Fin Lib and Banking Crises

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Financial Liberalization and Banking Crises:Cross-Country Analysis of Liberalization Policies

By

Apanard AngkinandUniversity of Illinois at Springfield

[email protected]

Wanvimol SawangngoenyuangClaremont Graduate University

[email protected]

Clas WihlborgCopenhagen Business School

[email protected]

July, 2007

Abstract:

Financial liberalization is often blamed for banking and currency crises in many countries. In this paper, we ask whether the anecdotal evidence with respect to liberalization and banking crises iswell founded, and whether explanations of banking crises can be improved by distinguishingamong different types of financial liberalization. We use a data set for financial liberalization for 42 countries during 1973-2002 and distinguish between liberalization with respect to behavioralliberalization (credit and interest rate liberalization), competitive liberalization (equity market,capital account liberalization, and banks’ entry and activity liberalization), and privatization. Theinteraction between liberalization and institutional factors such as strength of supervision anddeposit insurance coverage is studied as well.

J EL Classification: G21; G28; F3Keywords: Banking Crises; Financial Liberalization; Capital Regulation and Supervision

____________________________ We would like to thank Arthur Denzau, Tripon Phumiwasana, Thomas D. Willett, and participants at the2006 Annual Meeting of the Asia-Pacific Economic Association, and the 2007 Annual Meeting of theWestern Economic Association for their useful comments.



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1. Introduction

Many countries around the world have liberalized their financial sectors, particularly

during the 1980s and the 1990s, with the aims of improving financial development and economic

growth (Tornell et al, 2004; Bekaert et al, 2005). However, financial liberalization is often

followed by financial instability and is blamed as the cause of banking crises (Kaminsky &

Reinhart, 1999, Caprio and Klingebiel, 1996). In this paper, we ask whether different types of

financial liberalization affect the likelihood of banking crises to different degrees, and whether

the effects of liberalization depends on the strength of supervision, the existence deposit

insurance, and the quality of domestic institutions.

In our empirical analyses of the effects of financial liberalization on banking crises from

1973 to 2002, we use recently updated data from International Monetary Fund’s Financial

Reform Database. It was originally coded by Abiad and Mody (2005) and was updated by Omori

(2006). The major advantage of this database is that it divides financial reform data in 42

countries into seven dimensions. The extent of liberalization is specified in each dimension, and

the data exist for a long time span beginning in 1973. Most of existing studies that examine the

effects of financial liberalization on banking crises are limited to the use of a 0/1 dummy in

capturing the periods of non- and liberalized financial systems (for example, Demirgüç-Kunt and

Detragiache, 2001; Eichengreen and Arteta, 2002; Noy, 2004). These studies find similar results

suggesting that liberalizing financial systems results in the increasing probability of banking

crises. The disadvantages of using the dichotomous variable are that it does not reflect the extent

of liberalization, nor the type of restrictions that exist or has been abolished.

In this study we use the mentioned database to analyze both whether the intensity of

liberalization as defined by an index for absence of restrictions explains the likelihood of

banking crises, and whether it is meaningful to distinguish between liberalization with respect to

different types of restrictions. We also ask whether banking crises can be linked to the level of

liberalization (absence or relaxation of restrictions) or to changes in liberalization during a period

preceding a crisis.

Some studies have attempted to improve measures of financial liberalization by

constructing an index that capture the intensity of liberalization or using the continuous

economic variables. For example, Eichengreen and Arteta (2002) use the ratio of capital flows to



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GDP to measure the extent of external liberalization. Other studies such as Bekaert et al (2005)

use the intensity of equity market liberalization as defined by a measure of market capitalization.

These variables reflect changes in economic outcome rather than changes in financial

liberalization policies (Abiad and Mody, 2005), however. Kaminsky and Schumukler (2003) and

Abiad and Mody (2005) construct an index that captures both the intensity and changes in policy

of financial liberalization. Kaminsky and Schumukler construct the financial liberalization index

based on the liberalization of capital account, interest rate control, and equity market. The index

is divided into three levels: full liberalization, partial liberalization, and no liberalization. The

sample coverage is limited to 28 countries during the period of 1973-1999.

We use the Financial Reforms Database, which categorizes financial reforms into seven

dimensions. Six of them refer to eliminations of credit allocation controls, interest rate control,

capital account controls, equity market controls, entry barriers, and privatization, while the

seventh refer to enhancement of bank capital regulation and supervision. The intensity of

liberalization is captured on a four-point scale: fully repressed, partially repressed, largely

liberalized, and fully liberalized.

From this database, we employ an aggregate index for the six categories to capture the

degree of financial liberalization as well as the index for capital regulation and prudential

supervision. The six categories are also grouped into three types denoted behavioral

liberalization, competitive liberalization, and privatization. The availability of financial

liberalization data over long time-span periods allows us to distinguish between effects on

banking crises of changes in the level of liberalization and effects of a permanent level of

financial liberalization.

There are two reasons to suspect that most of the information about effects of

liberalization on crises can be obtained from the aggregate index for all categories of

liberalization, and that distinguishing between these categories may not be meaningful. First, the

data on all dimensions of liberalization are dominated by changes towards greater liberalization

although there are periods of reversals in some countries. Second, one type of liberalization is

often accompanied or followed by other types of liberalization. There are political as well as

economic arguments for this link among types of liberalization. If the link is very strong in terms

of timing, the correlation between the indexes for different types of liberalization will be high. In



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the extreme case, the aggregate index becomes observationally equivalent to indexes for

different dimensions of financial liberalization.

In Section 2 we discuss the role of government in banking while costs and benefits of

financial liberalization are summarized in Section 3. Since we focus on the relationship between

financial liberalization and banking crises, we review the existing empirical literature on the

effects of both domestic and international financial liberalizations on banking crises in Section 4.

Hypotheses are developed in Section 5. Empirical methodology and data are described in Section

6. Results of the empirical tests are presented in Section 7. Conclusions and policy implications

follow in the last Section.

2. The Role of Governments in Banking

A financial system is an important driving force for the growth in the economy, and

banks dominate the financial system in large parts of the world. Banks collect deposits from

individual savers and lend to firms or corporations. By doing so, banks enable consumption

smoothing for households facing volatile income streams. Banks also organize the payment

system by acting as clearing and settlement houses. If a debtor bank is unable to pay its interbank

balance, this deprives other institutions of expected funds and prevents them from settling. A

banking system also enables trading in, and sharing of, risk of firms and projects to allocate

financial resources according to wealth holders’ risk preferences. Hence, if a large part of the banking system fails, economic activity may be severely affected.

To ensure safe and sound banking, government in most countries has strongly regulated

as well as restricted banks’ operations. Banking restrictions take many different forms. For

instance, for fear that excessive capital inflows can promote unsustainable booms followed by

economic contraction, government implements capital controls. To avoid bank failures due to the

rising interest rates, particularly during the period of high inflation, government imposes interest

rate ceiling. Financial repression in the form of controls on interest rates as well as credit

allocation is also one way the government can raise funds at a relatively cheap interest rate rather

than raising tax rates (Giovannini and de Melo, 1993, Fry, 1997), and allocate credit in order to

achieve certain economic policies. Since governments in many countries have used banks to fund

budget deficits, governments have long treated banks as public utilities. Thereby, they have been



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reluctant to let troubled banks fail. At the same time, the survival of the banks has been assured

by recapitalizations and/or massive subsidies (Honohan, 1997).

The analyses by Shaw (1973), McKinnon (1973), and Beim and Calomiris (2000) show

that financial repression results in restrained economic growth. With financial repression such asinterest rate controls and high reserve requirement, banks cannot operate efficiently. They have

little incentives to explore new opportunities or to become innovative. With interest rates set

below equilibrium rates, savings are discouraged. With high reserve requirement and direct

credit allocation to certain industries and related parties, the funds available to the private sector

decline. With a limited supply of funds, banks need to ration credit. Well-established clients can

borrow funds at moderate interest rates, while small-scale investors have to obtain funds in

expensive and unstable informal credit markets (Diaz-Alejandro, 1985).

Due to evidence of inefficiency of financial repression, changes in political structures and

economic conditions (Abiad and Mody, 2005), and pressures from their trading partners, many

countries have reformed their financial sectors by moving towards fewer financial restrictions,

particularly during the 1980s and the 1990s. The important objectives of financial reform are to

enhance the efficiency of a banking system, improve the efficient allocation of credits, and

achieve a higher economic growth.

3. Benefits and costs of financial liberalizationA government can liberalize a financial sector by removing domestic and/or international

financial restrictions. Domestic or internal financial liberalization typically entails removal of

interest rate controls, direct credit allocation schemes, or both. They can also allow banks to

expand their activities, and they can privatize state-owned banks to reduce political influences.

