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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.

Monetary Policy in Belarus since the Currency Crisis 2011

Posted on October 8, 2012 | Policy Brief

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In the second half of 2010, the National Bank of Belarus carried out a soft monetary policy to stimulate domestic demand. Until March 2011, the country experienced strong economic growth. There was an increase in real incomes with a parallel increase in the negative trade balance and the reduction of international reserves. Stimulating policy became one of the reasons for the formation of a multiplicity of exchange rates on the foreign exchange market. Beginning of March and until the end of October 2011, there was an official and gray currency market in the country. High domestic demand and rapid devaluation processes led to the deployment of an inflationary spiral, which in turn meant a decrease in the growth of real incomes. 

Inter-Regional Convergence in Russia

Posted on October 1, 2012 | Policy Brief

20190408 Capital Flows from Russia Image 02

There was no inter-regional convergence in Russia during the 1990s but the situation changed dramatically after 2000. While interregional GDP per capita gaps still persist, the differentials in incomes and wages decreased substantially. Interregional fiscal redistribution has never played a major role in Russia, so understanding interregional convergence requires an analysis of internal capital and labor mobility. The capital market in Russia’s regions is integrated in a sense that local investment does not depend on local savings. Also, the barriers to labor mobility have come down. The situation is very different from the 1990s when many poor Russian regions were in a poverty trap: potential workers wanted to leave those regions but could not afford to finance their move. After 2000 (especially later in the first decade), these barriers were no longer binding. Overall economic development, as well as the development of financial and real estate markets, allowed even the poorest Russian regions to grow out of the poverty trap. This resulted in some convergence in the Russian labor market; the interregional gaps in incomes, wages and unemployment rates are now comparable to those in Europe.

Russia’s Regions are Finally Converging

Large interregional differences have always been an important feature of Russia’s transition to a market economy. This has been explained by the pre-transition geographical allocation of population and of physical capital that was determined by non-market forces. Soviet industrialization policies often pursued political or geopolitical goals. Even when they reflected economic realities, the economic decision-making was distorted substantially by central planning, price-setting and subsidies. In addition, the allocation of production was intended to serve a different country – the Soviet Union (or even the whole Council for Mutual Economic Assistance countries) rather than Russia alone. Moreover, believing in economies of scale rather than in competition, Soviet planners created many monotowns.[1] These towns, cities or even regions relied on a single industry. Therefore economic restructuring and inter-sectoral reallocation implied not only moving workers or capital between employers in one town, but also required moving workers or capital between cities.

Despite the need for geographical reallocation during the transition to a market economy, the differentials between Russian regions remained high (and even increased!) throughout the 1990s. However, after 2000 (especially later in the first decade) there was substantial convergence in incomes and wages (Figure 1). By 2010, this resulted in reduction of the inter-regional differences in incomes in line with European levels. In Figure 2, while inter-regional differences in Russia are still substantially above those in the US and Western Europe, they are comparable to those in the EU.

Figure 1. Differences among Russian Regions in Terms of Logarithms of Real Incomes, Real Wages, Unemployment, Real GDP Per Capita

Source: Guriev and Vakulenko (2012). Note: All variables measured as population-weighted standard deviations.

 

Figure 2. Income Differentials in Russia, Europe and the US

Note: For the EU and Western Europe the unit of observation is NUTS-2 region.[2]

Interestingly, despite income convergence, there was no convergence in GDP per capita among Russia’s regions. Inter-regional dispersions in GDP per capita remain high not only by European standards, but also by standards of less developed countries. Indeed, in Figure 3, Russia is placed in the international context using the data recently developed by Che and Spilimbergo (2012).

Che and Spilimbergo calculate interregional differences for 32 countries in a compatible way and plot them against GDP per capita (averaged out for 1995-2005, in real PPP-adjusted dollars). Their main finding is that that there is a negative correlation between interregional differences and GDP per capita.

Since Russia was not in Che and Spilimbergo’s dataset, Guriev and Vakulenko (2012) reproduced their calculations for Russia, both for the 1995-2005 average (as they do for the other countries) but also for the individual years 1995, 2000, 2005 and 2010. It turns out that while Russia was “abnormally uniform” in the early 1990s, it did experience substantial divergence in the late 1990s. There was continuing, albeit weaker, divergence even in the early 2000s – so Russia became “abnormally unequal” given its GDP level. Even though there was some convergence late in the first decade, Russia is still “abnormally unequal”. Given the fast economic growth since 2000, Russia should have become substantially “more uniform” – at least given the downward-sloping relationship between income and inter-regional inequality in Che-Spilimbergo’s data.

Figure 3. Russia’s Interregional Dispersion in GDP Per Capita in the International Context
 

Source: Che and Spilimbergo (2012). Note: The trend line is calculated without Russia.

Why didn’t income convergence happen in the 1990s and only start after 2000? Why hasn’t GDP convergence taken place? Large interregional differences are consistent with reduced income, wage, and unemployment differentials if the factors of production (labor and capital) have become more mobile while the productivity differences (due to geography, political and economic institutions, and inherited differences in infrastructure) remain in place. Therefore, in order to understand income convergence, an understanding of labor and capital mobility is needed.

