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Tijdschrift voor Economie en Management
Vol. LI, 3, 2006
Exchange Market Pressure in the Formerly
Planned Central and Eastern
European Countries:
the Role of Institutions
by A. VAN POECK, J. VANNESTE and M. VEINER
André Van Poeck
Universiteit Antwerpen,
Departement Algemene
Economie, Antwerpen
Maret Veiner
Universiteit Antwerpen,
Departement Algemene
Economie, Antwerpen
Jacques Vanneste
Universiteit Antwerpen,
Departement Algemene
Economie, Antwerpen
ABSTRACT
In this paper we find evidence that institutional improvements such as economic
liberalization, improved corporate governance, banking sector reform, improvements of rule of law and pushing back corruption have significantly reduced tensions on the exchange market in the formerly planned Central and Eastern European transition economies.
We also show that countries with extreme exchange rate arrangements (such as
a currency board or a freely floating exchange rate) have – ceteris paribus – been
less vulnerable to turbulence on the exchange market than countries with intermediate exchange rate arrangements, such as an adjustable fixed peg. This confirms
the so-called bi-polar view on exchange rate regimes for this group of countries.
Testing for the interaction between economic fundamentals (current account,
domestic credit growth and the inflation differential) and institutions our results
are in general quite supporting to the hypothesis that a higher quality of institutions lessens the adverse effect of weak economic fundamentals. Low corruption, efficient banking regulatory and supervisory systems and profound economic liberalization significantly reduce the impact on exchange market pressure
of domestic credit growth and inflation.
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I. INTRODUCTION
The role of institutions in economic performance has been one of the
research topics covered by Professor W. Moesen during his fruitful
academic career. In this paper we want to contribute to his field of
interest by focusing on the institutional developments which have
taken place in the formerly planned Central and Eastern European
countries (CEECs) and the impact on their exchange markets. The
research question is whether institutional reforms such as economic
liberalization, improved corporate governance, banking sector reform,
improvements of rule of law and pushing back corruption have
affected tensions on the currencies of these countries.
The formerly planned economies of Central and Eastern Europe
have experienced drastic changes since the beginning of the 1990s.
Together with the introduction of a market economy institutional
reform has been high on their economic and political agenda. In some
countries the institutional reforms were speeded up by the eagerness
to become member of the European Union. As a matter of fact, eight
CEECs successfully joined the EU in the spring of 2004 and others
are likely to follow.
Yet, these transition processes have not always been very smooth.
On the contrary, several transition countries have experienced highly
turmoil periods on the currency markets, like e.g. Hungary (1994),
the Czech Republic, Romania and Bulgaria (1997) and Russia (1998).
This being said, the general impression is one of decreasing financial
turbulence and increasing institutional quality.
The reason why institutional improvements are expected to lead to
lower tensions on the exchange markets is straightforward. Financial
and corporate governance, the quality of the legislative institutions
and the advancements of the liberalization process all contribute to
relieving the information asymmetries in the economy and consequently improve the quality of the investment decisions, thereby raising overall productivity and economic performance. Moreover, sound
institutions increase transparency and credibility of government and
central bank policies. All this is expected to contribute to a smoother
working of the financial markets.
But there’s a snake in the grass. We should also take into account
a possible adverse effect of institutional improvements on financial
vulnerability as they induce increased capital imports and capital
dependency. This makes the economies concerned more vulnerable to
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sudden changes in international investors’ sentiments. This raises the
difficult question of how to phase institutional reform and capital
mobility liberalization. In this respect it should be noted that since the
mid of the 1990s a number of transition countries have increasingly
benefited from capital imports, which make them more vulnerable to
sudden capital withdrawals. This concern has been voiced by a number of economists (see e.g. Buiter and Grafe (2002)). As a matter of
fact, in the examples cited above, the countries experienced rapid capital outflows (see Vanneste, Van Poeck and Veiner (2003)).
In this paper we therefore want to investigate whether formerly
planned economies with weaker institutional settings have been more
vulnerable to currency weakness than those with stronger institutions.
The susceptibility to currency turmoil is proxied by an indicator of
exchange market pressure (emp). The advantage of this measure is that
it enables comparison of countries with different exchange rate regimes.
One specific institution that has received attention in the economic
profession is the exchange rate regime under which an economy operates. A distinction can be made between intermediate exchange rate
arrangements, such as e.g. conventional fixed pegs and extreme
exchange rate systems, such as credible fixed exchange rate systems
(monetary union or currency board) and freely floating exchange rates.
It has been argued that intermediate exchange rate systems are more
vulnerable to exchange rate crises because they can never be made
fully credible (as long as the central bank cares about domestic objectives) and because the incentive of the central bank to devalue the
currency increases once economic agents expect it to happen (see
De Grauwe and Grimaldi (2002))1.
Although an extensive empirical literature on explaining or predicting the occurrence of foreign exchange crises exists (see e.g. Flood
and Marion (1998)) few studies have tested the role of the exchange
rate system and of institutions. Notable exceptions are Effenberger
(2004), Mulder, Perelli and Rocha (2002) and Ghosh and Ghosh
(2002)2. Effenberger (2004) tests a logit model with a binomial crisis
variable on 11 CEECs. Using institutional indicators in addition to
macroeconomic fundamentals he shows that the exchange rate regime,
the quality of the regulatory and supervisory setting and the degree of
liberalisation of the economy significantly influence the probability
of a currency crisis. Mulder, Perelli and Rocha (2002) explain the
probability and depth of external crises by macroeconomic, corporate,
and institutional indicators on a wider set of developed countries. Their
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results suggest that corporate balance sheet variables such as leveraged
financing and a the ratio of short term debt to working capital play an
important role in the occurrence of crises and the depth of crises. The
same holds for macroeconomic variables such as the ratio of bank and
corporate debt to exports and institutional indicators like the legal
regime of a country and shareholders’ rights. Ghosh and Ghosh (2002)
analyse 42 mainly emerging market countries. They find that overall
governance and rule of law, corporate sector governance and corporate financing structure significantly affect the vulnerability to crises.
Their findings also suggest that there exist interactions between structural vulnerabilities and macroeconomic imbalances. Weak governance
increases the sensitivity to the effects of macroeconomic and corporate sector weaknesses. All in all these studies confirm the impact of
institutions on financial crises and stress the interactions between
structural vulnerabilities and macroeconomic imbalances.
In our research we specifically focus on transition economies and
use data for 24 formerly planned economies in Central- and EasternEurope. This allows us to concentrate on transition-specific aspects,
such as e. g. banking sector reform. As our aim is to explain tensions
in the exchange market rather that currency crises we use a measure
of exchange market pressure instead of a binary crisis dummy as our
dependent variable. We explicitly test for interaction between macroeconomic and institutional variables. The different countries in the
sample have a lot in common. They all went through a difficult liberalisation process resulting in deep recession and high inflation. Further, they were subject to common external shocks, such as the Russian crisis. All this increases the probability that the differences in crisis
experience were related to the quality of their institutional setting and
the adopted exchange rate regime.
The remainder of this paper is as follows. In section II the literature on currency crises and institutions is briefly reviewed. Section III
recalls the bi-polar view on exchange rate regimes which is empirically
tested in section VI. Section IV sketches the institutional developments in the transition countries covered in the analysis. In section V
a quarterly measure of exchange market pressure is defined, computed
and documented for three subgroups of our dataset, i. e. EU members; EU candidates and potential candidates; and other countries of
the Commonwealth of Independent States. The regression analysis is
presented in section VI. Policy conclusions and prospects for further
research are discussed in the final section.
