Tag: EU

Non-Tariff Barriers and Trade Integration in the EAEU

It is a commonly held view that the Eurasian Economic Union (EAEU) is a political enterprise (Popescu, 2014) that has little economic meaning other than redistribution of oil rents (Knobel, 2015). With a new reality of low oil prices and reduced rents, a legitimate question is how stable this Union is, or whether there is any hope for mutual economic benefits that can provide incentives to all the participants to maintain their membership in the Union? Our answer is yes, there is hope, but only if countries, especially Russia, make progress on deep integration such as services liberalization, trade facilitation, free movement of labor and especially in the reduction of the substantial non-tariff barriers (NTBs). NTBs are hampering trade both within the Union (World Bank, 2012; Vinokurov, 2015), as well as against third country imports. Our research shows (see Knobel et al., 2016) that all the EAEU members will reap benefits from a reduction of NTBs against each other, but they will obtain considerably more substantial gains from a reduction in NTBs against imports from the EU and China.

Since the early stages of creation of the Customs Union (CU) between Belarus, Kazakhstan, and Russia back in 2010, the economic benefits of the CU have been questionable. The main reason for this in Kazakhstan was the increase in its import tariffs in order to implement the common external tariff of the CU, which initially was Russia’s external tariff (Tarr, 2015). Kazakhstan almost doubled its average tariff from 5.3% to 9.5% (Shepoltylo, 2011; Jondosov and Sabyrova, 2011) in the first year of its CU accession. Belarus did not increase its average tariff, but the structure of its tariffs shifted toward a protection of Russian industry.

In 2015, the CU was transformed into the EAEU, and Armenia and Kyrgyz Republic have joined the EAEU. These two countries are WTO members; Kyrgyzstan entered the WTO in 1998, and Armenia in 2001. In 2014, the simple average most-favored nation (MFN) applied tariff rate in Armenia was 3.7%, and 4.6% in the Kyrgyz Republic. Due to differences between Armenia and Kyrgyzstan’s WTO commitments and the EAEU tariff schedule, the new members of the EAEU are not implementing the full EAEU tariff schedule. That is, they have numerous exemptions. However, they have started a WTO commitments modification procedure.

Despite adverse impacts from the higher import prices from implementing the common external tariff of the EAEU in Armenia and the Kyrgyz Republic, there are potentially offsetting gains. Given the importance of remittances to the Kyrgyz Republic, the benefits coming from the right of workers to freely move and legally work inside EAEU likely dominate the tariff issues. Armenia also benefits from the free movement of labor, receives Russian gas free of export duties, and wants to preserve the military guarantee granted by Russia through the six-country Collective Security Treaty Organization.

In the case of Belarus, it receives Russian oil and natural gas free of export-duties, which, when oil prices were high, tended to dominate their calculus. Kazakhstan hopes for more FDI as a platform for selling to the EAEU market; but President Nazarbaev has expressed concerns that the EAEU is not providing net benefits to his country.

To date, the members have judged participation to be in their interest, but with the plunge in the price of oil and gas, the calculus could swing against participation in the EAEU. That is why it is so important to achieve progress with deep integration in the EAEU. One of the most important areas of deep integration for the EAEU is the substantial reduction of non-tariff barriers in goods trade, both between the EAEU members and against third countries. Estimates by the Eurasian Development Bank (Vinokurov et al., 2015) reveal that NTBs account are 15% of the value of intra-union trade flows.

In our paper, Knobel et al (2016), we estimate substantial gains to all the EAEU members from a reduction of NTBs. We employ a global computable general equilibrium model with monopolistic competition in the Helpman-Krugman style based on Balisteri, Yonezawa, Tarr (2014). Estimates of the ad-valorem equivalents of NTBs were based on Vinokurov et al (2015) for the EAEU member countries and Kee, Nicita, Olarreaga (2009) for non-members.

We find that the effects of deep integration are positive for all countries of the EAEU. Armenia’s accession to the EAEU will have a strong positive effect only if coupled with a decrease of non-tariff barriers. Armenian accession is associated with an increase in external tariffs, which causes a negative economic impact and decrease in output.

The effect of deep integration in the EAEU will be even greater if any spillovers effect reducing NTBs for EAEU’s major trading partners are present. Knobel et al. (2016) simulate a 50% decrease in “technical” NTBs inside the EAEU and a 20% spillover effect of reduction NTBs toward either the EU and USA or China. Reduction of NTBs in trade with the EU and the USA dominates the comparable reduction of NTBs with China for all countries of the EAEU in terms of the welfare gain. Armenia’s welfare gain with a spillover effect towards the EU is 1.1% of real consumption compared to 1.02% with a spillover effect towards China. Growth in welfare in Belarus will be 2.7% with a EU spillover versus 2.5% with a spillover effect towards China. Kazakhstan’s gain in real consumption is also greater in the first (EU+USA) case: 0.86% versus 0.66% (with spillover towards China). Russia’s gain in real consumption in the case of a spillover effect with the EU is 2.01% versus 0.63% in the case of China.

Summing up, our findings suggest an answer to the recent concern about stability of the EAEU. We think that eliminating NTB, hampering mutual trade, and decreasing NTBs in either European or Chinese direction could provide mutual economic benefits that could tie countries of the EAEU together, thereby giving a much needed solid economic ground for the Union.


The Issue of Repeat Cartel Offences

Image for FREE Policy Brief "The Issue of Repeat Cartel Offences"

Leniency policies have become an important antitrust tool but it is not clear whether they have effectively prevented recidivism or whether firms have learned to collude under, and even make strategic use of them. If “recidivism” is really an industry-level phenomenon, the appropriate policy measures are very different from what is necessary if individual firms, having been detected and punished for colluding, engage in the behavior again. Following Levenstein et al. (2015), this brief discusses the recidivism question as one about post-cartel behavior, i.e. the set of policies required to assure that effective competition emerges post-cartel breakup.

Measuring Recidivism

Cartels are one of the main concerns of the European Commission (EC) and the US Department of Justice (DOJ) and so, the US and EU Leniency Programmes (LPs) were designed, in 1978 and 1996 respectively, as a device for the deterrence and dissolution of collusive agreements (see Marvão and Spagnolo (2015a) for an in-depth review on the available evidence of the effects of LPs).

In the analysis of cartel formation, recidivism is an important issue. In the set of 510 cartel members fined by the EC in 1998-2014, Marvão (2015) identifies 89 “multiple offenders” (firms fined for collusion more than once), 10 “repeat offenders” (firms which initiate a cartel after being investigated for another cartel), and 5 recidivists following the definition from Werden et al. (2011): firms which initiate a cartel after being fined for another cartel.

The DOJ dataset compiled by Levenstein and Suslow (2015), spanning 1961-2013, preliminarily finds 113 “multiple offenders” but only 14 “repeat offenders”. Of these 14 firms, 5 that had been previously indicted were caught in the 1990s, but none was indicted again by the DOJ in the 2000s.

Although the number of (discovered) “true recidivists” is not zero, it is less than 1% in these two samples (EU, US). Recidivism seems to arise when there are lapses in enforcement; not surprisingly, some firms take advantage of these lapses to return to old behaviors. Designing policies that are able to prevent recidivism requires understanding whether this is an industry or firm-level phenomenon.

Industry Recidivism

Levenstein et al. (2015) use the above-mentioned EU and US datasets to show that collusion occurs in virtually all sectors of the economy, but with discernable patterns.

In the US, construction and chemicals are frequently cartelized (pre and post leniency). There are a large number of cartels in local markets in some industries, such as retail gasoline stations and dealers and ready-mix concrete. While collusion in these local markets is frequently uncovered, it is not necessarily amongst the same firms.

In the EU, chemicals and transport cartels are also frequent areas of collusive activity (although cartels that are strictly within national boundaries and prosecuted by national competition authorities are not included in the sample).

The authors show that there is a large share of repeat and multiple offenders in chemicals and a surprisingly high proportion of repeat offenders in the manufacture of transport and electrical equipment. The highest proportion of multiple offenders is found in pharmaceuticals and refined petroleum products. The transportation and storage market is a sector with a high incidence of collusion (83 convicted cartel members), but no repeat offenders.

While the determinants of cartel activity are varied and endogenous, some correlations with industry-driven recidivism can be discussed:

  1. Industry concentration. It increases the ease of tacit collusion and it should increase the likelihood of explicit collusion, but there are many cartel examples in unconcentrated industries. In some industries, it has been argued that high fixed costs make competition unstable, so that, absent collusion, firms price below long-run marginal cost and are unable to cover fixed costs (Pirrong, 1992).
  2. Culture and history. Spar (1994) argues that the cooperative culture necessary for survival for diamond miners facilitated collusion as the industry matured. Policy fluctuations can also contribute to this problem, as was the case in the US during the Great Depression.
  3. Inelastic demand. This is empirically challenging to capture if the observed prices have been affected by monopoly power, thus potentially raised to a level at which demand is elastic. In many cases, the direct consumer is a producer, so the downstream cost function and competitive intensity also influence elasticity of demand for the cartelized product. Grout and Sonderegger (2005) estimate the likelihood of collusion in the US and EU and rank industries accordingly. This could be used to target competition authority resources to select industries.

Firm Recidivism

Once a cartel breaks-up, cartel members may decide to compete in the market, merge, tacitly collude, or explicitly collude again. The latter does not mean that the cartel re-forms: a firm may collude in a new industry or product line or with a new set of co-conspirators.

