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The Long Shadow of Transition: The State of Democracy in Eastern Europe
In many parts of Eastern Europe, the transition towards stronger political institutions and democratic deepening has been slow and uneven. Weak political checks and balances, corruption and authoritarianism have threatened democracy, economic and social development and adversely impacted peace and stability in Europe at large. This policy brief summarizes the insights from Development Day 2019, a full-day conference organized by SITE at the Stockholm School of Economics on November 12th. The presentations were centred around the current political and business climate in the Eastern European region, throwing light on new developments in the past few years, strides towards and away from democracy, and the challenges as well as possible policy solutions emanating from those.
The State of Democracy in the Region
From a regional perspective, Eastern Europe has seen mixed democratic success over the years with hybrid systems that combine some elements of democracy and autocracy. Based on the V-Dem liberal democracy index, ten transition countries that have joined the EU saw rapid early progress after transition. In comparison, the democratic development in twelve nations of the FSU still outside of the EU has been largely stagnant.
In recent years, however, democracy in some of those EU countries, such as Bulgaria, the Czech Republic, Hungary, Poland and Romania have been in decline. Poland, one of the region’s top performers in terms of GDP growth and life expectancy, has experienced a sharp decline in democracy since 2015. Backlashes have often occurred after elections in which corruption and economic mismanagement have led to the downfall of incumbent governments and a general distrust of the political system. Together with low voter turnout, this created fertile ground for more autocratic forces to gain power helped by demand for strong leadership.
An example from Ukraine illustrated the role of media, both traditional and social, for policy-making. In some countries of the region, traditional media is strictly state-controlled with obvious concerns for democracy. This is less the case in Ukraine, where also social media plays an important role in forming political opinions. The concern is that, as elsewhere, opinions that gain traction on social media may not be impartial or well informed, affecting public perception about policy-making. A recent case showing the popular reaction to an attack on the former governor of the Central Bank suggests that those implementing important reforms may not get due credit when biased and partial information dominates the political discourse on social media.
Another case is the South Caucasian region: Armenia, Georgia and Azerbaijan. The political situation there has been characterized as a “government by day, government by night” dichotomy, implying that the real political power largely lies outside the official political institutions. In Georgia, the situation can be described as a competition between autocracy and democracy, with a feudalistic system in which powerful groups replace one another across time. As a result, trust in political institutions is low, as well as citizens’ political participation.
In the case of Azerbaijan, there is an elected presidency, but in reality, power has been passed on hereditarily, becoming a de facto patrimonial system. Lastly, in Armenia, the new government possesses democratic credentials, but the tensions with neighbouring Azerbaijan and Turkey have given increasing power to the military and important economic powers. Overall, democratisation in these countries has been hindered by a trend for powerful politicians to form parties around themselves and to retain power after the end of their mandates. Also, the historical focus on nation-building in these countries has led to a marked exclusion of minorities and a conflict of national identities.
The last country case in this part of the conference focused on the current political situation in Russia and on the likely outcomes after 2024. The social framework in Russia appears constellated by fears – a fear of a world war, of regime tightening and mass repressions, and of lawlessness – all of them on the rise. Similarly, the economy is suffering, in particular from low business activity, somewhat offset by a boost in social payments. Nonetheless, it was argued that it is not economic concerns, but rather political frustration, that has recently led citizens to take to the street. Despite this, survey data shows that trust in Putin is still over 60%, and that most people would vote for him again. However, survey data also points out that the most likely determinant of this trust is the lack of another reference figure, and that citizens are not averse to the idea of political change in itself. Lastly, Putin will most likely retain some political power after 2024, transiting “from father to grandfather of the nation”.
Voices from the civil society in the region also emphasized the importance of a free media and an active civil society to prevent the backsliding of democracy. With examples from Georgia and Ukraine, it was argued that maintaining the independence of the judiciary, as well as the public prosecutor’s office, can go a long way in building credibility both among citizens and the international community. The European Union can leverage the high trust and hopeful attitudes it benefits from in the region to push crucial reforms more strongly. For example, more than 70% of Georgians would vote for joining the EU if a referendum was held on the topic and the European Union is widely regarded as Georgia’s most important foreign supporter.
