Europeanization, EU Conditionality and Governance Quality: Empirical Evidence on Central and Eastern European Countries

Abstract

A large body of work within the Europeanization and conditionality literature has examined EU’s effect on governance quality in Central and Eastern European countries (CEECs). This article aims to contribute to existing work by addressing two questions. First, was EU’s accession conditionality conducive to better governance in CEECs or was it designed to pick up already committed reformers? Secondly, during which period was the EU more influential on governance quality in CEECs: accession or membership? To address these questions, we propose a simple model of moral hazard and adverse selection; and draw on survey-based governance quality data to test its predictions. We report that the EU has offered candidate status to countries that already had better governance quality relative to their peers before 1997. Nonetheless, EU conditionality also had some positive effects on CEEC governance during the accession period, but this effect tended to disappear during the membership period. On the basis of these findings, we argue that EU’s impact on governance quality in CEECs has to be examined in conjunction with path dependence and therefore the perceived risk of ‘backsliding’ requires more detailed analysis.

Full text

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Published as: Ugur, M. (2012), ‘Europeanization, EU conditionality and governance
quality: Empirical evidence on Central and Eastern European countries’, International
Studies Quarterly, ISSN 0020-8833 (print), 1468-2478 (Online).
Europeanization, EU conditionality and governance quality:
Empirical evidence on Central and Eastern European Countries
Mehmet Ugur, University of Greenwich, UK* - M.Ugur@gre.ac.uk
Abstract
A large body of work within the Europeanization and conditionality literature has examined
EU’s effect on governance quality in Central and Eastern European countries (CEECs). This
article aims to contribute to existing work by addressing two questions. First, was EU’s
accession conditionality conducive to better governance in CEECs or was it designed to pick
up already committed reformers? Secondly, during which period was the EU more influential
on governance quality in CEECs: accession or membership? To address these questions, we
propose a simple model of moral hazard and adverse selection, and draw on survey-based
governance quality data to test its predictions. We report that the EU has offered candidate
status to countries that already had better governance quality relative to their peers before
1997. Nonetheless, EU conditionality also had some positive effects on CEEC governance
during the accession period, but this effect tended to disappear during the membership period.
On the basis of these findings, we argue that EU’s impact on governance quality in CEECs
has to be examined in conjunction with path dependence and therefore the perceived risk of
‘backsliding’ requires more detailed analysis.
Key words: Governance quality, Europeanization, EU conditionality, Central and Eastern
Europe
* I would like to thank Nawar Hashem for help with data collection, merging and processing. I am also grateful
to two anonymous referees, whose comments have enabled me to enhance the analytical model and the
estimation methodology. I bear sole responsibility for any errors or omissions.

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1. Introduction
The Europeanization literature examines the extent to which polities and/or public policy
contents of EU member states or candidate countries converge towards a ‘European norm’-
usually proxied by existing European Union (EU) rules, legislation and institutional
frameworks. Using mainly a qualitative approach, this work has provided significant insights
into the extent to which Europeanization has affected governance quality in Central and
Eastern European Countries (CEECs).
On the other hand, there is also a well-developed body of work on the political economy of
institutional reforms in the context of World Bank or International Monetary Fund (IMF)
conditionality. This literature suggests that adherence to rules provides a ‘credibility bonus’
that reduces the cost of reforms. Therefore, policy makers that have a commitment problem
would be better off ‘tying their hands’ with external rules. The implication for CEECs is that
policy makers in these countries can reduce the cost of governance reform by tying their
hands with EU conditionality.
Both strands of the literature have provided a rich account of the actors and causal
mechanisms that must be taken into account when investigating the EU’s impact on
governance quality in CEECs since mid-1990s. Both strands, but especially the
Europeanization strand, have also produced rich sets of evidence on the strength and
distribution of EU’s impact across countries, public policy contents and areas of public
administration. However, the qualitative nature of the work have limited the scope for
deriving aggregate, comparable and reproducible conclusions about EU’s impact on
governance quality across countries and/or over time.
This article aims to contribute to the Europeanization and conditionality debate in three ways.
First, we demonstrate why the EU might grant accession country status or membership to
eligible countries that already have a good track record with respect to reform and governance
quality. To the extent that this is the case, it is necessary to disentangle the true effect of the
EU conditionality from the reform momentum that is due to path dependence. This is an issue

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that is not addressed either by the Europeanization literature or by the wider literature on
external conditionality. Secondly, we argue that CEECs may be faced with a moral hazard
problem that mirrors the EU’s adverse selection problem: the reform effort in candidate
countries may continue during the accession period when there is a probability of exclusion
from membership, but it may diminish or disappear after the country becomes an EU member.
Finally, the reform effort in CEECs can be expected to depend not only on the domestic cost
of reforms, but also on the way in policy makers in CEECs react to change in the rules of
engagement with the EU. Put differently, it is necessary to disentangle the true cost of reforms
from strategic behaviour that leads to lower levels of reform as a result of moral hazard.
The article is organised in five sections. In section 2, we provide an overview of the related
literature and develop the rationale for the moral hazard-adverse selection model of EU-
CEEC relations. In section 3, we present a simple model of utility maximization on the basis
of 2 choice variables: (i) the level of reforms (R) by the candidate country; and (ii) the
membership prospect (M) offered by the EU. The model suggests that the EU would tend to
offer accession country status to countries that are already good reformers relative to the
eligible group and that the accession country’s reform effort would weaken after EU
membership is secured. In section 4, we draw on survey-based governance quality data
compiled by two sources (the World Bank and the International Country Risk Guide) to verify
the extent to which the analytical predictions of the model are supported by evidence. In
section 5, we summarise the main findings and relate the latter to the debate on the pre- and
post-membership reform efforts of the CEECs.
2. Europeanization, conditionality and governance quality in CEECs
The Europeanization literature addresses the general question about the extent to which
polities and/or public policy contents of EU member states or candidate countries converge
towards the ‘European norm’ as a result of EU conditionality or rule transfers. (Bulmer and
Radaelli, 2004; Schimmelfennig and Sedelmeier, 2004; Grabbe, 2001 and 2003; and Goetz,
2005). The work that focuses on CEECs reports that Europeanization was visible first and
foremost in
linkage institutions
that link CEEC executives and EU authorities;
and in
support institutions
that support the multiple platforms of interaction
between the two sides (Ágh, 2003; Fink Hafner and Lajh 2003; Nakrosis 2003;