U.S. Steel was involved in 6 different US cartels between 1948 and 1969, with different cartel partners and in different steel products. VSL construction was similarly involved (including as a leader) in multiple US cartels across several decades with distinct, but overlapping partners.

In the EU, Akzo Nobel N.V. has been convicted for 9 cartels, which lasted between 1987 and 2007, and in which its co-conspirators were mostly overlapping – e.g. collusion with Arkema in 6 instances (although the latter changed its name during the period). Many of the other co-conspirators were also multiple offenders. While Akzo only received one fine increase for recidivism, it received 7 leniency reductions, of which 3 were full immunity.

Other EC repeat offenders are ABB and Degussa Evonik – both convicted 4 times and received full immunity twice – as well as Brugg and Sumitomo. The latter was convicted for 7 cartels, of which 5, in the automotive wire harness, were self-reported.

What may influence repeated cartel participation, at the firm level?

  1. Firm’s corporate culture. In such a case, the leadership of the organization expects managers to collude, and collusion occurs in many markets in which the firm operates. Firm norms and expectations of managerial behavior can repeatedly encourage collusion and “disregard” previous fines, as illustrated in the ADM case (Eichenwald, 2000).
  2. Firm structure. Multi-market collusion literature focuses on the ability of firms to target punishments in particular markets. Multi-market firms may also encourage the spread of collusion if they have learned to collude in one market and share their “best practices” in another. This seems to have been the case, for example, in the spread of the vitamin cartel from vitamins A and E to other vitamins (Connor, 2008). Multi-market collusion is encouraged not only by multi-product multinationals, but also multi-market relationships between what appear to be smaller firms in local markets. For example, if gas stations are owned by multi-market firms such as large oil firms or chains of stations, that may facilitate repeated collusion over time and/or across geographic locations.

Policy Tools

In complementarity with LPs, Levenstein et al. (2015) discuss additional (possibly) effective post-cartel policies, aimed at preventing firm-driven recidivism.

  1. Company Fines and Leniency. Theoretical research has emphasized the aptitude of well-designed and well-run LPs to improve cartel detection and deterrence (for a survey, see Spagnolo, 2008). However, Marvão and Spagnolo (2015b) note the generosity of the current EU LP: the average LP reduction is 45% and leniency is granted to 52% of convicted cartel members. In addition, Marvão (2015) shows that repeat offenders appear to receive larger EC leniency reductions, which suggests that firms can learn the “rules of the game”, colluding repeatedly and reporting the cartel to reduce their penalties. As such, fines need to be tougher and recidivism needs to be dealt with differently.
  2. Individual Accountability. Senior management in EU cartels does not seem to suffer from their participation in cartels. For example, Robert Koehler became CEO of SGL Carbon in 2012, after being convicted in 1999 of price-fixing in the graphite electrodes cartel. Imposing tougher sanctions, such as individual prison sentences or disqualification of senior executives from employment in their sector or role, may prevent repeated collusive behaviors (in new firms) and thus, increase deterrence levels.
  3. Follow-On Damages. Private damage suits may increase deterrence. In the US, private litigation plays a major role in the enforcement of antitrust law. Conversely, access to private damages is relatively new in the EU. A recently adopted EU Directive on damages (11/2014) prevents the use of LP statements in subsequent damage actions. However, Buccirossi et al. (2015) show that the effectiveness of damage actions can be improved if the civil liability of the immunity recipient is minimized and claimants receive full access to all evidence collected by the competition authority. Access to previous cartel decisions, for a given firm, will increase the amount of available information and can increase the likelihood and/or amount of successful damage claims.
  4. Consent Decrees. These impose conditions on the behavior of convicted firms (e.g. maximum price, and transparency). If these are violated, the authorities intervene, thus lowering the cost of prosecuting recidivists. In the US, decrees were routinely used by the DOJ in the 1960s and 1970s, but the practice was abandoned due to concerns of effectiveness and large costs. More recently, in September 2007, the Brazilian Administrative Council for Economic Defense enacted a resolution that allows for the use of consent decrees with the aim to settle cartel investigations. Two have already been executed.

If recidivism is industry-driven, its prevention may require a different set of tools, including those below, to complement leniency.

  1. Structural Remedies. Competition authorities have repeatedly permitted mergers among former cartel members, often without review, let alone structural intervention. Davies et al. (2014) examine mergers among former cartel conspirators and conclude that only 29% of the mergers were investigated by the EC. Remedies such as disclosure, divestiture of assets, selling minority shares in competitors, or licensure of intellectual property to competitors may change the nature of competition in the market and make collusion more difficult (see Marx & Zhou, 2015 regarding post-cartel mergers). This is particularly relevant if recidivism is industry-driven.
  2. Monitoring and screening. Some antitrust authorities have implemented monitoring and screening techniques to identify anticompetitive behavior in a given industry. These initiatives involve the analysis or monitoring of the characteristics of products or market structures that are thought to be more prone to collusion (mostly due to repeated offenses). Some examples are watch lists (e.g. Australia, UK, Chile), price observatories (e.g. Belgium, Spain, France), statistical screens (e.g. US FTC, Korea FTC), gasoline retail in Brazil and public procurement in Sweden (see Abrantes-Metz (2013) for further details on screens).


While literal recidivism, i.e. the formation of a cartel after having been convicted of illegal collusion, appears to be rarely detected in the EU and US, there remain policy gaps closing which could improve competition post-cartel.

A variety of post-cartel policies should be explored for their ability to increase the likelihood that workable competition, rather than tacit collusion or single firm dominance, will emerge. These reduce the reliance of competition authorities on leniency-driven self-reports, which will in turn make leniency more effective and less amenable to strategic use by firms determined to collude.



  • Abrantes-Metz, Rosa (2013). “Proactive vs Reactive Anti-Cartel Policy: The Role of Empirical Screens.” Available at SSRN: http://ssrn.com/abstract=2284740.
  • Buccirossi, Paulo, Catarina Marvão, and Giancarlo Spagnolo (2015). “Leniency and Damages,” CEPR Working Paper DP 10682.
  • Connor, John M. (2008). Global Price Fixing, 2nd ed. Berlin: Springer.
  • Eichenwald, Kurt (2000). The Informant. New York: Random House.
  • Grout, Paul and Silvia Sonderegger (2005) “Predicting Cartels,” Office of Fair Trading, Economic Discussion Paper.
  • Levenstein, M., Marvão, C., Suslow, V., 2015. Serial Collusion in Context: Repeat Offenses by Firm or by Industry? OECD Global Forum on Competition. DAF/COMP/GF(10/2015)
  • Levenstein, Margaret C., and Valerie Y. Suslow (2015). “Price Fixing Hits Home: An Empirical Study of U.S. Price-Fixing Conspiracies,” working paper.
  • Marvão, C., 2015. The EU Leniency Programme and Recidivism. Review of Industrial Organization, 48(1), 1-27
  • Marvão, Catarina and Giancarlo Spagnolo (2015a). “What do we know about the effectiveness of leniency policies? A survey of the empirical and experimental evidence,” in Beaton-Wells, C and C Tran (eds.), Anti-Cartel Enforcement in a Contemporary Age: The Leniency Religion, Hart Publishing.
  • Marvão, Catarina and Giancarlo Spagnolo (2015b). “Pros and Cons of Leniency, Damages and Screens”. Competition Law and Policy Debate (forthcoming)
  • Marx, Leslie M., and Jun Zhou (2015). “The Dynamics of Mergers among (Ex) Co-Conspirators in the Shadow of Cartel Enforcement,” working paper.
  • Pirrong, Stephen Craig (1992). “An application of core theory to the analysis of ocean shipping markets” Journal of Law and Economics, 35(1): 89-131.
  • Spar, Debora (1994). The Cooperative Edge: The Internal Politics of International Cartels, Ithaca: Cornell University Press.
  • van Driel, Hugo (2000). “Collusion in Transport: Group Effects in a Historical Perspective.” Journal of Economic Behavior and Organization, 41(4): 385–404.
  • Werden, Gregory, Scott Hammond, and Belinda Barnett (2011). “Recidivism Eliminated: Cartel Enforcement in the United States since 1999,” Georgetown Global Antitrust Enforcement Symposium, Washington DC, Sept. 22, 2011.

Examining Social Exclusion among the 50+ in Europe – Evidence from the Fifth Wave of the SHARE Survey

Though intuitive, the concept of social exclusion is complex and hard to measure. Recently, however, we have witnessed policymakers and international institutions increasingly pay attention to better understand material and social distress and to identify the means to improve a broadly defined standard of living. In this brief, we summarize some of the results and conclusions from a recently published First Results Book based on the latest data from the Survey of Health, Ageing and Retirement in Europe (SHARE). We discuss the approach adopted to measure material and social deprivation, and the subsequent identification of risk of social exclusion. We show that Europeans increasingly value the quality of their social life as they grow older and that factors, such as worsening health, unmet long-term care needs, loneliness or lack of social cohesion are important determinants of social exclusion among the 50+ population. If socio-economic policies are to respond effectively to the needs of older Europeans, then broader aspects of their lives need to be taken into account and public policy should go beyond simple targets of income-defined poverty.

