anomaly of Crawls

Many governments overestimated the likelihood of Many governments overestimated the likelihood of success on ERBS. It was generally understood that success on ERBS. It was generally understood that extremely weak and unstable government would have extremely weak and unstable government would have little chances of successfully stabilizing. Thus it seems little chances of successfully stabilizing. Thus it seems likely that the stronger governments of high inflation likely that the stronger governments of high inflation countries would be more likely to attempt ERBS. countries would be more likely to attempt ERBS.

A higher than expected tendency for such programs to A higher than expected tendency for such programs to end in crises such as occurred with Mexico in 1994 end in crises such as occurred with Mexico in 1994 and Brazil in 1999 could help explain the positive and Brazil in 1999 could help explain the positive correlation between strength of government and the correlation between strength of government and the probability of crises under forward looking crawls. This probability of crises under forward looking crawls. This is clearly an issue worthy of further investigation.is clearly an issue worthy of further investigation.

Robustness ChecksRobustness Checks

1.1. Crisis Indices: using equal weight system.Crisis Indices: using equal weight system.

2.2. Veto Player Approach: using “Checks” Veto Player Approach: using “Checks” from DPI. It counts the number of veto from DPI. It counts the number of veto players, actors whose approval is players, actors whose approval is necessary for a shift in policy from the necessary for a shift in policy from the status quo. The higher the score, the status quo. The higher the score, the greater is the policy constraints.greater is the policy constraints.

3.3. Alternative Measures of Exchange Rate Alternative Measures of Exchange Rate Regimes by Reinhart and Rogoff (2002).Regimes by Reinhart and Rogoff (2002).

Table 3. Sensitivity Analysis: A Probit Panel Estimation of Currency Crisis for Stable and Divided Government Using Equal Weight

Ci14 (1) (2) (3) (4) Stability Unified Stability Unified

STAB t-1 -0.1492*** (0.0562)

- -0.1497** (0.0563)

-

Unified t-1 - -0.0917 (0.3646)

- -0.0918 (0.3646)

ELEC t-1 -0.0294 (0.1746)

-0.0118 (0.1757)

-0.0483 (0.1924)

-0.0028 (0.1761)


-1.4614** (0.7175)

-2.2474*** (0.6684)

-1.4577** (0.7211)

-2.2969*** (0.7755)

Hard pegs t-1 0.3555

(1.3827) -0.2420 (0.4427)

0.2706 (1.4029)

-0.2306 (0.4269)

Crawls t-1 -2.3177*** (0.8426)

-0.0487 (0.2320)

- -

Forward Crawls t-1 - - -2.6318** (1.0281)

0.2365 (0.2556)

Backward Crawls t-1 - - -0.6403 (0.5994)

-0.5685 (0.4254)

Managed Floats t-1 -0.9826* (0.6263)

-0.5610 (0.4072)

-0.9801 (0.6608)

-0.5612 (0.4072)

Independent Floats t-1 -3.8414** (1.7573)

-0.7090** (0.3001)

-3.8471*** (1.7599)

-0.7075** (0.3003)

S1 -0.2075 (0.1604)

- -0.1903* (0.1492)

-

S3 0.2966*** (0.1014)

-0.1489 (0.5465)

0.3557** (0.1201)

-0.0914 (0.6465)

S4 0.1102

(0.0807) 0.6533** (0.5748)

0.0231 (0.0775)

0.1949** (0.7748)

S5 0.4003** (0.1836)

0.1396 (0.6294)

0.1103 (0.0808)

0.6552 (0.5694)

S6 - - 0.4014*** (0.1840)

0.1406 (0.6210)

M2/ Reserve t-1 0.0004

(0.0068) 0.0087

(0.0098) 0.0003

(0.0068) 0.0088

(0.0089)

Lending boom t-1 0.0023*** (0.0008)

0.0025* (0.0001)

0.0023*** (0.0008)

0.0025* (0.0013)

CA (% of GDP) t-1 -0.0007 (0.0004)

-0.0002 (0.0003)

-0.0006 (0.0004)

-0.0002 (0.0003)

REER t-1 0.0112*** (0.0041)

0.0086 (0.0059)

0.0112*** (0.0041)

0.0091 (0.0070)

