Location: CIS

Fact or Fiction? The Reversal of the Gender Education Gap Across the World and the Former Soviet Union

Posted on March 4, 2013 | Policy Brief

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In this policy brief, I discuss the reversal of the gender education gap in many countries around the world – a fact that is still not widely known, although is increasingly gaining attention. I describe recent studies that have documented this fact for both developed and developing countries and have provided evidence on the trend. As there has not been much analysis of the education gap in the former Soviet Union countries, I present some measures of the education gap in the USSR and FSU countries, and compare them to other countries around the world. Finally, I discuss the potential causes of the reversal identified in the literature and how the reversal of the gap is related to other gender disparities. 

The Eurasian Customs Union among Russia, Belarus and Kazakhstan: Can It Succeed Where Its Predecessor Failed?

Posted on November 5, 2012 | Policy Brief

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In 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union and imposed the Russian tariff as the common external tariff of the Customs Union. This resulted in almost doubling the external average tariff of the more liberal Kazakhstan. Russia has benefited from additional exports to Kazakhstan under the protection of the higher tariffs in Kazakhstan. However, estimates reveal that the tariff changes have resulted in substantial transfers from Kazakhstan to Russia since importers in Kazakhstan now purchase lower quality or higher priced Russian imports which are protected under the tariff umbrella of the common external tariff. Transfers from the Central Asian countries to Russia were the reason the Eurasian Economic Community (known as EurAsEC) failed, so this bodes badly for the ultimate success of the Eurasian Customs Union. What is different, however, is that the Eurasian Customs Union and its associated Common Economic Space aim to reduce non-tariff barriers and improve trade facilitation, and also to allow the free movement of capital and labor, liberalize services, and harmonize some regulations. Estimates by my colleagues and I show that if substantial progress could be made in trade facilitation and reducing non-tariff barriers, this could make the Customs Union positive for Kazakhstan and other potential Central Asian members. Unfortunately, so far the Customs Union has made these matters worse. On the other hand, Russia’s accession to the World Trade Organization will eventually substantially reduce the transfers from Kazakhstan to Russia, but this will need a strong political commitment from Russia which we have not yet seen. If that Russian political leadership is forthcoming, the Eurasian Customs Union could nonetheless succeed where its predecessor has failed.

In January 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union. Two years later, the three countries agreed to even closer economic ties, by signing the agreement to form a “common economic space.”  Regarding tariffs, the key change was that the three countries agreed to apply the tariff schedule of the Customs Union as their common external tariff for third countries. With few exceptions, the initial common external tariff schedule was the Russian tariff schedule. Kazakhstan negotiated exceptions from the common external tariffs for slightly more than 400 tariff lines, but was scheduled to phase out the exceptions over a period of five years (World Bank, 2012). In addition, the members agreed to have the Customs Union determine the rules regarding sanitary and phyto-sanitary standards (SPS) and standards on good. Fearing transshipment of goods from China through Kazakhstan and from the European Union through Belarus, Russia negotiated and achieved agreement on stricter controls on the origin of imports from countries outside of the Customs Union. The common economic space (CES) stipulates that, in principle, there will be free movement of labor and capital among the countries, there will be liberalization of services on the CES and coordination of some regulatory policies such as competition policy.

In February 2012, the Eurasian Economic Commission began functioning. It is intended to act as the regulatory authority for the Customs Union in a manner similar to the European Commission for the European Union.

The Economics of Tariff Changes — Gains for Russia and Losses for Kazakhstan

Some proponents of the Eurasian Customs Union have argued that as a result of the Customs Union firms in the three countries will have improved market access through having tariff free access to the markets in all three countries. Prior to 2010, however, along with other countries in the Commonwealth of Independent States (CIS), the three countries had agreements in place that stipulated free trade in goods among them. Thus, the Customs Union could not provide improved market access due to reducing tariffs on goods circulating among the three countries.

Since the common external tariff was essentially the Russian tariff, there was little change in incentives regarding tariffs in Russia. The big change occurred in Kazakhstan, who had a much lower tariff structure than Russia prior to implementing the Customs Union tariff. Despite the exemptions, Kazakhstan almost doubled its tariffs in the first year of the Customs Union (see World Bank, 2012). The increase in tariffs on many items which were not produced in Kazakhstan but produced in Russia, led to a substantial increase in imports from Russia and displacement of imports from Europe. Many of Russia’s manufacturing firms, which were not competitive in Kazakhstan prior to the Customs Union, were now able to expand sales to the Kazakhstani market. This represents gains for Russian industry.  Given the deeper manufacturing base in Russia compared with most of the CIS countries and the resulting uneven benefits of the common external tariff in favor of Russia, acceptance of the common external tariff has been a fundamental negotiating position of Russia regarding acceptance of members in the Customs Union.

Some cite the expanded Russian exports in Kazakhstan as evidence of success of the Customs Union. But the displacement of European imports, to higher priced or lower quality imports from Russia, represents a substantial transfer of income from Kazakhstan to Russia and is an example of what economists call “trade diversion”. Moreover, it is the reason the World Bank (2012) has evaluated the tariff changes of the Customs Union as a loss of real income for Kazakhstan.

Furthermore, the three countries together (and even a broader collection of CIS countries) constitute too small a market to erect tariff walls against external competition. They would lose the benefits of importing technology from advanced countries and would rely on high priced production from within the Customs Union. Some would argue that there are political benefits of trade to be taken into account, but experience has shown that when a customs union is inefficient and the benefits and the costs of the customs union are very unequal, the customs union can inflame conflicts (see Schiff and Winters, 2003, 194-195).