The Survey of Health Ageing and Retirement in Europe (SHARE) is an international research project focused on the European 50+ population, and combines information on key areas of life including health, labour market activity, financial situation, social involvement as well as family and social networks. The fifth wave of this panel study took place in 2013 with detailed interviews conducted in 15 European countries. The survey included a special set of questions aiming to improve the understanding of the degree of financial difficulties faced by the 50+, and to address the question of the extent of social exclusion in different European countries. The First Results Book documenting details of the survey has just been published by the international research team involved in the SHARE project. In this brief, we discuss some key results reported in this publication with focus on the analysis of deprivation and social exclusion in Europe among the 50+.

Capturing a Complex Concept of Social Exclusion in Socio-Economic Data

In recent years, the notion of “social exclusion” has been gaining importance as a reference in academic and policy circles with regards to the goals and conduct of socio-economic policy. In fact, in the Europe 2020 strategy, the European Union has made a formal commitment to “recognise the fundamental rights of people experiencing poverty and social exclusion, enabling them to live in dignity and take an active part in society” (European Commission, 2010). Yet, while the concept has an intuitive appeal, the approach to its measurement and analysis has been far from formalised and continues to leave room for a high degree of arbitrariness. This flexibility in the treatment of social exclusion, given the nature of the concept, may seem necessary and in fact desired, but at the same time requires a lot of care at the level of analysis and caution with regard to conclusions drawn from it.

The recent increase in the popularity of broad measures of financial circumstances, going beyond the simple income-based poverty indicators, reflects a number of limitations of the latter as far as it reflects overall material conditions and welfare of individuals. These limitations may be particularly important in the case of older individuals, for whom material wellbeing will be strongly affected by health status or disability, as well as by the extent of accumulated assets at their disposal (e.g. Laferrère and Van den Bosch, 2015; Bonfatti et al., 2015). With this in mind, the fifth wave of the SHARE survey was enriched with a set of additional questions aimed at identifying different sources of deprivation that 50+ individuals are especially exposed to. Based on available data we developed two SHARE-specific measures to assess material and social aspects of deprivation, which were further combined into a single indicator of social exclusion. 13 items from the SHARE questionnaire, exploring affordability of basic needs and financial difficulties among SHARE respondents, were brought together into an aggregate indicator of material conditions (Bertoni et al. 2015). The measure of social deprivation was derived from 15 SHARE items investigating social isolation, quality of neighbourhood and social involvement (Myck et al. 2015). In both cases, so-called hedonic weights were applied to individual items (weights based on the relationship of deprivation items with life satisfaction measure). Based on the threshold of the 75th percentile of total distribution of each of the two indices, individuals with high levels of deprivation in both dimensions were classified as at risk of social exclusion. The scientific value of developed measures has been validated by Najsztub et al. (2015), who found a good compliance in the cross-country variation of material and social deprivation and with common welfare indicators, such as the Human Development Index or income per capita.

Ageing and Social Exclusion among Older Europeans

Comparing material and social deprivation between those aged 50-64 years old and respondents aged 65+ shows that while the level of social deprivation is higher for the older group, the opposite is true for material deprivation (Myck et al. 2015). This suggests that social deprivation grows with age; on the one hand because of increased isolation of older people, and on the other, because older individuals may value their social circumstances more. This conclusion is supported in Shiovitz-Ezra (2015), who reports that, with regards to loneliness, social cohesion and neighbourhood quality play an increasingly important role among older respondents.

Figure 1 Proportion of Individuals at Risk of Social Exclusion by Country

fig1Source: Myck et al. (2015)

When analysing country variation of the two-dimensional indicator of being at risk of social exclusion, we can see that the proportion of the 50+ population exposed to this risk is the highest in Estonia (27.1%), Israel (25.5%) and Italy (23.1%; see Figure 1). On the other hand, countries with the lowest proportion of individuals at risk of social exclusion are Denmark, Sweden and Switzerland. In these countries the proportion is lower than 4%. Naturally, there is important variation in the risk of exclusion also within countries. For example, the results of Hunkler et al. (2015) show that compared to a native born, migrants suffer much higher degree of exclusion in their present country, which, to a lesser extent, is also true for their children.

An analysis of factors that affect the risk of social exclusion reveals that higher education, being employed or retired, and living with a partner substantially limit this probability (Myck et al., 2015). There is also a strong correlation between social exclusion and poor health status. Older people in poor health and those with limited ability to carry out activities of daily living are more vulnerable to both material and social deprivation (Laferrère and Van den Bosch, 2015). People requiring long-term care but reporting unmet needs in this domain are more likely to suffer from deprivation in the social dimension. Importantly from a policy point of view, Bertoni et al. (2015) provide evidence that eyesight and hearing loss contribute to a higher probability of social exclusion, and among the oldest old lead to reduced actual social participation.


Since the importance of different aspects of social life increases when people grow older, policy instruments targeted at income-defined poverty will be ineffective in addressing important aspects of older people’s welfare. It therefore seems important that broader aspects of everyday life are taken into account when constructing socio-economic policies aimed at reducing social exclusion among older Europeans.


  • Adena, M., Myck, M., Oczkowska, M. (2015) Material deprivation items in SHARE Wave 5 data: a contribution to a better understanding of differences in material conditions in later life. In: Börsch-Supan et al. (2015).
  • Bertoni, M., Cavapozzi, D., Celidoni, M., Trevisan, E. (2015) Development and validation of a material deprivation index. In: Börsch-Supan et al. (2015).
  • Bertoni, M., Celidoni, M., Weber, G., Kneip, T. (2015) Does hearing impairment lead to social exclusion?. In: Börsch-Supan et al. (2015).
  • Bonfatti, A., Celidoni, M., Weber, G., Börsch-Supan, A. (2015) Coping with risks during the Great Recession. In: Börsch-Supan et al. (2015).
  • Börsch-Supan, A., Kneip, T., Litwin, H., Myck, M., Weber, G. (eds) (2015) Ageing in Europe – Supporting Policies for an Inclusive Society. De Gruyter.
  • European Commission (2010) EUROPE 2020: A European strategy for smart, sustainable and inclusive growth.
  • Hunkler, C., Kneip, T., Sand, G., Schuth, M. (2015) Growing old abroad: social and material deprivation among first- and secondgeneration migrants in Europe. In: Börsch-Supan et al. (2015).
  • Laferrère, A., Van den Bosch, K. (2015) Unmet need for long-term care and social exclusion. In: Börsch-Supan et al. (2015).
  • Myck, M., Najsztub, M., Oczkowska, M., (2015) Measuring social deprivation and social exclusion. In: Börsch-Supan et al. (2015).
  • Najsztub, M., Bonfatti, A., Duda, D. (2015) Material and social deprivation in the macroeconomic context. In: Börsch-Supan et al. (2015).
  • Shiovitz-Ezra, S. (2015) Loneliness in Europe: do perceived neighbourhood characteristics matter? In: Börsch-Supan et al. (2015).

Who Cheats on a Cartel Agreement?

20150316 Who Cheats on a Cartel Image 01

Leniency policies, widely used by antitrust authorities, aim to deter and dissolve cartels by granting a fine reduction (up to immunity) to reporting cartel members. What are the characteristics of the reporting cartel members? Marvão (2014) addresses this question by developing and testing a model where cartel members are heterogeneous in terms of the value of the cartel fine they expect to receive. The author shows that the first reporting firm in a cartel tends to be the cartel leader (in the US) or a repeat offender (in the EU). Reporting is also shown to be more likely in cartels which affect a larger market (in the US) and in cartels which have a lower number of members but which affect a geographical area wider than the EEA (in the EU).

Analysis of Leniency Policies

Cartels are a perennial problem and are one of the main concerns of the European Commission (EC) and the US Department of Justice (DOJ). As cartels are secret, measuring the rate of success of cartel detection is challenging. The increased number of detections in recent years may be the result of a higher desistance rate and/or a higher incidence of cartels. The US and EU Leniency Programmes (LPs) were thus designed to work as a device for the deterrence and dissolution of collusive agreements and have been in place since 1978 and 1996, respectively.

The DOJ’s decision on cartel fines is made in accordance with the “U.S. Sentencing Guidelines” and is, in the vast majority of cases, followed by plea-bargaining. The US Leniency Programme grants full immunity to the first firm coming forward, whereas the other firms receive no leniency reduction. However, plea bargaining is present in over 90% of cartel offences and the settlements often lead to a reduced fine for the subsequent cartel members. Firms are also liable for the damages caused by the cartel’s activity. In addition, the Amnesty Plus Program benefits prosecuted cartel members who disclose previously undetected cartels.

EU fines are set in accordance with the “EU Guidelines on the method of setting fines” and are adjusted to account for aggravating and mitigating circumstances. The total fine is capped at 10% of the total worldwide turnover of the firm in the previous year. In the current LP, the first reporter receives immunity from fines and the subsequent firms receive a reduction of 10-75%, depending on their place in the reporting queue.

The empirical literature on LPs policies is relatively short and recent. It focuses on the adequacy of the leniency reductions and presents conflicting results. However, an understanding of the characteristics of the reporting firms, and of the cartels in which they take part, is vital to make policies provide the correct incentives for firms so as to dissolve and dissuade cartels.

The Issue of Repeat Offenders

The current EU fine guidelines state that a repeat offender is any firm that was previously found to infringe Articles 101 or 102 of the EU Treaty. The DOJ defines repeat offenders as any firm that “after release from custody for having committed a crime, is not rehabilitated”. While repeat offenders are a serious issue, the LP Notices are not explicit as to whether or not they should receive a lower leniency reduction, if any.