Interregional Labor Mobility in Russia

Andrienko and Guriev (2004) studied internal migration flows in Russia in the 1990s and showed that the lack of convergence was explained by a “poverty trap”. In general, Russians did move from poorer to richer regions. However, in Russia’s very poor regions (in about 30% of the regions hosting about 30% of Russia’s population) the potential outgoing migrants wanted, but could not afford, to leave; so for these regions, an increase in income would have resulted in higher rather than lower outmigration.

What changed since 2000? Why did barriers to mobility come down? There are multiple potential explanations: (i) economic growth simply allowed most of Russia’s regions to grow out of the poverty trap; (ii) the development of financial and real estate markets reduced the transactions costs of moving therefore reducing the importance of the poverty trap; (iii) the development of capital markets increased capital mobility; (iv) federal redistribution reduced interregional differences.

According to Guriev and Vakulenko (2012), federal redistribution played a very minor role, while the other three explanations are consistent with the data. Our analysis of capital flows is, however, limited by the lack of detailed data, but our study of panel data on net capital inflows and investment shows that, first, capital does flow to regions with higher returns to capital and with lower wages and incomes, thus contributing to convergence. Second, investment in Russia’s regions is not correlated with savings which suggests that Russia’s capital market is not regionally segmented. As our data on capital are limited to the period after 2000, we cannot compare the recent years to those during the 1990s, but at least we can argue that recently, the capital market was functioning well and was contributing to convergence.

It is striking to what extent the poverty trap and liquidity constraints used to be, but are no longer, binding for labor mobility. Figure 4 is a graphical illustration of the poverty trap. Based on a semiparametric estimation with region-to-region fixed effects it shows the relationship between income in the origin region and migration (both in logarithm). Each dot on this graph represents migration from one region to another in a given year (during 1995-2010). As discussed above, the relationship is non-monotonic. If the sending region is poor, an increase in income results in higher out-migration; for richer regions, a further increase in income results in lower migration. The peak is at log income equal to 8.7 which amounts to average income equal to exp(8.7) ≈ 6003 in 2010 rubles and 1.02 of the Russian average subsistence levels in 2010. The regions to the left of the peak are in the poverty trap while the regions to the right are in a “normal mode” where liquidity constraints are not a substantial barrier to migration.

While in the 1990s tens of regions were below this threshold (and therefore were locked in the poverty trap), by 2010 only one region was below this threshold. In this sense, overall economic growth allowed Russian regions to overcome liquidity constraints by simply growing out of the poverty trap. We ran additional tests to show that financial development also contributed to relaxing liquidity constraints.

Figure 4. Income in the Origin Region and Migration[3]
 
Note: results of semiparametric estimation

What Next?

Should we be worried about high interregional differentials in GRP per capita? Not necessarily. In order to ensure inter-regional convergence in incomes and wages, convergence in GDP per capita is not required. As long as barriers to labor and capital mobility are removed, mobility (or even a threat of mobility) protects workers. Therefore, the very fact of remaining large inter-regional dispersion in GDP per capita should not serve by itself as a justification for government intervention (e.g. region-specific government investment).

As reducing barriers to mobility is important for convergence, this is exactly where policies can contribute the most. Developing financial and housing markets and improving investor protection are better policies for reducing inter-regional differences in income; these factors have already reduced income differentials among Russian regions.

We should, however, provide an important caveat. Our analysis was done at the regional level. We therefore do not address the sub-regional level and have nothing to say on the need for town-level government interventions. There may well be many cases where individual towns (e.g. so called mono-towns) are locked in poverty traps. In those cases government intervention may be justified and desirable. Our results show that poverty traps did exist in Russia in the 1990s at the regional level. These may well still exist at the town level even now. We cannot extrapolate the quantitative value of the income threshold we identified for the poverty traps from regional level to the town level but our analysis provides very clear qualitative criteria for government intervention. If the average citizen of a town would benefit from moving out but cannot finance the move (e.g. because his/her real estate is worthless), then the government can and should step in through supporting financial intermediaries that could finance the move. Therefore our analysis is fully consistent with the rationale for the government’s mono-towns restructuring program.

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References

  • Andrienko, Yuri, and Sergei Guriev  (2004). “Determinants of Interregional Mobility in Russia: Evidence from Panel Data.” Economics of Transition, 12 (1), 1-27.
  • Che, Natasha, and Antonio Spilimbergo (2012). “Structural reforms and regional convergence.” CEPR Discussion Paper No. 8951.
  • Guriev, Sergei and Elena Vakulenko  (2012). “Convergence among Russian regions.” Background paper for the World Bank’s Eurasia Growth Project.
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[1] Russian law defines monotowns as town where at least 25% employment is in a single firm. Even now, the Russian government’s Program for the Support of Monotowns lists 335 monotowns (out of the total of 1099 Russia’s towns and cities) with the total of 25% of Russia’s urban population.
 
[2] EU (19): Belgium, Czech Republic, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Latvia, Lithuania, Netherlands, Austria, Poland, Portugal, Slovakia, Finland, Sweden, United Kingdom. For EU (19) we consider only those NUTS-2 units for which there is data for each year.  Western Europe: Austria, Belgium, Germany, Ireland, Greece, France, Italy, Netherlands, Norway, Portugal, Finland, Sweden, United Kingdom.
 
[3] The graph shows the relationship between the logarithm of the real income in the sending region and the logarithm in migration controlling for income in the receiving region, unemployment and public goods in both sending and receiving, year dummies and other factors influencing migration. Moscow and Saint Petersburg are excluded.