Non-Tariff Barriers — Extremely Costly Methods of Regulating Standards Worsened by the Customs Union

Non-tariff barriers, in the form of sanitary and phyto-sanitary (SPS) conditions on food and agricultural products and technical barriers to trade (TBTs) on goods, are a very significant problem of the Customs Union. There are standards based trade disputes between Belarus and Russia on several products, including milk, meat, buses, pipes and beer (see Petrovskaya, 2012). Anecdotal evidence indicates that Kazakhstani exporters complain bitterly regarding the use by the Russian authorities of SPS and TBTs measures, either to extract payments or for protection.

If the Customs Union could make substantial progress on reducing these barriers, it would be a significant accomplishment. My colleagues and I have estimated that progress on the non-tariff barriers and trade facilitation could outweigh the negative impact of the tariff changes for Kazakhstan (see World Bank, 2012). Unfortunately, so far the Customs Union has taken a step backward on both non-tariff barriers and trade facilitation.

A big problem in reducing standards as a non-tariff barrier is that standards regulation, in all three countries, is still primarily based on the Soviet system. As a holdover from the Soviet era, mandatory technical regulations are employed where market economies allow voluntary standards to apply. This regulatory system makes innovation and adaption to the needs of the market very costly as firms must negotiate with regulators when they want to change a product or how it is produced. Legislation in both Russia and Kazakhstan calls for conversion to a system of voluntary standards, but this is happening too slowly in all three countries. The problem is that the Customs Union has worsened the situation. Technical regulations are now decided at the level of the Customs Union, so firms that previously negotiated with their national standards authority, have had to now get agreement from the Customs Union. This has reportedly caused further delays, impeding innovation and the ability of firms to meet the demands of the market.

A second problem with efforts to reduce the non-tariff barriers is that the Customs Union is trying to harmonize standards of the three countries by producing mandatory technical regulations.  The alternative is to use Mutual Recognition Agreements (MRAs). Experience has shown that no customs union has been able to broadly harmonize standards based on mandatory technical regulations, with the exception of the European Union. In fact, even in the European Union, they have had to use MRAs and only harmonized technical regulations after decades of work. While each member of the Customs Union is expected to create a system of mutual recognition of certificates of conformity, these certificates are not presently recognized in the other countries of the Customs Union. There is little hope for a significant reduction in standards of non-tariff barriers unless the system of mutual recognition is more widely recognized and adopted.

Trade Facilitation —Participation in International Production Chains Made More Difficult by the Customs Union

Customs posts between the member countries have been removed and this has reduced trade costs for both exporters and importers in the three countries. Russia’s concerns regarding transshipment have, however, led to an opposite impact on trade with third countries, i.e., the costs of trading with countries outside the Customs Union have increased. Participation in international production chains has become a key feature of modern international production and trade. If goods cannot move easily in and out of the country, multinational firms will look to other countries to make their foreign direct investment and for international production sharing. Addressing this significant problem will take a change of emphasis on the part of Russia.

Russian WTO Accession —Liberalization That Will Significantly Reduce Transfers to Russia

It has apparently been agreed by the Customs Union members that the common external tariff of the Customs Union will change to accommodate Russia’s WTO commitments. As a result, the applied un-weighted average tariff will fall in stages from 10.9 percent in 2012 to 7.9 percent by the year 2020 (see Shepotylo and Tarr, forthcoming).[1]  This will have the effect of lowering the trade diversion costs of Kazakhstan. In addition, the Customs Union will be expected to adapt its rules on standards to conform to commitments Russia made as part of its WTO accession commitments. In the case of Belarus, it remains to be seen if it will implement the changes, as this will increase competition for its industries.

Conclusion — the Need to Russia to Exercise Political Leadership for Standards and Trade Facilitation Reform for Success of the Customs Union

In 1996, the same three countries formed a customs union. Later the same year, they were joined by Kyrgyzstan, then by Tajikistan and in 2005 by Uzbekistan. As Michalopoulos and I (1997) anticipated, the earlier Customs Union failed because it imposed large costs on the Central Asian countries, which had to buy either lower quality (including lower tech goods) or higher priced Russian manufactured goods under the tariff umbrella. The present Customs Union also started with the Russian tariff, which protects Russian industry and suffers from the same problem that led to the failure of the earlier Customs Union. Nonetheless, the present Customs Union could succeed. Crucially, due to Russia’s accession to the WTO, the tariff of the Customs Union will fall by about 40 to 50 percent.[2]  This will make the Customs Union a more open Customs Union, very significantly reduce the transfers from Kazakhstan to Russia, and thereby reduce the pressures from producers and consumers in Kazakhstan on their government to depart from enforcement of the tariffs of the Customs Union.  Further, the present Customs Union aims to reduce non-tariff barriers and improve trade facilitation, as well as it has “deep integration” on its agenda, i.e., services liberalization, the free movement of labor and capital and some regulatory harmonization. Although, to date, the Customs Union has moved backwards on non-tariff barriers and trade facilitation, one could optimistically hope for substantial progress. In the important area of non-tariff barriers, given the common history of Soviet mandatory standards, Russia will have to take the lead in moving the Customs Union toward a system of voluntary standards where no health and safety issue are involved, and toward a system of mutual recognition agreements and away from commonly negotiated technical regulations. On trade facilitation, Russia will have to reverse its pressure and find a way to allow the freer movement of goods with third countries while addressing its transshipment concerns.