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II. THE LITERATURE ON THE THEORY OF CURRENCY
CRISES AND INSTITUTIONS
Since the collapse of the Bretton Woods system in the 1970s the world
has witnessed a huge number of currency crises (see Feldstein (2002))
and they have been a widely studied subject. In this section we briefly
summarize three currently existing classes of crises models and the
role that institutions play in these models. Weak macroeconomic fundamentals are the main cause of currency crises according to the first
generation models pioneered by Krugman (1979). Krugman’s model
considers the situation where the government pursues an overly expansionary monetary policy in a fixed exchange rate regime. The excessive expansion of domestic credit results from monetization of fiscal
deficits or from supporting a weak banking system. It leads to a fall
in the domestic interest rate, capital outflow and a loss of international
reserves. Rational speculators regard this situation as unsustainable
and believe the maintenance of a fixed peg is impossible in the long
run. They anticipate the devaluation and launch an attack long before
the international reserves are completely exhausted. According to the
first generation models a currency crisis stems from monetary or fiscal policies that are inconsistent with the fixed exchange rate regime.
Institutions have no specific contribution in this view. Since such crises
result from macroeconomic imbalances they are in principle predictable.
However, the crisis of the EMS at the beginning of the 1990s has
demonstrated that countries with relatively sound macroeconomic fundamentals can be victims of speculative attacks too (see e.g. Eichengreen, Rose and Wyplosz (1994)). The EMS crisis gave support to
second generation models which incorporate the phenomenon of selffulfilling expectations and multiple equilibria. Castrén and Takalo
(2000) add the institutional setting to the model of self-fulfilling currency crises. They argue that institutions fostering corporate governance increase the credibility of the exchange rate peg. They also show
that the impact of institutional reforms depends crucially on the extent
of the reforms, partial reforms increasing instead of reducing the vulnerability of a fixed exchange rate.
Increasing attention to institutions is characteristic for the so-called
third generation models which were developed after the outburst of
the South-East Asian crisis of 1997. Besides macroeconomic fundamentals (the inconsistency of economic policy with the fixed
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exchange rate regime) and the role of expectations, these models
stress problems in the banking sector and weak institutions in general as the main driving forces behind banking crises which spill over
into currency crises. Weak supervision of the banking sector and
implicit government guarantees, leading to moral hazard problems
and over-indebtedness abroad are crucial elements in these models.
Pitt (2001) e.g. develops a model where the costs and benefits of
a fixed exchange rate are based on the country’s ability to meet its
external obligations while maximising economic growth. He concludes that liberalisation and institutional improvement increase the
return on investment as the economy grows and thereby lower the
cost of maintaining the peg. Stressing the difference between financial institutions in Taiwan and Korea during the recent Asian crisis
Huang and Xu (2000) particularly explain the financial crisis in
Korea with the high government participation in financing and lending decisions.
III. THE BI-POLAR VIEW ON EXCHANGE RATE REGIMES
It is clear from the above overview that including the institutional setting in crisis models is a relatively new phenomenon, mostly related
to the third generation crises models. Most of the models indicate that
the sources of turbulence can be linked to one or more of the following institutional aspects: the exchange rate regime; the degree of economic liberalization, the level of corporate governance, the quality of
the financial institutions, the development of the legal regime and the
degree of corruption.
With respect to the exchange rate regime, the so-called bipolar view
argues that conventional fixed pegged exchange rate systems are considered intrinsically more vulnerable to currency crises (see Fischer
(2001)). Hence in this view countries should prefer extreme exchange
rate arrangements (such as a currency board or a freely floating
exchange rate) to intermediate exchange rate arrangements, such as an
adjustable fixed peg. Moreover flexible exchange rate regime advocates stress that this system offers greater financial stability and allows
transition countries to reform their economies more smoothly. Masson
(1999) adds that structural differences between the CEECs and the
EU-countries make adjustable pegs in the CEECs especially vulnerable to speculative attacks.
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In an adjustable pegged exchange rate regime, a central bank
always has a temptation to renege on its promise not to devalue and
hence to abandon the peg. This temptation increases with the importance that the central bank attaches to other objectives than defending the peg. This can be any economic objective that is conceivably
part of the central bank’s (or the government’s) social welfare function and whose attainment involves a trade-off with the fixed peg
(e.g. output stabilisation or employment growth). It can be shown that
the temptation to renege increases with the size of the shock to the
economy (e.g. the deepness of the recession) and the cost of defending the peg (e.g. the output loss as a result of the interest rate increase
to defend the peg). The temptation to abandon the peg decreases with
the cost of the devaluation, such as the loss of credibility of the monetary authorities after the devaluation (De Grauwe and Grimaldi
(2002)).
IV. INSTITUTIONAL DEVELOPMENT IN THE TRANSITION
COUNTRIES
In this section we discuss several institutional indicators for the transition economies we consider in this paper. For analytical purposes
the countries are divided into three groups based on their progress
towards the membership of the EU, viz. the new EU members, the EU
candidates and potential candidates3 and the other CIS countries. The
first group consists of the Czech Republic, Estonia, Hungary, Latvia,
Lithuania, Poland, the Slovak Republic and Slovenia. The countries
Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Macedonia and
Romania constitute the second group and the third group is formed by
Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, the Kyrgyz
Republic, Moldova, Russia, Tajikistan, and Ukraine.
Economic liberalisation and institutional reform have been important issues in transition countries for the last 15 years. As a proxy
to reflect these processes several institutional indexes are available,
viz.:
o
o
o
o
the exchange rate regime
the index of economic freedom
the index of rule of law
the index of corruption
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o the governance and enterprise restructuring index
o the index of banking sector reform
o the index of non-banking sector reform.
Although the theoretical models limit themselves mostly to either
fixed (pegged) or flexible systems, central banks in practice pursue a
variety of exchange rate policies. The IMF classifies exchange rate
arrangements into eight categories depending on the level of flexibility. The classification is based on de jure declarations of the central
banks and does not necessarily reflect the actual policy followed by
those central banks. Recently, however, the IMF has started to correct
its classification towards the real situation and policy of the central
banks. Our comparison with one alternative classification, viz. the one
by Reinhart-Rogoff (2004) shows a high correlation between the
de facto and the de jure classification for the transition countries.
Therefore we use the IMF classification as it provides a more complete set of data over the entire sample period.
Table 1 shows the exchange rate regimes in the transition countries
over the period 1992-2005 (end of the year observations) according to
the official IMF classification. During the last 15 years the transition
countries have followed a variety of regimes and many countries have
changed their regime several times. In the CIS countries more flexible regimes have dominated over the entire period, the reason being
that the extremely low credibility that these countries enjoy often precludes the use of fixed exchange rates. In the two other groups we
observe a mixture of fixed and flexible exchange rate regimes. Estonia and Lithuania have operated constantly under a currency board
regime and Albania and Bulgaria have also introduced this regime.
But there is also a tendency for moving to a more flexible exchange
rate regime, actually in the Czech Republic, Poland, the Slovak Republic, Bosnia & Herzegovina and Croatia. The number of countries that
operate under an intermediate system i.e. neither permanently, fixed
or flexible, is low, viz. Hungary, Latvia, Slovenia, Macedonia and
Ukraine.
The insight on the role of economic liberalization for a country’s
vulnerability to crises is not clear-cut. Economic liberalization in
transition countries has created the necessary market forces which
enabled these economies to react to changing economic conditions
in an effective way. However, as Feldstein (2002) argues, capital
account liberalization has produced much more volatile capital flows
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which can destabilize domestic financial markets and the exchange
rate.
The negative side effects of economic liberalization can however be
counterbalanced by a good corporate governance environment. Corporate governance consists of various rules and organizations that govern good behavior of corporate owners, directors and managers of
companies.
Currency crises were also often preceded by banking crises which
were closely related to financial liberalization (Kaminsky and Reinhart (1996)). Therefore sound financial institutions are expected to
play a crucial role in preventing currency crises in the transition countries.
The index of economic freedom published by the Heritage Foundation (2005) measures how countries score on a list of 50 single variables divided into 10 broad factors: trade policy, fiscal burden of government, government intervention in the economy, monetary policy,
capital flows and foreign investment, banking and finance, wages and
prices, property rights, regulation, and informal market activity. The
scale runs from 1 to 5. The higher a country’s score on a factor, the
greater the level of government intervention in the economy and the
less economic freedom there is.