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.  

New Tools to Fight Corruption and the Need for Complementary Reform

Posted on June 20, 2012 | Policy Brief

High office buildings facing sky representing Institutions and Services Trade

Corruption remains a serious problem for most developing countries, undermining state capacity and incentives to invest besides social cohesion and democratic institutions. It is also an increasingly important problem for many highly developed ones. In Italy, for example, corruption has increased in the last decades and the parliament is now finally struggling to pass a (rather mild)”anti-corruption law”. Even in Sweden, a country constantly considered among the least corrupt ones in the world, the problem seems to be increasing according to a recent report by the Agency for Public Management (Statskontoret), which also suggests that the current legislation needs to be improved, for example by offering some form of protection to whistleblowers.

In most Central and Eastern European countries, however, the problem appears particularly serious. Corruption seems to have been rapidly increasing in the region this last decade (The Economist, April 11, 2011 ; Nations in Transit, editions 2001-2012), although there are some virtuous exceptions (for example Georgia and Estonia).

Corruption is often caused by, and at the same time, an instrument for political developments towards autocracy, such as those recently observed in some of these countries (limiting judicial autonomy, democratic participation and the free press). This suggests that in countries where these political developments are taking place we may expect a further worsening of the corruption problem in coming years.

A country that is apparently taking the fight against corruption seriously is India, where a strong grassroots anticorruption movement has developed. The issue has become central in recent political debates and several proposals have been put forward and debated in the parliament. Among these proposals is one by Kaushik Basu, the finance minister’s Chief Economic Advisor. He suggests – for a specific class of bribes paid to obtain a service to which one is entitled for – to treat bribe paying as legal while doubling the sanctions against bribe taking (Basu 2011). The logic behind this proposal is to create stronger incentives for bribe-paying individuals to report it to law enforcers and expose corrupt civil servants: reporting should lead to the restitution of the bribe, besides the conviction of the bribe taker.

Since this proposal was made last year, there has been a lively debate both at the Indian as well as the international level. The debate has however been rather informal, and involved some (voluntary and involuntary) misunderstanding of the proposal (see Dufwenberg and Spagnolo 2011 for a short account of this debate). The proposal has been deemed as “radical” by the proponent, and has sometime been treated and dismissed as a theoretical curiosity. In fact, the proposal is similar to existing legal provisions against corruption that have been in place for quite some time in several countries. The proposal is also related to other legal provisions widely used around the world to fight related forms of illegal transactions, in primis leniency policies now used by most antitrust authorities to fight price-fixing cartels, but also accomplice-witness amnesty and protection program against mafia-like criminal organization (see Spagnolo 2008 for an overview).

We know from academic research on these related revelation schemes that they can be very powerful if appropriately designed and administered, but they may fail or even be counterproductive if they are poorly designed or run (see e.g. Spagnolo 2004, Buccirossi and Spagnolo 2006, Apesteguia et al. 2007, Miller 2009, Bigoni et al. 2009). The exact details how these subtle mechanisms are designed and then actually implemented are crucial to their success.

Asymmetric Sanctions, Leniency and Whistleblowers

As earlier mentioned, the main idea behind Basu’s proposal for India, treating partners in corruption asymmetrically is not a theoretical curiosity. It is already present in milder form in the Russian, Japanese and German (violation-of-duty) legislation, where bribe payers face lower sanctions than bribe takers and in the way prosecutorial discretion is used in Anglo-Saxon countries. An analogous provision seems to have also been introduced in China in 1997, and its effectiveness has recently been questioned by some observers, although in a very superficial way. Unfortunately we have no serious evidence of how these legislations have affected corruption.

More generally, the idea of deterring a collaborative crime by shaping the incentives of criminal partners so that one of them has the incentive to betray the others and report information to law enforcers is well established. The Prisoner’s Dilemma story, where each among the partners in crime are promised a light sentence in exchange for cooperation to convict the other criminal partners is familiar to most countries’ standard law enforcement practice.

These schemes have been the main and most successful tool in the fight against mafia and political terrorism in Italy and other countries, and they are currently regarded as the most important and effective instrument in the hands of competition authorities in their fight against cartels (US Department of Justice, Spagnolo 2008, Acconcia et al. 2009).

Apart from law enforcement, analogous “divide and conquer” schemes have been widely used ever since the Roman Empire in war-related situations to break down enemies’ coalitions. They are tools that many do not like on moral grounds, because they induce distrust and betrayal of partners, which some people see as bad even when the betrayed partnership is a criminal one and distrust prevents the criminal activity.

Still related but somewhat different are the whistleblower protection (from retaliation) and reward schemes aimed at inducing innocent witnesses to report a crime. Reward schemes for whistleblowers have been used in the US since the civil war to limit corruption in federal procurement and to fight government fraud (through the False Claim Act, sometimes called the Lincoln Law from the president that introduced it). They have more recently been introduced by the IRS against tax evasion and by the Dodd-Frank Act against financial fraud.