Weak Institutions and Business Development
The quality of political and legal institutions strongly affects the business environment, in particular with regards to the protection of property rights, rule of law, regulation and corruption. Research from the European Bank for Reconstruction and Development (EBRD) highlights that the governance gap between Eastern Europe and Central Asia and most advanced economies is still large, even though progress in this area has actually been faster than for other emerging economies since the mid-‘90s. This is measured through enterprise surveys as well as individual surveys. In Albania, for instance, a perception of lower corruption was linked to a decrease in the intention to emigrate equivalent to earning 400$ more per month. Another point concerned the complexity of measuring the business environment and the benefits of firm-level surveys asking firms directly about their own actual experience of regular enforcement. For example, in countries such as Poland, Latvia and Romania the actual experience of business regulation measured via the EBRD’s Business Environment Enterprise Performance Survey, is far worse than one would expect from the World Bank’s well known Doing Business rating.
From the perspective of Swedish firms, trade between Sweden and the region has remained rather flat in the past years, as the complexity and risks of these markets especially discourage SMEs. Business Sweden explained that Swedish firms considering an expansion in these markets are concerned with issues of exchange rate stability, and the institutional-driven presence of unfair competition and of excessive bureaucracy. Moreover, inadequate infrastructure and the presence of bribery and corruption make everyday business operations risky and costly. It was generally emphasized that countries have to create a safe investment environment by reducing corruption, establishing a clear and well enacted regulatory environment, having dependable courts and strengthening domestic resource mobilization. Swedish aid can play a part, but there is a need to develop new ways of delivering aid to make it more effective.
An interesting example is Belarus, that has seen more economic and political stability than most neighbours, but at the same time a lack of both economic and political reforms towards market economy and democracy. Gradually the preference towards private ownership, as opposed to public, has increased in recent years and the country has seen a rising share of the private sector, even without specific privatization reforms. Nonetheless, international businesses are still reluctant to invest due to high taxes, a lack of access to finance as well as to a qualified workforce, but most importantly due to the weak legal system. An exception has been China, and Belarus has looked at the One Belt One Road Initiative as a promising bridge to the EU. Scandals connected with the two main Chinese-invested projects have damped the enthusiasm recently, though.
The economic and political risks of extensively relying on badly diversified energy sources, as is the case with natural gas imports from Russia in many transition states were also discussed. It was shown how some countries such as Ukraine, Poland and Lithuania have improved their energy security by either benefitting from reverse-flow technology and the EU’s bargaining power or building their own LNG terminals to diversify supply sources. However, either of these, as well as other energy security improving solutions are likely to come with an economic cost, though, that not all countries in the region can afford.
A Government Perspective
The main focus of this section was the Swedish government’s new inspiring foreign policy initiative, “Drive for Democracy”. Drawing from a definition of democracy by Kerstin Hesselgren, an early Swedish female parliamentarian, democracy enables countries to realize and utilize the forces of the individual and draw them into a life-giving, value-creating society. It was emphasized that the values of democracy are objectives by themselves (e.g. freedom of expression, respect for human rights) but also that democracy has important positive effects in other areas of human welfare. The Swedish government views democracy as the best foundation for a sustainable society, equality of opportunity and absence of gender or racial bias.
The “Drive for Democracy” specifically identifies Eastern Europe as one of the main frontiers between democracy and autocracy, and the Swedish government promotes human rights and stability through various bilateral programmes through the Swedish International Development Cooperation Agency, Sida, and multilateral initiatives within the EU, such as the Eastern Partnership. It was also emphasized that democracy is a continuous process that can always be improved, as indeed experienced by Sweden. Political rights were granted to women only in 1919 followed by convicts and prisoners in 1933 and to the Roma people only in 1950. Political and democratic rights are thus never once and for all given, and it is crucial that the dividends from democracy are carried forward to the younger generation.
Conclusion
In sum, the day illustrated clearly how democracy engages all segments of society, from the business sector to civil society, and the potential for but also challenges involved for democratic deepening in Eastern Europe. To get more information about the presentations during the day, please visit our website.
Participants at the Conference
- PER OLSSON FRIDH, State Secretary, Ministry for Foreign Affairs.
- ALEXANDER PLEKHANOV, Director for Transition Impact and Global Economics at EBRD.
- TORBJÖRN BECKER, Director, SITE.
- CHLOÉ LE COQ, Associate Professor, SITE and Professor of Economics, University of Paris II Panthéon-Assas.