A considerable increase in liberalization is noted over the last
decade in the transition countries, as shown by Figure 1 (and Appendix I). Nevertheless, there still remain significant differences between
the new EU members and other two groups considered. The highest
degree of economic freedom is found in the EU members’ group,
whereas the EU candidates and potential candidates and the CIS countries are generally characterized by a low degree of economic freedom. Estonia exhibits the overall highest degree of economic freedom. By 2007 two quite different countries will join the EU. The
degree of economic liberalization in Bulgaria is the highest within the
EU candidates and potential candidates and close Slovenia’s score.
Romania’s economic freedom is much lower and only at the CIS countries’ average level. Within the group of CIS countries, Armenia has
a relatively high degree of economic freedom, whereas in Belarus and
Tajikistan economic freedom is still very low.
To reflect the general quality of the legal system and the spread of
corruption we use two World Bank (2004) indicators, viz. the index
of rule of law and the index of control of corruption. Since 1996 the
World Bank assesses once every two years six dimensions of
317
318
3
2
3
(8)
(8)
5
3
7
8
3
8
3
8
8
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
1992
4
2
6
3
2
6
4
7
1997
7
2
6
3
2
6
4
7
7
2
6
3
2
6
7
7
1998
EU members
1996
7
2
6
3
2
6
7
7
1999
8
3
8
4
3
8
8
3
8
4
3
8
8
3
2
4
3
8
8
2
2
4
3
7
8
2
2
7
3
7
EU candidates and potential candidates
3
2
6
3
2
6
3
7
1995
8
2
2
7
3
7
7
2
6
3
2
7
7
7
2000
8
2
2
7
3
6
7
2
6
3
2
7
7
7
2001
8
2
2
7
3
6
7
2
4
3
2
7
7
7
2002
8
2
2
7
3
6
7
2
4
3
2
8
7
6
2003
2
8
2
7
3
7
7
2
4
3
2
8
7
4
2004
2
8
2
7
3
7
7
2
4
3
2
8
7
4
2005
10:36
8
3
8
4
3
8
3
2
3
3
2
5
3
7
1994
04-10-2006
8
3
8
8
8
8
3
2
3
(8)
(8)
5
3
7
1993
TABLE 1
Exchange rate regimes in the transition countries, 1992-2005
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(3)
(3)
(3)
(3)
(3)
(3)
(3)
(3)
na
(3)
(8)
(3)
(3)
(8)
(8)
(8)
(8)
(8)
(3)
(8)
8
8
(7)
7
8
8
8
8
(3)
8
8
8
7
7
8
7
8
4
8
7
8
8
4
7
8
7
8
6
8
7
8
8
7
3
7
7
8
6
8
4
8
7
7
8
7
7
8
7
7
4
8
7
7
8
8
7
8
8
7
4
8
7
7
8
8
7
8
8
7
7
8
7
7
8
7
7
8
7
8
7
8
7
6
8
7
7
8
7
7
3
8
7
6
7
7
7
8
7
7
3
8
7
6
7
7
7
8
7
7
3
8
7
6
7
7
7
8
7
7
3
04-10-2006
Note: End-year observations. Codes in parentheses refer to the periods when the newly-introduced national currencies have not yet
assumed the status as the sole legal tender. The meanings of the codes are:
Na = not available,
1 = currency union (no separate legal tender),
2 = currency board arrangements,
3 = conventionally fixed pegs (adjustable pegs, de facto pegs),
4 = horizontal bands,
5 = crawling pegs,
6 = crawling bands,
7 = managed floating without preannounced path for the exchange rate,
8 = independent floating.
Source: von Hagen and Zhou (2002), IMF Annual Report on Exchange Rate Arrangements and Exchange Restrictions.
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Commonwealth of Independent States
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FIGURE 1
Economic liberalization in transition countries, 1995-2005
Note:
The four categories of economic freedom:
o Free—countries with an average overall score of 1.99 or less;
o Mostly free—countries with an average overall score of 2.00 to 2.99;
o Mostly unfree—countries with an average overall score of 3.00 to 3.99; and
o Repressed—countries with an average overall score of 4.00 or higher.
Source: Heritage Foundation.
governance which cover the degree of democracy, formation and
implementation of policies and the respect of citizens. The index of
rule of law includes indicators such as perceptions of the incidence of
crime, the effectiveness and predictability of the judiciary, and the
enforceability of contracts. This indicator measures the success of a
society in developing an environment in which fair and predictable
rules form the basis for economic and social interactions and the extent
to which property rights are protected. Control of corruption measures
perceptions of corruption, conventionally defined as the exercise of
public power for private gain. The measures vary between –2.5 and 2.5
where the higher score is considered as the better result.
The development in governance has been quite different in
transition economies (see Figure 2 and Appendix II). Legal environment and corruption control improved in the group of new EU
members during the period covered. For the EU candidates and
potential candidates only Bulgaria, Croatia and Romania show a
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FIGURE 2
Rule of law and control of corruption in transition countries, 1996-2004
Source: World Bank - http://www.worldbank.org/wbi/governance/govdata2002/index.html.
clear improvement. But only Croatia has positive, although small,
values for both the rule of law and index of corruption. In contrast
all CIS countries stayed under “ground 0” and we observe a continuous deterioration for this group.
The development of reform in the enterprise sector, the banking
sector and the non-banking sector is taken from EBRD publications
((1996), (2005)). Corporate governance is evaluated through the governance and enterprise restructuring index which measures such
aspects as the corporate control mechanism and bankruptcy legislation.
The index of banking sector reform assesses the compliance of
supervision and competition in the transition countries’ banking sector towards international standards. The EBRD index of non-banking
sector reform reflects the level of the development of securities market rules and assesses the regulatory framework regarding non-banking
financial institutions (e.g. insurance companies).
The indexes of EBRD are given on a 1 to 4+ scale4 where 1 means
the least developed sector and 4+ denotes the level of advanced industrial economies.
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FIGURE 3
Development of enterprise reform in transition countries, 1993-2005
Source: EBRD Transition Reports
Figures 3 and 4 show the evolution of corporate governance, banking and non-banking sector reforms in the three groups of transition
countries. Enterprise and banking sector reforms started in all transition countries from a situation of an (under)developed and/or nonexistent institutional framework (see Appendix III and IV). The group
of the EU members has followed the quickest reform path of all transition economies. Today the Czech Republic, Hungary and Estonia
have banking sector standards close to the advanced economies. The
same holds for Croatia. The corporate governance indexes in the EU
(potential) candidates and CIS countries still remain on average at a
moderate level. The hard road towards a market economy can be illustrated for example by the decreased score of the enterprise sector index
of Albania in 2003. Also striking is the low level of corporate governance in EU-candidate Romania.
The data in Appendix III and IV clearly illustrate the negative
impact of 1998 Russian crisis on the institutional setting of the Russian
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FIGURE 4
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Source: EBRD Transition Reports
Development of banking and non-banking sector reforms in transition countries, 1992-2005
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323
324
Index of economic freedom
Rule of law
Index of corruption
Index of banking sector reform
Index of non-banking sector reform
Index of enterprise reform
1
Index of
economic
freedom
–∞∞0.78
1
Rule of
law
–∞∞0.69
0.94
1
Index of
corruption
–∞∞0.79
0.82
0.78
1
–∞∞0.75
0.77
0.75
0.76
1
Index of
Index of
banking sector non-banking
reform
sector reform
TABLE 2
Correlation matrix of institutional variable
–∞∞0.80
0.86
0.79
0.89
0.77
1
Index of
enterprise
reform
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enterprise sector and financial markets. The crisis caused a set-back
of the Russian transition process of almost seven years in banking sector reform.
It goes without saying that the above mentioned indexes are often
highly correlated, as countries tend to perform strongly or weakly in
many institutional standards at the same time. Table 2 shows the simple correlation coefficients between institutional variables which range
from (in absolute value) 0.69 to 0.94. As a result, in the regressions
reported in section VI not all institutional variables can be included at
the same time, since this would result in multicollinearity. Therefore
one should not be too much convinced about the contribution of one
specific institutional characteristic and regard each of them more as
an aspect of overall institutional quality.