When witnesses are working in the same organization as the wrongdoers, or when the latter are powerful individuals (besides being prone to commit illegal acts, like violent retaliation), blowing the whistle typically generates very harsh consequences for the witness; ranging from various forms of harassment in the organization, to the loss of job, isolation and directly or indirectly induced death.[1] Legal action is typically slow and uncertain but immediate, certain, and very costly, while whistleblower protection provisions are typically imperfect (if present). This is why, even with a relatively efficient legal enforcement system like the American, large rewards are seen as necessary and justified to induce more whistleblowing and compensation for its consequences.

Trust, Distrust and Corruption

In some sense, one can see Basu’s proposal of legalizing bribe paying for services one is entitled to (while doubling sanctions for bribe taking) as transforming potential accomplice-witnesses into potential innocent whistleblowers. The question is then whether this scheme will induce more people to blow the whistle and consequently fewer bureaucrats to demand/accept bribes. Some observers have suggested that this provision might instead induce more people to pay bribes because it makes it legal and thereby may erode moral norms against bribe paying.

In Dufwenberg and Spagnolo (2011), we argued that amending Basu’s proposal in a way resembling leniency programs used in antitrust, where immunity is awarded only if the wrongdoing is reported to the law enforcement agency, is one way to avoid sending the signal that bribe paying is now legal. The real problem for these schemes is therefore whether at the end they will really induce bribe payers to report.

The way these revelation mechanisms deter corruption is by generating “distrust” among potential partners in crime (Bigoni et al. 2012). By making it very attractive to report to law enforcers for one party and very costly to be reported for the others, these schemes may deter illegal cooperation by ensuring that the parties cannot trust each other.

However, for these schemes to generate distrust and produce their potentially strong deterrence effects, the risk that accomplice-witnesses and other potential whistleblowers report must be a real one. For this to be the case, whistleblowers must trust the law enforcement agency to which they report. The example of leniency policies in antitrust is illuminating. In the US, as long as competition authorities retained discretion, colluding firms rarely applied for reporting under the leniency program. It was only when the Department of Justice gave up discretion by making immunity “automatic” – subject to an explicit set of conditions being satisfied – and committed to this policy through published rules that firms started to again to report information on cartels.

Besides a high risk of being reported, for these schemes to elicit reports and produce deterrence it is also necessary that sanctions for convicted parties are sufficient. To continue the parallel with antitrust enforcement, even after the authorities gave up discretion on the programs, they are not inducing cartel members to report in other countries than the US.

Indeed, the most serious problem for the success of the Basu proposal, as well as for that of the leniency-based modification put forward in Dufwenberg and Spagnolo (2011), remains whether witnesses/bribe payers will trust the law enforcement agency to which they should report the crime. If the law enforcement agency is inefficient or also corrupt, reporting may lead to further harassment or worse, rather than protection and justice.

When protection programs are poorly administered and law enforcement agencies inefficient or corrupt, so that potential witnesses don’t trust law enforcement agencies, it becomes very difficult to induce whistleblowers to report, as well as dangerous for the whistleblower.

A second important reason why these schemes may fail to generate reports and to produce the intended deterrence effects is, as we mentioned, the low sanctions against bribe takers. Recent experimental results (in Bigoni et al. 2012) suggest that reporting incentives provided by leniency programs are only effective in deterring collusion if the sanctions for the convicted partners are sufficiently strong. If not, these schemes may have no effects or even perverse ones (they reduce the sum of expected sanctions, and because of their complexity, they could be manipulated; see e.g. Buccirossi and Spagnolo 2006). Basu did suggest doubling the sanctions for the bribe payers. This, however, may or may not be enough for the case at hand, and would require a more thorough evaluation.

Note than in the case of corruption, there is an additional reason for sanctions to be reinforced, in particular by the requirement to always remove from office the convicted bribe taker. The reason is that if the bribe taker is not removed from office after the report, bribe payers may fear that after whistleblowing the bribe taker may retaliate in future interactions.

Conclusions

Asymmetric sanctions as proposed by Basu (2011) and leniency conditional on reporting as proposed by Dufwenberg and Spagnolo (2011) have the potential to deter corruption in a systematic way.  Necessary conditions for this to happen, however, are that:

  1. Sanctions are sufficiently robust to ensure that the increased risk of being convicted because of a report by a whistleblower dominate on the lenient treatment offered to induce reports;
  2. Potential whistleblowers trust that the law enforcement institutions will act on the report and protect them from retaliation by the corrupt and their friends, rather than harass them.

Countries with sufficiently independent and efficient law enforcement institutions should definitely consider introducing or reinforcing their revelation schemes, asymmetric treatment or leniency conditional on reporting, to counter the current widespread increase in corruption.

Simply introducing these schemes in countries with weaker institutions, in particular with a low level of independence of law enforcement agencies, may do more harm than good: after all they imply reduced sanctions and their complexity makes them easily manipulated.

These schemes can be very useful for these countries, but only if they are introduced as part of a broader set of complementary reforms that include increased judicial independence and the creation of a specialized law enforcement unit with particularly high levels of accountability and independence, able to credibly offer to whistleblowers at least confidentiality and protection from retaliation, if not monetary rewards.

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References

[1] The sad recent stories of Sergei Magnitsky in Russia and of S.P. Mahantesh in India clarify that this risks are real.

Putin and the Modernization of Russia – a Chimera?