International or external financial liberalization refers to the removal of capital account controls

by allowing the flow of funds in and out of the country, possibly including direct investments by

foreigners in the domestic banking sector.

As noted, the benefits of financial liberalization include the stimulation of savings,

improved credit allocation and, indirectly, higher growth when financial resources are channeled

to more productive sectors. Domestic financial liberalization also reduces the financial

constraints on many firms. Leaven (2003) finds that the financing constraints have reduced for

both large and small firms over time. In fact, under financial repression large firms favored



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access to external sources of funds, but the difference between big and small firms concerning

cost of borrowing has disappeared. He also finds that financial liberalization reduces

imperfections in asymmetric information costs of firm’s financial leverage.

Turning to international financial liberalization, capital controls discourage foreign directinvestment (FDI) directly in some instances or indirectly, because multinational firms operating

in a country face higher cost of borrowing locally than in international markets (Desai et al,

2006). Hence, the removal of capital control can lead to more FDI, which will bring in new

technology and management skill.

In addition, both external and internal financial liberalizations tend to improve the

financial infrastructure (Schmukler, 2004) and bank governance. The benefits from reducing

foreign bank entry restrictions is that foreign investors will monitor their banks’ activities, and

host governments have to adopt an international accounting standard, thereby increasing

transparency. If foreign banks dominate the banking sector, governments are less likely to bail

them out. A lower likelihood of bail out disciplines banks and reduces moral hazard.

The process of eliminating financial restrictions can also incur costs, particularly during a

transition period, and possibly more permanently if banks’ excessive risk-taking incentives are

strong. Diaz-Alejandro (1985) argued that financial liberalization is destined to cause crisis.

Many recent studies show that almost all banking crises have been associated with financial

liberalization (Kaminsky & Reinhart, 1999, Williamson et al, 1998). Caprio and Klingebiel

(1996) and Eichengreen and Arteta (2002) conclude that banks are more likely to fail in a

liberalized regime than under financial repression. One possible explanation could be that

financial liberalization exposes the risk and poor performance of pre-liberalization portfolios

(Caprio et al, 2000).

There are a number of financial crisis theories that associate free, unsupervised financial

markets with crises. For example, Minsky (1992) explains banking crises referring to three

different kinds of financial transactions-- hedging, speculation and Ponzi schemes. In a Ponzi

scheme banks must borrow or sell assets to repay interest. According to Minsky, speculation and

Ponzi schemes may dominate the markets under some circumstances, unless supervisors prevent

this from happening. Wolfson (2002) later expands Minsky’s theory of financial crises into the

global context. During the Asian crisis, for example, “too much” money flowed into emerging



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markets. Large capital flows into the Asian countries fueled expectations of further profits

leading to greater inflows and the expansion of corporate debt collateralized by assets with

ultimately inflated values. These crisis theories describe how crises can arise in uncontrolled and

unsupervised markets but they are not exact in specifying how different aspects of liberalization

and government involvement contribute to, or reduce, the likelihood of banking crises.

There exist a number of arguments why different aspects of domestic liberalization may

increase the likelihood of crises. According to Alba et al (2000), when governments liberalize the

financial sector, initial conditions, the regulatory framework, as well as macroeconomic

conditions may contribute to or reduce the likelihood of banking crises. Financial liberalization

creates new business environments for both bank managers and supervisors. Pre-financial

liberalization, bank managers and staff were used to deal within a controlled environment.

During post-liberalization new types of risk arise and bankers must manage them. If the

managers or supervisors are not familiar with the new environment, they cannot monitor banks’

activities properly. As a result over-lending or excessively risky lending may occur (Noy, 2004).

Another argument for costs of financial liberalization is that the eliminations of interest

rate controls and direct regulation of credit can strengthen price competition, reduce profitability

in the banking sector and thereby increase the fragility of the system. Inefficient banks facing

narrow profit margins would be more vulnerable to fluctuations in economic activity (Noy,

2004). However, for an opposite argument the increasing competition can contribute to greater

efficiency and market discipline on banks’ willingness to hold capital as a buffer.

Liberalization of markets for securities tends to increase the volatility of interest rates in

the market place. There is an argument that interest rate volatility is associated with substantial

costs because it requires more sophisticated risk management and it reduces client’ ability to

service debt (Caprio et al, 20001; Alba et al, 2000). After liberalization, banks could find

themselves lacking skilled people to manage portfolios efficiently, since these skills are not

developed during periods of financial repression.

The arguments why external liberalization contributes to currency and banking crises are

commonly put forward in the debate about the merits and demerits of controls of capital account

1 Caprio et al (2000) argue that with a weak banking system, macroeconomic shocks can lead the increase in interestrates, which then will reduce client’ ability to service debts, and at the same time banks are encouraged to borrowabroad and lend locally.



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transactions. For example, capital inflows may lead to an investment boom, increasing asset

prices and consumption booms. Thus, with large capital inflows and a pegged exchange rate, the

government has to tighten monetary policy and sterilize inflows. The latter will give further

impetus to inflows, inflationary tendencies, and a real appreciation (Alba et al, 2000). In the end

a currency crisis can contribute to bank failures as well. The effects on banks are particularly

strong if the spread between the world interest rate and the domestic interest rate has induced

banks to borrow abroad in order to expand domestic lending. Honohan (1997) argues that a crisis

can be made worse by bankers’ tendency to base their behavior on observations of each other.

In the open environment, banks’ incentives and skills in risk assessment and management

are challenged. Extensive guarantees of banks, or perceptions that failing banks will be bailed

out, increase the likelihood of financial inflows being invested in excessively risky projects, and

inexperience could lead to financial resource misallocation. One possible consequence of a surge

of inflows is a bubble (McKinnon and Pill, 1997), and the removal of capital account restrictions

increases the probability of capital reversals.

The implication of this overview of potential benefits and costs of liberalization is that

benefits can be accompanied by risks if incentives in the market place do not encourage

prudence or supervision is weak. Excessive risk taking can be exacerbated by far-reaching

guarantees of banks, low levels of skills in risk assessment, weak governance in banks and lax

supervision.

4. Existing empirical evidence on liberalization and banking crises

Recent empirical studies have used different measures to proxy the financial

liberalization. In a study of the relationship between financial liberalization and banking crises,

Demirgüç-Kunt and Detragiache (2001) uses a simple 0/1 dummy as a proxy the interest rate

controls. In a logit model of banking crisis regressions, a dummy variable of 1 is assigned if

there is no interest rate control and 0 otherwise. By focusing on domestic financial liberalization

and observing the date policy makers announce interest rate decontrols for 53 countries during

the period 1980-1995, they find that financial liberalization is strongly and positively correlated

with the probability of banking crises. Similar to Demirgüç-Kunt and Detragiache, Weller (2001)

divides data into before and after financial liberalization using interest rate decontrol as a cutoff.



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He observed monthly data for 26 emerging countries and finds that the likelihood of banking

crises increases after financial liberalization.

Eichengreen and Arteta (2002) extend the analysis in Demirgüç-Kunt and Detragiache by

distinguishing between the effects of domestic and international financial liberalization on banking crises. International financial liberalization is captured by a 0/1 dummy, where 1 is

assigned for periods with an absence of capital account controls. They focus on the sample of 75

emerging markets and developing countries during the period of 1975-1997. In banking crisis

regressions they do not find that capital account liberalization contributes to banking crises, but

their finding with regard to domestic financial liberalization is consistent with those in

Demirgüç-Kunt and Detragiache. Furthermore, by interacting domestic financial liberalization

with international financial liberalization they find a positive effect of this interaction term on

banking crises, suggesting that capital account liberalization increases the likelihood of banking

crises for countries that liberalize interest rate controls.

Noy (2004) examines whether banking crises are caused by insufficient supervision as

well as the loss of monopoly power after countries liberalized their financial systems. He uses

proxies similar to those in Eichengreen and Arterta (2002) and finds similar results. Domestic

financial liberalization is highly correlated with the advent of banking crises but international

financial liberalization is not. Interaction between domestic financial liberalization and

supervision, as well as with other institutional variables, suggests that poor supervision and

institutions explain the adverse effects of domestic financial liberalization.