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References

  • Michalopoulos, Constantine and David G. Tarr (1997), “The Economics of Customs Unions in the Commonwealth of Independent States,” Post-Soviet Geography and Economics, Vol. 38, No. 3, 125-143.
  • Petrovskaya, Galina (2012), “Belarus, Rossia, Ukraina. Obrechennye na torgovye konflikty” (Belarus, Russia, Ukraine. Doomed for trade conflicts), Deutsche Welle, June 14. www.dw.de/dw/article/0,,16023176,00.html.
  • Schiff, Maurice and L. Alan Winters (2003), Regional Integration and Development, Washington DC: World Bank and Oxford University Press.
  • Shepotylo, Oleksandr, and David G. Tarr (2008), “Specific tariffs, tariff simplification and the structure of import tariffs in Russia: 2001–2005,” Eastern European Economics, 46(5):49–58.
  • Shepotylo, Oleksandr, and David G. Tarr (forthcoming), “Impact of WTO Accession on the Bound and Applied Tariff Rates of Russia,” Eastern European Economics.
  • Shymulo-Tapiola, Olga (2012), “The Eurasian Customs Union: Friend or Foe of the EU?”  The Carnegie Papers, Carnegie Endowment for International Peace, October. Available at: www.CarnegieEurope.eu,
  • World Bank (2012), Assessment of Costs and Benefits of the Customs Union for Kazakhstan, Report Number 65977-KZ, Washington DC, January 3, 2012. Available at: http://documents.worldbank.org/curated/en/2012/01/15647043/assessment-costs-benefits-customs-union-kazakhstan

[1] The final “bound rate” of Russia is higher at 8.6 percent on an un-weighted average basis; but there are about 1,500 tariff lines where the applied rate of Russia is below the bound rate.   The applied weighted average tariff will fall from 9.3 percent in 2012 to 5.8 percent in 2020.

[2] Russian tariffs fall more on an un-weighted average basis than they do on a weighted average basis. See Shepotylo and Tarr (forthcoming).

Corruption in Eastern Europe as Depicted by Popular Cross-Country Corruption Indicators

Posted on October 15, 2012 | Policy Brief

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In recent years, variously defined indicators of corruption from different sources have aimed at raising awareness about corruption and to provide researchers with better data for analyzing the causes and consequences of corruption. Most of them have achieved spectacular popularity, and are regularly cited in news reports on corruption around the world. However, in a 2006 study for the World Bank, Stephen Knack warns that the particular properties and limitations of these indicators are often neglected by data users, often leading to wrong interpretations and sometimes puzzling disagreements about the actual situation in a country or a region and its changes over time. The first part of this brief summarizes the main conclusions of this study; the second part presents updated data from different sources on recent corruption trends in the new EU members and the neighbors to the east, as a clear exemplification of the issues discussed.

Existing corruption indicators differ in many ways: where the original information or evaluation comes from, how they are built, who are their constituencies or audiences, as well as which of the many aspects of corruption they intend to capture. For these reasons, no single indicator or data source is best for all purposes.

The corruption indicators can be subdivided into three main groups: those based on surveys, either of firms or households, those reporting expert assessments, and finally, the recently popular composite indexes.

Two examples of firms’ surveys that will be presented below are the Business Environment and Enterprise Performance Survey (BEEPS) and the World Economic Forum (WEF) “Executive Opinion Survey”. Similar enterprise surveys have been conducted by the World Bank and in the IMD World Competitiveness Yearbook. However, BEEPS and WEF are more systematic and better comparable across countries and years, have broader coverage and disclose more information about their definitions and methodology, which makes them, in a sense, more research-friendly.

Surveys are relatively well-suited for evaluating the administrative corruption since they measure the prevalence of corruption as experienced by users of government services. They can also measure some aspects of state capture by asking about perceived undue influence over laws and regulations that affect business. However, surveys are definitely less effective in assessing the prevalence of corrupt transactions that occur entirely within the state, for example when politicians bribe bureaucrats or when funds are illegally diverted. Many types of conflict of interest are also not easily captured by surveys. For example, the equity stakes of public officials or employment promises to them by the firms (World Bank, 2000).

Expert assessments of corruption have been most widely used for comparisons across countries and over time because of bigger coverage in both dimensions. A large and growing number of organizations provide such assessments. Some examples are Freedom House’s Nations in Transit (NIT), the International Country Risk Guide (ICRG), the World Bank’s Country Policy and Institutional Assessment (CPIA). Corruption ratings from these sources are based on the assessment by a network of correspondents with country-specific expertise. In some cases, the final ratings are subsequently determined centrally by a smaller group of people. The organizations that are behind these indicators may be very different, with potential implications for what their ratings are measuring. Some are advocacy NGOs. Others are for-profit companies marketing their product to multi-national investors and paying subscribers. Most subscribers to the ICRG, for example, are more interested in conditions faced by foreign investors than in those faced by local residents. Corruption ratings produced by development agencies are also potentially influenced by their constituents (if for example they take into account the consequences for funds allocation decisions or relations with local partners).

An important difference as compared to the firms or households surveys is that corruption assessments place less emphasis on experience and more on perceptions. Moreover, the respondents in a firms’ survey can be asked more specific and objective questions because they comprise a more homogeneous group. For example, a typical question can be “Was an informal gift or payment expected or requested to this establishment, in reference to the application for an electrical connection?” (from the BEEPS 2009 questionnaire). Instead, a questionnaire directed to a group that includes public officials, academics, journalists, etc. must frame questions in such a way that they can be answered meaningfully by all of them, which necessitates broader questions.

More recently, composite indexes have gained popularity. Well known examples include Transparency International’s widely-cited “Corruption Perceptions Index” and the World Bank Institute (WBI) “Control of Corruption” index (Kaufmann, Kraay and Mastruzzi, 2008). Although the statistical methods used to produce them vary somewhat, both indexes standardize several corruption indicators such as ICRG, CPIA and even survey outcomes, to place them on a comparable scale, then aggregate them, so as to obtain a single value for each country. As a result, composite indexes suffer from the same problem as the corruption measures from individual sources such as ICRG, NIT or CPIA: if any component of a composite index is constructed in an opaque manner, the composite index will be opaque as well. Further limitations are introduced by the process of aggregation. Composite indexes have no explicit definition, but instead are defined implicitly by what goes into them. The sources used in constructing these composite indexes change over time, and from country to country in a given year. For any pair of countries the index values are very likely to reflect differing implicit definitions of corruption.