Posted on June 11, 2012 | Policy Brief

20180315 The State of Russia Image 01

Vladimir Putin is once more the Russian President and a new government has been formed consisting of most of the same faces and mentality. Putin’s victory looks complete – yet there is a very real risk that it will be Pyrrhic. Even if the ‘managed’ political and economic system – rooted in a lack of competition and openness – that has been his defining project can remain stable, it will continue to sap the country’s vitality. In the election campaign, even Putin acknowledged the country’s lack of modern and competitive industries, as well as a business environment plagued by corruption, cronyism and excessive regulation. Yet, in calling for further modernisation of the economy, Putin has also called for more of the same policies, notably a central role for the Russian state in supporting new industries and technological leadership; a newly established State Corporation for Siberia and the Far East is a case in point. 

However, this very model has so far achieved very limited results. Oil and gas still account for nearly 70% of total merchandise exports and around half of the federal budget. While relying on publicly funded and managed entities – such as Rusnano – to shepherd the economy into more diversified and more productive spaces, particularly in high-tech activities, has also yielded a relatively meagre harvest. Rusnano itself has already acknowledged the limited portfolio of innovative projects to fund.

In the arena that provides the most compelling metric of competitiveness – export markets – relatively few Russian firms compete in international markets and very few do in higher value added trade. Ricardo Hausmann (2007) has argued that the products that a country exports also reflect the proximity of products and their reliance on similar sets of inputs, such as physical assets and knowledge or skills. Near the start of Russia’s transition it has been calculated that Russia had comparative advantage in only 156 out of 1242 product lines when using a 4-digit SITC classification. Most were natural resources. In contrast, China had comparative advantage in 479 product lines. And as regards proximity, few of Russia’s export products were closely connected to other products, meaning that there was limited scope for enhancing exports. Yet, by 2010 our research shows that there has been an increased concentration on natural resource exports. The contraction of manufacturing has, further, been associated with a fall in the number of Russian product lines with comparative advantage to 103. In contrast, the number for China increased in 2010 to 513. So, despite Putin’s rhetoric, the Russian export basket has become even more concentrated since the mid-1990s. Moreover, the ability to shift into proximate products, as well as diversify into new ones, remains very restricted. This is due to several factors.

A common diagnosis is that failings in the business environment are to be blamed. This is not a new complaint. While the options for limiting these constraints may not be straightforward but the broad policy direction and options are well understood. The challenge is in enforcement. In this – as also with improving governance and further reducing the role of public ownership – improvement is only likely to start with serious political commitment. That is still lacking.

But modernising the economy depends on much more than a good business climate. Critically, it depends on what sorts of skills and knowledge are available to the economy. Yet, even here where many have believed that Russia is relatively favourably situated, on closer inspection, the situation turns out to be far more problematic. In fact, our evidence indicates deterioration in the quality of both skills and education over time, including limitations on the supply of high quality management. Evidence from surveys suggests that Russian firms face problems in finding workers with the appropriate skill profile. While this may be the situation for existing firms, it seems likely that potential entrants to new, diversified activities may, if anything, face even steeper constraints. To understand whether this is indeed the case, the leading – 270 – recruitment firms in Russia were surveyed using face-to-face interviews in 23 locations in Russia, including Moscow and St. Petersburg. This included a small experiment looking at skills availability for work in more innovative activities, such as web technology aimed at social networking and marketing. The aim was to see whether innovative activities faced more binding constraints when trying to hire.

The results of this survey are unequivocal. Not only are there widespread skill gaps for all types of skills, but it takes firms a much longer time to fill vacancies for skilled personnel. This is particularly true for relatively innovative activities. Recruiting managers or high level professionals in the major Russian cities on average takes 3-5 times longer for innovative activity. Even in Moscow, recruiting a manager or high level professional would take between 3-4 times longer; the gap was yet greater in the Urals, Siberia and the Far East.

Moreover, looking at the sorts of skills that are lacking for each type of potential recruit (e.g., a manager); recruiters also report an absence of basic or essential skills. For example, lack of problem solving and management skills were overwhelmingly the most commonly cited limitations for managers, with high level professionals most commonly lacking both problem solving and practical skills. Among the consequences, many firms decide to postpone launching new products and/or modernizing plant.

In short, our evidence shows not only widespread skill shortages but also major barriers on the availability of personnel for firms wishing to establish new or relatively innovative activity. At the same time, anecdotal evidence also suggests that among the thin layer of top talent – likely to be essential for high tech and other innovative activities – many prefer to emigrate. In contrast, Russia fails to attract talent from other countries, not least because of a restrictive migration regime.

The last decade has seen an emphasis on modernising and diversifying Russia. The results have been depressingly limited. Yet Putin and his government propose more of the same. In effect, they are continuing to take a huge gamble by relying on a mix of energy prices and publicly funded industrial policy to paper over the structural weaknesses of the economy. As this article has shown, what Russia currently produces and exports – and the underlying skills and knowledge – provide a very weak base for achieving the goals of modernisation.

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References

  • Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
  • Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
  • Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011

 

Buyer Power as a Tool for EU Energy Security

Posted on June 7, 2012 | Policy Brief

20120607 Buyer Power as a Tool for EU Energy Image 02

In this policy brief we address the recently revived idea of a common energy policy for the EU – an idea of the EU acting as a whole when dealing with energy security issues. We focus on a particular mechanism for such a common policy – the substantial “buyer power” of the EU in the natural gas market. We start by relating the “buyer power” mechanism to the current context of the EU energy markets. We then discuss the substitutability between “buyer power” and alternative energy security tools available to the EU.  In particular, we argue that two main energy security tools – the diversification of the gas sources and the liberalization of the internal gas market – may counteract such buyer power, either by decreasing the leverage over the gas supplier(s) or by undermining coordination. Thereby, investing both into diversification, market liberalization and energy policy coordination may be inefficiently costly. These trade-offs are often overlooked in the discussion of EU energy policy.