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Zubek 2002; and Lippert et al. 2001). These findings were supported by Goetz
(2005), who reports that change was visible at the level of “governmental and
administrative actors, structures and procedures that were in charge of the
accession negotiations, the transposition of the
acquis
, and the management of
pre-accession funds.” Europeanization was also reported in the reform of the
civil service instigated by the EU through formulation of “baselines for
civil service development” and provision of “technical and financial
assistance [that] was made available through the SIGMA programme and through
PHARE projects” (Goetz, 2005. See also Meyer-Sahling, 2004; Scherpereel,
2003).
A sub-set in this literature examines the mechanisms through which Europeanization has
affected governance quality in CEECs. For example, Grabbe (2001) reports that the accession
conditionality has influenced public policymaking processes in CEECs through a number of
mechanisms, including: gate keeping (the threat of suspending accession negotiations);
benchmarking and monitoring; provision of institutional templates; and financial assistance.
On the other hand, Schimmelfennig and Sedelmeier (2004: 663) report that the effectiveness
of rule transfer from the EU to the CEECs has been dependent on the credibility of EU
conditionality and the domestic cost of rule adoption. Furthermore, they point out that the
domestic cost of rule adoption has limited the effectiveness of EU conditionality in the
context of democratic reforms more than it has in the context of acquis adoption.
Among this body of work, Goetz (2001, 2002) is the most pessimistic: he asserts that
Europeanization is bound to remain limited/shallow because of weak ‘uploading capacity’ of
CEECs, inadequate time for learning and socialisation, and the restriction of engagement with
EU institutions to mainly political, administrative and economic elites of the CEECs.
However, in a more recent review of the literature, Goetz (2005) observes that
Europeanization has affected polity, politics and public policies in CEECs; although these
effects have remained shallower than it is the case in previous member states.
The Europeanization literature has made significant contributions to our understanding of
reforms and governance quality in CEECs under EU conditionality. However, its qualitative
nature has limited the extent to which its findings can be aggregated and/or used for

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comparative purposes. More importantly, the Europeanization literature rightly considers the
effect of the domestic cost of reforms on reform outcomes, but does not problematize four
issues that arise when the EU and CEEC policy-makers interact strategically. First, what is the
relationship between the pre- and post-1997 reform effort in CEECs? Secondly, what is the
relationship between EU’s offer of candidate country status in 1997 and the pre-1997 reform
efforts of the CEECs? Third, how do policy makers in CEECs react to changes in the ‘rules of
the game’ that govern their relations with the EU? Finally, is it not necessary to distinguish
between the domestic cost of reform and the moral hazard problem as potential determinants
of reform effort in CEECs?
Some political economy work that adopts a strategic approach tends to address some of these
issues explicitly. For example, Bronk (2002) examine EU’s impact on CEEC governance
quality from the perspective of credible commitments. He draws attention to a ‘credibility
bonus’ that policy-makers in CEECs can enjoy by tying their hands under EU conditionality.
In this perspective, EU’s impact on reform efforts is not a result of simple rule transfer or
compliance per se. Rather, it originates from EU’s role as a commitment device that reduces
the scope for discretionary (hence uncertain/reversible) policy choices by the political and
administrative elite. This, in turn, increases the credibility of the commitment to reforms by
providing ‘credibility benefits’ such as lower risk premiums on public and private borrowing
from international markets and substantial inflows of foreign direct investment (FDI). Put
differently, EU conditionality can instigate a virtuous circle, whereby tighter EU
conditionality leads to higher levels of credibility and credibility benefits that, in turn, leads to
higher levels of reform and governance quality.
This approach draws on a well-established research agenda in the political economy of
macroeconomic policy design, dating back to Kydland and Prescott’s (1977) seminal
contribution on rules versus discretion in monetary policy. In this perspective, subscription to
rules ties the policymaker’s hands and reduces the scope for optimal policy adjustment in the
face of shocks. However, rules still remain superior to discretion as the latter can be abused to
maximise political gains. Given this scope for political opportunism and in the absence of a
credible domestic commitment mechanism, external conditionality can emerge as a substitute

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commitment mechanism that would tie the policymaker’s hands and produce efficient
outcomes by preventing policy reversals.
1
Nevertheless, there is evidence suggesting that conditionality in International Monetary Fund
(IMF) programmes or in development aid has been less effective than what this line of
research would imply. For example, the rate of non-compliance with aid conditionality from
1973-97 is reported by Moussa and Savastano (1999) as 54.5 percent. Interestingly, non-
compliance has increased as the IMF has become more experienced in designing and
negotiating conditionality. Hence, non-compliance increased from about 50 percent in 1970s
to about 72 percent in the 1990s.
2
Other work examines the mismatch between IMF structural adjustment credits and the policy
environment in recipient countries; and demonstrates that IMF credits tended to favour policy
environments that are too weak and diminished in policy environments that are sufficiently
good for funds to be effective (Collier and Gunning, 1999). Opposite findings led Dollar and
Svensson (2000) to conclude that the primary role of the international financial institutions
has been to pick up winners rather than increase recipient’s commitment to reforms.
In the light of these findings, two questions arise with respect to EU’s impact on governance
quality in CEECs. First, does the EU ‘pick up winners’ - i.e., does it grant accession status to
already committed reformers; or does it actually function as a commitment device that
increases the pace and quality of governance reforms in CEECs? Secondly, when is it more
likely for EU conditionality to function as a commitment device that would underpin the
reform effort – during accession or during membership? To address these questions, we first
propose a simple utility-maximisation model that demonstrates the adverse selection and
moral hazard problems faced by the EU and CEECs, respectively. Then, we test the
predictions of the model, using survey-based governance data compiled by the World Bank
and the International Country Risk Guide (ICRG).
1
In the European context, the role of the European Monetary System as an external anchor for anti-inflationary
policies has been discussed widely. See, for example, Melitz (1988); Giavazzi and Pagano (1988); Fratianni and
von Hagen (1992: 43-98); Gros (2001).
2
Non-compliance is measured as failure to disburse (or withdraw) at least 75 percent of the total IMF loan under
a particular arrangement.