Repeat offenders are also a highly debated issue. In Marvão (2012), it is shown that recidivism is one the factors which influence the granting and scale of EU leniency reductions. Connor (2010) has suggested that there is evidence of a significant incidence of recidivism, and identifies 389 recidivists worldwide in the period between 1990 and 2009. This number constitutes 18.4% of the total number of firms involved in 648 international hard-core cartel investigations and/or convictions. Werden et al. (2011) have contested Connor’s definition of recidivism and his calculation of the numbers of multiple and repeat offenders. The main discrepancy between the two arguments appears to be in how cartel members who merge and form a new firm are dealt with. Werden et al. (2011) follow the legal practice (DOJ and EC) and suggest that no repeat offenders have been fined in the US, since 1999.

The Model by Marvão (2014)

The aim of Marvão (2014) is to understand the specific characteristics of reporting cartel members and of the cartels in which they take part.

If firms are similar in everything but their own beliefs on the likelihood of being caught by the authorities, firms may have different incentives to report the cartel. Different beliefs may be generated from public statements issued by EU or US officials, knowledge of the budget allocated to the detection and conviction of cartels, and the proportion of convictions in cartel investigations, among others. Harrington (2013) formalizes this behaviour but his underlying assumption of homogeneity of firms only allows for symmetric equilibria.

Marvão (2014) extends the game in Harrington (2013) to include firm heterogeneity. In the first game stage, a two-firm cartel collapses for internal reasons. In the second stage, each firm receives a private signal on the expected probability of detection and conviction by the authorities. Given the signal received, and the expectations on the other firm’s behavior, firms decide to report if the signal is above their threshold level. In addition to the individual fine, the cartel sanction includes a payment for overcharges and other costs inherent to being fined. These costs may include attorney fees, negative impact on consumer’s perception (which may lead to lower sales), managers being fired, future punishment by other firms and possible future damage claims (from customers). Each cartel member can apply to the LP and receive a fine reduction.

The model shows that the cartel member with the highest expected fine will be the first to report the cartel, provided that it receives a sufficiently high and unbiased signal on the probability of being caught.

Empirical Evidence in Marvão (2014)

The theoretical model is tested with the use of data on cartel convictions. The US data employed in the empirical analysis is an excerpt from John Connor’s Private International Cartels dataset (1984-2009; 799 cartels). The EU data was self-collected by the author and includes 81 cartels in the period of 1998 to 2011.

Cartel Leaders

US data on the individual turnover are not available, but sales and overcharges are likely to be larger for the cartel leader. Although this creates a further incentive to report the cartel, the US DOJ guidelines state that leaders cannot receive immunity from fines. It is thus surprising that the results show that, in US cartels, the leader seems to be more likely to report and receive immunity from fines. The cartel leader is identified as the firm mentioned in the DOJ decision as a ringleader or mentioned in the history of the case as the cartel disciplinarian/bully. This result suggests that different definitions of ringleaders are used, or that the rule is not always enforced by the DOJ.

In the EU, it is only the coercer of the cartel who is not allowed, since the LP of 2002, to receive immunity from fines. Although the EU public statements on cartel convictions do not identify the leader or coercer of the cartel, it is likely that the coercer is also the leader of the cartel. However, with no explicit data on the leader, the results cannot be obtained.

Repeat Offenders

Surprisingly, the US results show that repeat offenders are more likely to receive immunity from fines. Even more concerning is the fact that this likelihood is larger with each additional repeat offender in the cartel.

The EU results show that firms that have colluded more than once are more likely to report the cartel and receive immunity from fines. This effect is particularly strong if the report occurs after the end of the cartel.

It may be that repeat offenders are larger in terms of sales or have better knowledge of how to interpret the signals received, perhaps due to their previous collusive agreements, and thus, are better at choosing the timing of the report and what evidence to provide the authorities with. Although it is in the authorities’ interest to give incentives to the reporting of a cartel, legislation should ensure that the deterrence effect is not diminished by the existence of excessive leniency reductions.

Additional Results

Reports are more likely to occur in US cartels which serve markets with a moderate and, to a lesser extent, large number of buyers; as well as in cartels which are shorter and smaller. This is perhaps because collecting evidence is easier and/or quicker. In addition, firms which are convicted in both US and EU are more likely to be the first reporter in the US if they received a lower EU fine, perhaps because they are quicker to report the cartel to the DOJ.

EU Reports are more likely to occur in longer and smaller cartels. The latter result is noteworthy as it contrasts with the work done in Sjoerd (2005) and Brenner (2009), where the number of cartel members is never significant.

In EU cartels reported after their end, the reporter is less likely to have received other reductions. Although these reductions could be due to firms claiming not to know that the agreement was illegal, it could also be that firms apply for other reductions if they do not expect to receive a (large) leniency reduction.


When the perceived probability of conviction is high, firms are more inclined to report the cartel. This prosecution effect is magnified by the existence of the EU and US Leniency Programmes. In addition, a pre-emption effect exists as when firms believe that other firms will report, there is an incentive to be the first reporter and apply for a fine reduction within the LP. Therefore, identifying the most likely reporter in a cartel is key to designing a successful LP.

Marvão (2014) shows that the main sources of fine heterogeneity are recidivism and leadership of the cartel, which illustrate the need for more proactive competition authorities.

Reports are also more likely in cartels that affect a larger market (in the US) and in cartels that have a lower number of members but which affect a geographical area wider than the EEA (in the EU). Leniency Programmes should thus be in line with these incentives, by focusing on dissolution of cartels in these markets and by increasing firm’s beliefs on the likelihood of conviction. This could be done, for example, through unannounced inspections, screenings and requests for information or for a meeting with a firm representative. These measures, provided that they are credible, would supplement and enhance leniency.


  • Brenner, S., 2009. An empirical study of the European corporate leniency program. International Journal of Industrial Organization 27 (6), 639–645.
  • Connor, J. M., 2010. Recidivism revealed: Private international cartels 1990-2009. CPI Journal 6, 2.
  • Harrington, J. E., 2013. Corporate leniency programs when firms have private information: The push of prosecution and the pull of pre-emption. Journal of Industrial Economics 61 (1), 1–27.
  • Marvão, C., 2012. The EU Leniency Programme: Incentives for self-reporting. Trinity College Dublin. Working paper.
  • Sjoerd, A., 2005. Crime but no punishment. An empirical study of the EU 1996 leniency notice and cartel fines in Article 81 proceedings. Master’s thesis, Economic Faculty of the Universiteit van Amsterdam.
  • Werden, G., Hammond, S., Barnett, B., 2011. Recidivism eliminated: Cartel enforcement in the United States since 1999. Research Paper

On Leniency, Damages and Deterrence

Authors: Catarina Marvão and Giancarlo Spagnolo, SITE.

On November 26th of 2014, an EU Directive on antitrust damage actions was signed into law. The Directive is to praise as it does a lot to facilitate private antitrust actions in the EU. However, the Directive also tries to address a possible conflict between public and private antitrust law enforcement due to the central role played by Leniency Programs in cartel detection and prosecution. This conflict has long been at focus of legal debate. Private damage actions may reduce the attractiveness of Leniency Programs for cartel participants if their cooperation with the competition authority increases the chance that the cartel’s victims will bring a successful suit. The Directive strikes a compromise between public and private enforcement by preventing the use of leniency statements in subsequent actions for damages and limiting the liability of the immunity recipient to its direct and indirect purchasers. A new paper by Buccirossi, Marvão and Spagnolo (2014) shows that damage actions will actually improve the effectiveness of such programs, through a legal regime in which the civil liability of the immunity recipient is minimized and full access to all evidence collected by the competition authority, including leniency statements, is granted to claimants, a legal regime already implemented in Hungary since 2011.

The Political Economy of the Latvian State Since 1991: Some Reflections on the Role of External Anchors

This brief discusses the role of external anchors or goals such as WTO accession, NATO and EU accession in Latvia’s development strategy since 1991. On the one hand the external goals ‘depoliticised’ many potentially contentious areas of Latvian life. On the other hand, some developments would not have happened or would not have happened as fast without the constraints imposed by the external goals. For example liberalisation of the citizenship laws was prompted by NATO accession and the balance was tipped when the rejection of Latvia from fast-track EU accession talks in December 1997 led Latvia to abandon its quota or ‘windows’ naturalisation system. Most recently, Eurozone accession was an externally defined exit strategy from the austerity episode induced by the economic and financial crisis. Today there are no big external goals left to guide policy making. Home grown problems such as inequality require home grown solutions. But even now an external dependency persists. For example a long needed reform of the financing model of higher education has had to wait for a World Bank report published in September 2014 for action to be taken.

On January 1st, 2015 Latvia assumed the Presidency of the European Union. This milestone represents a certain level of maturity of the Latvian state and offers an opportunity for reflection on some aspects of how politics and political economy have evolved in Latvia between 1991 and today.

After Latvia regained independence in 1991, it faced (at least) two political economy challenges: one was to disentangle the economy from the Soviet system in which it had been deeply integrated, and the second, perhaps more difficult challenge, was to create an independent nation state. At a formal level, the solution to the latter challenge appeared straightforward – assume continuity of the Latvian state. Effectively this meant reinstating the pre-war constitution, which was indeed done for the most part. Symbolically this continuity was signalled by, for example, calling the first post-Soviet parliamentary elections held in June 1993 the elections for the 5th Saeima (parliament). The elections for the 4th Saeima had taken place more than 60 years earlier in October 1931.