The standardization procedure used to place different indicators on a common scale precludes the ability to track changes meaningfully over time.  A final issue with the composite indexes is the interdependence of expert sources. If expert assessments display high correlations driven by the fact that they consult each other’s ratings – or that they all base their ratings on the same information sources – this can undermine the main premise of the aggregation methodology that more sources produce more accurate and reliable estimates. The addition of another expert-based source containing little new information – relying on the same information sources as its competitors, or even checking their ratings – can actually reduce the accuracy of the composite index.

A general caveat in the use of corruption indicators, beyond the weaknesses of individual types discussed above, concerns the importance of their intended use. For some purposes, broader measures may be preferable: for example, a researcher studying the relation between corruption and economic growth may have no particular view on exactly which aspects of corruption most impair growth, and is hence content with a general measure. For other purposes, however, narrower measures may be required. For example, a donor funding projects in a country may be interested in a measure of corruption in public procurement, while a donor providing budget support might prefer a measure of the likelihood of funds diversion to unintended purposes. The design of effective anti-corruption reforms requires narrow measures to identify specific problem areas and track progress over time, and so on.

Finally, it is important to remember that some indicators are more suitable than others for measuring changes over time. Broad, multi-dimensional indicators are potentially problematic in this respect, because there is no way to ensure that the implicit weights given to the various dimensions do not change over time. Some indicators have no fixed and explicit criteria provided for each ratings level, so there is no way of ensuring that the same numerical rating means the same corruption level from one year to the next.

With this background in mind, it is easy to understand why, while it is often possible to form a broad assessment on the general situation and trends in corruption, different sources might often disagree markedly on specific countries, and in particular on which countries have improved and which have not. The evidence from different sources on recent corruption trends reported below provides a clear example in this respect. We are going to focus on the new EU members (Estonia, Bulgaria, Romania, Slovenia, Slovakia, Czech Republic, Hungary, Poland, Lithuania, Latvia), indicated as EU-group, and the non-Baltic former Soviet Republics (Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan), indicated as CIS-group [1].

Levels and Trends in Corruption for the New EU-Members and the Eastern Neighbors

The Business Environment and Enterprise Performance Survey (BEEPS) is a nationally-representative survey of business firms assessing corruption and other problems faced by businesses in the ECA region. The BEEPS is sponsored by the European Bank for Reconstruction and Development (EBRD) and the World Bank, and has covered almost every country in the region since 1999. The two most recent waves with a good coverage of our countries are 2005 and 2009. The surveys typically contain multiple questions pertaining to narrower aspects of corruption, and so do the BEEPS.

Looking at the outcomes of the BEEPS, the most dramatic change between 2005 and 2009 is in the “bribe tax”, the share of annual sales paid in “informal payments or gifts to public officials to get things done”. The average in the new EU members increased more than four-fold from .72% to 3.11% of firm revenues. A positive value for the bribe tax was reported by 28.12% of firms in 2005, increasing to 62.1% in 2009, although this might simply reflect an increasingly open attitude in answering the survey. The corresponding increases for the CIS-group are more moderate, from 1.31% to 4.26% bribe tax and from 40.7% to 60.1% of firms declaring positive values. The only country where the bribe tax did not increase is Poland, although data for 2009 are not available for Belarus, Georgia, Tajikistan, Ukraine and Uzbekistan. The biggest increases are reported in Estonia and Slovenia, although they started from the lowest levels within the EU-group (0.29 and 0.17 respectively). These are two countries that, as we will see later, are consistently singled out as the best performers by the other indicators. This apparent contradiction might be due to a different reporting attitude in these countries. Similarly, the lowest level of bribe tax in the CIS-group for 2009 is reported in Russia (1.31), while the highest levels (8.8) in Azerbaijan, a country that according to other indicators is doing relatively well.

Besides the bribe tax, among the numerous other questions on corruption issues in the BEEPS, most show evidence of a modest improvement.  For example, in 2005 about 13.4% (24%) of firms in the EU- (CIS-) group reported that paying bribes was frequently, usually or always necessary to get things done, and this figure is down to 6.75% (18.8%) in 2009.  Most questions about specific public services also show evidence of a decline in the incidence of bribe paying, e.g. when paying taxes, dealing with customs and the courts.

The assessment on the fairness of the courts got worse in both areas, but at the same time it is considered a big obstacle by fewer businesses as compared to 2005. Also, the share of businesses that admit to paying a kickback payment to obtain a government contract, and the share of sales required for this payment, decreased over this period, markedly for the new EU members, though only slightly for the former Soviet Republics.

Slovenia and Estonia are the champions also in this respect, as well as Armenia in the CIS-group. Kickback payments are most expensive in Latvia (3.06% of sales) and Russia (4.65%). Corruption was however cited as the biggest obstacle to doing business by an increasing share of firms everywhere [2]. In the CIS-group as a whole, the share of firms that consider corruption the biggest obstacle to business increased from 6.4% in 2008 to 8.16% in 2009. The individual countries with the biggest shares are Romania (9.5%) and Azerbaijan (17.8% of firms), respectively in the first and second group. Ironically, the biggest increase between 2005 and 2009 is in Poland, the only country where the reported bribe tax actually decreased. This highlights how tricky it is to aggregate the information from these sources, given that very different aspects of the situation in a country are captured by each item.