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3. Governance reforms and EU accession under uncertainty and strategic interaction
The relationship between the EU and an accession country can be modelled as a utility-
maximisation game with 2 choice variables for the actors: (1) the level of reforms (R) to be
chosen by the accession country; and (2) the membership prospect (M) that the EU chooses to
offer to the latter. Policy-makers in CEECs will choose the level of reforms that would
maximise their utility specified in equation (1) below. On the other hand, the EU will choose
the level of membership prospect (measured as a commitment index) that maximizes its
utility function in equation (2).
          (1)
        (2)
Finally, the level of reforms chosen by a CEEC and the membership prospect offered by the
EU will determine the probability of membership (π). As specified in equation 3, higher levels
of reforms and commitment by CEECs and EU respectively, lead to higher probability of
membership – i.e., the partial derivatives of the membership probability function (π) with
respect to (R) and (M) are positive.
3
      (3)
Variable definitions and solution of the model for equilibrium levels of reform effort and
membership prospect are given in the Appendix. Reporting only the solution here, we can
The variables are defined as follows:
Ua, Ue = Utility functions of the accession country and the EU, respectively
M = Membership prospect the EU offers to the accession country
R = Accession country’s reform effort to comply with EU conditionality
Z = Worth of membership for the accession country
πZ = Expected value of membership, given the probability of membership (π)
sZ = EU support received during the accession period as a fraction of the worth
3
We draw on a similar model proposed by Cooper and Ross (1985) in the context of moral hazard problems
related to product warranties.

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of membership (Z)
(1- π)sZ = Expected value of EU support when membership does
not materialize
P = Benefits derived by the EU as a result of CEEC convergence towards
EU norms/standards
Ca(R, R0) = Cost of reforms for policy makers in CEECs
Ce(M, M0) = Cost of membership for the EU
π(M,R) = Probability of membership as a function of EU’s membership commitment
and candidate country’s reform effort
πM > 0 and πR > 0 are partial derivatives and indicate that the probability of
membership will increase as the membership commitment and reform effort increase.
The cost functions [Ca(R, R0) and Ce(M, M0)] are defined as quadratic functions that depend
on the difference between the current and past levels of: (a) reform in the accession country
(R-R0); and (b) level of EU commitment to membership (M-M0). Stated formally:
              
 (4)
              
 (5)
In equation 4, the cost of reform for policy makers in accession countries is assumed to be
higher, the higher is the level or required reform (R). This is due to political risk (e.g.,
resistance by veto points, increased Euroskepticism, etc.) or adjustment costs in the economic,
business and public policy domains that are associated with reforms. However, the cost of
reforms is assumed to be lower, the higher is the stock of past reforms (R0). Higher past
reform levels dampen the cost of current reforms either by reducing the level of reform
required to satisfy EU conditionality or by enabling policy makers to exploit path-dependence
dynamics.
In equation 5, the cost of membership for the EU is assumed to be higher, the higher is the
level of current commitment (M). This may be due to political risks associated with
perceptions of adverse enlargement effects by EU nationals or budgetary costs of integrating a
candidate country. On the other hand, the cost of membership is assumed to be lower, the
higher is the level of past EU commitment to membership. This is because anti-enlargement

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actors, having observed EU’s strong commitment in the past, would reduce their lobbying
activities in the current period as they realise that their opposition is less likely to change the
EU’s stance. This relative withdrawal of the anti-enlargement lobbying activities, in turn, will
increase the scope for the EU to signal a high level of commitment to enlargement.
To find the equilibrium levels of reform (R) and membership prospect (M) that would
maximize the utilities of the accession country and the EU, we differentiate the utility
functions (equations 1 and 2) and set them equal to zero. In this process, the cost functions in
(1) and (2) will be replaced by their equivalents in (4) and (5). We provide the solution in the
appendix and reproduce only the equilibrium levels of reform (R) and (M) below.
       (6)
     (7)
From (6), we can see that the level of reform effort (R) by the candidate country is positively
related to: (i) the benefit of membership (Z); (ii) reforms’ contribution to the probability of
membership (πR); and (iii) the level of past reforms (R0). However, the level of reform in the
candidate country is negatively related to: (i) the level of EU support (s) for convergence
reforms; and (ii) the marginal cost of reforms (h).
From (7), we can see that the level of EU commitment to membership (M) is positively
related to: (i) the benefit of membership (Z); (ii) the level of EU support to the candidate
country (s); (iii) the contribution of the membership prospect to the probability of
membership (πM); and (iv) the level of past commitment (M0). However, the membership
prospect is negatively related to the marginal cost of membership (d).
Given this setting, three questions arise. First, how would the EU choose the candidate
country for membership from a group of eligible countries if it knows that the equilibrium
level of reforms to be chosen by CEECs is related negatively to the cost of reform in the
candidate country (h) and the level of EU support (s)? Secondly, what would be the reform
effort of a candidate country when the latter knows that its reform effort increases the
probability of membership with a factor (πR)? Third, what would be the reform effort of the
member country when the latter knows that its reform effort has no effect on the probability of