V. EXCHANGE MARKET PRESSURE IN THE TRANSITION
COUNTRIES
In section VI we investigate in a more formal way the extent to which
foreign exchange markets in transition countries have been subject to
tensions between 1990 and 2005. To this purpose we compute a quarterly based measure of exchange market pressure (emp) for each of the
transition countries. We also define a currency crisis and compute the
proportion of crises quarters to which the transition countries have
been subject.
The notion of exchange market pressure was introduced by Girton
and Roper (1977). They started from the insight that excess demand
or supply on the foreign exchange market can result in a change in the
price of foreign exchange as well as in a change in the level of foreign reserves. The interesting feature of the concept is its equal applicability to countries with different institutional frameworks and
exchange rate regimes.
We also tried an extended measure of exchange market pressure
which includes the change in the interest rate differential, in addition
to reserve and nominal exchange rate changes (see Eichengreen et al.
(1995)). The correlation with the simple measure proved to be very
high viz. from 0.71 for Poland to 0.94 for Bulgaria. Therefore, and for
reasons of data availability we stick to the narrower concept of Girton
and Roper5. We take into account the different volatility of the components by using variance smoothing weights. The weight on the
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intervention term is the ratio of the standard error of the percentage
change of the exchange rate over the standard error of the percentage
change of reserves. Exchange market pressure is thus defined as:
emp = e˙ −
se˙
⋅ r˙
sr˙
(1)
where:
e:
rate of depreciation of domestic currency;
r:
increase in domestic international reserves;
se˙ , sr˙ : standard error of the variables respectively.
The data are derived from IMF International Financial Statistics
(see Appendix V). Changes in the domestic exchange rate are computed relative to the German mark using the fixed euro conversion
rate after 1999. We drop the possibility of intervention by foreign
authorities, which is quite a realistic assumption for the transition
countries. So only the unilateral intervention measure is used.
The general trend of emp-measure over time is shown in Figure 5.
The impact of Russian crisis in 1998 can be easily detected. We can
also see the diminishing volatility and declining tensions form the
beginning of the 21st century.
FIGURE 5
Exchange market pressure in the CEECs, 1994-2005
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Table 3 shows the statistics of the emp-measure and crisis quarters
by country and country group. A crisis quarter is defined as one in
which the emp-measure exceeds the mean value by 1.5 standard
deviation. However the general picture and conclusions are not
TABLE 3
Emp-measure in transition countries: 1990-2005
Country
Observations
Average
emp
Standard
deviation
Number
of “crisis”
quarters1
Proportion
of “crisis”
quarters1 (%)
51
55
64
49
51
64
51
56
441
44
–∞∞1.89
–∞∞0.28
1.28
–∞∞1.54
–∞∞4.49
–∞∞1.44
–∞∞1.15
–∞∞1.22
–∞∞1.30
–∞∞4.97
4.55
0.88
6.42
5.24
7.71
8.29
5.27
6.75
6.37
11.84
0
0
0
0
0
0
0
0
0
0
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
20
56
52
36
58
–∞∞0.06
4.89
–∞∞9.10
0.10
10.54
1.00
50.37
24.22
4.31
52.73
0
6
1
0
3
0.00
0.11
0.02
0.00
0.05
266
–∞∞0.61
35.93
10
3.76
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
52
28
40
36
44
47
47
48
13
48
20.78
–∞∞2.16
20.06
5.72
–∞∞1.77
4.76
11.52
16.46
2.79
25.94
150.11
7.92
37.16
12.60
13.64
13.26
20.71
53.10
8.11
73.66
5
0
3
0
0
0
1
6
0
6
0.10
0.00
0.08
0.00
0.00
0.00
0.02
0.13
0.00
0.13
Commonwealth
of Independent
States
403
7.99
64.12
21
5.21
1110
2.24
42.83
31
2.79
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
EU members
Albania
Bosnia &
Herzegovina
Bulgaria
Croatia
Macedonia
Romania
EU candidates
and potential
candidates
All countries
1
A “crisis” quarter occurs when the time series exceeds the sample mean by 1.5 standard
deviation
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significantly altered by using weaker (1 standard deviation) or stronger
(2 standard deviations) definitions of currency crises.
The emp-measure in the eight EU member countries has been low
and not much fluctuating. The average emp-measure amounts to –1.30
and standard deviation to 6.37. The EU-candidates and potential candidates have higher average exchange market pressure (–∞∞0.61) and
the emp-measure varies considerably over time.
The countries belonging to the Commonwealth of Independent
States (CIS) form the most volatile region, the average emp-measure
equals 7.99 and shows a high standard deviation of 64.12. The incidence of crisis quarters is also much higher in the CIS countries as
compared to the other two sets of countries.
VI. REGRESSION ANALYSIS
In this section we test the bi-polar view on exchange rate regimes
and the role of institutions in explaining exchange market pressure in
transition economies while controlling for economic fundamentals.
The exchange rate regime dummy takes the value of 1 for the extreme
and 0 for the intermediate regimes6. Hence the expected coefficient of
this dummy is negative.
We have to keep in mind that evaluating the role of institutions in
currency crises involves several problems. Firstly, the quality of institutions is hard to measure and therefore offers ground for debate. Secondly, the available institutional indexes do not always coincide completely with the theoretical concepts that we want to measure, e.g. the
index of economic freedom measures a wider set of factors than only
economic liberalisation. Lastly, the frequency of these data is lower
than for the financial and macro-economic data.
As for the choice of the fundamentals we based ourselves on the
findings of the theoretical and empirical literature (see Flood and
Marion (1998), for an overview). The following explanatory variables
were used in our regressions: current account balance (as % of GDP),
domestic credit growth rate, inflation differential (with Germany) and
the growth rate of government borrowing (see data definitions and
sources in Appendix V). We did not include international reserves
or the money supply-reserves ratio since reserves also enter in the
computation of the emp-measure. The panel for the 24 transition
economies has quarterly data over the period 1990 (Q1) – 2005(Q4).
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Our regressions are presented in Table 4 and Table 5. These results
confirm to a large extent the importance of the economic fundamentals: the current account, domestic credit growth and inflation differential significantly contribute and with expected sign in explaining
exchange market pressure. The coefficient on the growth rate of government borrowing has the expected sign, but is statistically not significantly different from zero.
We also included a dummy for the Russian crisis representing a
contagion effect. This dummy takes the value 1 for 1998 Q3 and Q4
for all countries in the sample except for Russia. As expected the Russian crisis affected the other transition countries considerably, the coefficient being positive and significant in all regressions.
The exchange rate regime dummy enters with the expected sign and
is statistically significant at 10%-level. The bi-polar view of exchange
rate regimes is thus confirmed in this sample of 24 transition countries.
As for the legal system variables we find that lower corruption
decreases the vulnerability to currency crises. The coefficient on the
index of corruption has the expected sign but is insignificant. This
conclusion is in line with Effenberger (2004) who also does not find
a relation between the occurrence of currency crises and the legal system.
Efficient banking regulatory and supervisory systems reduce
exchange market pressure in the transition countries, as shown by the
significance of the index of banking sector reform. Surprisingly the
index of enterprise reform turns out to be insignificant, whereas Ghosh
and Ghosh (2002) and Mulder, Perrelli and Rocha (2002) find banking regulation, supervision and corporate governance to be significant
in predicting financial crises. On this point our result is in line with
Effenberger’s (2004) finding and can be explained by the fact that in
our sample of countries capital market financing in most cases plays
only a marginal role.
The second column of Table 4 reports our estimation results for a
more refined version of the bi-polar view. The hypothesis tested is that
extreme exchange rate arrangements lead to lower exchange market
pressure, where a currency board even outperforms a freely floating
exchange rate regime. This is tested by including an additional dummy
for a currency board. As the currency board dummy turns out to be
insignificant we cannot discriminate between irrevocably fixed and
floating exchange rate regimes as to their predicted impact on emp.
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TABLE 4
Econometric estimation of the bi-polar view
on exchange market pressure in transition countries
Regression No.