At a practical level the challenges were more complex – Latvia had had no practical experience of statehood for nearly fifty years and mistakes were made. For example, Latvia initially diplomatically recognised Taiwan rather than the Peoples Republic of China.

There was a presumption that newly independent Latvia should become a market economy but little consensus on how this should be achieved. This is in contrast to Estonia where a group of ‘young market economy Turks’ were able to implement a kind of zero option i.e. zero tariffs, fast privatisation, etc. In Latvia there were strong protectionist sentiments and the initial privatisation was a muddled process.

Advice and advisers were abundant in post-independence Latvia. In the early 1990s, Latvia was awash with international advisers: the IMF and the World Bank were both present, the Germans were advising on a constitution for the Bank of Latvia, the British were active in public administration reform, the Danish advised on research and higher education and so on. Advice was often conflicting with different advisers promoting their own visions of structures as models that Latvia should adopt e.g. on legal and education systems. Today, we see something akin to this in the Eastern Partnership countries such as Moldova and Ukraine.

There was a general sense of the desirability of a ‘return to Europe’ but no plan or strategy. Nevertheless, even without a conscious plan a strategy emerged – namely a strategy of external anchors.

The external goals or anchors that emerged included the following:

  • World Trade Organisation, 1998
  • NATO, 29 March 2004
  • European Union, 1 May 2004
  • Eurozone, 1 January 2014

The most important effect of the external anchors was that they ‘depoliticised’ many potentially contentious areas of Latvian life. This has been particularly important given the fragmentation that has historically dominated Latvian politics. Thus, in the interwar period, no less than 32 different political parties were represented in the Saeima. In the early post-Soviet parliaments, similar tendencies were observed with newly created parties being the winners in terms of the number of seats in the first four elections. The election of 2006 was the first in which the previously largest party returned as the largest party. Between the first post-Soviet election in 1993 and the 2014 election, there have been no less than 17 governments which mostly have been uneasy coalitions of 3 or 4 partners with divergent views and interests. In this context the benefit of external anchors is self-evident.

The external anchors each contributed in different ways: WTO accession contributed to modify the protectionist sentiments that were rife in the early years of independence. Rather curiously, Estonia, which adopted a radical free trade policy right from the first days of independence, had more difficulties in achieving their WTO membership than ‘protectionist’ Latvia. Estonia was obliged to implement additional economic regulations in order to conform to the rules of the WTO and the EU (to which it was committed to join as its WTO application proceeded), and as a consequence, Estonian WTO accession was delayed to 1999. The WTO accession process also gave Latvia’s fledgling Foreign Ministry invaluable experience of multi-lateral negotiation.

Apart from the obvious security benefit, NATO membership was conditional on the creation of the Latvian anti-corruption Bureau (KNAB) and on the liberalisation of citizenship legislation, the latter because NATO was concerned about the prospect of a member state with a large number of non-citizen residents.

EU accession represents the biggest and most significant anchor. The requirement of candidate countries to accept the EU acquis communautaire took huge swathes of economic and social legislation out of the political arena. While the economic criteria for accession presented few difficulties of principle for Latvia – most people were in favour of a market economy – the requirement of respect for and protection of minorities presented problems for many Latvian politicians and liberalisation of the citizenship law was resisted until after 1997 when the rejection of Latvia from fast-track EU accession talks in December 1997 prompted a rethinking of Latvia’s intransigent position on the quota or ‘windows system’.

It is hard to over-estimate the impact of EU accession on Latvia. What would Latvia be like today if it were not a member state of the EU? There are sufficient tendencies even now in Latvia to suggest we would observe something like a tax-haven, off-shore economy, probably with weak democratic institutions. EU accession has saved the Latvian people from something like such a fate.

Even later in Latvia’s largely self-inflicted financial and economic crisis of 2008-10 it was the ‘Holy Grail’ of accession to the Eurozone that politically anchored Latvia’s famous austerity programme.

What of today? The ‘big’ external anchors are used up, and Latvia today:

  • Is the fourth poorest country in the EU with GDP per capita in 2013 at 67% of the EU average (only Croatia, Romania and Bulgaria are poorer);
  • Is a particularly unequal society – Latvia has some of the worst poverty and inequality indicators in the EU;
  • Has a shadow economy at 23.8% of GDP (data on 2013; Putniņš and Sauka (2014)); and
  • Has an internationally uncompetitive higher education system.

These and other problematic aspects of Latvian life and society are home grown and it is hard to imagine external anchors that can improve poverty or inequality, that can reduce the size of the shadow economy, or which can improve the quality of the Latvian higher education system.

Nevertheless, Latvian policy makers seem to be addicted to the external anchor concept and often find difficult to progress without it. The recent experience of reform of the financing of higher education illustrates. Latvia has historically had a funding mechanism for universities and other higher education institutions based entirely on student numbers. The lack of a link between funding and quality has resulted in a Latvian higher education system that is strong on enrolment but low on quality e.g. as measured by peer-reviewed publications. At some level this has been understood and there has been much talk of reform. Although various reports and evaluations have been published, there has been little progress on concrete reform until the Ministry of Education commissioned the World Bank in December 2013 to produce a report on funding models for Latvia. The final report was delivered in September 2014 and action has now been taken to adopt the World Bank recommended three-pillar model where the funding criteria will now include performance and innovation.

Of course, the new model will not solve all the problems of Latvian higher education – far from it – but it illustrates the pervasive nature of policy makers seeming dependency on external anchors.


  • Putniņš, Tālis & Arnis Sauka (2014). “Shadow Economy Index for the Baltic Countries. 2009-2013,” The Centre for Sustainable Business at SSE Riga, May 2014.

The Role of Belarusian Private Sector

The development of a private sector and the expansion of its role in the economy is one of the key goals repeatedly announced by the Belarusian authorities. The reforms carried out in Belarus in 2006-2014 moved the country from 106th to 57th position in the World Bank Doing Business ranking. The official statement is that reforms boosted the rapid development of business initiatives and its impact on economic development. Unfortunately, there is no clear confirmation of this statement. The absence of a transparent and clear methodology in Belarusian statistics on how to evaluate the role of the private sector makes it difficult to evaluate the exact input of the Belarusian business in the economy and compare its role to other countries.

In the last 5 years, the Belarusian authorities have repeatedly highlighted the need to develop the private sector, perceiving it as the main source for sustainable economic growth and competitiveness of Belarus in the future.

However, it may be difficult to assess the real role of the private sector in the Belarusian economy. First, existing data do not allow a clear identification of the boundaries between the private and state-owned sectors in Belarus. Furthermore, there are certain methodological differences in identifying and evaluating the private sector between Belarusian official statistics, the World Bank approach and alternative methodologies. These methodological variations combined with data limitations result in significantly different estimates of the role of the private sector for the Belarusian economy. The problem concerns both the evaluation of the role of small and medium enterprises (SMEs) and the private sector in general.

Small and Medium Enterprises

One good example of the abovementioned data issue is the statistics for SMEs sector. Unlike the EU, Belarus does not include individual entrepreneurs to the micro organizations in the SME sector. This results in highly different estimates for the number of SMEs per 1000 inhabitants (Figure 1). If we follow the methodology of the National Statistical Committee of the Republic of Belarus (Belstat), the number is 9.7 firms per 1000 people. However, switching to the EU methodology (IFC report, 2013) raises the number significantly up to 35.9. Moreover, the inclusion of unregistered self-employed individuals involved in the shadow economy (which according to estimations of the authorities amount to at least 100,000 inhabitants) increases the number to 46.5 firms per 1000 people, which is above the level of many European countries.

Figure 1. SME density

figure1Source: own estimations from Belstat data, Eurostat.

Private Sector

As for the private sector in general, the problem here is that the official statistics counts enterprises with mixed form of ownership and state presence to the private sector. This makes it difficult, if at all possible, to obtain the exact input of the private sector to the economy and see the dynamics of its change.

More specifically, there are three potential ways to assess the contribution of the private sector. Unfortunately none of them provides reliable estimates of the role of business. The first method is to use official data. The main problem here is that the private sector according to official statistics includes enterprises with state presence as well as large private companies that are under state control and not totally independent. Thus, the contribution of the private sector calculated based on these figures is likely overestimated.

The second method is to look at enterprises that do not report to the Belarusian ministries, following the methodology of the World Bank used in their evaluation of Belarus machinery industry (Cuaresma et al., 2012). Here, non-ministry reporting enterprises work as a proxy for a private firm, as in this case it doesn’t have to report directly to Belarusian ministries and is independent from the state.

The problem is that the majority of large private enterprises, even though there is no state share in them, are not in this list. In Belarus these enterprises often form a part of state concerns on the one hand and are independent on the other. The example here is JSC “Milavitsa”, one of the largest lingerie producers in EE, which is a part of the Bellegprom concern. Therefore, this methodology likely underestimates the role of the private sector.

The third way is to try to exclude state presence from the official data of the private sector. According to official statistics, the private sector includes several groups of enterprises, such as individual entrepreneurs, legal entities with/without state/foreign presence, etc. However, the absence of a clear distinction between these sub-groups allows for only rough estimates, through the extraction of the state presence.