The three mentioned papers explained the likelihood of banking crises by focusing on the

liberalization of interest rate controls as well as capital account. Other aspects of domestic

financial liberalization have also been examined in other studies. For example, in studying the

relationships among financial liberalization, financial crises, and economic growth, Rancier et al

(2006) construct two dummies to proxy financial liberalization. One is from the dates of equity

market liberalization and another is from the patterns of private capital flows. Both financial

liberalization variables are associated with the higher probability of banking and currency crises

(or twin crises). Barth et al (2004) focus on restrictions on bank activity, entry restrictions and

privatization. They find that restrictions on banking activity and foreign bank entry increase the

likelihood of banking crises. Their finding that restrictions on bank activity and competition

increases financial fragility is consistent with the argument that liberalization improves credit



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allocation. Barth et al use data for the types of regulatory restrictions on banks from their country

survey, The Regulation and Supervision of Banks around the World: a New Database. Although

these variables capture the extent of regulatory restrictions across countries, they exist only as

cross sectional data for the year 2001.

The relationship between bank entry restrictions and banking crises is studied by Caprio

and Martinez-Peria (2000) who also examined the relationship between government ownership

of banks and banking crises. They find that the share of bank assets owned by the government

had a positive and significant effect on the likelihood of banking crises. With regard to the

presence of foreign banks, Demirgüç-Kunt et al (1998) find that foreign control of banks does

not increase the likelihood of a banking crisis. Foreign control improves the efficiency of the

domestic banking system and accelerated long-run economic growth. Claessens et al (2001), who

look at bank balance sheets in 80 countries from 1988- 1995, observe that a foreign presence in

domestic banking markets increase competition and lower the profit margins of the domestic

banks in developing countries. In developed countries, foreign banks enjoy less profit than

domestic bank. Claessens et al do not extend the analysis to include crises, however.

The review of these studies that focus on different aspects of liberalization suggests that

the correlation among different types of liberalization is high, as we shall see below. Thus, to

identify effects of one type of liberalization it is desirable to control for other types of

liberalization.

5. Types of liberalization, data, and hypotheses with respect to

banking crises

Data on liberalization of different types of restrictions and supervision are taken from

Omori (2006). The dataset is an updated version of the International Monetary Fund’s Financial

Reform Database coded by Abiad and Mody (2005). The data covers 42 countries (9 developed

and 33 emerging market and developing countries) during the period of 1973-2002.

The potentially important advantage of the database is that it has time-series measures for

the intensity of reforms in seven dimensions. As Omori (2006) notes in her analysis of the pace

of financial reform, there is diversity among countries in terms of intensity, liberalization

dimension, and speed of reform.



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For each country, the following six dimensions capture liberalization of different kinds of

restrictions:

(1) Elimination of credit controls including reserve requirements,

(2) Elimination of interest rate controls,

(3) Elimination of entry barriers and expanding bank activities,

(4) Security market policy,

(5) Elimination of capital account restrictions,

(6) Reduction of state ownership of the banking sector,

The seventh dimension of financial reform does not refer to liberalization per se, but to

capital regulation and prudential supervision:

(7) Enhancement of capital regulations and prudential supervision of the banking sector

(CRS).

Each dimension is measured on a 0 to 3 scale: 0 (fully repressed), 1 (partially repressed),

2 (largely liberalized), and 3 (fully liberalized). For the banking regulation and supervision

dimension, 0 is not regulated and supervised, 1 is less regulated/supervised, 2 is largely

regulated/supervised and 3 is highly regulated/supervised.

In our empirical analyses, we test the impact of these dimensions of financial

liberalization as well as the total financial liberalization on the likelihood of banking crises. The

total Financial Liberalization index (FL) is constructed by summing the first six dimensions of

liberalization; therefore, this aggregate index has a scale of 0 to 18. The banking crisis episodes

data are taken from Caprio et al (2005)2. Descriptive statistics for banking crises and financial

liberalization variables are reported in Table 1.

Since each dimension of liberalization is highly correlated (see Table 2a for correlations),

analyzing the impact of individual type of liberalization on banking crises does not provide

2 Caprio et al (2005) compile the banking crisis data based on published financial sources and interviews withexperts. There are two kinds of banking crises; a systemic banking crisis is defined as the situation when much or allof bank capital is exhausted; a borderline banking crisis is identified when there is evidence of significant banking problems such as government intervention in banks and financial institutions.



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significant contribution. We, therefore, use the following rationale to distinguish components of

liberalization into three types.

To enjoy faster growth, many governments have initiated liberalization by allowing

banks to set interest rates or to allocate credit more freely. We argue that these types of liberalization are nearly equivalent since freedom to allocate credit without freedom to set

interest rates on loans implies that the allocation will be determined by the interest rate structure.

Similarly freedom to set interest rates on loans while controlling credit allocation will result in

continued excess demands and supplies for some types of loans. Controls on deposit interest

rates while loan rates and credit allocation are free will also lead to excess demands for credit.

Credit and interest rate controls of all kinds can be viewed as restrictions on banks

actions and behavior. We consider these restrictions the most fundamental ones, meaning that

other types of restrictions matter less if banks cannot freely allocate available funds and set

interest rates. The first two dimensions, eliminations of credit and interest controls, refer to what

we denote “Behavioral Liberalization”. It refers to the score for these two dimensions added

together:

i) Behavioral Liberalization = (1) + (2)

Other types include restrictions in equity markets and on international capital transactions

implying restrictions on the set of available sources and uses of bank funds, as well as lesscompetition from non-bank financial institutions. Restrictions on the range of activities of banks

can be involved in and restrictions on entry have similar effects. The scores for the third through

the fifth dimensions are, therefore, added to capture liberalization of restrictions on banks’

choices of uses and sources of funds, and competition. We denote this aggregate index

“Competitive Liberalization”. The correlations among these three dimensions are as high as

between 0.6 to 0.7 (Table 2a). Thus, it is likely that not much information is lost when using this

aggregate variable instead of (3), (4) and (5) individually.

ii) Competitive Liberalization = (3) + (4) + (5):

We also consider government ownership a third type of restriction. Thus, a third kind of

liberalization is denoted privatization.

iii) Privatization = (6)



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The correlations between the three types of liberalization are also high raising questions

about the possibility of identifying effects by type. We return to this issue.

To capture the idea that there is a learning period after a financial restriction is relaxed,

and, therefore, that liberalization may have temporary effects, we include the change in types of liberalization over a five-year period as independent variables (ΔFL, or ΔBehavioral

Liberalization, ΔCompetitive Liberalization, ΔPrivatization).

In the empirical analyses, we include both changes and levels of liberalizations in

banking crisis regressions. The change and the level of each type of liberalization are not

seriously correlated (correlations are from 0.29 to 0.35; see Table 2a). However, for each of three

types of liberalization its lags of the level up to five years are very highly correlated (0.8-0.9)

(see Table 2b). Thus, it is probably not possible to identify the different lags and the duration of

temporary effects. The change over five years was chosen because this period length appears to

have more explanatory value than changes over shorter periods.

By including both changes and levels, we may be able to identify both temporary and

permanent effects of liberalization. By controlling for the level of liberalization, we assess

whether change in the level of liberalization over a five-year period have temporary effects on

the incidence of banking crises. Similarly, we can assess the permanent impact of the level of

behavioral liberalization by holding for the change in liberalization constant.

Our first hypothesis refers to temporary and permanent effects of financial liberalization

on the likelihood of banking crises.

Hypothesis 1: On temporary and permanent effects of financial liberalization:

Hypothesis 1.a: The relaxation of financial restrictions on banks will temporarily increase

the likelihood of banking crisis, since liberalization may be associated with a period of learning

and adjustment.

The behavioral liberalization (credit and interest rate controls) may temporarily increase

the likelihood of banking crises, because there is a learning period before risk assessment and

risk management skills can be developed. Furthermore, banks are often settled with large

amounts of pre-liberalization bad loans that were not recognized as bad before. The increase in

the amount of problem loans during a learning period of liberalizing credit and interest rate



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controls may increase the likelihood of banking crises. This is a temporary effect of behavioral

liberalization, and is captured by the change in the behavioral liberalization variable.

The competitive liberalization and privatization may also have a temporary effect in

increasing the likelihood of banking crises. Liberalizing competitive restrictions can increase therisk exposure and the vulnerability of the banking system. Given the liberalization of behavioral

and competitive restrictions, we also expect that privatization may increase the likelihood that a

banking crisis occurs because governments’ willingness to support banks in distress is likely to

decline.

Hypothesis 1.b: Over the longer term we expect that the relaxation of financial

restrictions on banks reduces the incidence of banking crises.

In the long term, risk management skills develop, credit allocation becomes more

efficient, and bad loans should decline. In addition, with the presence of strong regulation and

supervision of banks as well as market discipline, we expect that behavioral and competitive

liberalizations reduce the likelihood of banking crises. In the long run, privatization can affect

banks’ behavior through improved governance. These are the permanent effects, which are

reflected by the level of financial liberalization variables.