More difficulties emerge with respect to evaluating change over time since different measures often move in opposite directions for a given country. For example, both Hungary and Azerbaijan experienced the biggest increases in bribe tax, but also a sharp decrease in kickback payments for government contracts and it is hard to balance the one against the other. This is also a reason why the picture emerging from these data does not necessarily agree with the aggregate indicators discussed below, although they are in part based on the very same outcomes of the surveys.

The World Economic Forum (WEF) “Executive Opinion Survey” is another cross-country survey of firm managers. The sample in each country is selected with a preference for executives with international experience, who tend to be from larger and exporting firms. The questions are designed to elicit “the expert opinions of business leaders” on corruption and other issues, and focus much less on direct firms’ experiences. Moreover, the aim is solely to produce country-level measures of the business climate, and not firm-level analyses. Cross-country rankings on several corruption questions from this survey are published in WEF’s annual Global Competitiveness Report. Ratings are computed as the simple average of all executives’ responses.

The 2011 WEF data include 7 variables related to corruption, all scaled from a low value of 1 to a high value of 7: Diversion of public funds, Irregular payments and bribes, Judicial independence, Favoritism in decisions of government officials, Burden of government regulation, Transparency of government policymaking and Ethical behavior of firms. The sample includes a total of 142 countries, including many developed countries, and covering most of the countries we have been addressing above. Both the average rating and the average rank are slightly higher for the EU-group, but the similar average hides quite a bit of variation between different countries and in different dimensions.

In particular, the CIS-group ranks higher with respect to both the extent to which government regulation is perceived as a burden for business, and the perceived transparency of policymaking, and the two averages are extremely close when it comes to the assessment of favoritism in officials’ decisions. The largest difference between the two groups seems to be the prevalence of irregular payments and bribes, in accordance with the evidence from the BEEPS.

Nevertheless, some countries in the second group, like Georgia and Tajikistan, have a higher average ranking than most of the new EU members and position themselves extremely well even in global terms in some dimensions. For example, Georgia is number 7 in the world with respect to the (absence of) burden of regulation, although not many more reach the upper quartile or even the upper half of the ranking. On the other hand, some of the new EU countries do very poorly in some respects, like the Slovak Republic ranking 135th (of 142) in terms of favoritism by public officials and the Czech Republic being 124th in diversion of public funds.

Compared to 2010, the EU-group saw a slight worsening in their rating, while the CIS-group improved. More in detail, half of the countries in the first group went down, including some quite substantial drops (Estonia, Poland and Slovenia, down by more than 1 point) while the others improved, though not spectacularly. All but one country (Georgia) in the second group improved their average rating from 2010, the biggest progress taking place in Azerbaijan with 1.5 points.

As opposed to the surveys discussed above, the NIT, CPIA and ICRG each provide a single measure of corruption, intended to reflect a mix of various aspects of corruption.

The NIT index is mostly concerned with the impact of corruption on business. It measures the corruption with on a 1-7 scale, 1 being the best possible rating and 7 being the worst, with quarter-point increments allowed.

The ranges of variation in the ratings during the last five years for the two regions do not overlap at all: all of the new EU countries positioned themselves always below a score of 4, while all the countries in the CIS-group stayed well above this threshold. This implies that the best performers within this group (Georgia and Armenia) have a consistently lower rating than the worst performing EU countries (Bulgaria and Romania). However, the trend over time in this period is very similar across the two regions. Both the averages are very flat, with a slight upward trend (i.e. to the worse). In the EU-group, this reflects the fact that five countries saw worsening in their rating, three saw no change at all and only two (Estonia and Lithuania) a slight progress. The lowest (and hence best) score is Estonia and Slovenia’s 2.25. Also in the other group only two countries – Armenia and Georgia – improved their rating. They also have the lowest scores in the region, 5.25 and 4 respectively. Six countries kept a stable rating while four got worse. The highest (and hence worst) score, 6.75, goes to Turkmenistan and Uzbekistan.

The CPIA question “Transparency, Accountability and Corruption in the Public Sector”, is assessed on a 1-6 scale, where a lower level corresponds to a worse situation in terms of corruption. This index focuses on less developed countries, so the EU-group is not covered. The most recent available data are for the period 2008-2011, during which four out of the six developing regions in the world improved.

In contrast to the stagnation with slight worsening described by the NIT, the ECA region is the one that sees the steepest improvement in the CPIA rating, increasing to 2.87 in 2011. This contrasting assessment can be explained by the fact that only six of our CIS-group countries are included in the CPIA sample: Armenia, Azerbaijan, Georgia, Kyrgyzstan, Moldova and Uzbekistan. If we look at the average only in those six, also the NIT rating improved by about the same relative amount (1.5% of the value range). The two indexes do not agree, though, on the individual countries that they reward with a higher or punish with a lower score. In particular, only Georgia improved in both ratings, while Uzbekistan, for example, got a better CPIA score but a worse NIT score; Armenia and Azerbaijan, that respectively improved and worsened in the NIT assessment, are completely stable in the CPIA, and the opposite is true for Moldova.

Unlike the CPIA, the ICRG sample includes most developed countries. The focus of the ICRG is to establish the relative incidence of corrupt transactions. Its corruption ratings range from a minimum value of 0 to a maximum of 6, where higher rating corresponds to a better situation.

The latest available data are however not as recent as for the other indicators discussed here. In the three years up to 2007, the mean rating remained stable in both groups, around 2.5 in the new EU members and 1.8 in the former soviet countries, although only three of eleven countries from this group are included. Also in this case, the two ranges of values for the two regions do not overlap.

In the EU, Lithuania’s rating went down while Poland’s went slightly up. Estonia and Slovenia are again the best performers together with Hungary. The lowest rating in the region goes to Bulgaria, just as in the NIT evaluation, together with Latvia. All the three countries in the CIS-group made improvements, although from dismally low levels. This is not in contrast to the other assessments, since the data refer to an earlier period. The highest score of the three is Moldova’s (low) 1.5.