1
2
Explanatory variables
Constant
Current account
Domestic credit growth
Inflation differential
Government borrowing
Dummy for Russian
crisis contagion
GDP per capita
CIS countries dummy
Extreme exchange rate
arrangement dummy
Currency board dummy
Average index of corruption
Index of banking sector reform
Index of non-banking sector reform
Index of enterprise reform
6.4271
(0.6577)
–∞∞0.3745**
(–∞∞2.8436)
0.2932***
(9.4232)
0.3767***
(5.5247)
0.0012
(0.9480)
17.2841***
(3.5508)
–∞∞0.0324
(–∞∞0.0112)
2.6667
(0.7191)
–∞∞3.9943*
(–∞∞1.7484)
–∞∞4.2170
(–∞∞1.0462)
–∞∞8.8515***
(–∞∞2.7098)
3.4527
(1.2412)
5.5784
(1.5198)
10.7206
(1.0353)
–∞∞0.3815***
(–∞∞2.8950)
0.2943***
(9.4585)
0.3820***
(5.5936)
0.0011
(0.9206)
17.0073***
(3.4914)
1.4708
(0.4703)
2.9591
(0.7966)
–∞∞5.2751**
(–∞∞2.1074)
4.6425
(1.2500)
–∞∞5.5798
(–∞∞1.3367)
–∞∞9.6359***
(–∞∞2.8978)
3.4539
(1.2420)
5.5778
(1.5201)
Statistics
R2
R2ad
F
0.241
0.231
23.28
0.243
0.232
21.63
Notes: 1. Dataset consists of 937 quarterly observations for 24 countries over the 1st quarter of 1990 to the 4th quarter of 2005.
2. t-statistics are given in parentheses. *, ** and *** statistically significant at
10%, 5% and 1% level respectively.
3. Institutional indexes – higher value implies to better institutions
4. Exchange rate arrangement dummy takes the value 1 for regimes 2, 7 and 8;
the value equals 0 for all other exchange rate regimes.
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As an alternative to the specification in Table 4 we also tested
for interactions between the institutional variables – including the
exchange rate system – and the economic fundamentals. This specification takes the following general form:
(
)
emp = a0 + ∑ a j1 + a j 2 Insti F j
with
Insti: dummy of exchange rate regime or institutional variable i,
Fj: economic fundamental variable j.
The interpretation of the exchange rate dummy is same as in the
regressions reported in Table 4. For the other institutional variables
we define the overall sample average as the threshold value. If the
index of an institutional variable exceeds the mean value the corresponding dummy variable equals one, otherwise zero.
The results are shown in Table 5 and are in general quite supporting to the hypothesis that a higher quality of institutions lessens the
adverse effect of economic fundamentals. Low corruption, efficient
banking regulatory and supervisory systems and profound economic
liberalization significantly reduce the impact on emp of domestic
credit growth and inflation differential. The coefficient on the variable (aj2) has a sign that is opposite to the coefficient aj1 but is smaller
– roughly half – in absolute value.
The exchange rate dummy has only a significant interaction with
government borrowing growth. Extreme exchange rate regimes
entirely dampen the impact of increasing government borrowing on
emp. Interactions of extreme exchange rate regimes with other economic fundamentals are insignificant.
It is further shown that better legal environment significantly largely
mitigates the effect of the Russian crisis contagion dummy on
exchange market pressure.
VII. CONCLUSIONS
This research focussed on exchange market pressure in 24 Central and
East European transition economies between 1990 and 2005. Although
an extensive literature exists on explaining the occurrence of foreign
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TABLE 5
Interaction of institutions and economic fundamentals on exchange
Exchange rate
arrangement
dummy
Regression No.
Constant
1
–∞∞4.1944**
Average
index of
corruption
2
3
4
(–∞∞4.1566)
(–∞∞2.8864)
–∞∞7.6139***
(–∞∞4.1633)
Current account –∞∞0.2862
(–∞∞1.0039)
–∞∞0.2182
(–∞∞1.4740)
–∞∞0.1637
(–∞∞1.0805)
–∞∞0.2436
(–∞∞1.6592)
–∞∞0.1855
(–∞∞1.2369)
Insti
0.0008
(0.0027)
–∞∞0.0950
(–∞∞0.4040)
–∞∞0.2839
(–∞∞1.2360)
–∞∞0.0490
(–∞∞0.1912)
–∞∞0.1735
(–∞∞0.7391)
Domestic credit
growth
0.2717***
(4.1850)
0.4442***
(9.2607)
0.4191***
(10.3684)
0.3616***
(10.4094)
0.3861***
(10.5515)
Insti
0.0101
(0.1407)
–∞∞0.2284***
(–∞∞3.8623)
–∞∞0.2566***
(–∞∞4.4412)
–∞∞0.2628***
(–∞∞3.6822)
–∞∞0.2529***
(–∞∞4.2290)
Inflation
differential
0.2300
(1.1079)
0.6714***
(6.5986)
0.6837***
(6.9457)
0.3008***
(4.3233)
0.6455***
(6.7124)
Insti
0.1481
(0.6825)
–∞∞0.4673***
(–∞∞3.6838)
–∞∞0.4328***
(–∞∞3.3425)
0.1583
(0.2698)
–∞∞0.3421***
(–∞∞2.6101)
Government
borrowing
0.2049**
(2.0897)
0.0012
(0.6280)
0.0012
(0.6204)
0.0010
(0.8224)
0.0013
(0.6825)
–∞∞0.2040**
(–∞∞2.0810)
–∞∞0.0008
(–∞∞0.3303)
–∞∞0.0008
(–∞∞0.3258)
–∞∞0.0037
(–∞∞0.0349)
–∞∞0.0010
(–∞∞0.4007)
22.6275***
(2.8535)
28.2374***
(4.2076)
27.4833***
(3.5412)
–∞∞5.3661***
5
(–∞∞4.1639)
Dummy for
Russian crisis
contagion
–∞∞7.4973***
Index of
enterprise
reform
(–∞∞2.3101)
Insti
–∞∞7.5206***
Index of
Index of
banking
non-banking
sector reform sector reform
28.3382***
(4.3391)
30.0754***
(4.4552)
Insti
–∞∞7.3156
(–∞∞0.7310)
–∞∞22.3539**
(–∞∞2.3739)
–∞∞16.9007*
(–∞∞1.7304)
–∞∞23.4573**
(–∞∞2.4164)
–∞∞24.0213**
(–∞∞2.5348)
GDP per capita
–∞∞4.4352***
(–∞∞2.6802)
–∞∞1.1575
(–∞∞0.6752)
–∞∞1.0239
(–∞∞0.5973)
–∞∞1.4107
(–∞∞0.7593)
–∞∞0.4689
(–∞∞0.2649)
0.277
0.270
31.1
0.281
0.272
31.1
0.246
0.236
26.0
0.273
0.264
30.0
R2
R2ad
F
Notes:
0.228
0.218
23.9
1. Dataset consists of 937 quarterly observations for 24 countries over the
1st quarter of 1990 to the 4th quarter of 2005.
2. t-statistics are given in parentheses.
*, ** and *** statistically significant at 10%, 5% and 1% level respectively.
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exchange crises few studies have tested the role of the institutional setting. Using transition specific indicators such as the indexes of enterprise, banking sector and non-banking sector reforms we investigate
whether transition countries with intermediate exchange rate regimes
and weaker institutional settings have been more vulnerable to
exchange market tensions.
Economic liberalisation and institutional reform have considerably
increased in the period covered. Nevertheless there still remain significant differences between the three groups of countries considered,
viz. the new EU members, the EU candidates and potential candidates
and the CIS countries.
In the regression analyses we used the Girton and Roper definition
of exchange market pressure (emp). The emp-measure in the group of
EU members and EU (potential) candidates has been low and not
much fluctuating. The CIS countries proved to be the most volatile
region with high average emp-measures.
The regression results confirm the bi-polar view on exchange market regimes. The incidence of economic fundamentals (current
account, domestic credit growth and the inflation differential) for
exchange market pressure is as expected. The contribution of sound
institutions for reducing exchange market turbulence is clearly demonstrated. Low corruption, efficient banking regulatory and supervisory
systems and profound economic liberalization significantly reduce
exchange market pressure in the transition countries. And, as expected,
the Russian crisis heavily affected the other transition countries.