The security of energy supply has been part of the European political agenda for more than half a century – at least, since the creation of the European Coal and Steel Community (ECSC) in 1952. However, the Community’s view on the energy security policy and its desirable tools has been changing over time. In the early decades of European integration energy security issues were predominantly seen as belonging to the national competence level. Due to substantial variation in the energy portfolios and energy needs among the Member States, attempts to create a common energy policy were largely unsuccessful. The first large move towards a common energy policy came in the mid-1980s with the idea of developing a common internal energy market. The focus was on liberalization, privatization and integration of the internal markets, with an objective of achieving more competitive prices, improving infrastructure, and facilitating cooperation in case of energy supply shocks. In particular, the internal market was seen as a tool to (partially) overcome the disparity in the energy risk exposure among the Member States.  A considerable effort was put in this direction and a certain progress was accomplished.

The second half of 2000s has been characterized by a number of gas crises between one of the largest EU gas suppliers, Russia and the transit countries  – Ukraine (in 2006, 2007 and 2009) and Belarus (in 2004 and 2010).  These crises repeatedly caused reduction, and sometimes even complete halts, of Russian gas flows to the EU. As a result, the focus of the EU energy policy shifted towards measures ensuring the security of external energy supply. The policy debate has been stressing the dependency of the EU on large fuel suppliers, such as Russia in case of gas, and the need to lower this dependency. Suggested remedies included diversification of gas sources (in particular, away from Russian gas – such as construction of Nabucco pipeline or introduction of new LNG terminals), strengthening of the internal market, and more efficient energy use. The debate was further heated by the construction (and late 2011 launch) of the Nord Stream pipeline, which, according to popular opinion, would further increase the EU dependence on Russia.

In what follows, we address this external energy policy debate. We argue that the dependence per se is not necessarily dangerous for the EU and can be counteracted with due coordination between the Member States. Further, we argue that in dealing with large gas suppliers, there is certain substitutability between such coordination and other proposed energy policy measures, such as diversification of the energy routes or further market liberalization. Thereby, the EU would be better off by carefully choosing an appropriate mix of energy policy tools, rather than by getting all of them at once.

Indeed, the dependency of the EU on Russian natural gas is large. The share of Russian gas in the total EU gas consumption is around 20%,1 and for the group of EU Member States importing gas from Russia this share constitutes around one third.1  Furthermore, in a number of EU Member States – such as Austria, Bulgaria, Estonia, Finland, Lithuania and Slovakia – the share of Russian gas in total consumption is above 80%.3

However, it is important to remember that the dependency is mutual. The current share of gas exports to the EU of total Russian gas exports is around 55%,1 and these gas exports constitute around one fifth7 of Russian federal budget revenues. These observations suggests that the EU as a whole would also possess a substantial market power in the gas trade between Russia and the EU, and this market power can be exercised to achieve certain concessions.

More precisely, this situation could be viewed through a prism of what the economic literature refers to as “buyer power”. Inderst and Shaffer (2008) identify buyer power as “the ability of buyers (i.e., downstream firms) to obtain advantageous terms of trade from their suppliers (i.e., upstream firms)”.5 The notion of buyer power is typically used in the context of vertical trade relationship between a small number of large sellers and a few large buyers. As there are only a few agents, each with considerable market power, the outcome of such trade would typically be determined through some kind of bargaining procedure, rather than via a market mechanism. In such bargaining, the extent of buyer power depends on the seller’s outside option, or, in other words, on the ease for the seller to cope with a loss of a large part of its market.

Consider for example a single seller serving a few buyers. Intuitively, were there a disagreement between the seller and a small buyer, it should be relatively easy for the seller to reallocate the freed-up capacity to the remaining buyers, making each of them consume just a little bit more of a product. However, the larger is the freed-up capacity of the seller in case of a disagreement, the more difficult it is for the seller to reallocate this capacity to the rest of the market. Moreover, allocating this relatively large capacity to the remaining buyers is likely to suppress the price and lower the monopoly profits of the seller. Inderst and Wey (2007) show that, under some relatively standard modeling requirements, “the supplier’s loss from a disagreement increases more than proportionally with the size of the respective buyer”.6 In other words, an increase in the size of the buyer undermines the seller’s outside option, thereby weakening the seller’s bargaining position and allowing the buyer to negotiate a preferential treatment.

It is relatively straight-forward to see the parallels between this argument and the gas trade relation between the EU and Russia. In a sense, the buyer power theory provides an economic (rather than political) rational for the September 2011 European Commission proposal to coordinate the external energy policy in order to “exercise the combined weight of the EU in external energy relations”.2 At the same time, the large buyer mechanism also allows us to see more clearly, why such a coordination policy may come into conflict with the other proposed energy policy tools.