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membership, which is now equal to 1? Answers to these questions can be best developed by
pointing out the moral hazard and adverse selection problems faced by the parties.
From equation (6), the accession country is faced with two types of moral hazard – one during
the accession period and one during the membership period. During the accession period, the
candidate country must deliver reforms that contribute to the probability of membership.
Otherwise, the EU could withdraw the membership offer or delay its realization. This is the
level of reform that must satisfy EU conditionality – the so-called Copenhagen criteria for
accession. However, this reform effort will be dampened by two factors: the level of EU
support as a fraction of the membership benefits (s); and the incremental cost of reforms (h).
The combination of these factors represents the scope for moral hazard in CEECs. In other
words, they represent the incentives for CEEC policy makers either to reduce the reform
effort or to deliver less reform than what was agreed. This type of behaviour will occur when
the EU provides generous support towards the cost of convergence reforms (as s increases) or
when the marginal cost coefficient (h) increases. Nonetheless, equation (6) also indicates that
the candidate country’s reform effort will remain positive as long as: (a) the value of EU
aid/support remains a fraction of the membership benefits - i.e., as long as s < 1 in the
numerator; and (b) the trade-off between R0 and this positive value will be boosted by the
path-dependence dynamics of the past reform efforts – i.e. by the contribution of R0 to current
reform efforts. Therefore, during the accession period, that the candidate country will
maintain a positive level of reform effort that is related to its past track record, the EU’s
incentive package, and the perceived cost of reforms. However, the level of reform delivered
during membership will fall below the level of accession reforms as membership probability
is now 1 and the reform effort does not affect the chance or membership – i.e. πR = 0. Any
reforms that may or may not be undertaken in CEECs will be a function of path dependence
(R0) or other factors not included in the model – for example rule/policy transfer through
adoption of EU legislation, elite socialization, arbitrage through political and/or economic
markets, etc. In other words, the linkage between EU conditionality and reform weakens even
if it does not disappear altogether. Therefore, we can expect reform performance to slow
down or stall after CEECs join the EU as full members.
On the other hand, the EU is faced with an adverse selection problem. This problem is due to
its awareness of the moral hazard problem faced by the accession country. To minimise its

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loss when the moral hazard problems kicks in, the EU will be inclined to offer candidate
country status and membership prospect mainly to countries with good track record for
reforms. This is for two reasons. First, countries with good track record are less likely to
renege on their reform commitments after membership or as EU assistance (s) becomes more
generous. Secondly, even if they renege, the gap between EU norms/rules and candidate
country’s governance quality will be narrower compared to other potential candidates without
a good track record. The narrower gap, in turn, enables the EU to minimise the risk of non-
compliance by new members or that of gridlock in EU decision making due to divergent
norms and values.
In the next section, we examine the extent to which these analytical predictions are consistent
with the evidence on governance quality in CEECs and a control group of eligible countries in
south-eastern Europe.
4. Empirical analysis: model specification, data quality and results
We specify two models to test the analytical conclusions derived above. The first is a logistic
regression model that relates the probability of accession status to the level of past reform
effort by a candidate country. The second is a random-effect panel data regression for
estimating the effect of accession and membership periods on governance quality of 10
CEECs that had been included in the enlargement agenda of 1997. In addition to the
governance data, we use data for control variables such as per-capita income, openness to
trade, size of the stock of market (measured as a ratio of the market value of listed companies
to GDP), and ratio of urban population to total population. Data for control variables is from
World Bank Development Indicators (WDI) database; whereas governance data is from
World Bank Governance Indicators (WGI) and International Country Risk Guide (ICRG)
databases. Definitions of governance scores are in Table A1 and Table A2 in the appendix.
Inclusion of per-capita GDP, openness to trade, size of the stock market, and size of the urban
population as control variables with potential effect on governance quality is informed by the
relevant literature (see, for example, Alonso and Garcimartin, 2010; Al-Marhubi, 2004; and
Kandil, 2003).

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The governance measure for each country consists of the sum of scores for six governance
dimensions. In the WGI data, the total score is the sum of scores for: voice and accountability;
rule of law; regulatory quality; political stability; government effectiveness; and control of
corruption. ICRG scores, on the other hand, measures governance quality along the following
dimensions: democratic accountability; law and order; government stability; bureaucratic
quality; ethnic tensions; and control of corruption.
Instead of governance quality scores as magnitudes, we use a relative measure that is equal to
the difference between the country score and the group average. The group consists of 17
countries - 11 CEECs that had been granted accession country status in 1997 (Bulgaria,
Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia,
and Slovenia) and 6 south-eastern European countries (Albania, Bosnia and Herzegovina,
Croatia, Macedonia, Serbia, and Turkey) that were not included in the enlargement agenda of
1997 but are considered eligible due to their European geography. Table A1 in the appendix
summarizes the governance quality of CEECs relative to 17 countries eligible for accession
status due to their locations in Europe. The evidence in Table A1 indicates the following: (i)
the 10 CEECs that were granted accession status in 1997 had higher governance quality
scores than the group in 1997; (ii) the 10 CEECs increased their leads over the group average
from 1997 to the accession year (2004 for the majority and 2007 for Bulgaria and Romania);
and (c) relatively higher governance quality in the 10 CEECs tended to stabilise or disappear
after accession.
This summary evidence is line with the main predictions of the moral hazard and adverse
selection model presented in section 3. However, the descriptive nature of this evidence does
not allow causal inference. To do this, we first estimate a logistic regression model to
establish the partial effect of past governance quality in CEECs on EU’s decision to grant or
withhold accession status in 1997. Then, we estimate a random-effect regression to establish
the effect of EU conditionality on governance quality in CEECs during two periods: (i) the
accession period from 1997-2004 (from 1997-2007 for Bulgaria and Romanian); and (ii) the
membership period from 2004 (from 2007 for Bulgaria and Romania) to the last year for
which data exists (2009). All estimations are based on panel data for the specified period.
We address two issues before reporting and discussing the estimations results. The first issue
concerns the subjective nature of the governance quality scores and whether such scores can
be used for empirical estimation. The second issue is the large confidence interval (i.e., the