Both of the widely-known composite indexes of corruption (TI and WBI index) show large differences between the EU members and their eastern neighbors. The average score, varying from 1 to 10 and from -2.5 to 2.5, respectively, are much higher for the first than for the second group. Similarly the ranks – from 1 (best) to 182 (worst) for TI, reversed scale from 0 (worst) to 100 (best) for WBI – reflect a much worse situation in the CIS-group. However, the former Soviet countries improved their WBI rank between 2009 and 2010, as opposed to the new EU members which saw a slight drop. Although changes over time for these indexes should be taken with caution, this is coherent with the 2010-2011 comparison in the WEF.

The two indexes also agree on best and worst performer, respectively; Estonia and Bulgaria in the first group (Slovenia was best performer in 2009 according to WBI) and Georgia and Turkmenistan (on par with Uzbekistan according to TI) for the second. Both the largest improvement (Lithuania) and the largest backslide (Slovenia) from 2009 happened in the EU-group, but a larger share of the CIS-group countries experienced improvements, which is reflected by a smaller drop in the average score. The main difference between the two indexes is that WBI uses more sources and reports a value even for cases when only one source is available (TI requires a minimum of three sources), obtaining as a consequence a broader coverage. Otherwise, the two indexes are quite correlated, and subject to the same problems.

Summing up, all the indicators agree, not surprisingly, that the situation looks much brighter in the EU-group than in the CIS-group. Although, it is not clear that they are keeping up the good work in the most recent years. There is relatively more evidence of improvement over time in the CIS-group, despite the dismal starting point. Only few countries emerge unequivocally as good or bad performers. One example being the coherently positive performance of Georgia; for most of the other countries, the picture is mixed.

Given the variety and breadth of indicators, this conclusion was very much expected. Corruption is such a broad and multidimensional phenomenon that different indicators and different assessments are bound to result in different, often contrasting pictures. Unless one is very clear on which specific aspect is in focus, and sticks consequently with one particular measure, any conclusion based on general comparisons of corruption indicators both between countries and over time should be taken with serious cautiousness.

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References

[1] Turkmenistan and Uzbekistan are only unofficial members of the official Commonwealth of Indipendent States (CIS), and Georgia is not a member any longer since 2009.

[2] Bigger obstacles in the EU-group are the level of tax rates (19% of firms), access to finance and an inadequately educated workforce (11% each), along with political instability (10%). The biggest concern for most firms in the CIS-group is instead market practices from competitors in the informal sector.

Political Instability in Fragile Democracies: Political Cycles Kyrgyz Style

Posted on September 24, 2012 | Policy Brief

Political Cycles Kyrgyz Style Image

Democratization is rarely a straight and predictable process. Freedom House data from the Central and Eastern European Countries (CEEC) and the countries of the Commonwealth of Independent States (CIS) since 1991 reveals two distinct patterns. In one set of countries, democratization took root quite quickly and the transformation of political institutions seems quite deep and sustainable. In the other countries, the road to democratization, if ever started, has been much more partial and full of reversals. Among the CIS countries, none is regarded as free by Freedom House in 2012, four are regarded as partly free (Armenia, Kyrgyz Republic, Moldova and Ukraine), while the remaining seven countries (Azerbaijan, Belarus, Kazakhstan, Russia, Tajikistan, Turkmenistan, and Uzbekistan) are regarded as non-free. There has also been volatility over time within countries. Russia and Belarus have seen their score steadily deteriorating, while countries on the Balkan and south-east Europe have seen gradual improvements. With the lack of consolidated democratic institutions has also typically followed much political instability. Frequent changes in power, civil unrest, popular revolutions and military conflicts have pervaded countries like Ukraine, Georgia, and the Kyrgyz Republic. In other nations, repressive leaders have put a lid on visible instability, but at the cost of political rights and a fair judiciary system. In both cases, the economy has suffered as instability has deterred investors looking for a predictable environment guided by transparent rules of the game implemented equally for all. Corruption has flourished and political connections and nepotism has determined the opportunities for economic success.  

Shock “Therapy” the Market Way

Posted on September 5, 2011 | Policy Brief

Policy Brief Image with Tall Buildings Representing Transition, Market Economy and Shock Therapy

Twenty years after transition began and the merits of “shock therapy” were argued the most hotly, (former) transition countries are hard hit by global shocks originating in Western market economies. Although discussions now focus on troubles in Western developed countries, countries in Eastern Europe and the CIS were particularly hard hit in 2008/09. This should not come as a surprise given their pre-crisis vulnerabilities. As transition countries opened up to trade and capital flows—like other countries that want to reap the benefits of the global economy—they also became subject to the shocks that hit open economies. The very high current account deficits and/or reliance on commodity exports prior to the crisis exposed many countries in this region to two of the shocks that have been most costly to emerging markets and developing countries in the past, namely sudden stops in capital flows and terms of trade shocks. However, the lesson from the crisis should not be that opening up is bad in general, but that shock absorbers should be put in place to minimize the damage market-based “shock therapy” can do.

Shock Therapy and Transition

It is now twenty years since the failed 1991 coup that led to the breakup of the Soviet Union and started the transition from plan to market in (then) communist countries. A few years earlier, in 1989, the Stockholm Institute of East European Economies was set up at the Stockholm School of Economics. Its first director was Anders Åslund who was a strong proponent of shock therapy (see Åslund 1992). The basic idea was that a rapid transition from plan to market through changing institutions, privatizations and other liberal reforms would minimize the cost of transition. There are still different views on the merits of shock therapy as a reform strategy, but this brief will not address this debate.