- THOMAS DE WAAL, Senior Fellow at Carnegie Endowment for International Peace.
- NATALIIA SHAPOVAL, Vice President for Policy Research at Kyiv School of Economics.
- ILONA SOLOGUB, Scientific Editor at VoxUkraine and Director for Policy Research at Kyiv School of Economics.
- KETEVAN VASHAKIDZE, President at Europe Foundation, Georgia.
- MARIA BISTER, Senior Policy Specialist, Sida.
- HENRIK NORBERG, Deputy Director, Ministry for Foreign Affairs.
- YLVA BERG, CEO and President, Business Sweden.
- LARS ANELL, Ambassador and formerly Volvo’s Senior Vice President.
- ERIK BERGLÖF, Professor in Practice and Director of the Institute of Global Affairs, London School of Economics and Political Science.
- KATERYNA BORNUKOVA, Academic Director, BEROC, Minsk.
- ANDREI KOLESNIKOV, Senior Fellow, Carnegie Moscow Center.
Gender Gaps in Wages and Wealth: Evidence from Estonia
This policy brief introduces two related papers examining two types of gender gaps in Estonia. First, it presents the work of Vahter and Masso (2019), who study the wage gender gaps in foreign-owned firms and compare this gap with the situation in domestic ones. Then it summarizes a paper of Meriküll, Kukk, and Rõõm (2019), who focus on the wealth gender gaps and highlight the role of entrepreneurship in this gap.
Gender inequality is not only a moral issue. An extensive literature has highlighted the cost of gender inequality in terms of economic (in)efficiency. Most of the academic work has, however, focused on either the US and Western Europe or developing countries. Research focusing on systematic gender disparities in Eastern Europe is rather scarce. Yet, there is much to be learned from this region. The purpose of the FROGEE (Forum for Research on Gender in Eastern Europe) project is to study several issues related to gender inequality in former socialist countries.
This policy brief summarizes two papers presented at the 2nd Baltic Economic Conference at the Stockholm School of Economics in Riga, on June 10-11, where a special session on gender economics was held with the support of the FROGEE project. The event, organized by the Baltic Economic Association (see balticecon.org), gathered more than 85 researchers from the Baltics and all over the world. These two papers focus on Estonia, one of the most successful economies among the transition countries, where however the gender wage gap is among the largest in the European Union.
Firm ownership and gender wage gap
An important source of wage inequality originates in firm-specific pay schemes (see for instance Card et al. 2016). Understanding the characteristics of firms associated with a gender pay gap is thus a necessary step to design relevant policy responses. In a paper entitled “The contribution of multinationals to wage inequality: foreign ownership and the gender pay gap”, Jaan Masso and Priit Vahter, both at the University of Tartu, compare the situation in foreign-owned firms with domestic ones. The fact that foreign-owned firms provide on average higher wages to their employees is well documented. However, the question of whether this premium differs between men and women remains largely overlooked.
A potential channel linking firm ownership and gender wage gap is the transfer of management practices from the home country of the investor to the affiliate. The great majority of FDI in Estonia originates from Finland and Sweden, two countries that regularly top international rankings on gender equality and that have set the fight against gender inequality as a top priority. Observing a lower level of gender wage gap in firms owned by Swedish and Finnish capital would suggest the existence of such a mechanism, even if there is evidence that Scandinavian countries do not stand out in a positive way when it comes to women in the top of the distribution (see for instance Boschini et al., 2018, and Bobilev et al., 2019).
On the other hand, Goldin (2014) has shown that a large part of the gender wage gap in the US can be explained by differences in job “commitment”: firms disproportionately reward workers willing to be available 24/7, more flexible regarding business trips, spending longer hours in the office, etc. Such workers happen to be more often men than women. Multinational firms may require such commitment and flexibility to a larger extent than domestic firms, due for instance to their higher exposure to international competition. This would imply a larger gender pay gap in foreign-owned firms compared to local firms.
To investigate this issue, Masso and Vahter (2019) rely on Estonian administrative data, providing information on the whole universe of workers and of firms in the country between 2006 and 2014. This matched employer-employee dataset allows to track the wage of individuals over the years, but also to compare wages both across and within firms. It thus becomes possible to estimate the gender wage gap at the firm level (controlling for relevant individual-level factors affecting wages, such as age and experience), and then to check whether this measure systematically differs between domestic and foreign-owned firms.