An additional consideration is that effects of liberalization could depend strongly on the

effectiveness of supervision, institutional quality, and the extent of deposit guarantees behind banks.

Hypothesis 2: On the role of bank capital regulation and prudential supervision (CRS),

institutional quality, and deposit insurance:

Hypothesis 2.a: Stronger capital regulations and supervisions and (legal and political),

and higher institutional quality in a country are expected to lower the likelihood that

liberalization increases the likelihood of banking crisis.

Hypothesis 2.b: The stronger the protection of bank depositors and other creditors of

banks, the greater is the likelihood that liberalization will result in a banking crisis.

Additional hypotheses with respect to the interactions between, for example, behavioral

and competitive restrictions could be formulated, but the high degree of correlation between



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different kinds of liberalization data prevents us from using interactions between types of

liberalization (see Table 2a).

6. Model Specification

The data set on financial reform covers 42 countries for the period 1973-2002. We study

the effects of financial liberalization for this total sample of countries, as well as for a group of

20 emerging market economies. These countries have liberalized to various degrees during the

period. The emerging markets group corresponds to the selection by the Economist3.

The hypotheses with respect to the likelihood of banking crisis are tested using the

following model specification:

,

, , , 1 , , 1 , , 1 ,,

ln ,1

i t

i t j j i t k k i t l l i t i ti t

P

L Z Q XP

where, , 1 , , 1 , , 1

, , ( )

1 prob( 1| , , )

1 j j i t k k i t l i ti t i t Z Q

P BC Z Q Xe

BCi,tis the onset of banking crisis dummy variable, which takes a value of one in the first

year that crisis erupts, and 0 if there is no crisis. The subscript i refers to a country and t indicates

time. Z j is j types of financial liberalization, which are discussed in the previous section.

X is an l-element vector of a standard set of macroeconomic control variables used in thereviewed literature. These variables are lagged one period relative to the onset of banking crisis

dummy. They include the real GDP growth rate, the ratio of current account to GDP, the ratio of

money supply to international reserves, the growth rate of the ratio of domestic credit provided

by banking sector to GDP, the inflation rate, the Northern interest rate, and OECD income4.

Following Arteta and Eichengreen (2002), the Northern interest rate is the weighted average of

the interest rates in Germany, USA, UK, Switzerland, France and Japan. The weights are the

3 Emerging market countries are Argentina, Brazil, Chile, Colombia, Egypt, Hong Kong, India, Indonesia, Israel,South Korea, Malaysia, Mexico, Pakistan, Peru, the Philippines, Singapore, South Africa, Thailand, Turkey,Venezuela. We exclude Taiwan due to the missing of many macroeconomic variables. Other countries in the sampleinclude Australia, Canada, France, Germany, Italy, Japan, New Zealand, US, UK, Bangladesh, Bolivia, Costa Rica,Ecuador, Ghana, Guatemala, Jamaica, Morocco, Nepal, Sri Lanka, Uruguay, and Zimbabwe.4 Since we control for the world interest rate, we do not include the real domestic interest rate in regressions. This isalso because the domestic interest rate correlates with the liberalization of interest rate control variables and has nomeaningful effect during the pre-liberalization when interest rates were controlled.



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fractions of debt denominated in the relevant currencies. The OECD income is the GDP of the

OECD member-nations.

Another set of variables controls for institutional quality and differences in deposit

insurance systems (Qk

). We use the real GDP per capita to capture general institutional quality.This variable is highly correlated with variables like corruption and rule of law but it captures the

quality of the legal and political systems in a country more generally.5 A proxy for the coverage

of explicit deposit insurance captures the difference in deposit insurance systems. It measures the

maximum deposit insurance coverage in a country relative to the value of the average (per

capita) deposit. To test whether the effects of financial liberalization depend on institutional

variables, we interact financial liberalization variables with each of the Qk variables (that is, Z j ×

Qk ). The descriptions and sources of the variables used in regressions are reported in Data

Appendix.

To reduce the effects of any source of simultaneity bias, we lag all independent variables

one year and exclude crisis years following the onset of a crisis within the same crisis episode.

To reduce the problem of correlated error terms across countries and over time in the panel

regressions, we use robust and clustering standard errors of estimates by country to correct the

covariance matrix of the estimates for heteroskedasticity and autocorrelation among the

observations across time within each country.

In order to achieve the objective of investigating whether there is information in the data

for types of restrictions relative to an aggregate financial liberalization index, it would be

desirable to use both levels and changes in behavioral liberalization, competitive liberalization,

and privatization, as well as interactions between these variables and supervision (CRS), deposit

insurance coverage and GDP/capita. The number of variables becomes very high this way,

however, and, more seriously; behavioral liberalization, competitive liberalization, privatization

and CRS are very highly correlated as shown in Table 2a. Thus, independent effects of all the

dimensions of financial reform may not be identified.

To alleviate the problems of number of data points and correlation among types of

liberalization we follow the following procedure:

5 The correlations between the GDP/Capita and the rule of law or corruptions are 0.6-0.7.



- 16 -

The first set of regressions in Table 3 include only the total financial liberalization index

in level (FL) and change over the preceding five years (FL) along with the index for capital

regulation and prudential supervision (CRS). In table 4, interactions between FL and CRS,

deposit insurance coverage and institutional quality6 (GDP/Capita) are introduced. Thereafter,

we divide FL into the three types (behavioral liberalization, competitive liberalization, and

privatization) in level, change, and in interactions but in steps. Thus, in Table 5 we divide the

level of FL into the three types while the change and interaction variables remain aggregated. In

Table 6, the change in liberalization is divided into three types while the level and interactions

remain aggregated. Finally, in Table 7, the interaction terms are divided into interactions with the

changes in three types of liberalization, while the aggregate liberalization index in the level and

the change is used. Interactions between the levels of types of liberalization and institutional

variables do not appear meaningful considering the high correlations among the types in levels,

as well as between the levels and institutional variables, in particular CRS. This step procedure

allows us to study the contributions of the types of liberalization while saving on degrees of

freedom and reducing potential problems of multicollinearity. All regressions include the same

macro variables as well as the levels of CRS, deposit insurance coverage and GDP/capita.

7. Empirical results

Table 3 reports the empirical results for the effects of the aggregate index for financial

liberalization in the level (FL) and preceding change (FL) on the probability of banking crises

for all the 42 countries and for 20 emerging markets. In this regression without interactions the

period is also divided into two sub-periods, 1973-1989 and 1990-2002. This division may strain

the data set, since the number of banking crises in emerging markets during the second sub-

period is only 17.

Focusing on the full period and all countries (column 1), the coefficient for the FL is

positive and strongly significant, suggesting that financial liberalization increases the likelihood

of banking crises. The FL seems to be associated with an increase in the likelihood of banking

crisis as well, but the significance level is low (75 percent probability of being different from

6 We experimented with a Corruption index and Rule of Law index as indicators of institutional quality. They are both highly correlated with GDP/capita and do not seem to contribute additional information.



- 17 -

zero). The coefficient for regulation and supervision (CRS) is negative and strongly significant. 7

The coefficient for deposit insurance coverage is positive as well on a weak level of significance.

In column 2, the results for emerging markets are the same but at a lower level of significance

with respect to FL and CRS, while FL and deposit insurance coverage are insignificant.

Dividing into sub-periods (columns 3-6), the results are very different in the two periods.

While results with respective to FL and FL for all countries for the first sub period remain

similar to the results for the whole period, the results for emerging markets and the second sub-

period are very different. Furthermore, CRS is significant only in the second sub period. The

only variable that remains robust in terms of sign (in additional to macroeconomic control

variables) is deposit insurance coverage. It has a positive sign in all cases, but with a low level of

significance.

If the results for the sub periods can be considered valid at all, they indicate that the level

of financial liberalization had a positive impact on banking crises during the first sub-period,

while regulation and supervision were effective at preventing crises during the second sub

period. However, this conclusion must be hedged given the relatively few crisis episodes in the

second sub-period in particular. The results for GDP per capita are also surprising in the second

sub-period, wherein the coefficients are positive and significant for all as well as emerging

markets.

In Table 4 interaction terms between FL on the one hand, and CRS, deposit insurancecoverage and GDP/capita on the other, are included. The impact of FL appears entirely through

the interactions in this case, while the result for FL remains unchanged. The impact of CRS

also comes through the interaction term while the level alone actually switches sign and becomes

positive. Thus we can conclude that interactions are important.