As a result, all obtained numbers are qualitatively different from each other and there is no clear answer if any of them reflects the real picture.

For example, the contribution of the private sector in total employment according to the three different methods (Figure 2) provides the following results. Officially, in 2013 around 53% of the active labor force worked in the private sector. However, the exclusion of state presence in private property changes the results significantly and the share of the active labor force involved in the private sector drops to a level of 31%, while the non-ministry reporting enterprises employ around 18% of the active labor force.

Figure 2. Private sector in employment (%)

figure2Source: own estimations from Belstat data.

The input of the private sector in the total production volume (Figure 3) is also very diverse depending on the method of evaluation. Official data show that the private sector is responsible for 80% of total production volume. However, the exclusion of state presence decreases the value to a level of just 26%, which is similar to the result demonstrated by the non-ministry reporting enterprises (25%).

Figure 3. Private sector in total production volume (%)

figure3Source: own estimations from Belstat data.

At the same time, the absence of a clear definition of the private sector does not allow for obtaining reliable information about its effectiveness. If we take the rate of return on assets (ROA), again, there is a significant gap in the results of the different methods of estimation (Figure 4). ROA of the private sector according to official statistics is significantly lower than similar indicators based on the data obtained by the other two methods (in 2013: 1.17 vs. 2.4 and 1.3 respectively). Thus, the lower the “measured” state presence, the higher is the productivity of the private sector, especially in comparison with the effectiveness of the state sector (0.25).

Figure 4. Return on Assets (BYR/BYR)

figure4Source: own estimations from Belstat data.


The above discussion has illustrated that diffuseness of data and the definition of the private sector is likely to create troubles for understanding the importance of the private sector in Belarus. This, in turn, may undermine the effectiveness of economic and political measures targeted towards this sector.

The implementation of a clear, unified and transparent methodology of how to estimate the role of business and what exactly can be treated as a private sector in statistics would allow for a better understanding of the obstacles and barriers that the private sector is dealing with, as well as to help developing effective measures of business support. Until then, the official statistics should not stick to just one definition of the private sector. Instead, it can use all three abovementioned gradations, as a better reflection of the realities of Belarusian business.


  • Cuaresmo, J., Oberhofer, H., Vincelette, G. (2012).‘Firm Growth and Productivity in Belarus: New Empirical Evidence in the Machine Building Industry’, World Bank, Policy Research Working Paper No. 6005.
  • ‘Business Environment in Belarus 2013.Survey of Commercial Enterprises and Individual Entrepreneurs’, IFC, Report.

Is Cutting Russian Gas Imports Too Costly For The EU?

20140608 FREE Network Policy Brief

This brief addresses the economic costs of a potential Russian gas sanction considered by the EU. We discuss different replacement alternatives for Russian gas, and argue that complete banning is currently unrealistic. In turn, a partial reduction of Russian gas imports may lead to a loss of the EU bargaining power vis-à-vis Russia. We conclude that instead of cutting Russian gas imports, the EU should put an increasing effort towards building a unified EU-wide energy policy.

Soon after Russia stepped in Crimea, the question of whether and how the European Union could react to this event has been in the focus of political discussions. So far, the EU has mostly implemented sanctions on selected Russian and Ukrainian politicians, freezing their European assets and prohibiting their entry into the EU, but broader economic sanctions are intensively debated.

One such sanction high on the political agenda is an EU-wide ban on imports of Russian gas. Such a ban is often seen as one of the potentially most effective economic sanctions. Indeed the EU buys more than half of total Russian gas exports (BP 2013), and gas export revenues constitute around one fifth of the Russian federal budget (RossBusinessConsulting,2012 and our calculations). Thus, by banning Russian gas the EU may indeed be able to exert strong economics pressure on Russia.

However, the feasibility of such sanction is questionable. Indeed, in 2012 Russia supplied around 110 bcm of natural gas to EU-28 (Eurostat), which constitutes 22.5% of total EU gas consumption. There are a number of alternatives to replace Russian gas, such as an increase in domestic production by investing in shale gas, or switching to other energy sources, such as nuclear, coal or renewables. However, many of the above alternatives, e.g. shale gas or nuclear power, involve large and time-consuming investments, and thus cannot be used in the short run (say, within a year). Others, such as wind energy, are subject to intermittency problem, which again requires investments into a backup technology. The list of alternatives implementable within a short horizon is effectively down to replacing Russian gas by gas from other sources and/or switching to coal for electricity generation. Below, we argue that even if such a replacement is feasible, it is likely to be very costly for the EU, both economically and environmentally.

Notice that any replacement option will be automatically associated with a significant increase in economic costs. This is due to the fact that a substantial part of Russian gas exports to Europe (e.g., according to Financial Times, 2014 – up to 75%) are done under long-term “take-or-pay” contracts. These contracts assume that the customer shall pay for the gas even if it does not consume it. In other words, by switching away from Russian gas, the EU would not only incur the costs of replacing it, but also incur high financial or legal (or both) costs of terminating the existing contracts with Russia, with the latter estimated to be around USD 50 billion (Chazan and Crooks, Financial Times, 2014).

Due to this contract clause, own costs of replacement alternatives become of crucial importance. The coal alternative is currently relatively cheap. However, a massive use of coal for power generation is associated with a strong environmental damage and is definitely not in line with the EU green policy.

What about the cost of reverting to alternative sources of gas? First, in utilizing this option, the EU is bound to rely on external and potentially new gas suppliers. Indeed, the estimates of potential contribution within the EU – by its largest gas producer, the Netherlands – are in the range of additional 20 bcm (here and below see Zachmann 2014 and Economist 2014). Another 15-25 bcm can be supplied by current external gas suppliers: some 10-20 bcm from Norway, and 5 bcm from Algeria and Libya. This volume is not sufficient for replacement, and is not likely to be cheaper than Russian gas.

This implies that the majority of the missing gas would need to be replaced through purchases of Liquefied Natural Gas (LNG) on the world market, in particular, from the US. This option may first look very appealing. Indeed, the current gas price at Henry Hub, the main US natural gas distribution hub, is 4.68 USD/mmBTU (IMF Commodity Statistics, 2014). Even with the costs of liquefaction, transport and gasification – which are estimated to be around 4.7 USD/mmBTU (Henderson 2012) – this is way lower than the current price of Russian gas at the German border (10.79 USD/mmBTU, IMF).

However, this option is not going to be cheap. A substantial increase in the demand for LNG is likely to lead to an LNG price hike. Notice that, at the abovementioned prices, US LNG starts losing its competitive edge in Europe already at a 15% price increase. Just for a very rough comparison, the 2011 Fukushima disaster lead to 18% LNG price increase in Japan in one month after disaster. Some experts are expecting the price of LNG in Europe to rise as much as two times in these circumstances (Shiryaevskaya and Strzelecki, Bloomberg, 2014).

Moreover, it is not very likely that there will be sufficient supply of LNG, even at increased prices. For example, in the US, which is the main ”hope” provider of LNG replacement for Russian gas, only one out of more than 20 liquefaction projects currently has full regulatory approval for imports to the EU. This project, Cheniere Energy’s Sabine Pass LNG terminal, is planned to start export operations no earlier than in the 4th quarter of 2015 with a capacity of just above 12bcma (World LNG Report, 2013). Of course, there are other US and Canada gas liquefaction projects currently undergoing regulatory approval process, but none of them is going to be exporting in the next year or two. Another potential complication is that two thirds of the world LNG trade is covered by long-term oil-linked contracts (World LNG Report, 2014), which significantly restricts the flexibility of short-term supply reaction, contributing to a price increase. All in all, LNG is unlikely to be a magical solution for Russian gas replacement.

All of the above discussion suggests that it may be prohibitively expensive for the EU to do completely without Russian gas. Maybe the adequate solution is partial? That is, shall the EU cut down on its imports of natural gas from Russia, by, say, a half, instead of completely eliminating it?

On one hand, this may indeed lower the costs outlined above, such as part of take-or-pay contract fines, or costs associated with an LNG price increase. On the other hand, cutting down on Russian gas imports may lead to an important additional problem, loss of buyer power by the EU.

Indeed, the dependence on the gas deal is currently mutual – as outlined above, not only Russian gas is important for the EU energy portfolio; the EU also represents the largest (external) consumer of Russian gas, with its 55% share of the total Russian gas exports. In other words, the EU as a whole possesses a substantial market power in gas trade between Russia and the EU, and this buyer power could be and should be exercised to achieve certain concessions, such as advantageous terms of trade from the seller etc.

However, the ability to have buyer power and to exercise it depends crucially on whether the EU acts as a whole to exercise a credible pressure on Russia. That is, the EU Member States may be much better off by coordinating their energy policies rather than diluting the EU buyer power by diversifying gas supply away from Russia. This coordination may be a challenge given the Member States’ different energy profiles and environmental concerns. Also, such coordination requires a stronger internal energy market that will allow for better flow of the gas between the Member States. While demanding any of these measures would be double beneficial: they will improve the internal gas market’s efficiency, and at the same time reinforce the EU’s buyer power vis-à-vis Russia.