13
lack of precision) associated with governance quality scores compiled from different sources
– as the WGI scores are.
Concerns about the first issue are well-documented in the literature (see, for example, Kurtz
and Schrank, 2007; Knack, 2006; Arndt and Oman, 2006). These concerns relate to the ‘halo
effect’ discussed by Kurtz and Schrank (2007) and Kaufmann et al (2007) and the
endogeneity problem discussed in the context of the relationship between governance quality
and economic performance in general (Knack and Keffer, 1997; Acemoglu et al, 2001; Rodrik
et al, 2004, etc.). However, this endogeneity problem can be and has been addressed in the
empirical literature. For example, Acemoglu et al (2001) have introduced instrumental
variables (i.e., settler mortality rates in early colonial period) that are correlated with
institutional quality but are not dependent on current economic performance. Knack and
Keefer (1997), on the other hand, used a measure of ethnic cleavage and the number of law
students as instrumental variables. Rodrik et al (2004) have used lagged values and conducted
Granger causality tests to demonstrate that institutional quality measures determine economic
performance rather than the other way round. Finally, Kaufmann et al (2007) demonstrate that
economic performance (e.g., growth) is likely to impact on governance quality only in the
long run.
The endogeneity problem does not affect the estimations in this article because we do not
estimate to the effect of governance quality on economic performance (e.g. growth). On the
contrary, governance quality in this paper is the dependent variable and we estimate the
partial effects of its determinants – including past governance quality and other factors such
as EU conditionality, per-capita income, openness to trade or financial development.
However, the halo effect may contaminate the estimations in this article to the extent that
contemporaneous values of per-capita income (or other economic variables) and governance
quality are highly correlated. To minimise this risk, we have used two-year-lagged values of
all economic variables.
The second issue concerns the statistical significance of the quality scores and whether they
can be used for comparison across countries or over time. For example, Knack (2006) as well
as Arndt and Oman (2006) warn that cross-country differences in scores or differences over
time may not be statistically significant due to the margin of error associated with individual
scores. This problem is especially acute when the reported governance scores consist of

14
aggregated scores from different sources. We acknowledge that the WGI data we use in this
article is particularly prone to this problem. We cannot eliminate this risk, but we control for
its implications by reporting estimates using both WGI and ICRG data. The extent of
convergence/divergence between the estimation results from the two datasets will enable us to
assert or qualify the relevance of our findings.
Bearing in mind the elaborations above, we estimate the following logit model using
unbalanced panel data for the period 1995-2003. The dependent variable is the odds ratio for
accession status being granted to 10 CEECs and Cyprus in 1997 and the maintenance of this
status until 2003; given that this status was withheld from other peers and given the economic
and governance characteristics of each country in the sample. The model can be stated as
follows:
)1()( 2322210 ititititit dmoptdmpcgdpdmgqAccessionP

 
The variables are defined as follows:
P(Accessionit) = 1 if the country was given candidate status in 1997; 0 otherwise.
dmgqit-2 = difference between country i’s total governance quality score and
the group average score, lagged 2 years.
dmpcgdpit-2 = difference between country i’s per-capita GDP and the average
per-capita GDP for the group, lagged 2 years.
dmoptit-2 = difference between country i’s openness to trade and the average
openness to trade for the group, lagged 2 years.
εit = error term.
This model enables us to estimate the impact of past reform performance on the odds ratio for
a country being granted a candidate status in 1997 and the maintenance of this status until
2004 for the following countries: Bulgaria, Cyprus, Czech Republic, Estonia, Hungary,
Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia. We estimate this model with a
control group of other countries in the south-eastern periphery of the EU, consisting of
Albania, Bosnia and Herzegovina, Croatia, Macedonia, Serbia, and Turkey. All independent
variables measure the country-specific differences from the group average. Per-capita GDP is
measured in constant US dollars with a base period of 2002; and openness to trade is

15
measured as the ratio of the sum of exports and imports to gross domestic product in nominal
values. Estimation results are given in Table 1 below.

16
Table 1: Factors affecting the probability of accession-country status:
Unbalanced panel data for 1995-2004
Dependant variable:
accession status
With WGI data
With ICRG data
dmgqit_2
69.1535***
1.2509**
(118.3240)
(0.1343)
dmpcgdpit_2
0.9978
0.9987*
(0.0019)
0.0007
dmoptit_2
1.2659**
1.9171***
(0.1558)
(0.3271)
Number of countries
17
14
Number of observations
p-value for Wald test
50
0.02
79
0.00
Standard errors in brackets. Standard errors for odds ratio is given by exp(coefficient)*se(coefficient).
*, ** and *** indicate statistical significance at 10%, 5% and 1%, respectively.
WGI does not have data for years 1997 and 1999.
Results in Table 1 indicate that the model as a whole is well-specified and statistically
significant. This is confirmed by the Wald test results indicating that the null hypothesis of
jointly insignificant variables should be rejected at 5% significance for WGI data and at 1%
for ICRG data. Looking at the main explanatory variable of interest - relative governance
quality in the past (dmgqit-2) – we can see that the coefficient for the odds ratio is greater than
1 and statistically significant in both datasets. Hence, it is possible to infer that past reform
performance increases the odd ratio for accession status being granted in 1997 and maintained
throughout the period until 2003. This result is in line with the predictions of the analytical
model in section 3 and has two important implications for the debate. First, the EU tended to
sign accession partnership contracts with CEECs that were above-the-average reformers
before the start of the accession period. Secondly, the past the relationship between past
performance and the accession status continued to prevail during the accession period too.
Hence, it is possible to conclude that the EU had ‘picked up winners’ (i.e., countries with
governance scores) at the beginning of the accession period, but the maintenance of the
accession country status was also related to subsequent improvements in terms of reforms and
governance quality.