The interaction terms in Table 4 tell us that the impact of liberalization on banking crises

depend on both CRS and the level of domestic institutions (proxied by GDP/Capita). The impact

of financial liberalization on the likelihood banking crises is reduced if there is effective capital

regulation and prudential supervision (CRS). The influence of CRS in reducing the impact of

liberalization becomes stronger if GDP/Capita is high according to the significant coefficients of

7The estimated coefficients in logit regressions do not indicate the magnitude of increase or decrease in the

probability of banking crisis. However, the sign of the coefficient indicates the direction of the effect.



- 18 -

GDP/Capita and its interaction with FL in the regression for all countries. The latter result is not

robust for a sample of emerging markets, however.

The results so far, before dividing the liberalization into types, indicate that financial

liberalization increases the likelihood of banking crisis, but this effect can be countered by

effective capital regulation and supervision. Next we want to see whether effects of particular

types of liberalization can be identified.

In Table 5, the level of FL is replaced by the levels of behavioral liberalization,

competitive liberalization, and privatization. Other variables including FL and the interaction

terms of FL are the same as in Table 4. Among these three types of liberalization, the only effect

with even weak significance (the 15 percent level of significance) is the negative coefficient for

privatization.

In Table 6, the change in financial liberalization (FL) has been divided into types:

behavioral liberalization, competitive liberalization, and privatization. All changes refer to

the change from the period beginning six years before and ending one period before observations

for the dependent variable. The level FL and the FL interaction terms are included as in previous

regressions. Significant results for the change in different types of liberalization are essentially

absent as was in the case for FL. In both Tables 5 and 6, the results with respect to interactions,

CRS, and GDP/Capita are similar to those in Table 4.

We turn finally to interactions between changes in types of liberalization, and CRS,

deposit insurance coverage, and GDP/Capita, while FL and FL are entered on the aggregate in

Table 7. Here the coefficient for the level of FL is again positive and significant while the

coefficient for CRS is negative and significant as in the first Table (Table 3) without interactions.

None of the types of change in liberalization interact significantly in both country groups with

CRS. The signs for the interaction between behavioral liberalization and CRS are negative for

both country groups, however, as previous results for FL have suggested. The interaction

between privatization and CRS is positive and significant at the 10 percent level for a group of

emerging markets, which indicates that a substantial change in privatization increases banking

the probability of banking crises to a greater extent when CRS is relatively strong. This result is

not intuitive.

Change in types of liberalization seems to be more relevant when they are interacted with

deposit insurance coverage. Both the change in behavioral liberalization and privatization



- 19 -

interact significantly with deposit insurance coverage. The positive sign for the former

interaction indicates that the removal of behavioral restrictions on banks increases the probability

of banking crises to a greater extent when deposit insurance coverage is high and, accordingly,

conditions for moral hazard in banking exists. The negative sign for the latter interaction implies

that the privatization has a lesser impact on banking crises when deposit insurance coverage is

high. In other words, privatization does not seem to worsen the moral hazard problem caused by

high deposit insurance coverage.

We can now go back to the explicit hypotheses formulated in Section 5.

There is no support for Hypothesis 1.a stating that the removal of financial restrictions is

associated with a learning period and a temporary increase in the probability of banking crises.

This result holds for both the aggregate financial liberalization index (FL) and different types of

liberalization.

Hypothesis 1.b is rejected. When we use the aggregate financial liberalization index (FL),

the permanent effect of liberalization does not seem to reduce the likelihood of banking crises;

on the opposite, it increases crises. In addition, when distinguishing between levels of different

kinds of liberalization, we do not find significant effects for the individual types. The

insignificance of competitive and behavioral liberalizations could be a result of their high

correlation. The negative sign for privatization alone in Table 6 is an indication that the long-

term effect on improved governance dominates but its coefficient is significant only at the 15

percent level and only for the sample of all countries.

Hypothesis 2.a is supported in the sense that the effects of strengthened regulation and

supervision (CRS) seem to be a reduction in the likelihood of banking crises. This effect seems

stronger at high levels of financial liberalization according to the results for all countries in

Tables 4-6 when the aggregate index of FL is used.

Finally, results from testing Hypothesis 2.b depend on whether the permanent or

temporary effects of liberalization are considered. According to Tables 4-6 when the aggregate

index of FL is used, Hypothesis 2.b is not supported, or there is no evidence that financial

liberalization will increase the likelihood of crises relatively more at high levels of deposit

insurance coverage. However, when considering the temporary effect, behavioral liberalization is

associated with the higher likelihood of banking crises at high levels of deposit insurance

coverage according to Table 8, but the significance level is not high. On the other hand, the



- 20 -

temporary impact of privatization (reduce the state ownership of banks) is a reduction in the

likelihood of banking crises.

8. Conclusion

The evidence presented in Tables 3-7 does not lead to clear-cut and robust conclusions of

the effects of financial liberalization on banking crises. Results are sensitive to country group,

period, and the inclusion of interaction terms. This sensitivity depends to some extent on few

observations on banking crises in sub-periods, and to some extent on high correlation among

types of financial sector reform. Effects of reforms with respect to restrictions on financial

market and banking activities can be separated from effects of reforms of regulation and

supervision, however.

Conclusions which can be drawn with a modest level of confidence are that financialliberalization seems to be associated with the increased probability of banking crises, but this

effect can be counteracted with strengthened capital regulation and supervision. When

distinguishing the index of total financial liberalization into different types; however, we do not

find significant effects for the individual types (behavioral liberalization, competitive

liberalization, and privatization) on the likelihood of banking crises. In other words,

distinguishing among types of liberalization does not add much information relative to using an

aggregate index for financial liberalization, or there is no particular type of financial

liberalization that lead to a higher likelihood of banking crises than others.

We also investigate whether the likelihood of banking crises will be temporarily higher

after the relaxation of financial restrictions due to learning period for risk assessment and

management skills to be developed. We find that it is more meaningful to distinguish between

different types of liberalization when studying the temporary effects (captured by changes in

liberalization) and taking into account the impact of deposit insurance coverage. Although their

significance levels are not high, the results show that at a high level of deposit insurance

coverage the change in behavioral liberalization increases the likelihood of crises at a greater

extent, whereas the change in privatization lowers the likelihood of crises. A higher competition

and lower likelihood of bank bail out as a result of privatization could discipline banks and lower

moral hazard.



- 21 -

Data Appendix: Data Descriptions and Sources

Variable Description Source

The Onset Banking

Crisis

The onset of banking crisis dummy, which is equal to 1 in a first year of

each banking crisis episode (both systemic and non-systemic bankingcrises), and 0 otherwise

Caprio and Klingebiel

(2005)

Real GDP Per Capita The log of real GDP per capita (constant 2000 US$). WDI

Real GDP GrowthRate

Real GDP growth (annual %) WDI

CA to GDP Current account balance (% of GDP) WDI

Growth of DomesticCredit

The log difference of the ratio of domestic credit provided by bankingsector (% of GDP)

WDI

M2 to Reserve The ratio of money and quasi money (M2) to gross international reserves WDI & IFS

Inflation The log difference of GDP deflator WDI

Northern Interest Rate The weighted average of the interest rate in Germany, USA, UK,Switzerland, France, and Japan. The weights are the fraction of debtdenominated in the relevant currencies

Authors’ calculationfollowing Eichengreenand Arteta (2000)

% of ∆ OECD income The growth rate of the average GDP of the OECD (high income) nations Authors’ calculation

Behavioral Lib. The aggregate index of the variables of elimination of credit controls(include reserve requirements) and interest rate controls. The scale is 0-6.

Authors’ calculation based on Omori (2006)

Competitive Lib. An aggregate index of equity market lib., capital account lib. and entry &activity lib. The scale is 0-9.

Authors’ calculation based on Omori (2006)

Privatization Privatization of state ownership of the banking sector. The scale is 0-3. Omori (2006)

CRS (CapitalRegulation &Supervision)

Enhancement of prudential regulations and supervision of the bankingsector Omori (2006)

FL Behavioral Lib. + Competitive Lib. + Privatization. The scale is 0 – 18. Omori (2006)

∆ Behavioral Lib. Change of Behavioral from the previous five years Authors’ calculation based on Omori (2006)

∆ Competitive Lib. Change of Competitive Lib. from the previous five years Authors’ calculation based on Omori (2006)

∆ Privatization Change of Privatizationfrom the previous five years Authors’ calculation based on Omori (2006)

∆ FL Change of Total Financial Lib. from the previous five years Authors’ calculation based on Omori (2006)

Deposit InsuranceCoverage The interval data of the ratio of deposit insurance coverage per deposits per capita. This index ranges from 1 to 10 (the variable is constructed based on the data from Demirgüç-Kunt et al, 2005)

Angkinand andWilhborg (2006)



- 22 -

References

Abiad, Abdul and Ashoka Mody (2005) “Financial Reform: What Shakes It? What Shapes It?”