The results of the interaction-specification are in general quite supporting to the hypothesis that a higher quality of institutions lessens
the effect of economic fundamentals on exchange market pressure.
This is for example the case for transition countries having reformed
their financial sector towards international standards. Their institutional improvement is rewarded through a milder effect of domestic
credit growth and inflation differential on exchange market pressure.
Another example is the attenuating effect of a better legal environment offsetting the Russian crisis contagion.
Clearly institutional development in transition economies is the issue
at stake when exchange market pressure is studied.
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NOTES
1.
2.
3.
4.
5.
6.
In developing countries financial instability seem to go hand in hand with flexible
exchange rates, though. The reason may be that the extremely low credibility precludes the use of fixed exchange rates.
The effect of political institutions like government turnover and democracy is not considered in our study. Lebland and Satyanath (2004) use a logit estimator to determine
the factors behind developing countries’ currency crises. They conclude that turnover
in government and devided democratic government are robustly associated with crises
in addition to economic fundamentals. Shortland (2004) tests the probability to devaluation with a panel logit analysis in 98 least developed countries. She concludes that
economic imbalances have little explanatory power in maintaining the exchange rate,
while the low turnover of the governer of the central bank and the strength of the government lessen the probability to devalue.
Also Serbia and Montenegro is considered to be a potential candidate for the EU but
due to the data deficiencies we exclude the country from our analysis.
The “+” is expressed numerically as 0.3.
In the spirit of the emp-measure one might also include changes in capital controls.
The empirical research testing the effectiveness of capital controls often relies on data
from the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions.
However, this source does not measure the intensity of controls and only reports on
capital outflows. In the case of transition countries it is especially hard to connect
increased capital controls with increased speculative pressure on their currencies. The
eight EU joiners have achieved almost full alignment with the aquis’ requirements on
free capital movement. The fall of iron curtain has attracted foreign capital also in the
other transition economies. Hence during the last decade there has been almost a constant trend of liberalisation of capital flows. For these various reasons we do not include
capital controls in our emp-measure calculations.
Dummy takes the value of 1 for the exchange rate arrangements 1, 2, 6, 7 and 8 and
the value of 0 for the exchange rate arrangement 3, 4, and 5 (see Table 1).
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335
336
2.29
2.46
1.54
2.91
3.05
3.09
3.18
3.45
2.75
1999
2.43
2.43
1.40
2.84
2.98
2.91
3.31
3.15
2.68
2.14
2.29
1.51
2.74
2.90
2.83
3.38
3.05
2.60
EU members
1998
2.20
2.19
1.40
2.69
2.84
2.84
3.18
3.20
2.57
2000
3.58
3.50
3.53
3.40
3.50
3.48
3.56
3.60
3.55
3.30
3.49
3.53
3.56
3.59
3.21
3.72
3.53
4.61
3.60
3.63
3.20
3.67
3.51
4.61
3.49
3.55
3.20
3.64
3.78
4.40
3.35
3.49
EU candidates and potential candidates
2.33
2.44
1.50
3.24
3.50
3.24
3.18
3.74
2.89
1997
3.59
3.55
3.48
4.04
3.28
3.39
2.10
1.89
1.29
2.49
2.53
2.64
2.85
3.01
2.35
2001
3.24
3.89
3.28
3.29
3.35
3.78
3.47
2.29
1.73
1.39
2.49
2.35
2.60
2.76
3.25
2.36
2002
3.28
3.49
3.26
3.06
3.23
3.71
3.34
2.35
1.68
1.44
2.30
2.21
2.83
2.71
2.86
2.30
2003
3.10
3.30
2.98
3.11
3.04
3.66
3.20
2.39
1.76
1.34
2.36
2.19
2.81
2.44
2.75
2.26
2004
2.93
3.16
2.74
2.95
3.00
3.58
3.06
2.31
1.65
2.40
2.31
2.18
2.59
2.43
2.64
2.31
2005
10:36
2.53
3.46
2.88
2.38
2.40
1.51
1996
04-10-2006
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
1995
The index of economic freedom, 1995-2005.
APPENDIX I
Economic liberalization
9213-06_TEM_06/3_07_VanPoeck
Pagina 336
3.50
3.65
3.75
3.82
4.10
3.55
4.05
3.85
3.70
3.69
4.78
3.45
3.94
3.83
3.89
3.65
3.83
3.50
4.58
3.95
3.88
3.50
4.35
4.20
3.78
2.99
4.00
3.48
3.54
4.30
3.83
3.80
3.50
4.29
4.19
3.85
4.14
2.40
3.49
3.60
4.15
3.75
3.74
3.21
4.33
4.18
3.80
3.90
3.78
3.35
3.75
4.21
3.75
3.83
3.03
3.93
4.10
3.68
2.85
3.80
3.75
3.79
4.11
3.88
3.69
2.78
3.58
4.16
3.48
3.70
3.65
3.30
3.74
4.09
3.84
3.63
2.59
3.50
4.19
3.40
3.55
3.41
3.13
3.54
4.10
3.59
3.50
2.63
3.39
4.04
3.19
3.70
2.70
3.09
3.46
4.15
3.49
3.38
2.58
3.43
4.04
3.29
3.61
3.34
3.11
3.61
4.05
3.16
3.42
04-10-2006
Note: The index takes scores from 1.00 to 5.00 where lower score means freer economy.
Source: Heritage Foundation.
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
Commonwealth of Independent States
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337
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Pagina 338
APPENDIX II
Rule of Law and Corruption
Index of Rule of Law, 1996-2004
1996
1998
2000
2002
2004
EU members and candidates
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
0.61
0.33
0.62
0.18
–∞∞0.14
0.44
0.11
0.49
0.33
0.62
0.54
0.78
0.08
0.19
0.57
0.13
0.91
0.48
0.6
0.73
0.85
0.25
0.27
0.64
0.32
0.89
0.57
0.74
0.8
0.9
0.46
0.48
0.65
0.4
1.09
0.69
0.69
0.91
0.85
0.48
0.6
0.51
0.49
0.93
0.68
–∞∞0.92
–∞∞0.88
0.05
0.11
–∞∞0.41
–∞∞0.12
–∞∞0.36
–∞∞0.8
–∞∞0.76
0.05
0.07
–∞∞0.44
–∞∞0.18
–∞∞0.34
–∞∞0.44
–∞∞0.79
–∞∞1.12
–∞∞1.17
–∞∞0.9
–∞∞0.83
–∞∞0.49
–∞∞0.78
–∞∞1.27
–∞∞0.79
–∞∞0.86
–∞∞0.58
–∞∞0.85
–∞∞1.31
–∞∞0.87
–∞∞0.98
–∞∞1.04
–∞∞0.65
–∞∞0.7
–∞∞1.18
–∞∞0.83
–∞∞0.90
EU candidates and potential candidates
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
–∞∞0.3
–∞∞0.18
–∞∞0.09
–∞∞0.5
–∞∞0.53
–∞∞0.27
–∞∞0.31
–∞∞0.93
–∞∞1.04
–∞∞0.22
–∞∞0.04
–∞∞0.33
–∞∞0.25
–∞∞0.47
–∞∞0.75
–∞∞0.83
–∞∞0.11
0.15
–∞∞0.3
–∞∞0.21
–∞∞0.34
Commonwealth of Independent States
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
Note:
–∞∞0.44
–∞∞0.81
–∞∞0.96
–∞∞0.8
–∞∞0.69
–∞∞0.65
–∞∞0.19
–∞∞0.8
–∞∞1.34
–∞∞0.64
–∞∞0.73
–∞∞0.35
–∞∞0.81
–∞∞1.08
–∞∞0.73
–∞∞0.8
–∞∞0.67
–∞∞0.13
–∞∞0.78
–∞∞1.42
–∞∞0.76
–∞∞0.75
–∞∞0.51
–∞∞0.98
–∞∞0.99
–∞∞0.56
–∞∞0.76
–∞∞0.9
–∞∞0.54
–∞∞0.86
–∞∞1.25
–∞∞0.71
–∞∞0.81
The scores lie between -2.5 and 2.5, with higher scores corresponding
to better outcomes.