17
Table 1 also indicates that the EU tended to sign accession partnership contracts with CEECs
that have relatively higher levels of openness to trade. This result is compatible with EU’s
emphasis on accession country’s ability to cope with competitive pressures that would result
from trade liberalisation within the customs union and the single market. Finally, the
coefficients for the relative per-capita income levels are marginally less than 1 and
statistically significant only with the ICRG data. Therefore, it is possible to conclude that
relative per-capita income levels were not a significant determinant of EU’s choice of
accession partners.
The analytical model in section 3 above also indicates that the change in governance quality
may differ between the accession and membership periods because of the change in the
‘strictness’ of EU conditionality – even though the level of past reform (i.e., governance
quality in the past) may have a path-dependence effect. Therefore, we estimate a random-
effect model for the determinants of governance quality in two periods: the accession period
from 1997-2004 (2007 for Bulgaria and Romania); and the membership period from 2004-
2009 (2007-2009 for Bulgaria and Romania). In this model, we regress the governance
quality performance of the countries relative to the group average on the following
determinants: (i) an EU conditionality dummy that captures the period of accession or
membership; (ii) past levels of relative governance quality (to capture path dependence); and
(iii) lagged values of economic/demographic variables that have been demonstrated to affect
governance quality in the literature (e.g., per-capita income, openness to trade, market
capitalisation of listed companies, and ratio of urban to total population). The model and
estimation results are presented below.
)7(
25
2423220
itit
ititititit udmurbpop
dmmrktcapdmoptdmpcgdpEUdummydmgq






Where:
dmgq, dmpcgdp and dmopt are as defined above.
EUdummyit = 1 if the country was given a candidate or membership status,
depending on the time period specified above; 0 otherwise.
dmmrktcapit-2 = relative size of the capital market, measured as market value of
listed companies as proportion of GDP, lagged two years
dmurbpopit-2 = relative size of urban population, measured as urban population as a

18
proportion of population, lagged two years.
uit = error term.
Table 2: Impact of EU conditionality and past performance on governance quality:
Unbalanced panel data for the accession period
Dependant variable:
governance quality
With WGI data
With ICRG data
EU dummy (accession)
4.5072*
1.6311
(0.9476)
39.0905
dmgqit_2
0.9886*
3.5104*
(0.0424)
0.7617
dmpcgdpit_2
0.0004*
-0.0054
(0.0001)
0.0044
dmoptit_2
0.0061
-0.1288
0.0089
0.1895
dmmrketcapit_2
-0.0096
-0.0127
0.0228
0.2971
dmurbpopit_2
-2.6313*
0.2084
-3.4600
1.9182
Number of countries
14
13
Number of observations
41
34
* significant at 1%
F-statistic 0.00
F-statistic 0.00
Standard errors in parenthesis.
Accession period: 1997-2004 for 9 CEECs; 1997-2007for Bulgaria and Romania
The F-statistic for joint significance of the variables is less than the critical value of 5% and
therefore it is admissible to examine the individual effects of the explanatory variables. We
have two main explanatory variables of interest here: EU conditionality dummy for the
accession period and relative governance quality in the past. The coefficient of EU dummy is
positive in both datasets, but only the coefficient estimated with WGI data is significant. This
lends support to the prediction of the analytical model about EU conditionality during
accession, but this support needs to be qualified because of the weak precision associated with
WGI data. With this caveat in mind, it is possible to conclude that there is some empirical
support for the analytical model prediction that EU conditionality during the accession period
is likely to have a positive effect on reform effort and consequent governance quality.
However, EU conditionality during the accession period is not the only factor that affects
governance quality in the CEECs: path dependence also has a positive and statistically

19
significant effect in estimations with both datasets. The estimated coefficient indicates that an
accession country’s governance quality would be 1 – 3.5 units higher than the group average
in the current period if its governance quality was 1 unit higher than the group average two
years ago. In other words, relatively better performers in the past are likely to outperform the
group average mainly because of path dependence. It is not possible to make consistent
inference about the impact of economic and demographic determinants of governance quality
as either the estimates are not statistically significant or their signs are inconsistent between
the two datasets.
Table 3: Impact of EU conditionality and past performance on governance quality:
Unbalanced panel data for membership period
Dependant variable:
governance quality
With WGI data
With ICRG data
EU dummy
(membership)
0.2991
11.2221
(0.4637)
(9.6479)
dmgqit_2
0.9912*
1.6854*
(0.0062)
(0.1288)
dmpcgdpit_2
0.0000
-0.0050
(0.0001)
(0.0017)
dmoptit_2
0.0017
-0.1446
(0.0053)
(0.1107)
dmmrketcapit_2
-0.0005
0.0200
(0.0017)
(0.0348
dmurbpopit_2
-0.0320
-1.1952
(0.1069)
(-2.2240)
Number of countries
15
14
Number of observations
60
56
* significant at 1%
F-statistic 0.00
F-statistic 0.00
Standard errors in parenthesis.
Membership period: 2004-2009 for 9 CEECs; 2007-2009 for Bulgaria and Romania
Lastly, in Table 3, we present the estimation results for the membership period - i.e., 2004-
2009 for 10 CEECs and 2007-2009 for Bulgaria and Romania. The results during membership
are consistent across both data sources and comparable with accession period results in Table
2. The estimated coefficients for the membership dummy are positive, but they are not
statistically significant. Hence, we cannot infer that EU conditionality under membership has
had an effect on governance quality and the reform effort that underpins it. This is in line with
the analytical prediction of our model, which implies that reform effort by CEEC policy-