In the wake of the academic debate of shock therapy, the broader research agenda was put under the heading “transition economics”, which became a new field in economics. This also lead Erik Berglöf, the new director of the Stockholm Institute of East European Economies, to change the institute’s name to the Stockholm Institute of Transition Economics, or SITE for short, the name we still use today. The economics of transition was also the title of the fifth Nobel symposium in Economics (Berglöf and Roland, 2007).

The use of the label “transition economics” may see a revival in the aftermath of the Arab spring. However, the economic issues that now face the (former) transition countries are much the same issues that emerging markets, developing countries and also advanced countries around the world grapple with. This is not least true when we look at what has happened in the current crisis.

Below this brief will argue that the shock therapy ex-communist countries were subject to in the early 90’s has been changed to the shock “therapy” open market economies around the world have been facing for a very long time. And just as there were heated debates on what the right therapy was then, the world is now debating what the “therapy” for the current shocks should be.

Output Drops Around the World

Significant drops in output have not only been observed in countries transitioning from plan to market but have occurred with regularity throughout modern history in countries around the world. The figure from Becker and Mauro (2006) shows the frequency of countries that entered into a major output loss event—defined as a cumulative loss of at least 5 percent of initial GDP in an event that last at least two years—during the 20th century. In the after-war period, a relative modest 5 to 10 percent of countries have entered into a period of significant output loss. However, in the great depression, almost half of the countries for which data is available entered into a period of significant loss of output.

Since the methodology used in Becker and Mauro follows countries until they return to pre-crisis levels of GDP, it is too early to provide a full account of what the number would be in the current crisis that started in 2008. Nevertheless, it is straightforward to compute how many countries have experienced output losses in 2008/09 (which is the first criteria to satisfy in the Becker and Mauro measure) and this number is close to fifty percent, on par with the great depression. This is not to say that the total output loss will be as high as in the great depression, but it clearly tells the story that this is the worst global crisis we have seen since then in terms of how many countries have been affected. The share of countries affected at the onset of this crisis varied greatly in different parts of the world and at different levels of development. The most surprising statistic from this crisis is that 90 percent of advanced economies experienced an output drop whereas “only” 40 percent of emerging market countries did. The regional differences between emerging markets are also striking; 85 percent of countries in Central and Eastern Europe (CEE) and more than half of CIS countries saw output decline, far above other regions.

Shocks 2.0

The Becker and Mauro paper also looks at the correlates of major output drops and focuses on a number of domestic and external macro, financial and political shocks as triggers of output collapses. A large dataset of shocks and output drops is used to compute the frequency of the different shocks; the likelihood that a particular shock leads to an output collapse (as defined above); and the output loss associated with such event. These numbers are then used to calculate how much different types of shocks have cost in terms of lost output for emerging markets and developing countries. The scale in the chart shows how much it would be worth in terms of GDP per annum to avoid a certain shock.


For emerging market countries, the worst shock has been sudden stops in capital flows that cost almost a percent of GDP per year. Unless countries have high levels of foreign exchange reserves, sudden stops in capital flows mean that (often large) current account deficits have to contract and even become surpluses quickly because there is no external financing available for a deficit. This, in turn, affects domestic production and demand and can have a serious effect on output. Add to this the financial uncertainty that is often associated with sudden stops and it makes it the number one shock to worry about for emerging market countries integrated in the global economy and financial markets.

Less developed countries are in several cases dependent on concentrated commodity exports to generate foreign exchange. This makes this group of countries more vulnerable to terms-of-trade shocks. The estimates of how costly these shocks are range from around half a percent of GDP per year, as is shown in the chart, to around 2.5 percent of GDP if a more extensive sample including very long-lasting output events is used.

Other shocks like currency, political and debt crisis have also been associated with significant losses in output, but tend to occur less frequently, which makes the cost per year smaller.

The 2008/09 Crisis

As was mentioned previously, not enough time has passed since the start of the crisis in 2008 to use the methodology in Becker and Mauro to compute cumulative output losses since many countries are still below their pre-crisis GDP levels. However, projected losses can be computed by using the IMF’s World Economic Outlook forecasts of GDP growth rates. If we then rank the countries according to worst output performance, CEE and CIS countries dominate the “top-ten” list with seven entries. Latvia at the top of the list is projected to lose a cumulative 40 plus percent of pre-crisis GDP during the 11 years it is projected to take the country to return to the GDP level it enjoyed in 2007. The other Baltic countries, Ukraine and Armenia have also been hit particularly hard in this crisis. Russia and Romania are close behind three advanced countries that had to seek IMF and EU assistance to deal with the crisis; Ireland, Iceland and Greece.

The forecasts used for these calculations are constantly being revised and the ranking of countries based on actual outcomes will certainly look different years from now. We can only hope that the current forecasts are too pessimistic although right now many revisions go in the wrong direction.

Could we have predicted what countries were hit in this crisis based on history? Based on the Becker and Mauro (2006) paper: Yes and no. “No” regarding the fact that overall, many advanced countries were hit this time. The paper found that in the past, the frequency of output collapses have decreased with the income level of countries, contrary to what has been the case this time. “Yes” for the fact that CEE and CIS countries were hit significantly more that other emerging markets since they were particularly vulnerable to the sudden stops and terms-of-trade shocks that the paper showed often are associated with severe output losses.

The signs of vulnerability in CEE and CIS countries were easy to see, but warnings ignored; the Baltic countries and Romania had double-digit current account deficits that where to a large part financed by external debt. For example, current account deficits in Latvia passed 20 percent of GDP in some years, far beyond the 4-5 percent deficits some Asian countries had prior to the Asian crisis in 1997. Ukraine also had large current account deficits and concentrated (metal) exports on top of that, exposing the country to both sudden stops and terms-of-trade shocks.