In particular, consider the diversification of the gas supplies across producers. The argument for the diversification is that it decreases the dependency on each particular supplier, thereby lowering the exposure to the idiosyncratic risks of these suppliers. However, lower volumes of gas imports from such suppliers imply a loss of the EU’s buyer power vis-a-vis these suppliers. This would worsen the terms of the respective gas trade deals or undermine the stability of the supply. Of course, this argument suggests by no means that a diversification strategy is useless or harmful for the EU energy security; however, one would need to account for the relative importance of lower dependency vs. lower buyer power in making the diversification decisions. In other words, the EU can achieve the same level of gas supply stability by investing either into further diversification of gas supply or into better coordination among the members. Trying to achieve both objectives at the same time may result in efficiency loss, at least from the gas supply security perspective. Importantly, this tradeoff has been largely overlooked in the discussion of the EU energy policy.

Another energy policy objective pursued by the EU in the last decades is the creation of an integrated and deregulated internal gas market. Again, the relationship between this energy policy objective and the buyer power is two-fold. On one hand, better integration of internal gas markets would help to even out the disparities in the gas supply risk exposure across the Member States, thereby facilitating cooperation and lessening the tensions between the energy security interests on the national vs. community-wide level. On the other hand, gas market liberalization and a push towards more competitive gas trade environment within the EU may come into conflict with the supranational coordination of buyer power. Once large state-run gas purchasing actors are dissolved and replaced by multiple private, not necessarily domestic, and possibly small market participants, it might be much more difficult, if at all possible, to achieve coordination in bargaining with the gas supplying side. As Finon and Locatelli (2007) argue, “if the major gas buyers are weakened in the name of the principles of short-term competition, their bargaining power and their financial capacity to handle large import operations would be reduced”.4 Moreover, there is a clear conceptual contradiction between coordination among gas buyers and the competitiveness principles of the European gas market. Again, this tradeoff needs to be taken into account in the common energy policy design.

Finally, it is important to mention that the “large buyer” argument is less relevant for the EU markets for other fuels, such as oil, liquefied natural gas, or coal. The key difference comes from the inherent structure of the gas market, as compared to the one of oil, coal, etc. Indeed, the EU imports most of its natural gas via pipelines, which makes it difficult for both sides of the deal to switch to an alternative partner. In other words, the natural gas market serving the EU is effectively a local market. Instead, fuels like oil, liquefied natural gas, or coal are traded more globally, and are much more fungible (that is, it is much easier to find an alternative supplier or a consumer). Global markets imply smaller market shares of the EU (indeed, the EU consumes only about 16 %1 of the world oil). This, coupled with better fungibility of oil, LNG, etc. undermines the power of the large buyer argument for other fuels.

To sum up, the EU has a noticeable potential for improving its position in the gas trade deals and enhancing the stability of its gas supplies. This potential comes from the large buyer power possessed by the EU in the gas market, and is in line with the long considered and recently revived idea of “one voice” common energy policy. At the same time, the extent to which the buyer power can be used as an energy policy tool may be limited by the other policy instruments, such as diversification of gas supplies, a shift towards LNG or alternative fuels, or internal market liberalization. This has to be taken into account in choosing the optimal energy security policy mix.

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References

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.

Assessing Inflation Persistence in Belarus

Posted on April 23, 2012 | Policy Brief

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Author: Igor Pelipas, BEROC.

Generally speaking, inflation persistence can be defined as the speed at which inflation returns to its equilibrium level after a shock. Since 1995, the dynamics of inflation in Belarus is affected by the various internal and external shocks, which, in turn, cause the structural breaks in the corresponding historical data. The deep currency crisis in 2011 led to a huge increase of inflation, and reached a three-digit value. In the current year, the reduction of inflation is one of the most vital problems for the Belarusian authorities. In this context, the understanding of inflation persistence in Belarus is of great importance for appropriate monetary policy and macroeconomic stabilization measures. Additionally, the issue of inflation persistence is topical in the debates on the possibilities of inflation targeting in Belarus. There is an extensive body of literature on the inflation persistence in the US, the EU member states, and in other countries. Inflation persistence, however, has not yet been a subject of analysis in Belarus. In this policy brief, we have attempted to fill the gap by presenting the results of an inflation persistence assessment in Belarus.

Property Rights and Internal Migration

Posted on April 16, 2012 | Policy Brief

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Authors: Paul Castañeda Dower and Andrei Markevich, CEFIR.

Russia currently faces an important policy challenge related to relatively high levels of regional inequality. Regional imbalances that persist, especially in unemployment, reflect inefficiency and may lead to political instability. National capital and labor markets should work to correct these imbalances. This policy brief focuses on the labor market. In particular, why internal migration is relatively low in Russia, and suggests a new direction of policies to increase the mobility of the Russian workforce.

Interregional differences in income and unemployment remain high in Russia relative to the US and Europe (Andrienko and Guriev 2004). Figure 1 shows the change in unemployment for Russia’s regions between 1992 and 2007 plotted against the level of unemployment in 1992. We calculate the change in unemployment using 2007 since the global financial crises led to a different type of convergence, a widespread increase in unemployment. The absence of a downward slopping trend demonstrates that convergence across regions is not taking place.