20
makers is likely to slow down as the latter is no longer a pre-requisite for increasing the
probability of membership (which is now 100%). However, past reform performance (i.e.,
path dependence) is still a significant determinant of governance quality in CEECs during
membership – with the effect ranging between 1 – 1.7.
The findings in Tables 1-3 above can help fill in some of the gaps in the existing
Europeanization and conditionality literature.
First, the finding that accession status has had a positive effect on governance quality is in
line with the conditionality literature that predicts a positive effect from EU conditionality to
reform and governance quality improvement in CEECs. However, our estimations provide
additional evidence that would qualify the assertions of the conditionality literature in two
ways. First, EU conditionality does not function within a tabula rasa in CEECs; and the effect
of conditionality must be separated from the effect of path dependence. The estimations
results indicate that past performance is a strong and significant determinant of current
governance quality in both the accession and membership periods. Secondly, the
conditionality literature does not explain (or does not very much discuss) the following
question: if EU conditionality is conducive to higher levels of reforms and governance
quality, why does the EU not offer accession partnerships to all European countries? The
analytical model in section 3 and the estimation results above provide some explanation: the
EU exercises adverse selection in response to the risk of moral hazard by accession partners.
Hence, the EU selects countries with already good track record in terms of reform and
governance quality and its conditionality can then help policy-makers in these countries
resolve some of the commitment problems that may lead to reform reversals.
Secondly, the findings we report above also provide a wider perspective within which the
findings of the Europeanization literature should be interpreted and evaluated. The
Europeanization literature tends to be based on exogenous choice of reform effort by CEEC
policy-makers. In this approach, the reform effort of CEEC policy makers is a negative
function of the domestic cost of reforms – and this is compatible with our analytical model
argument. However, the Europeanization literature also makes an assumption that contradicts
the predictions of the analytical model above: reforms under EU conditionality are negative
function of the strictness of EU conditionality.

21
We agree with the Europeanization literature that domestic cost of reform has a negative
effect on reform effort, but were unable to verify this argument empirically due to lack of
‘reform cost’ data. However, the evidence we provide in Table 2 and 3 contradicts the
Europeanization literature’s thesis that strict EU conditionality is associated with weak reform
performance. On the contrary, EU conditionality tended to be associated with higher reforms
(i.e., better governance quality) when it was strict during the accession period, and the
association has become insignificant during membership when conditionality is less
asymmetric.
Thirdly, the positive effect of path dependence indicated by our findings can be placed in the
context historical institutionalism and institutional economics literature. According to the
positive feedback hypothesis in this literature, institutional structures tend to have a high level
of persistence due to high costs of switching. High costs of switching, on the other hand, may
be due to resistance of stakeholders who benefit from the existing institutional set up and/or
high mobilisation costs faced by constituents demanding change (Pierson, 1996, 2000;
Thelen, 1999; Levi, 1997). The positive feedback process may also be due to reactive
sequences, which imply that a chain of temporally ordered events may occur as a reaction to
antecedent events (Abbott, 1983; Ebbinghaus, 2005).
Conclusions and discussion
The impact of EU conditionality on the reform effort and consequent institutional quality in
CEECs has attracted significant interest before and after EU enlargement towards these
countries. Before enlargement, the focus was mainly on the extent to which EU conditionality
or the Europeanization process had contributed to the reform effort and improved governance
quality. After accession, the emphasis has been on whether EU membership would enable
CEECs to build on pre-accession reforms or whether the disappearance of EU leverage would
lead to ‘backsliding’. The analysis above suggests that it is difficult to provide uniform and
time-invariant answers to these questions. One of the reasons is that the outcome depends
both on past performance and rules of engagement with the EU. The other reason is that it is
highly difficult to devise a quick institutional fix for politics when it comes to long-term
commitments (Posen, 1993). Despite these caveats, the findings above can still support a
number of conclusions that contribute to the ongoing debate.

22
One conclusion is that EU conditionality (i.e., the combination of incentives and constraints
devised in accession partnerships and membership pacts) matters; but this is only one of the
factors to be taken into account. In addition, the level of pre-existing commitment to reforms
and the level of path dependence are also important factors. EU conditionality or the
Europeanization process in accession countries can help policy-makers maintain their
commitments to reform in the face of frequent shocks and in the absence of a strong domestic
commitment mechanism that combines both rules (e.g., a constitution) and values (e.g.,
commitment to democracy, accountability, meritocracy, etc.). Another conclusion is that the
prospect of status change (e.g., the prospect of graduation from a peripheral transition country
status to a core European country status with scope to influence EU decision making) is likely
to be more effective in instigating commitment to reforms compared to side payments in the
form of EU assistance.
The third conclusion is that the domestic cost of reform (i.e., resistance to reforms and the
impact of such resistance on re-election probability) does enter the calculation of the policy
makers and may reduce the level of reform performance. However, this cost is also a
subjective magnitude that depends not only on the true cost of reforms but also on policy-
makers’ perceptions and their ideological orientations. In addition, it is also a negative
function of the momentum of past reforms and depends on the rules of engagement with the
EU and other external factors. Given these qualifications, it may be misleading to explain the
level of reform and consequent governance quality by referring to the cost of reforms as an
exogenously-given quantity.
A fourth conclusion is that the impact of EU membership on reforms and consequent
governance quality is uncertain. Therefore, it may be misleading to establish a causal link
between the risk of backsliding (i.e., the probability of lower reforms and deterioration in
governance quality) and the EU conditionality during the EU membership period. Recently,
both international think-tanks and scholars working on Central and Eastern Europe have
expressed concerns about this risk. For example, the Nations in Transition (NIT) project by
Freedom House has alerted the relevant audience to the risk of backsliding in CEECs. In
addition, a special issue of the Journal of Democracy (volume 14, no. 4, 2007) included 7
studies. Most of the contributors (e.g., Rupnik, 2007; Krastev, 2007; Mungiu-Peppodi, 2007;
and Greskovits, 2007) suggested that CEECs were experiencing some degree of backsliding