No. of obs. 710 582 710 582


Prob > Chi-Square 0.0000 0.0000 0.0000 0.0000

Pseudo R2 0.0853 0.0530 0.0988 0.0628

Log-Likelihood -145.8872 -135.4895 -143.7260 -195.0301

Table 4a. Probability of Crises for Stable Government Using Equal Weight


Floats Independent

Floats STAB = 1 0.3001 0.3534 0.0054 0.0813 0.0000 STAB = 2 0.2318 0.2503 0.0082 0.0755 0.0001 STAB = 3 0.1379 0.2053 0.0122 0.0701 0.0002 STAB = 4 0.0740 0.1655 0.0177 0.0650 0.0006 STAB = 5 0.0356 0.1311 0.0252 0.0602 0.0015 STAB = 6 0.0153 0.1019 0.0353 0.0557 0.0033 STAB = 7 0.0059 0.0778 0.0484 0.0515 0.0069 STAB = 8 0.0020 0.0583 0.0651 0.0475 0.0136 STAB = 9 0.0006 0.0428 0.0860 0.0437 0.0252 STAB = 10 0.0001 0.0309 0.1115 0.0402 0.0441 STAB = 11 0.0000 0.0218 0.1421 0.0370 0.0730 STAB = 12 0.0000 0.0151 0.1779 0.0339 0.1146

Table 4b. Probability of Crises for Divided Government Using Equal Weight


Floats Independent

Floats Unified = 1 0.0474 0.0906 0.0519 0.0288 0.0228

Divided = 0 0.0572 0.1766 0.0829 0.0907 0.0204

Table 4c. Probability of Crises for Stable Government with Two Crawls Using Equal Weight

Hard pegs Adjustable

Forward Crawls

Backward Crawls

Managed Floats

Independent Floats


Table 4d. Probability of Crises for Divided Government with Two Crawls

Using Equal Weight

Hard pegs

Adjustable Forward Crawls

Backward Crawls

Managed Floats

Independent Floats

Unified = 1 0.0472 0.0885 0.0813 0.0347 0.0280 0.0223

Divided = 0 0.0570 0.1547 0.1125 0.0275 0.0889 0.0198

Table 5. Sensitivity Analysis: A Probit Panel Estimation of Currency Crisis Using Checks (Veto Player)

(1) (2) (3) (4)

Checks t-1 0.0824** (0.0385)

0.0676* (0.0402)

0.1055** (0.0472)

0.1021** (0.0463)

ELEC t-1 -0.0636 (0.1574)

-0.0597 (0.1610)

-0.1116 (0.2171)

-0.1238 (0.2205)


-2.9618*** (0.4254)

-3.0467*** (0.4472)

-3.1374*** (0.5839)

-3.2797*** (0.5771)

Hard pegs t-1 -2.2490** (1.2015)

-2.4548** (1.2312)

-1.9432 (1.3418)

-2.1054 (1.4786)

Crawls t-1 -0.2231 (0.3863)

- 1.2551** (0.5065)

-

Forward Crawls t-1 - 0.8113* (0.5079)

- 1.8772** (0.8827)

Backward Crawls t-1 - -0.7902** (0.3856)

- 0.9136*** (0.3589)

Managed Floats t-1 0.3889

(0.4453) 0.2981

(0.4538) 0.8372** (0.3741)

0.8039** (0.3741)

Independent Floats t-1 0.3104

(0.6192) 0.2202

(0 6228) 0.7819* (0.4467)

-0.8025* (0.4481)

S1 0.3445

(0.3265) 0.3868

(0.3328) 0.3888

(0.2788) 0.4271

(0.2996)

S3 0.0008

(0.0936) -1.1217 (0.1444)

-0.3449** (0.1732)

-0.4725* (0.2982)

S4 -0.1146 (0.1011)

0. 1667* (0.1007)

-0.2144** (0.0919)

-0.3547*** (0.1378)

S5 -0.2019 (0.1384)

-0.1004 (0.1021)

-0.0781 (0. 0611)

-0.2082** (0.0923)

S6 - -0.1865*** (0.1396)

- -0.0749 (0.0613)

M2/ Reserve t-1 0.0146** (0.0063)

0.0147** (0.0063)

0.0020 (0.0072)

0.0025 (0.0074)

Lending boom t-1 0.0004** (0.002)

0.0004** (0.002)

0.0013* (0.0007)

0.0013* (0.0007)

CA (% of GDP) t-1 -0.0002* (0.0001)

-0.0003** (0.0001)

-0.0016*** (0.0003)

-0.0017*** (0.0003)

REER t-1 0.0140 *** (0.0037)

0.0157 *** (0.0039)

0.0110** (0.0052)

0.0125** (0.0051)