Internal migration could solve regional imbalances in unemployment by matching unemployed individuals from areas with high unemployment to job vacancies in areas with more employment opportunities. In the US, for example, Blanchard and Katz (1990) show that regional economies adjust to region-specific shocks mainly through internal migration. However, disparities persist in Russia, in part, because of the lack of internal migration, which is relatively low compared to the US and Europe (Andrienko and Guriev 2004). It is not surprising then that a recent report by the World Bank (World Bank 2010) claims that Russians should be moving more within the country than they currently are, considering the economic costs and benefits of migration. The remainder of this policy brief discusses the connection between property rights and internal mobility in order to understand why the Russian labor market allows such high levels of regional disparities.

To address this issue, we look to the past since there is evidence from the late Tsarist period linking property rights to internal migration that has modern day policy implications. For most of Russia’s history, labor mobility has been restricted and controlled. Serfdom limited peasants’ mobility for centuries; restrictions survived after emancipation under the Russian repartition commune regime. The Soviet propiska system introduced in 1932 heavily regulated internal migration till the very end of the USSR and there are remnants of this propiska system even today. However, the extensive state control over internal mobility was not always the case. In the late Russian Empire, internal mobility was relatively unrestricted by the state and internal migration worked to correct regional imbalances (Markevich and Mikhaillova 2012). This historical period offers a good opportunity to investigate the economic causes of labor mobility in Russia without the veil of legal and political restrictions.

Figure 2 shows a startling pattern in the migration flows from the European provinces to the Asian part of the empire during this period. The sparsely populated regions of Siberia and Northern Kazakhstan that had abundant virgin land were attractive destinations for Russian peasants. We propose that an important factor in understanding the explanandum is the Stolypin agrarian reform, the timing of which is exhibited by the vertical dotted line in Figure 2. The annual number of migrating households was about 15,000 before the reform but dramatically increased to a level of 40,000 households per year after the reform. We argue that the reform increased migration flows largely because it improved the liquidity of peasants’ assets, providing greatly needed funds to finance migration.

The Stolypin titling reform can be thought of as a quasi-natural experiment through which one can judge the importance of financial constraints. For our purposes, the reform’s impact on liquidity is limited to forty-one European provinces (guberniya) where at least five percent of the rural population resided in repartition (peredel’naya) communes. The remaining nine European provinces, where few, if any, peasants were members of repartition communes, constitute the control group. The reform gave households the right to exit from repartition communes and convert their communal allotment to individual ownership of land recognized by a land title. The conversion to individual ownership improved the liquidity of land and made migration more attractive since migration no longer entailed losing one’s allotment and households could more easily sell their land allotments to finance migration.

Using a panel dataset of regional migration to the Asian part of the empire, we apply a difference-in-differences analysis using the distinction between treatment and control groups mentioned above. Our results indicate that 160,000 of the 441,000 households that migrated after the reform can be attributed to the reform. In other words, the relaxing of land liquidity constraints explains at least 18.1% of all post-reform Europe-Asia migration in the late Russian Empire. To understand how large of an impact the reform had, we make a back of the envelope calculation that yields an estimate of 0.12 percentage points of GDP growth per year or about 5% share of total economic growth during this period (Chernina et al 2012).

This historical evidence of the relative importance of liquidity of land for internal migration translates well into the contemporary policy discourse. After consulting both qualitative and quantitative studies on internal migration in Russia, Andrienko and Guriev (2005) conclude that “the most important barrier to migration is the underdevelopment of financial and real estate markets.” Figure 3 shows the relationship between growth of unemployment in a region and the share of privatization of residences using an added variable plot. Here, we condition the relationship on GDP per capita in 2000 and include federal district fixed effects in order to more closely isolate the liquidity effect of privatization. We use as base year 2000 instead of 1992 as in figure 1 because not all regions had initiated privatization until as late as the mid to late 90’s. While this correlation is not strong and is merely suggestive of an underlying relationship between private ownership and mobility, the graph illustrates that those regions with greater levels of privatization in 2000 subsequently experienced greater declines in unemployment during 2000-2007.

In summary, the ability of property rights to affect the financing of migration as well as the role that property rights play in the opportunity cost of migration calls for policymakers to include the issue of property rights when considering barriers to internal mobility. These findings fit well within the new economics of migration literature that criticizes and widens the previous narrow focus on wage differentials. In transition countries, these findings also point towards the importance of how privatization occurred. Different ways of organizing private ownership lead to different transaction costs incurred in buying and selling residential property. For example, in some former Soviet Republics, the privatization of individually owned apartments often did not fully specify property rights concerning the ownership of the apartment building and the internal structures that support the individual apartments. These ambiguities increase transaction costs and reduce the liquidity of the asset. Policies concerning internal mobility should therefore pay closer attention to the liquidity of Russians’ assets and how to improve it.

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References

  • Andrienko, Y., Guriev, S. (2004). “Determinants of Interregional Labor Mobility in Russia.” Economics of Transition 12(1).
  • Andrienko, Y., Guriev, S. (2005). “Understanding Migration in Russia.” CEFIR Policy Paper Series 23.
  • Blanchard, O. and Katz, L. (1992) “Regional Evolutions”, Brooking Papers on Economic Activity, 1.
  • Chernina E., Castañeda Dower P., and Markevich, A. (2012) “Property Rights, Land Liquidity and Internal Migration” NES Working Paper.
  • Markevich, A. and Mikhailova, T. (2012). “Economic Geography of Russia” in The Handbook of Russian Economy. Oxford University Press, eds. Alexeev, M. and Weber, S.