Source: World Bank, http://www.worldbank.org/wbi/governance/govdata2002/
index.html.
338
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Pagina 339
Index of Corruption, 1996-2004
1996
1998
2000
2002
2004
0.55
0.05
0.59
–∞∞0.52
–∞∞0.12
0.38
0.39
0.98
0.29
0.35
0.49
0.69
–∞∞0.1
0.07
0.49
–∞∞0.08
0.83
0.34
0.38
0.76
0.76
0.01
0.27
0.47
0.25
1.08
0.50
0.38
0.66
0.6
0.09
0.25
0.39
0.28
0.89
0.44
0.3
0.82
0.65
0.23
0.36
0.16
0.39
0.97
0.49
–∞∞0.92
–∞∞0.35
–∞∞0.5
–∞∞0.33
–∞∞0.3
–∞∞0.38
–∞∞0.46
–∞∞0.63
–∞∞0.5
–∞∞0.15
0.02
–∞∞0.48
–∞∞0.48
–∞∞0.37
–∞∞0.85
–∞∞0.6
–∞∞0.17
0.23
–∞∞0.73
–∞∞0.34
–∞∞0.41
–∞∞0.72
–∞∞0.54
–∞∞0.04
0.08
–∞∞0.52
–∞∞0.25
–∞∞0.33
–∞∞0.71
–∞∞1.01
–∞∞0.6
–∞∞0.64
–∞∞0.86
–∞∞0.69
–∞∞0.51
–∞∞0.69
–∞∞1.12
–∞∞0.89
–∞∞0.77
–∞∞0.76
–∞∞1.13
–∞∞0.07
–∞∞0.73
–∞∞0.87
–∞∞0.86
–∞∞0.87
–∞∞1.05
–∞∞1.15
–∞∞0.98
–∞∞0.85
–∞∞0.72
–∞∞1.07
–∞∞0.78
–∞∞1.03
–∞∞1.05
–∞∞0.84
–∞∞0.89
–∞∞0.9
–∞∞1.07
–∞∞0.96
–∞∞0.93
–∞∞0.53
–∞∞1.04
–∞∞0.91
–∞∞0.91
–∞∞1.1
–∞∞0.92
–∞∞0.86
–∞∞0.72
–∞∞1.11
–∞∞0.89
–∞∞0.90
EU members and candidates
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
EU candidates and potential candidates
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
0.05
na
–∞∞0.62
–∞∞0.45
–∞∞0.93
–∞∞0.17
–∞∞0.42
Commonwealth of Independent States
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
–∞∞0.6
–∞∞0.9
–∞∞0.86
–∞∞0.98
–∞∞0.79
–∞∞0.73
–∞∞0.19
–∞∞0.69
–∞∞1.53
–∞∞0.69
–∞∞0.80
Note:
The scores lie between -2.5 and 2.5, with higher scores corresponding
to better outcomes.
Source: World Bank, http://www.worldbank.org/wbi/governance/govdata2002/
index.html.
339
340
3
3
3
2
2
3
3
2
2.63
1
1
1
1
1
2
1.17
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
1993
3
3
3
3
3
3
3
2.7
2.96
1996
1998
3
3
3
2.7
2.7
3
2.7
2.7
2.85
3
3
3.3
2.7
2.7
3
2.7
2.7
2.89
EU members
1997
3
3
3.3
2.7
2.7
3
3
2.7
2.93
1999
3.3
3
3.3
2.7
2.7
3
3
2.7
2.96
2000
2
1
2
2
2
2
1.83
2
1
2
2.7
2
2
1.95
2
1
2.3
2.7
2
2
2.00
2
1.7
2.3
2.7
2
2
2.12
2
1.7
2.3
2.7
2
2
2.12
2
1.7
2.3
2.7
2.3
2
2.17
2.3
1.7
2.3
2.7
2.3
2
2.22
3.3
3.3
3.3
2.7
2.7
3.3
3
2.7
3.04
2001
3
1.7
2.3
2.7
2.3
2
2.33
3.3
3.3
3.3
2.7
3
3.3
3.3
3
3.15
2002
2
2
2.7
2.7
2.3
2
2.28
3.3
3.3
3.3
3
3
3.3
3.3
3
3.19
2003
2
2
2.7
3
2.3
2
2.33
3.3
3.3
3.3
3
3
3.3
3.3
3
3.19
2004
2
2
2.7
3
2.3
2.3
2.38
3.3
3.7
3.7
3
3
3.7
3.7
3
3.39
2005
10:36
EU candidates and potential candidates
3
3
3
2
2
3
3
2.7
2.71
1995
04-10-2006
2
1
2
2
2
2
1.83
3
3
3
2
2
3
3
2.7
2.71
1994
Enterprise reform index, 1991-2005
APPENDIX III
Corporate Governance
9213-06_TEM_06/3_07_VanPoeck
Pagina 340
1
1
1
1
1
1
1
1
1
1
1.00
1
1
1
1
1
2
2
1.7
1
1
1.27
2
1.7
1.7
2
1
2
2
2
1
2
1.74
2
1.7
1.7
2
2
2
2
2
1
2
1.84
2
1.7
1
2
2
2
2
2
1
2
1.77
2
1.7
1
2
2
2
2
2
1.7
2
1.84
2
1.7
1
2
2
2
2
1.7
1.7
2
1.81
2
2
1
2
2
2
2
2
1.7
2
1.87
2
2
1
2
2
2
2
2.3
1.7
2
1.90
2.3
2
1
2
2
2
2
2.3
1.7
2
1.93
2.3
2.3
1
2
2
2
1.7
2.3
1.7
2
1.93
2.3
2.3
1
2
2
2
1.7
2.3
1.7
2
1.93
2.3
2.3
1
2.3
2
2
2
2.3
1.7
2
1.99
04-10-2006
Note: 1 – soft budget constraints (lax credit and subsidy policies weakening financial discipline at the enterprise level), few other
reforms to promote corporate governance;
2 – moderately tight credit and subsidy policy but weak enforcement of bankruptcy legislation and little action taken to
strengthen competition and corporate governance;
3 – significant and sustained actions to harden budget constraints to promote corporate governance effectively (eg privatisation combined with tight credit and subsidy policies and/or enforcement of bankruptcy legislation);
4 – substantial improvement in corporate governance, for example, an account of an active corporate control market, significant new investment at the enterprise level;
4+ – standards and performance typical to advanced industrial economies, effective corporate control exercised through domestic financial institutions and markets, fostering market-driven restructuring.
Source: EBRD Transition Reports.