To sum up, the EU completely banning Russian gas imports does not seem a feasible option in the short run. In turn, half-measures are not necessarily better due to the loss of the EU’s buyer power. Thereby, the best short-term reaction by the EU may be to put the effort into working up a strong unified energy policy, and to place “gas at the very back end of the sanctions list” for Russia as suggested by the EU energy chief Gunther Oettinger (quoted by Shiryaevskaya and Almeida, Bloomberg, 2014).



More Commitment is Needed to Improve Efficiency in EU Fiscal Spending

20140526 More Commitment is Needed Image 01

The member states of the European Union coordinate on many policy areas. The joint implementation of public good type projects, however, has stalled. Centralized fiscal spending in the European Union remains small and there exists an overwhelming perception that the available funds are inefficiently allocated. Too little commitment, frequent rounds of renegotiation and unanimous decision rules can explain this pattern.

Currently, the EU allocates only about 0.4% of its aggregate GDP to centralized public goods spending (European Commission (2014)). This is surprising given the fiscal federalism literature’s classic predictions of efficiency gains from coordinated public goods provision (see for example Oates (1972) and the more recent contributions of Lockwood (2002) and Besley and Coate (2003) for a discussion). Yet, recent proposals to expand centralized fiscal spending in the EU have been met with skepticism if not outright rejection. The most frequently cited argument claims existing funds are already being allocated inefficiently and any expansion of centralized spending would turn the EU into a mere transfer union (Dellmuth and Stoffel (2012) provide a review).

Centralized fiscal spending in the EU is provided through the “Structural and Cohesion Funds”, which are part of the EU’s so called “Regional Policy” and were initially instituted in 1957 by the Treaty of Rome for the union to “develop and pursue its actions leading to the strengthening of its economic, social and territorial cohesion” (TFEU (1957), Article 174). At that point, the six founding members agreed it was important to “strengthen the unity of their economies and to ensure their harmonious development by reducing the difference existing between the various regions and the backwardness of the less favoured regions” (stated in the preamble of the same treaty). A reform in 1988 has further emphasized this goal by explicitly naming cohesion and convergence as the main objectives of regional policy in the EU.

Today, actual fiscal spending in the EU is far from achieving this goal. The initially agreed upon contribution schemes are often reduced by nation specific discounts and special provisions as the most recent budget negotiations for the 2014-2020 spending cycle showed yet again. Moreover, the perception is that available funds are being spent inefficiently (see for example Sala-i-Martin (1996) and Boldrin and Canova (2001)).

Figure 1. 2011 EU Structural and Cohesion Funds

Figure 1 shows the national contributions to the structural funds as well as EU spending from that same budget in each member nation in per capita terms (data published by the European Commission). If fiscal spending was efficiently structured to achieve the above mentioned goal of convergence, one would observe a strong negative correlation between contributions and spending. The data shows, however, that while some redistribution is clearly implemented, rich nations still receive large amounts of the funds meant to alleviate inequality in the union (see Swidlicki et al. (2012) for a detailed analysis of this pattern for the contributions to and spending of structural funds in the UK).

What prevents a group of sovereign nations from effectively conducting the basic fiscal task of raising and allocating a budget to achieve an agreed upon common goal? In a recent paper, we theoretically examine the structure of the bargaining and allocation process employed by the EU (Simon and Valasek (2013)). Our analysis suggests that efficiency both in terms of raising contributions and allocating fiscal spending cannot be expected under the current institutional setting. While poorly performing local governments, low human capital in recipient regions, and corruption might all play a role in creating inefficiency (see for example Pisani-Ferry et al. (2011) for a discussion of the Greek case), improving upon those will only solve part of the problem.

We demonstrate that the inefficiency of EU spending in promoting the goal of convergence can be explained by the underlying institutional structure of the EU, where sovereign nations bargain over outcomes in the shadow of veto. Specifically, we model the outcome of the frequent negotiation rounds employed by the EU as the so-called Nash bargaining solution, explicitly taking into account the possibility for each member nation to veto and to withdraw its contribution (as the UK threatened in the most recent budget negotiations). It turns out that it is precisely the combination of voluntary participation, unanimity decision rule and the lack of a binding commitment to contribute to the joint budget that generally prevents efficient fiscal spending. In such a supranational setting, the distribution of relative bargaining power arises endogenously from countries’ contributions and their preferences over different joint projects. This creates a link between contributions to and allocation of the budget that is absent in federations, where contributions to the federal budget cannot simply be withdrawn and spending vetoed. Since the EU members lack such commitment, this link will necessarily lead to an inefficient outcome.

Why Does the EU Have These Institutions?

If the currently employed bargaining process cannot lead to an efficient outcome, why then did the EU member nations not institute a different allocation process right from the start? Of course, agreeing on a binding contract without the possibility for individual veto is politically difficult. More complicated bargaining processes may also be much more costly in terms of administration than is relying on informal negotiations and mutual agreement. Our analysis suggests another alternative: If the potential members of the union are homogeneous with respect to their income and the social usefulness (or spillovers) of the projects they propose to be implemented in the union, then Nash bargaining will actually lead to the budget being raised and allocated efficiently. The intuition behind this result is simple: If all countries have the same endowment, their opportunity costs of contributing to the joint budget are the same. Moreover, symmetric spillovers do not give one country a higher incentive to participate in the union than the other. Consequently, all countries have the exact same bargaining position. Thus, equilibrium in the bargaining game must produce equal surpluses for all nations. At the same time, with incomes and spillovers perfectly symmetric, the efficient allocation also produces the same surplus for each nation, so that it coincides with the Nash bargaining solution. It is important to notice, though, that symmetric income and spillovers do not imply homogeneous preferences: Each nation can still prefer its “own” project to the others. Instead, symmetry leads to a perfectly uniform distribution of bargaining power in equilibrium. Moreover, our analysis shows that efficiency is achieved if the union budget is small relative to domestic consumption and member countries have similar incomes.

This resonates well with the history of the European Union. In fact, the disparities between the founding members were not large, so that the current bargaining institutions could reasonably have been expected to yield efficiency. Only the inclusion of Greece, Ireland, Portugal and Spain created a more economically diverse community (European Movement (2010)). Our model shows that as the asymmetries between member countries or the importance of the union relative to domestic consumption grow, Nash bargaining leads to increasingly inefficient outcomes. Figure 2 shows this effect for a union of two nations. Keeping aggregate income constant and assuming symmetric spillovers between the two nations’ preferred projects, we vary asymmetry in their domestic incomes. The graphs show the Nash bargaining outcome (marked with superscript NB) compared to the generally efficient solution. As country A’s income increases, so does its outside option (i.e. all else equal, the higher the income, the less a country would lose if the joint projects were not implemented). Thus, country A’s bargaining position relative to country B increases in equilibrium, leading to an inefficient outcome. The allocation of funds to the union projects (upper right panel) depicts this channel very clearly: While the efficient allocation is independent from the distribution of national incomes, the Nash bargaining solution reflects the changing distribution of power. Nation A is able to tilt the allocation more toward its own preferred project the higher its income. Moreover, it is able to negotiate a “discount” for its contribution. While its contribution (labeled xa) does increase with its income (labeled ya), country A still pays less than would be budgetary efficient given its higher income (upper left panel). As a result of the inefficiencies introduced by the bargaining process, aggregate welfare in the union declines as asymmetry grows. Again, it is worth noting, that the loss in aggregate welfare is relatively small when asymmetry is small, but grows more than proportionally as the countries become more and more unequal (lower right panel).

Figure 2. The Effect of a Union of Two Countries


This has troubling implications for the EU, as income asymmetry has increased with every subsequent round of expansion while the bargaining procedure for the fiscal funds has essentially stayed the same. It is not surprising then that a larger and more asymmetric EU has resulted in supranational spending that is increasingly inefficient.

The EU as a “Transfer Union”

We go on to show that the level of redistribution inherent in the Nash bargaining solution depends crucially on the overall size of the budget the union intends to raise. Increasing the EU’s budget for centralized fiscal spending would indeed lead to more “transfers” to low income members (in terms of net contributions), bringing the EU closer to the original goal of convergence. In fact, the EU could pick a budget such that inequality in terms of total welfare between member nations is completely alleviated. Such an outcome necessarily implies that the net gain from being part of the union for high-income nations is lower (albeit still positive) than for low-income members. However, this in turn has consequences for the endogenous distribution of bargaining power: Richer nations would be able to assert even more power and push even further for their own preferred projects, rendering the allocation of funds across projects less efficient. This trade-off between equality and efficiency implies that complete convergence is not necessarily socially desirable.

Arguably, this trade-off might be more important for a transition period than in the long run. If fiscal spending does not only lead to convergence in instantaneous welfare, but also has a positive effect on long-run performance and GDP growth, income asymmetries across countries will decrease even if the allocation of spending across projects is not entirely efficient. Less inequality in turn will lead to a more efficient allocation process in the future and endogenously reduce the level of necessary transfers. However, whether the growth effect of the EU’s structural funds is indeed positive remains a much-debated empirical question (see for example Becker et al. (2012)).

Institutions Fit for a Diverse Union

As the EU has expanded from the original six nations to the current 27, there has been a concurrent evolution of decision-making rules. A qualified majority rule is now used in many areas of competency. We show that the allocation of fiscal spending could also benefit from the implementation of a majority rule. Efficiency would be improved as long as the low-income member nations endogenously select into the majority coalition while their contributions to the budget remain relatively low. In connection to this, the EU might benefit from enforcing rules specifying contributions as a function of national income (such rules exist, but are easily and often circumvented), forcing wealthier member nations to pay more. An exogenous tax rule without the possibility to negotiate a discount, for example, may indeed improve overall efficiency.