No. of obs. 649 649 649 649


Prob > Chi-Square 0.0000 0.0000 0.0000 0.0000

Pseudo R2 0.0762 0.0871 0.1285 0.1390

Log-Likelihood -229.2448 -226.5282 -113.6916 -112.3195

Table 6a. Probability of Crises for Checks Using Pooled Precision Weight


Floats Independent

Floats Checks = 1 0.0005 0.1250 0.0846 0.098 0.0236 Checks = 2 0.0021 0.1430 0.0982 0.1036 0.0312 Checks = 3 0.0076 0.1626 0.1132 0.1096 0.0405 Checks = 4 0.0228 0.1840 0.1299 0.1157 0.0521 Checks = 5 0.0581 0.2070 0.1481 0.1221 0.0661 Checks = 6 0.1263 0.2316 0.1680 0.1288 0.0829 Checks = 7 0.2367 0.2578 0.1896 0.1356 0.1028

Table 6b. Probability of Crises for Checks with Two Crawls Using Pooled Precision Weight

Hard pegs Adjustable Forward Crawls

Backward Crawls

Managed Floats

Independent Floats

Checks = 1 0.0003 0.0967 0.2706 0.0271 0.0968 0.0238 Checks = 2 0.0017 0.1088 0.2530 0.0455 0.1026 0.0313 Checks = 3 0.0069 0.1220 0.2360 0.0728 0.1086 0.0407 Checks = 4 0.0224 0.1362 0.2197 0.1111 0.1148 0.0522 Checks = 5 0.0605 0.1515 0.2040 0.1619 0.1213 0.0662 Checks = 6 0.1365 0.1680 0.1890 0.2260 0.128 0.0829 Checks = 7 0.1855 0.2605 0.1747 0.3024 0.135 0.1026

Table 6c. Probability of Crises for Checks Using Equal Weight


Floats Independent

Floats Checks = 1 0.0216 0.0001 0.1334 0.0201 0.0033 Checks = 2 0.0277 0.0010 0.0885 0.0261 0.003 Checks = 3 0.0352 0.0048 0.0560 0.0333 0.0027 Checks = 4 0.0442 0.0182 0.0337 0.0423 0.0025 Checks = 5 0.0549 0.0551 0.0193 0.0531 0.0023 Checks = 6 0.0677 0.1350 0.0105 0.0659 0.0021 Checks = 7 0.0826 0.2714 0.0054 0.0811 0.0019

Table 6d. Probability of Crises for Checks with Two Crawls Using Equal Weight

Hard pegs Adjustable

Forward Crawls

Backward Crawls

Managed Floats

Independent Floats


Table 7. Sensitivity Analysis: A Probit Panel Estimation of Currency Crisis Using R-R Regimes

(1) (2) (3) Stability Unified Checks

STAB t-1 -0.1786*** (0.0710)

- -

Unified t-1 - -0.4153 (0.3216)

-

Checks t-1 - - 0.0331

(0.0563)

ELEC t-1 -0.2323 (0.2006)

-0.3646* (0.2202)

-0.1600 (0.2199)


-1.4993** (0.7594)

-2.0052*** (0.4315)

-2.3529*** (0.5490)

Hard pegs t-1 0.0089

(1.3676) 0.0088

(0.2501) -2.1491* (1.1620)

Crawls t-1 -1.1607* (0.6558)

-0.1778 (0.2114)

0.6981* (0.4287)

Moving Bands t-1 -1.4685** (0.7728)

0.3148* (0.1862)

-0.2346 (0.5019)

Managed Floats t-1 -0.8614 (1.0535)

-0.7360** (0.3336)

1.1414** (0.5766)

Floats t-1 -0.7012 (0.6177)

-0.1213 (0.3453)

1.1241** (0.5220)

S1 -0.3693 (0.2710)

- 0.4549* (0.2590)

S3 0.1833** (0.0887)

0.3362 (0.3678)

-0.2230** (0.1174)

S4 0.2108** (0.1022)

0.0983 (0.4311)

0.1205 (0.1014)

S5 0.0629

(0.1384) 1.0662** (0.5120)

-0.5404** (0.2722)

S6 0.1292** (0.0556)

0.5328 (0.4919)

-0.3932*** (0.1540)

M2/ Reserve t-1 0.0175*** (0.0064)

0.0165* (0 0095)

0.0026 (0.0062)

Lending boom t-1 0.0024** (0.0010)

0.0006*** (0.0002)

0.0005 (0.0006)

CA (% of GDP) t-1 -0.0040*** (0.0006)

-0.0005*** (0.0001)

0.0012*** (0.0002)

REER t-1 0.0117*** (0.0038)

0.0118*** (0.0037)

0.0066 (0.0044)