American Economic Review, 95(1), March, 66-88.

Alba, Pedro; Amar Bhattacharya, Stijn Claessens, Swati Ghosh , and Hernandez, Leonard (2000)

“The Role of Macroeconomic and Financial Sector Linkages in East Asia’s Financial

Crisis” in The Asian Financial Crisis Causes, Contagion and Consequences. Agenor,

Pierre-Richard; Miller, Marcus; Vines, David and Weber, Alex (eds) New York:

Cambridge University Press.

Angkinand, Apanard and Clas Wihlborg (2006) “Deposit Insurance Coverage, Credibility of

Non-insurance and Banking Crisis” LEFIC Working paper No. 010, Center for Law,

Economics and Financial Institutions, Copenhagen Business School.

Barth, James R., Gerard Caprio Jr., and Ross Levine (2004), “The Regulation and Supervision:

What Works Best?” J ournal of Financial Intermediation, 13, 205-248.

Beim, David, and Calomiris, Charles (2000), Emerging Financial Markets. New York, NY:

McGraw Hill College.

Bekaert, Geert; Harvey, Campbell, and Lundblad, Christian. (2005), “Growth Volatility and

Financial Liberalization”, J ournal of International Money and Finance24, 370-403.

Caprio, Gerald, Jr., Hanson, James, and Honohan, Patrick (2000) “The Benefits and Pitfalls of

Financial Liberalization.” World Bank Policy Paper. Washington: World Bank.

---------- and Daniela Klingebiel (1996) “Bank Insolvency: Bad Luck, Bad Policy, or Bad

Banking.” Presented at the Annual World Bank Conference on Development Economics.

----------Daniela Klingebiel, Luc Laeven, and Guillermo Noguera, (2005). Banking Crisis

Database. In Systemic Financial Crises: Containment and Resolution. Honohan, Patrick,

and Luc Laeven (eds) New York, NY: Cambridge University Press.

---------- and Maria Soledad Martinez-Peria, 2000, “Avoiding Disaster: Policies to Reduce the

Risk of Banking Crises,” Working Paper No. 47, Cairo, Egypt: Egyptian Center for

Economic Studies.

Claessens, Stijn, Asli Demirgüç-Kunt, Harry Huizinga (2001), “How does foreign entry affect

domestic banking markets”, J ournal of Banking and Finance25, 891 – 911.

Diaz-Alejandro, Carlos (1985) “Good-Bye Financial Repression, Hello Financial Crash.”

J ournal of Development Economics. 19, 1-24.



- 23 -

Demirgüç-Kunt, Asli, Ross Levine and Hong-Ghi Min (1998) “Opening to Foreign Banks:

Issues of Stability, Efficiency, and Growth”, in The Implications of Globalization of

World Financial Markets, The Bank of Korea.

Demirgüç-Kunt, Asli, and Enrica Detragiache (2001) “Financial Liberalization and Financial

Fragility”, in Financial Liberalization: How Far, How Fast?, Gerard Caprio Patrick

Honohan, and Joseph E. Stiglitz (eds), Cambridge University Press.

Demirgüç-Kunt, Asli, B. Karacaovali and L. Laeven (2005). “Deposit insurance around the

World: A comprehensive database,” World Bank Policy Research Working Paper No.

3628, the World Bank: Washington, DC.

Desai, Mihir A., C. Fritz Foley and James R. Hines Jr. (2006) “Capital Controls, Liberalizations,

and Foreign Direct Investment.” Review of Financial Studies19(4), 1433-1464.

Eichengreen, Barry and Carlos Arteta (2002). “Banking Crises in Emerging Markets:

Presumptions and Evidence” in Financial Policies in Emerging Markets. Mario I. Blejer

and Marko Skreb (eds) Cambridge, Mass.: MIT Press.

Fry, Maxwell, (1997) “In Favour of Financial Liberalization”. The Economic J ournal, Vol.

107(442), 754-770.

Giovannini, Alberto and de Melo, Martha (1993) “Government Revenue from Financial

Repression.” The American Economic Review, Vol. 83(4), 953-963.

Honohan, Patrick (1997) “Banking System Failures in Developing and Transition Countries:

Diagnosis and Prediction.” BIS Working Papers No. 39. Bank for International

Settlements.

Laeven, Luc (2003) “Does Financial Liberalization Reduce Financing Constraints?” Financial

Management. 32(1), 5-34.

Kaminsky, Graciela and Reinhart, Carmen (1999) “The Twin Crises: The Causes of Banking and

Balance-Of-Payments Problems.” The American Economic Review89, 473-500.

Kaminsky, Graciela and Sergio Schmukler (2003), “Short-Run Pain, Long-Run Gain: The

Effects of Financial Liberalization.” NBER Working Papers No, 9787, National Bureau

of Economic Research.

Minsky, Hyman (1992) “The Financial Instability Hypothesis”, the J erome Levy Economics

Institute Working Paper No. 74, Bard College, Annandale-on-Hudson, New York.

McKinnon , Ronald (1973) Money and Capital in Economic Development, Washington, D.C.:

Brookings Institution.



- 24 -

McKinnon, Ronald, and Pill, Huw (1997), “Credible Economic Liberalizations and

Overborrowing.” American Economic Review, 87 (May), 189-93.

Noy, Ilan (2004) “Financial Liberalization, Prudential Supervision, and the Onset of Banking

Crises”, Emerging Markets Reviews, 5, 341-359.

Omori, Sawa (2006) “Measuring Financial Reform” forthcoming in the special issue of

International Interactions on the Measurement of International Economic Interactions.

Ranciere, Romiam, Aaron Tornell, and Frank Westermann (2006) “Decomposing the Effects of

Financial Liberalization: Crises vs. Growth”, J ournal of Banking & Finance, 30, 3331-

3348.

Schmukler, Segio (2004). “Financial Globalization: Gain and Pain for Developing Countries.”

Federal Reserve Bank of Atlanta Economic Review, Second Quarter, pp39-66.

Shaw, Edward (1973) Financial Deepening in Economic Development, New York: Oxford

University Press.

Tornell, Aaron, Frank Westermann, Lorenza Martinez. (2004), “The Positive Link Between

Financial Liberalization, Growth and Crises”. NBER Working Paper No. 10293. National

Bureau of Economic Research.

Weller, Christian. (2001). “Financial Crises After Financial Liberalization: Exceptional

Circumstances or Structural Weakness?” The Journal of Development Studies, 38(1), 98-

127.

Williamson, John and Molly Mahar (1998). “A Survey of Financial Liberalization”. Essays in

International Finance No. 211. New Jersey: Princeton University Printing Services.

Wolfson, Martin (2002) “Minsky's Theory of Financial Crises in a Global Context.” J ournal of

Economic Issues, 36:2, pp. 393-400. Wooldridge, Jeffrey M. (2002) Econometric

Analysis of Cross Section and Panel Data. The MIT Press.



- 25 -

Table 1: Descriptive Statistics

Variable Obs Mean Std. Dev. Min Max

The Onset of Banking Crisis 746 0.070 0.255 0 1

Real Growth Rate of GDP 746 3.859 3.540 -9.016 14.421

CA (% of GDP) 746 -2.332 4.489 -16.287 22.305

M2/Reserves 746 7.971 7.601 0.778 53.5711Growth Rate of Domestic Credit 746 0.026 0.152 -1.018 1.3212Inflation 746 0.186 0.413 -0.178 4.823

Northern Interest Rate 746 6.694 2.330 2.634 15.518

% change OECD Income 746 2.699 1.178 0.123 4.743

Institutional Variables

CRS 746 0.727 0.944 0 3

Deposit Insurance 746 2.135 3.110 0 103Real GDP per Capita 746 8.014 1.433 4.941 10.456

Financial Liberalization Policies

Interest Rate Lib. 746 2.090 1.223 0 3

Credit Allocation Lib 746 1.672 1.230 0 3

Equity Market Lib. 746 1.605 1.066 0 3

Entry & Activity Barrier Lib. 746 1.413 1.115 0 3

Capital Account Control 746 1.838 1.096 0 3

Privatization 746 1.253 1.170 0 3

Behavioral Lib. 746 4.855 2.847 0 9

Competitive Lib. 746 3.761 2.220 0 6

Total FL 746 9.870 5.560 0 18

∆ Behavioral Lib. 746 0.901 1.557 -5 6

∆ Competitive Lib. 746 1.091 1.604 -3 8

∆ Privatization Lib. 746 0.204 0.648 -2 3∆ Total FL 746 2.196 2.852 -7 14

Interaction Term

Total FL CRS 746 10.995 15.512 0 54

Total FL Deposit Insurance 742 25.020 39.284 0 170

Total FL GDP per Capita 746 84.038 54.174 0 188.212

Δ Behavioral Lib. CRS 746 0.507 1.427 -2 10

Δ Behavioral Lib. Deposit Insurance 742 1.801 7.880 -50 50

Δ Behavioral Lib. GDP per Capita 746 7.083 12.638 -44.096 49.021

Δ Competitive Lib. CRS 746 0.760 1.636 -4 10

Δ Competitive Lib. Deposit Insurance 746 2.374 7.559 -24 63

Δ Competitive Lib. GDP per Capita 746 8.701 12.879 -25.570 71.020

Δ Privatization CRS 746 0.240 1.003 -2 9

Δ Privatization Deposit Insurance 746 0.697 2.968 -10 30

Δ Privatization GDP per Capita 746 1.670 5.446 -19.104 30.05

Note: 1 log difference of claim on domestic private credit/GDP, 2 log difference of GDP deflator, 3 log of real GDP per capita



26

Table 2a: Correlation among Financial Liberalization and Institutional Variables

obs. 746 C R

S

D e p o s i t I n s u r a n c e

R e a

l G D P p e r C a p i t a

I n t e

r e s t R a t e L i b .