Russia’s dependency on energy and mineral exports was also well known, with 80 percent of export revenues coming from this source. However, the pre-crisis boom in oil and mineral prices had made Russian policy makers think this was a strength and not a vulnerability. On top of that, the strong external position of the government and central bank obscured the external financial vulnerabilities that had built up in the private sector. With the sharp decline in oil prices in the crisis, Russia was hit both by a terms-of-trade shock and a sudden stop in capital flows to the private sector.

There were of course individual countries in other regions that were showing vulnerabilities and were hit in the crisis, but the countries in the CEE and CIS region stood out as particularly vulnerable to the shocks that hit emerging market and developing countries in the past. The IMF’s Global Financial Stability Report from October 2008 summarizes these vulnerabilities in its Table 1.5 on macro and financial indicators for emerging markets very well. The shaded boxes that indicate potential problems in the table completely dominated the picture for CEE and CIS countries whereas other regions looked significantly less vulnerable. In short, history told us what shocks matter and the vulnerability indicators clearly showed where the shocks would do most damage.

Therapy 2.0

What are the policy lessons from this? Countries will always be subject to different types of shocks, and the question is how these shocks can best be absorbed to minimize the economic costs. In other words, what is the “therapy” needed to deal with these shocks? A key challenge is to find the policies and tools that strike the right balance between crisis prevention and high sustainable growth. Isolation to protect against external shocks is certainly not the answer.

Early warning systems (EWS) that identify vulnerabilities ahead of time and give policy makers time to reduce these vulnerabilities and thus avoid crisis is of course what everyone dreams of. The IMF and others have worked on various EWS models since the Mexican and Asian crises with mixed success (see Berg, Borensztein and Pattillo, 2005). With this crisis, the G20 and other groups of policy makers have made new calls for developing EWS, at times seemingly unaware of past efforts and the limited success in this area.

However, at the IMF the more formalized or mechanical EWS models are complemented with both bi-lateral and multilateral surveillance with the bulk of the findings made publicly available and communicated to relevant policy makers. These surveillance efforts contain much more information than more limited EWS models and also come with policy recommendation on how to deal with potential vulnerabilities.

There are of course limitations also with the surveillance by the IMF and other international and domestic organizations. First of all, they have to get it right and at the right time. This is far from trivial, not least because of our limited understanding of the links between the financial sector and the real economy. And even when the analysis gets it “right” in the sense of identifying vulnerabilities, it may take a long time before vulnerabilities translate into real problems and during this time, the analysis and recommended policies may seem misguided.

This is linked to the second major issue; to make relevant policy makers (politicians) listen to and take action on the advice. There is a reason Reinhart and Rogoff called their book “This time is different” since this is often the response to warnings from the IMF and others that suggest a party has been going on for too long and the punch bowl needs to be taken away.

Given the limitations of early warnings and surveillance more generally, there remains a strong need to reduce vulnerabilities in a systematic manner and develop tools to deal with the crises that were not prevented. This will require both domestic measures and a strong commitment to international cooperation. The latter part is of course extremely important right now in order to find appropriate solutions (read debt resolutions) to the problems cross-border banking and capital flows have created. It will also be key in setting up the rules for the future: what capital requirements should banks have; (how) should financial transactions or institutions be taxed; how can cross-border supervision be made more efficient; what type of crisis resolution mechanisms should be put in place both at the international and regional levels; etc, etc. Unless there is broad international agreement on these issues they will do little to address the weaknesses that were at the heart of this crisis.

On the domestic side, the usual IMF recommendation of creating a stable macroeconomic environment—with fiscal room to maneuver and a monetary policy that leads to stable prices—is always going to be part of a countries ability to absorb shocks. For countries that are integrated in international financial markets, exchange rate flexibility and a reasonable level of international reserves seem to be advisable. Jeanne and Rancière (2008) analyze optimal foreign exchange reserves for countries that are subject to sudden stops. Becker (1999) instead looked at accumulation of government assets as part of an optimal public debt and asset management strategy in a world with bailouts of the private sector which seems particularly relevant today.

The macro side should of course be combined with strong domestic supervision of the financial sector; structural policies that lead to sustainable growth in a competitive global environment; and strategies in commodity exporters to reduce the vulnerabilities associated with a narrow export base.

Although advanced countries get most of the attention in the international financial press today, emerging market and developing countries should not think that this is a new world were the shocks of the past do not matter to them. They do, so better get ready for “shock therapy” the market way while there still is time.

Bibliography

  • Becker, T., (1999), “Public debt management and bailouts”, IMF WP 99/103.
  • Becker, T. and P. Mauro, (2006), “Output drops and the shocks that matter”, IMF WP 06/172.
  • Berg, A., E. Borensztein, and C. Pattillo, (2005), “Assessing Early Warning Systems: How Have They Worked in Practice?”, IMF Staff Papers, 52:3, 462-502.
  • Berglöf, E. and G. Roland (2007), The economics of transition—The fifth Nobel symposium in economics, Stockholm Institute of Transition Economics (SITE) and Palgrave Macmillan.
  • IMF (2008), Global Financial Stability Report, “Financial stress and deleveraging”, October, Table 1.5 p.46.
  • Jeanne, O. and R. Rancière, (2008), “The optimal level of international reserves for emerging market countries: A new formula and some applications”, CEPR Discussion Papers 6723.
  • Reinhart, C. and K. Rogoff, (2009), “This time is different: eight centuries of financial folly”, Princeton University Press.
  • Åslund, A., (1992) “Post-Communist Economic Revolutions: How Big a Bang?”, Center for Strategic & International Studies, Washington D.C..

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.