No. of obs. 641 527 627

Wald Chi-Square Test

169.90 151.97 148.25

Prob > Chi-Square 0.0000 0.0000 0.0000

Pseudo R2 0.1024 0.0756 0.0934

Log-Likelihood -153.1022 -196.3370 -119.8105

Table 8a. Probability of Crises for Stable Government Using R-R Regimes Hard pegs Adjustable Crawls

Moving Bands

Managed Floats

Floats


Table 8b. Probability of Crises for Divided Government Using R-R Regimes

Table 8c. Probability of Crises for Checks Using R-R Regimes Hard pegs Adjustable Crawls

Moving Bands

Managed Floats

Floats


Hard pegs

Adjustable Crawls Moving Bands

Managed Floats

Floats

Unified = 1 0.0469 0.1019 0.0636 0.0461 0.0225 0.0823

Divided = 0 0.1039 0.1702 0.0740 0.1023 0.0879 0.1016

Conclusions (1)Conclusions (1)

The most important conclusion of our The most important conclusion of our analysis is that weak political institutions analysis is that weak political institutions significantly increase the probability significantly increase the probability currency crises. currency crises.

This paper demonstrates that both unstable This paper demonstrates that both unstable government and divided government will government and divided government will make currency crises more likely make currency crises more likely particularly under Bretton Wood narrow particularly under Bretton Wood narrow band adjustable peg regimes than other band adjustable peg regimes than other types of exchange rate regimes. types of exchange rate regimes.

Conclusions (2)Conclusions (2)

These findings are consistent with the These findings are consistent with the “unstable middle” hypothesis, while are not in “unstable middle” hypothesis, while are not in line with the “two corners” hypothesis.line with the “two corners” hypothesis.

It also implies that countries with weak It also implies that countries with weak political institutions should at least consider political institutions should at least consider move away from the “dead center” of narrow move away from the “dead center” of narrow band adjustable peg in order to avoid severe band adjustable peg in order to avoid severe speculative attacks. By contrast, countries speculative attacks. By contrast, countries with strong political institutions are more with strong political institutions are more likely to effectively manage intermediate likely to effectively manage intermediate exchange rate regimes in a stable manner.exchange rate regimes in a stable manner.

Grouping of BOR’s Exchange Rate Grouping of BOR’s Exchange Rate RegimesRegimes

1. Dollarization 2. Currency Unions 3. Currency Board 4. Fixed Peg to a Single Currency 5. Fixed Peg to a Basket 6. Horizontal Bands 7. Forward looking Crawling Peg 8. Backward looking Crawling Peg 9. Forward looking Crawling Band 10. Backward looking Crawling Band 11. Tightly managed Floating 12. Other managed Floating 13. Independently Floating

Hard Pegs

Intermediate Regimes

Floating Regimes

Hard Pegs

Adjustable Parities

Crawls

Managed Floats

Floats

R-R Regime ClassificationR-R Regime Classification

Hard pegs include the most rigidly peg or currency Hard pegs include the most rigidly peg or currency board. board.

Adjustable parities include a pre-announced narrow Adjustable parities include a pre-announced narrow horizontal band and a horizontal band and a de factode facto peg. peg.

Crawls include Crawls include de factode facto and pre announced crawling and pre announced crawling pegs or bands as well as pre announced crawling pegs or bands as well as pre announced crawling band that is wide than or equal to +/- 2%.band that is wide than or equal to +/- 2%.

Moving bands, Managed floating, and Freely floating Moving bands, Managed floating, and Freely floating are treated as three individual categories. We do not are treated as three individual categories. We do not consider “freely falling” regime in this paper since in consider “freely falling” regime in this paper since in reality few countries would choose to have, nor they reality few countries would choose to have, nor they could implement a “freely falling” exchange rate. could implement a “freely falling” exchange rate.

Simple Descriptive StatisticsSimple Descriptive Statistics

VariableVariable ObservationObservationss

MeanMean Std. Dev.Std. Dev. MinMin MaxMax

StabilityStability 10861086 7.827.82 2.122.12 11 1212

ElectionElection 11581158 0.270.27 0.450.45 00 11

DividedDivided 10611061 0.460.46 0.490.49 00 11

ChecksChecks 11301130 3.263.26 1.891.89 11 77

M2/ResM2/Res 11071107 7.937.93 14.0514.05 0.190.19 148.31148.31

CA/GDPCA/GDP 10851085 -1.16-1.16 9.449.44 -41.49-41.49 39.6239.62

LendingLending 10861086 3.713.71 18.5418.54 0.0140.014 112.51112.51

REERREER 892892 102.16102.16 17.9617.96 4242 205205

by eric m.p. chiu and thomas d. willett

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