C r e

d i t A l l o c a t i o n L i b

E q u i t y M a r k e t L i b .

E n t r y & A c t i v i t y B a r r i e r L i b .

C a p i t a l A c c o u n t C o n t r o l

P r i v a t i z a t i o n

B e h a v i o r a l L i b .

C o m p e t i t i v e L i b .

F L

∆ B

e h a v i o r a l L i b .

∆ C

o m p e t i t i v e L i b .

∆ P

r i v a t i z a t i o n L i b .

∆ F

L

CRS 1

Deposit Insurance 0.186 1

Real GDP per Capita 0.559 0.103 1

Interest Rate Lib. 0.528 0.150 0.461 1

Credit Allocation Lib 0.648 0.066 0.442 0.636 1

Equity Market Lib. 0.674 0.185 0.645 0.665 0.659 1

Entry & Activity Barrier Lib. 0.625 0.266 0.388 0.618 0.606 0.619 1

Capital Account Control 0.565 0.200 0.594 0.643 0.598 0.711 0.563 1

Privatization 0.486 0.128 0.478 0.432 0.519 0.500 0.366 0.537 1

Behavioral Lib. 0.650 0.119 0.499 0.904 0.905 0.732 0.677 0.686 0.526 1

Competitive Lib. 0.715 0.251 0.623 0.739 0.715 0.891 0.841 0.873 0.538 0.804 1

FL 0.729 0.203 0.619 0.831 0.837 0.854 0.778 0.834 0.696 0.922 0.947 1

∆ Behavioral Lib. -0.100 -0.035 -0.061 0.328 0.206 0.051 0.006 0.072 -0.012 0.295 0.049 0.140 1

∆ Competitive Lib. -0.023 0.012 -0.021 0.259 0.128 0.229 0.304 0.307 0.033 0.214 0.323 0.258 0.380 1

∆ Privatization Lib. 0.143 0.129 0.036 0.192 0.217 0.179 0.200 0.230 0.347 0.226 0.234 0.283 0.172 0.228 1

∆ FL -0.035 0.017 -0.037 0.369 0.233 0.197 0.220 0.264 0.090 0.333 0.262 0.286 0.799 0.822 0.449 1



27

1 - y r L a g B e h a v i o r a l L i b .





1 - y r L a g C o m p e t i t i v e L i b .





1 - y r L a g P r i v a t i z a t i o n





1 - y r L a g T o t a l F L




1-yr Lag Behavioral Lib. 1

2-yr Lag Behavioral Lib. 0.957 1

3-yr Lag Behaviora l L ib. 0.91 0.956 1

4-yr Lag Behavioral Lib. 0.859 0.907 0.955 1

5-yr Lag Behavioral Lib. 0.814 0.855 0.904 0.953 1

1-yr Lag Competit ive Lib. 0.801 0.801 0.793 0.778 0.76 1

2-yr Lag Competit ive Lib. 0.781 0.798 0.797 0.789 0.773 0.976 1

3-yr Lag Competit ive Lib. 0.756 0.778 0.795 0.793 0.784 0.948 0.976 1

4-yr Lag Competit ive Lib. 0.728 0.752 0.773 0.789 0.787 0.917 0.947 0.975 1

5-yr Lag Competit ive Lib. 0.698 0.722 0.747 0.767 0.783 0.884 0.914 0.945 0.974 1

1-yr Lag Privatization 0.485 0.5 0.512 0.516 0.524 0.539 0.548 0.555 0.557 0.556 1

2-yr Lag Privatization 0.468 0.485 0.502 0.514 0.519 0.526 0.538 0.546 0.555 0.556 0.961 1

3-yr Lag Privatization 0.448 0.467 0.484 0.502 0.514 0.508 0.524 0.535 0.544 0.553 0.924 0.96 1

4-yr Lag Privatization 0.428 0.447 0.467 0.485 0.503 0.491 0.507 0.522 0.534 0.543 0.888 0.921 0.959 1

5-yr Lag Privatization 0.413 0.427 0.448 0.468 0.487 0.474 0.49 0.506 0.521 0.534 0.855 0.886 0.919 0.958 1

1-yr Lag Tota l FL 0.917 0.903 0.882 0.854 0.829 0.951 0.932 0.909 0.882 0.853 0.678 0.657 0.633 0.61 0.59 1

2-yr Lag Tota l FL 0.887 0.917 0.901 0.88 0.851 0.936 0.95 0.931 0.907 0.879 0.681 0.678 0.656 0.632 0.609 0.981 1

3-yr Lag Tota l FL 0.852 0.886 0.916 0.9 0.877 0.916 0.935 0.948 0.929 0.904 0.683 0.681 0.677 0.655 0.631 0.957 0.981 1

4-yr Lag Tota l FL 0.813 0.85 0.884 0.915 0.898 0.891 0.914 0.933 0.947 0.926 0.679 0.683 0.681 0.677 0.656 0.928 0.956 0.98 1

5-yr Lag Tota l FL 0.778 0.81 0.847 0.882 0.913 0.864 0.888 0.912 0.931 0.945 0.676 0.68 0.683 0.681 0.679 0.9 0.926 0.954 0.979

Table 2b: Correlations between Behavioral Restriction and Competitive Restriction during the Previous 5 Years



28

Table 3: The Effect of the Aggregate Financial L iberalization Index (FL) on Banking Crises

(1) (2) (3) (4) (5) (6)

All Emg All Emg All Emg

1973-2002 1973-1989 1990-2002

FL 0.0933 ** 0.0767 # 0.1877 ** 0.0683 -0.0039 -0.0754

(0.0337) (0.2692) (0.0474) (0.6200) (0.9647) (0.5517)

∆ FL 0.0606 # -0.0116 0.1643 # 0.1733 -0.0137 -0.1287 #

(0.2427) (0.8872) (0.1267) (0.3693) (0.8597) (0.2047)

CRS -0.6611 *** -0.8869 * -0.1159 0.3543 -1.2882 *** -1.3343 **

(0.0029) (0.0510) (0.8288) (0.8083) (0.0003) (0.0200)

Deposit Insurance 0.0495 # 0.0445 0.1384 # 0.1005 # 0.0185 0.1017 #

(0.1879) (0.3443) (0.1202) (0.2730) (0.7716) (0.2720)

Real GDP per Capita -0.1060 0.0962 -0.5750 ** 0.1149 0.5428 *** 0.7796 ***

(0.4014) (0.6985) (0.0386) (0.8330) (0.0098) (0.0035)

Real Growth Rate of GDP 0.0243 0.0341 0.0290 0.0718 -0.0312 -0.0098

(0.5345) (0.5798) (0.6680) (0.3318) (0.5755) (0.9083)

CA (% of GDP) -0.0784 ** -0.0764 # -0.0754 # -0.0158 -0.0837 # -0.1251 #

(0.0252) (0.1400) (0.1740) (0.8165) (0.1515) (0.1456)

M2/Reserves 0.0272 # 0.0448 # 0.0282 0.0452 0.0329 # 0.0754 #

(0.1330) (0.1442) (0.5130) (0.5687) (0.1883) (0.2924)

Growth Rate of Domestic Credit 0.5237 # 0.8417 # -0.1054 0.1018 0.6682 1.2883 #

(0.3045) (0.1875) (0.9222) (0.9352) (0.4051) (0.2844)

Inflation 0.7904 *** 0.5850 # 1.4990 *** 1.2968 # 0.3699 0.4223

(0.0001) (0.1178) (0.0064) (0.2001) (0.3334) (0.4355)

Northern Interest Rate 0.0712 # 0.0737 0.1314 0.2926 # -0.2292 # -0.4600 **

(0.2729) (0.3972) (0.3455) (0.1491) (0.1331) (0.0303)

% change OECD Income -0.2126 # -0.2728 # -0.3060 # -0.3835 # -0.0176 0.2373

(0.1625) (0.2526) (0.1824) (0.3128) (0.9344) (0.4287)

Constant -3.2691 *** -4.2566 ** -1.2618 -6.9717 * -5.0069 *** -5.7177 *

(0.0007) (0.0240) (0.5433) (0.0757) (0.0080) (0.0636)

No of Obs 746 347 324 138 422 209

Wald Chi-Square 67.907 72.973 46.582 56.050 49.962 58.175

Prob > Chi-Square 0.000 0.000 0.000 0.000 0.000 0.000The dependent variable is the onset of banking crisis dummy. All independent variables are lagged by one year. “∆” refers to a change over five years. Regressions are estimated using the logitmodel, and t-statistics are calculated using robust and clustered standard errors within a country. *, **, *** indicate the significance levels of 10%, 5%, and 1% respectively. # indicates thecoefficient value zero that falls outside one standard deviation of the estimate. The numbers in parentheses are p-values.