It is important to note, however, that a unanimous approval of such a change is unlikely. The institutional mechanism of Nash bargaining is an “absorbing state” after the constitution stage, in the sense that not all member nations can be made better off by switching to an alternative institution. Therefore, the discussion of alternative institutions and decision making processes is particularly relevant when considering new mechanisms that increase fiscal spending at the union level, such as the proposed EU growth pact. If the same bargaining process remains to be employed even for new initiatives, even though a majority rule is preferable and implementable relative to the status quo, the opportunity for the EU to achieve efficiency in its fiscal spending is lost.


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  • Boldrin, M and Canova, F (2001) ”Europé’s Regions – Income DIsparities and Regional Policies” Economic Policy 32: 207 – 253
  • Delmuth, L.M. and Stoffel, M.F. (2012) “Distributive Politics and Intergovernmental Transfers: The Local Allocation of European Structural Funds” European Union Politics 13: 413 – 433
  • European Commission (2014) Data available at http://ec.europa.eu/regional_policy/what/future/index_en.cfm
  • European Movement (2010) “The EU’s Structural and Cohesion Funds” Expert Briefing, available at http://www.euromove.org.uk/index.php?id=13933
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Trade Policy Uncertainty and External Trade: Potential Gains of Ukraine Joining the CU vs. the Signing Free Trade Agreement with the EU

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This policy brief summarizes the results of recent research which predicts gains in Ukrainian exports from signing a deep and comprehensive free trade agreement with EU, and compares these gains with predicted gains from joining the Customs Union of Belarus, Kazakhstan, and Russia. We argue that the gains would be mostly due to elimination of uncertainty in trade policy of Ukraine with the CU and the EU countries. We find that European integration brings higher potential for export growth, and that it also shifts the structure of Ukrainian exports towards capital goods, reducing the share of raw materials in total export.

Trade Policy Uncertainty and Export

Trade policy uncertainty (TPU) is a powerful negative factor that prevents economy from the realization of its export potential. In a recent paper, Handley and Limao (2012) argue that since the exporting decision involves substantial fixed costs, TPU significantly affects investment and entry decisions in international trade. In particular, they show that preferential trade agreements (PTAs) are important even when the pre-PTA tariff barriers are low. Comparing pre- and post-EU accession patterns of Portuguese exports, they find that Portuguese trade increased dramatically after 1985. The increase was the largest towards the EU partners, suggesting that it was caused by the accession. Export expanded through considerable entry of Portuguese firms into EU markets, even in industries where applied tariffs did not change. Handley and Limao estimated that the tariff reduction, which averaged 0.66 percentage points, has been responsible for only 20 percent of the increase in exports to EU10 after the EU accession, while 80 percent of the increase was due to resolving TPU.

Handley and Limao further argue that the Portuguese example should be highly relevant for any small open economy, facing important trade policy choices. In this regard, Ukraine is facing a very hard choice of selecting its regional integration strategy – towards the EU or the Customs Union (CU) with Belarus, Kazakhstan and Russia, resulting in severe TPU. The options are mutually exclusive since the CU trade policy is not compatible with neither the WTO commitments of Ukraine, or with the parameters of the deep and comprehensive free trade agreement (FTA) between Ukraine and the EU, finalized in 2012. Average tariff protection within the CU in 2012 was 10 percent (Shepotylo and Tarr, 2012), while the average WTO binding tariff rates in Ukraine were only 5 percent; the parameters of the FTA with the EU are even less protective, which would cause even stronger disagreements regarding the tariff schedules. Moreover, technical and phyto-sanitary standards in the EU and the CU are different; therefore, it would be extremely hard to harmonize the Ukrainian standards with both of them.

Despite low tariff protection, uncertainty on the parameters of the long run trade policy of Ukraine with the CU and EU countries is extremely high. It is crucial for both foreign and domestic investors to understand in what direction the regional integration will proceed before making decisions on investing or exporting, since these decisions can incur substantial sunk costs. Suppose that a large European multinational firm were interested in including Ukrainian companies in its production chains only if Ukraine signs the FTA with the EU (integrate vertically). If Ukraine instead joined the CU, this presumed European company would rather be interested in horizontal integration and invest by building a plant for final assembly of products to serve the Ukrainian and CIS markets. For Russian companies the situation would be the reversed. They would be interested to integrate vertically if Ukraine is a member of the CU and integrate horizontally if Ukraine signed FTA with EU. However, since vertical and horizontal integration are quite different strategies, neither European nor Russian companies invest in Ukraine before the uncertainty is resolved. The same holds true for domestic companies which would like to extend their export activities to new markets. Since entrance to new markets is costly and requires some irreversible investment, it is optimal to wait until the policy uncertainty is resolved.

Modeling Trade Policy Options of Ukraine

In Shepotylo (2013), we investigate which integration scenario is more preferable for Ukraine under the assumption that TPU is fully resolved and Ukraine trades up to its potential. Based on export data in 2001-2011, we estimate the gravity model by Helpman, Melitz, and Rubinstein (2008) method, adjusted for panel data case and endogeneity of a decision to sign a PTA. Using this model, we predict bilateral exports of Ukraine under three counterfactual scenarios: a) Ukraine joined the Customs Union in 2009 (CU); b) Ukraine signed the FTA with the EU in 2009 (EU FTA); c) Ukraine joined the EU in 2009 (EU). The model predictions take into account the level of economic development, geographical location, industrial structure, and quality of government and regulatory agencies. It also accounts for macro trends, including the global trade collapse of 2008-2009.

The results are not intended for a short-term forecast, but should be rather used as indicators of the long-run effects. Their interpretation is as follows. Suppose that Ukraine has signed the FTA with the EU in 2009. Taking into account all observable characteristics of Ukraine, what would be the level of Ukrainian export of product k to country j, if Ukraine, in all other respects, would behave as a typical country-member of the FTA EU? That would involve removal of the trade policy uncertainty, stronger integration of domestic companies into the global supply chains, and increase in foreign direct investments from the EU countries.

Unlike the studies based on the Computable General Equilibrium (CGE) method, which assumes that the policy choice affects the economy only marginally through reduced tariff barriers, and that the underlying economic structure and expectations of the economic agents remain intact, the gravity model captures all changes that occur in the economy over the investigated period and extract the differences in export flows between any two counterfactual scenarios, given all background economic changes.


Our main results are as follows. First, the actual exports of Ukraine are far below their potential, compared with performance of both the CU countries and the FTA EU countries. The expected long run gains in Ukrainian exports to all countries under the CU scenario are equal to 17.9 percent above the export level in 2009-2011. The corresponding number for the FTA EU scenario is 36 percent, and for the full EU scenario, 46.1 percent. Based on 2011, the export of Ukraine would have been 98 billion US dollars under the EU scenario, 91 billion US dollars under the FTA EU scenario, and 72 billion US dollars under the CU scenario. All these numbers should be compared with the actual 68 billion US dollars of Ukrainian export in 2011.

Figure 1. Ukrainian Export under the Different Scenarios

Second, any scenario predicts that Ukraine severely underperforms in its trade with both CIS and EU countries, while its export to the rest of the world is in line with the predictions of the model. These results are consistent with the theory that unresolved TPU in relationships with the CIS and EU countries severely hurts the Ukrainian export potential to these countries.

Table 1. Ukrainian Export under the Different Scenarios
Note: CIS – Commonwealth of Independent States; EU12 – countries that joined EU after 2003; EU15 – countries that joined EU before 2004; RoW – rest of the World

Third, CU integration would be more beneficial for the Ukrainian agriculture and food industry, while FTA EU or full EU integration would be more beneficial for textiles, metals, machinery and electrical goods, and transportation. Conditional on not worsening its market access to Russia, Ukraine would expand its trade in these sectors to all countries, including Russia and other members of CU.

Figure 2. Expected Increase of Ukrainian Export under the Different Scenarios


Finally, the CU integration would lead to a small increase in the share of capital goods from 17 percent to 20 percent of total exports. FTA EU would increase the share of capital goods to 28 percent, while full EU integration would increase it to 29 percent. In all scenarios, the share of raw materials would decline from 16 percent to 10-12 percent. The share of intermediate goods would decline from 48 percent to around 40 percent under the two EU scenarios and would only marginally decrease under the CU scenario. The share of consumer goods would remain stable around 20 percent.


Ukraine would be better off by signing a deep and comprehensive trade agreement with the EU and integrate into its production chains than joining the CU. Right now, Ukraine severely underperforms by exporting far below its potential. Evidence shows that high trade policy uncertainty plays a large role in Ukraine’s poor performance, since the gap between actual and potential exports are mainly due to low levels of export to the EU and CIS countries. Moreover, Ukraine should be interested in moving the integration process even further, because EU accession would bring even better results.


  • Handley, K., & Limão, N. (2012). Trade and investment under policy uncertainty: theory and firm evidence (No. w17790). National Bureau of Economic Research.
  • Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading partners and trading volumes. The Quarterly Journal of Economics,123(2), 441-487.
  • Shepotylo, O., & Tarr, D. (2012). Impact of WTO accession and the customs union on the bound and applied tariff rates of the Russian federation. World Bank Policy Research Working Paper, (6161).