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
Commonwealth of Independent States
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10:36
Pagina 341
341
342
3
3
3
2
2
3
2.7
3
2.71
1.3
1
2
2
1.3
1
1.43
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
1993
3
3
3
3
3
3
2.7
3
2.96
1996
1998
3
3.3
4
3
3
3
2.7
3
3.13
3
3.3
4
2.7
3
3.3
2.7
3
3.13
EU members
1997
3.3
3.7
4
3
3
3.3
2.7
3.3
3.29
1999
3.3
3.7
4
3
3
3.3
3
3.3
3.33
2000
2
1
2
2.7
3
3
2.28
2
1
2
2.7
3
3
2.28
2
1
2.7
2.7
3
2.7
2.35
2
2.3
2.7
2.7
2.7
2.7
2.52
2
2.3
2.7
3
2.7
2.7
2.57
2.3
2.3
3
3.3
2.7
2.7
2.72
2.3
2.3
3
3.3
2.7
2.7
2.72
3.7
3.7
4
3.3
3
3.3
3.3
3.3
3.45
2001
2.3
2.3
3.3
3.7
2.7
2.7
2.83
3.7
3.7
4
3.7
3
3.3
3.3
3.3
3.50
2002
2.3
2.3
3.3
3.7
2.7
2.7
2.83
3.7
3.7
4
3.7
3.3
3.3
3.3
3.3
3.54
2003
2.7
2.7
3.7
4
2.7
3
3.13
3.7
4
4
3.7
3.3
3.3
3.7
3.3
3.63
2004
2.7
2.7
3.7
4
2.7
3
3.13
4
4
4
3.7
3.7
3.7
3.7
3.3
3.76
2005
10:36
EU candidates and potential candidates
3
3
3
3
3
3
2.7
3
2.96
1995
04-10-2006
2
1
2
2.7
2
2
1.95
3
3
3
3
2
3
2.7
3
2.84
1994
Index of banking sector reform, 1991-2005
APPENDIX IV
Financial Institutions
9213-06_TEM_06/3_07_VanPoeck
Pagina 342
1
1
1
1
1
1
2
1
1
1
1.1
1
1
1
1
1
2
2
2
1
1
1.3
2
2
2
2
2
2
2
2
1
2
1.9
2
2
1
2
2
2
2
2
1
2
1.8
2.3
2
1
2.3
2.3
2.7
2
2.3
1
2
1.99
2.3
2
1
2.3
2.3
2.7
2.3
2
1
2
1.99
2.3
2
1
2.3
2.3
2.3
2.3
1.7
1
2
1.92
2.3
2
1
2.3
2.3
2
2.3
1.7
1
2
1.89
2.3
2.3
1
2.3
2.7
2
2.3
1.7
1
2
1.96
2.3
2.3
1.7
2.3
2.7
2
2.3
2
1.7
2.3
2.16
2.3
2.3
1.7
2.3
3
2.3
2.3
2
1.7
2.3
2.22
2.3
2.3
1.7
2.7
3
2.3
2.7
2
2
2.3
2.33
2.7
2.3
1.7
2.7
3
2.3
2.7
2.3
2
2.7
2.44
04-10-2006
Note: 1 – little progress beyond establishment of a two-tier system;
2 – significant liberalisation of interest rates and credit allocation, limited use of direct credit and interest rate ceilings;
3 – substantial progress in establishment of bank solvency and a framework for prudential supervision and regulation, full interest rate liberalisation with little preferential access to cheap refinancing, significant lending to private enterprises and significant presence of private banks;
4 – significant movement of banking laws and regulations towards BIS standards, well functioning banking competition and
effective prudential supervision, significant term lending to private enterprises, substantial financial deepening;
4+ – standards and performance norms of advanced industrial economies, full convergence of banking laws and regulations with
BIS standards, provision of full set of competitive banking services.
Source: EBRD Transition Report.
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
Commonwealth of Independent States
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10:36
Pagina 343
343
344
2
1.7
2
1
1.7
2
2
2
1.80
1
1
1
1
1
1
1
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Average
Albania
Bosnia & Herzegovina
Bulgaria
Croatia
Macedonia
Romania
Average
1993
1997
1998
1999
2.7
1.7
3
2
2
3
2.7
2.7
2.48
2.7
2
3.3
2.3
2.3
3.3
2.3
2.7
2.61
2.7
2
3.3
2.3
2.3
3.3
2.3
2.7
2.61
3
3
3.3
2.3
2.7
3.3
2.3
2.7
2.83
EU members and candidates
1996
3
3
3.7
2.3
3
3.7
2.3
2.7
2.96
2000
1
1
2
2
1
2
1.4
1.7
1
2
2
1
2
1.54
1.7
1
2
2.3
1
2
1.6
1.7
1
2
2.3
1.7
2
1.74
1.7
1
2
2.3
1.7
2
1.74
1.7
1
2
2.3
1.7
2
1.74
1.7
1
2
2.3
1.7
2
1.74
3
3
3.7
2.3
3
3.7
2.3
2.7
2.96
2001
1.7
1.7
2.3
2.7
1.7
2
2.02
3
3.3
3.7
3
3
3.7
2.3
2.7
3.09
2002
1.7
1.7
2.3
2.7
1.7
2
2.02
3
3.3
3.7
3
3
3.7
2.7
2.7
3.14
2003
1.7
1.7
2.3
2.7
2
2
2.08
3.3
3.3
3.7
3
3
3.7
2.7
2.7
3.18
2004
1.7
1.7
2.3
2.7
2
2
2.08
3.7
3.3
4
3
3
3.7
2.7
2.7
3.26
2005
10:36
EU candidates and potential candidates
2.7
1.7
3
2
2
3
2.7
2.7
2.48
1995
04-10-2006
1
1
1
2
1
2
1.2
2.7
1.7
2
2
2
2
2.7
2.7
2.23
1994
Index of non-banking sector reform, 1990-2005
9213-06_TEM_06/3_07_VanPoeck
Pagina 344
1
1
2
1
1
1
1
1.7
1
1.7
1.24
1
1
2
1
1.7
1
2
1.7
1
1.7
1.41
1
1
2
1
1.7
1.7
2
2
1
2
1.54
1
1
2
1
1.7
2
2
3
1
2
1.67
1
1
2
1
1.7
2
2
3
1
2
1.67
2
1.7
2
1
2
2
2
1.7
1
2
1.74
2
1.7
2
1
2
2
2
1.7
1
2
1.74
2
1.7
2
1.7
2.3
2
2
1.7
1
2
1.84
2
1.7
2
1.7
2.3
2
2
1.7
1
2
1.84
2
1.7
2
1.7
2.3
2
2
2.3
1
2
1.90
2
1.7
2
1.7
2.3
2
2
2.7
1
2
1.94
2
1.7
2
1.7
2.3
2
2
2.7
1
2.3
1.97
2
1.7
2
1.7
2.3
2
2
2.7
1
2.3
1.97
04-10-2006
Note: 1 – little progress;
2 – formation of securities exchanges, market-makers and brokers, some trading in government paper and/or securities, rudimentary legal and regulatory framework for the issuance and trading of securities;
3 – substantial issuance of securities by private enterprises, establishment of independent share registries, secure clearance and
settlement procedures, and some protection of minority shareholders, emergence of non-bank financial institutions (eg
investment funds, private insurance and pension funds, leasing companies) and associated regulatory framework;
4 – securities laws and regulations approaching IOSCO standards, substantial market liquidity and capitalisation, well-functioning non-bank financial institutions and effective regulation;
4+ – standards and performance norms of advanced industrial economies: full convergence of securities laws and regulations
with IOSCO standards, fully developed non-bank intermediation.
Source: EBRD Transition Report.
Armenia
Azerbaijan
Belarus
Georgia
Kazakhstan
Kyrgyz Republic
Moldova
Russia
Tajikistan
Ukraine
Average
Commonwealth of Independent States
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10:36
Pagina 345
345
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10:36
Pagina 346
APPENDIX V
Data sources
e –
Rate of depreciation of domestic currency. Defined as the percentage
change of exchange rate vis-à-vis Deutsche mark. Calculated on the basis
of IMF International Financial Statistics line ae.
r –
Proportional change in domestic international reserves. Defined as the
change in the level of reserves divided by money base of previous period
– IMF International Statistics financing of the balance of payments (line
79dad), for Poland the change in net foreign assets (line 11-line16c) was
used; the whole was deflated by inherited money base (IFS line 14).
CA – Current account (as % of GDP) – IMF International Financial statistics
line 78ALD and line 99b.
DC – Domestic credit growth rate – percentage change compared to previous
period. Calculations based IMF International Financial statistics line 32
(domestic credit).
Real depreciation rate – defined as q = e – p + p*, where p and p* are domestic and German inflation rates respectively. The time series are lagged for
1 period. IMF International Financial statistics line 64 ‘consumer price index’ and
line ae ‘bilateral dollar rate’.
Inflation differential (with Germany) – IMF International Financial statistics line
64 consumer price index.
Growth rate of government borrowing – percentage change compared to previous period. IMF International Financial statistics lines 12a and 22a (claims on
central government).
D–
346
Exchange rate dummy – dummy variable takes the value of 1 for the
exchange rate arrangements 1, 2, 6, 7 and 8 (see Table 1) and the value of
0 for the exchange rate arrangement 3, 4, and 5.