29

Table 4: The Interaction of the Aggregate Financial Liberalization Index(FL) and Institutional Variables, 1973-2002

(1) (2)

All Emg

FL -0.1298 0.1202(0.3739) (0.6761)

∆ FL 0.0619 # -0.0347

(0.2279) (0.7022)

FL CRS -0.1449 * -0.0990 #

(0.0632) (0.2481)

FL Deposit Insurance -0.0076 0.0090 #

(0.3754) (0.3117)

FL GDP per Capita 0.0343 * -0.0051

(0.0633) (0.8843)

CRS 1.3893 # 0.4008

(0.2304) (0.7612)

Deposit Insurance 0.1211 # -0.0289(0.2122) (0.7547)

Real GDP per Capita -0.4007 * 0.0821

(0.0597) (0.8200)

Real Growth Rate of GDP 0.0187 0.0411

(0.6546) (0.5324)

CA (% of GDP) -0.0959 ** -0.0654 #

(0.0138) (0.2246)

M2/Reserves 0.0331 * 0.0468 #

(0.0716) (0.1501)

Growth Rate of Domestic Credit 0.5456 # 0.7874 #

(0.3138) (0.2266)

Inflation 0.8768 *** 0.5955 #

(0.0003) (0.1272)

Northern Interest Rate 0.0589 0.0998 #

(0.3777) (0.2303)

% change OECD Income -0.2344 # -0.2809 #

(0.1144) (0.2659)

Constant -1.4552 -4.3138 *

(0.3308) (0.0827)

No of Obs 746 347

Wald Chi-Square 73.938 115.941

Prob > Chi-Square 0.000 0.000

The dependent variable is the onset of banking crisis dummy. All independent variables are lagged by one year.“∆” refers to a change over five years. Regressions are estimated using the logit model, and t-statistics arecalculated using robust and clustered standard errors within a country. *, **, *** indicate the significance levelsof 10%, 5%, and 1% respectively. # indicates the coefficient value zero that falls outside one standard deviation of the estimate. The numbers in parentheses are p-values.



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Table 5: The Effect of Different Types of Financial Liberalization onBanking Crises, 1973-2002

(1) (2)

All Emg

∆ in FL 0.0550 # -0.0378(0.2796) (0.6542)

Behavioral Liberalization -0.0999 0.1483

(0.5736) (0.6257)

Competitive Liberalization -0.0905 0.2332

(0.6279) (0.4017)

Privatization -0.2634 # -0.2325

(0.1423) (0.4632)

FL CRS -0.1362 # -0.0861

(0.1169) (0.4352)

FL Deposit Insurance -0.0071 0.0093 #

(0.4157) (0.2805)

FL GDP per Capita 0.0338 * -0.0056(0.0579) (0.8510)

CRS 1.2176 0.1193

(0.3516) (0.9438)

Deposit Insurance 0.1186 # -0.0434

(0.2281) (0.6315)


(0.0562) (0.7037)


(0.6217) (0.6199)

CA (% of GDP) -0.0977 ** -0.0740 #

(0.0139) (0.2257)

M2/Reserves 0.0365 ** 0.0572 #(0.0409) (0.1057)


(0.3115) (0.2406)

Inflation 0.8577 *** 0.4608 #

(0.0003) (0.2678)

Northern Interest Rate 0.0713 # 0.1544 *

(0.3103) (0.0771)

% change OECD Income -0.2425 * -0.2770 #

(0.0958) (0.2551)

Constant -1.5881 # -5.2303 *

(0.2958) (0.0547)

No of Obs 746 347






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Table 6: Change in Types of Financial Liberalization, 1973-2002

(1) (2)

All Emg

FL -0.1317 0.1487

(0.3664) (0.6021)Δ Behavioral Lib. 0.0444 0.0775

(0.7033) (0.6956)

Δ Competitive Lib. 0.1099 # -0.0762

(0.2837) (0.6043)

Δ Privatization -0.1085 -0.3002

(0.6505) (0.3743)

FL CRS -0.1394 * -0.0575

(0.0879) (0.6098)

FL Deposit Insurance -0.0071 0.0085

(0.4195) (0.3942)

FL GDP per Capita 0.0345 * -0.0101

(0.0613) (0.7677)CRS 1.3176 # -0.1719

(0.2778) (0.9178)


(0.2233) (0.9591)


(0.0656) (0.6690)


(0.6582) (0.5386)

CA (% of GDP) -0.1008 *** -0.0687 #

(0.0096) (0.2312)

M2/Reserves 0.0319 * 0.0477 #

(0.0895) (0.1360)Growth Rate of Domestic Credit 0.5505 # 0.7972 #

(0.3076) (0.2276)

Inflation 0.8740 *** 0.4728 #

(0.0002) (0.2449)

Northern Interest Rate 0.0555 0.0759

(0.4103) (0.3823)

% change OECD Income -0.2396 * -0.3002 #

(0.0991) (0.1962)

Constant -1.4270 -4.6548 *

(0.3432) (0.0716)

No of Obs 746.0000 347.0000






Table 7: Interactions between Change in Types of Financial Liberalization andInstitutions, 1973-2002

(1) (2)

All Emg

FL 0.0959 ** 0.0992 #

(0.0473) (0.2388)

∆ FL -0.0792 -0.3577(0.8570) (0.5592)

Δ Behavioral Lib. CRS -0.2508 # -0.1411

(0.2410) (0.5747)

Δ Behavioral Lib. Deposit Insurance 0.0387 # 0.0924 **

(0.2511) (0.0431)

Δ Behavioral Lib. GDP per Capita 0.0186 0.0261

(0.7287) (0.7234)

Δ Competitive Lib. CRS 0.1507 -0.2938 #

(0.4112) (0.2883)

Δ Competitive Lib. Deposit Insurance -0.0192 -0.0103

(0.4611) (0.7746)

Δ Competitive Lib. GDP per Capita 0.0226 0.0481

(0.6488) (0.5603)

Δ Privatization CRS 0.1800 0.7471 *

(0.3436) (0.0800)

Δ Privatization Deposit Insurance -0.1062 ** -0.1425 **

(0.0208) (0.0155)

Δ Privatization GDP per Capita 0.0023 0.0137

(0.9740) (0.9028)

CRS -0.7792 ** -0.6692 #

(0.0163) (0.2736)


(0.1350) (0.9607)

Real GDP per Capita -0.1312 -0.0239

(0.4905) (0.9319)Real Growth Rate of GDP 0.0175 0.0068

(0.6834) (0.9234)

CA (% of GDP) -0.0904 ** -0.0944 #

(0.0167) (0.1518)

M2/Reserves 0.0206 # 0.0492 #

(0.2785) (0.1480)


(0.2412) (0.2143)

Inflation 0.7708 *** 0.5679 #

(0.0001) (0.1188)

Northern Interest Rate 0.0578 0.0792

(0.4056) (0.4297)% change OECD Income -0.2332 # -0.3001 #

(0.1159) (0.1409)

Constant -2.9859 * -3.2603 #

(0.0650) (0.1497)

No of Obs 746 347Wald Chi-Square 103.967 43.426

Prob > Chi-Square 0.000 0.003The dependent variable is the onset of banking crisis dummy. All independent variables are lagged by one year. ∆FL refers to a change over five

years. Regressions are estimated using the logit model, and t-statistics are calculated using robust and clustered standard errors within a country.

Fin Lib and Banking Crises

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