23
and that the EU connection has played some role in this process. Whilst some point out the
cost of convergence in economic policy as an explanatory variable, some point out the
Euroskeptic reaction that brought populist forces and parties to power after accession.
The empirical findings presented in this article both support and qualify these qualitative
observations. The evidence confirms that EU conditionality did not have a statistically
significant effect on reform efforts and governance quality in CEECs during membership. As
such, it lends indirect support to qualitative/descriptive evidence indicating stagnation or slow
down in the pace of reform after EU membership. However, it also qualifies the backsliding
argument in two ways. First, past performance matters and therefore any slowdown or
deterioration in governance quality is bound to be country-specific. The persistence of stalling
or the level of deterioration will depend on the level of governance quality achieved in the
past. Ipso facto, the adverse impacts of stalling reforms or governance quality deterioration
will also depend on how far each country had improved its governance quality during the
accession period. Secondly, when analysing the causes of backsliding, it is necessary to
isolate the impact of EU membership from the wider impact of the external environment
within which the risk of backsliding emerges. In the emerging literature on backsliding, this
separation is not systematic and therefore there is a risk of mis-specification or ad hoc
inclusion/exclusion of the relevant factors. This analysis in this article does not address this
issue directly, but it points out the way in which it can be addressed analytically and
empirically.

24
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Appendix
Table A1: Governance data description and measures: WGI Data
Voice and
accountability
Captures perceptions of the extent to which a country's citizens are able to participate in
selecting their government, as well as freedom of expression, freedom of association, and a
free media
Regulatory
quality
Captures perceptions of the ability of the government to formulate and implement sound
policies and regulations that permit and promote private sector development.
Rule of law
Captures perceptions of the extent to which agents have confidence in and abide by the
rules of society, and in particular the quality of contract enforcement, property rights, the
police, and the courts, as well as the likelihood of crime and violence.
Political stability
Measures perceptions of the likelihood that the government will be destabilized or
overthrown by unconstitutional or violent means, including domestic violence and terrorism
Government
effectiveness
Government effectiveness captures perceptions of the quality of public services, the quality
of the civil service and the degree of its independence from political pressures, the quality
of policy formulation and implementation, and the credibility of the government's
commitment to such policies.
Control of
corruption
Captures perceptions of the extent to which public power is exercised for private gain,
including both petty and grand forms of corruption, as well as "capture" of the state by elites
and private interests.
All scores range from -2.5 to 2.5, with higher scores representing better governance quality.
Source: http://info.worldbank.org/governance/wgi/mc_countries.asp
Table A2: Governance data description and measures: ICRG Data
Law and order
Law and Order the strength and impartiality of the legal system, the popular
observance of the law. Ranges from 0 – 6.
Government stability
This is an assessment both of the government’s ability to carry out its declared
program(s), and its ability to stay in office. Ranges from 0 – 12.
Ethnic tensions
This is an assessment of the degree of tension within a country attributable to racial,
nationality, or language divisions. Ranges from 0 – 6.
Democratic accountability
This is a measure of how responsive the government is to its people. Ranges from 0
– 6.
Corruption control
This is an assessment of corruption within the political system. Ranges from 0 – 6.
Bureaucracy quality
The institutional strength and quality of the bureaucracy. High scores are given to
countries where bureaucracy has the strength and expertise to govern without
drastic changes in policy or interruptions in government services. Ranges from 0 –
4.
The higher the score, the better is the institutional quality and/or the lower is the risk.
Source: http://www.prsgroup.com/ICRG_Methodology.aspx

29
Table A3: Summary measures of relative governance quality for accession countries (total country score –
average for 17 countries in the region).
With WGI data
With ICRG Data
Start of
accession
Start of
membership
2009
Start of
accession
Start of
membership
2009
Czech Republic
5.42
5.85
6.65
7.81
1.02
1.46
Estonia
4.05
7.11
7.46
2.44
0.58
Hungary
5.09
7.02
5.73
6.23
5.60
-
1.00
Latvia
1.19
5.11
5.00
1.77
-
0.04
Lithuania
2.45
5.75
5.21
2.19
1.96
Poland
4.92
4.44
5.69
6.73
4.14
5.50
Slovakia
3.05
5.69
5.77
2.23
2.44
1.96
Slovenia
6.59
7.10
7.09
5.52
2.87
Bulgaria
-1.70
2.61
2.63
3.06
2.35
-
1.71
Romania
-0.47
2.00
2.34
0.56
-0.36
-
1.96
CEEC average
relative to the
group
3.06
5.27
5.36
4.44
2.71
0.96

30
Solution of the utility maximisation model.
The utility functions for the accession country (Ua) and the EU (Ue) are:
          (A1)
        (A2)
The probability of membership as a function of CEEC reform and EU commitment:
      (A3)
The variables are as defined in section 3 above.
The cost functions for the CEEC and EU depends on the difference between current and past
commitments. The past commitment of each side is denoted by the variable with zero
subscript. R0 is the level of past reform (hence past governance quality) in CEECs and M0 is
the level of membership prospect offered by the EU at the beginning of the accession period.
The difference (R – R0) and (M – M0) reflects the extra effort during each year of the
accession period.
              
 (A4)
              
 (A5)
Replace the cost functions in (A1) and (A2) with their equivalents in (A4) and (A5):
            
   (A1’)
        
     (A2’)
Differentiate (A1’) with respect to reforms (R) and (A2’) with respect to membership
prospect (M), and set equal to zero to find the turning point.

           (A6)

        (A7)
From (6) and (7), the equilibrium conditions for the accession country and the EU are as
follows:
       (A6’)
    (A7’)

31
Now we can solve for the level of reform (R) and membership prospect (M) that maximise
utility for both sides simultaneously. These levels are:
       (A8)
     (A9)
From (A8), we can see that the level of reform is negatively related to EU support towards
adjustment costs (s) and the coefficient of the marginal costs of reforms (h). These are the
sources of moral hazard for accession countries. From (A9), we can see that the current
membership prospect is a positive function of past EU commitment (M0) and negative
function of the coefficient of the marginal cost (d). These are the sources of adverse selection
by the EU.