However, simply comparing the gender pay gap between these two types of firms could lead to spurious conclusions. Foreign-owned firms have on average different characteristics than domestic ones: they do not operate in the same sectors, they do not have the same size nor the same productivity. To overcome this issue, the authors rely on a matching method: for each foreign-owned firms, they match a domestic firm with similar (observable) characteristics.
They find that in domestic firms, women are on average paid 19% less than men, even after accounting for many other factors associated with wage. In foreign-owned companies, both men and women are better paid. However, both genders do not benefit from the same premium: men are paid roughly 15% more in foreign-owned firms, whereas the premium for women is only 5.4%. This difference implies an even larger gender wage gap in multinational firms. To illustrate the economic significance of these results, for a man and a woman earning a monthly wage of 1146 euros (the average gross wage in Estonia in 2016), the premium for switching from a domestic to a foreign-owned firm is respectively 171 and 62 euros. Further, they provide some evidence that lower “commitment” is associated with a stronger wage penalty in foreign-owned firms. All in all, these results suggest that there is not necessarily a relationship between a multinational wage policy (especially in its gender wage-gap dimension) and the gender norms prevailing in its country of incorporation.
Gender and wealth gap
The vast majority of academic papers studying gender inequality focuses on the wage gap. But gender inequality can affect other types of economic outcomes, such as labor force participation, unemployment duration, or wealth. The latter is of particular interest since wealth can greatly contribute to empowerment. Merike Kukk, Jaanika Meriküll and Tairi Rõõm, all at the Bank of Estonia, extend the literature with a paper entitled “What explains the Gender Gap in Wealth? Evidence from Administrative Data”. This paper is one of the first to study the gender wealth gap in a post-transition country. The literature on the gender wealth gap is rather scarce because of a lack of suitable data: wealth measures are often computed at the household level, while individual-level data is necessary for such a study.
The main aim of this paper is to depict a precise portrait of this phenomenon in Estonia. In particular, the authors do not simply estimate the overall wealth gap but investigate the magnitude of the gap across the wealth distribution. In other words, is there a difference between the poorest men and the poorest women? Or on the other side of the distribution, are the richest men more wealthy than the richest women?
For this purpose, Kukk, Meriküll and Rõõm combine administrative individual-level data on wealth with survey results. The administrative data are generally considered of much better quality than the other, but they do not provide a lot of additional information on individuals. On the other hand, survey data provide a wealth of information about individual characteristics. Merging allows getting the best of both worlds. Regarding the methodology, the authors use unconditional quantile regression to track gender differences at different deciles of the wealth distribution. They further decompose this “raw” gender gap into two components: the “explained” part, i.e., the part of the gap resulting in differences in characteristics between men and women (demographics, education, etc.), and the “unexplained” part.
This study estimates the raw, unconditional gender wealth gap in Estonia to be 45%, which is of similar magnitude as in Germany. Interestingly, this difference is essentially driven by differences in the top of the distribution: there is a large gap between the richest men and the richest women. This “raw” difference is however explained by a single variable: self-employment, as men are much more likely to have business assets than women. Once controlling for the entrepreneurship status, the wealth difference between the richest Estonians becomes insignificant. This suggests the need to support policies encouraging female entrepreneurship and to remove barriers particularly affecting women. For instance, the literature has previously pointed out that women have less access to external sources of capital than men (e.g., Aidis et al., 2007). Such distortions can ultimately result in a wealth gap at the top of the distribution, as documented by this paper.
In addition, the literature has proposed several mechanisms that could result in gender-specific patterns of wealth accumulation. The simplest channel is through the wage gap, as it can be seen as the accumulation of the wage gap over time (e.g. Blau and Kahn, 2000). The authors thus compare the gender gaps in wealth and income. They uncover a strong wage gap, with men earning significantly more than women starting at the 6th decile: the higher we go in the income distribution, the larger the wage gap. How to reconcile this finding with the absence of a wealth gap conditional on entrepreneurship status? A possible explanation suggested by the authors is that women simply accumulate wealth better than men do.
Conclusion
These two papers illustrate two different mechanisms explaining gender-specific economic outcomes. The larger wage gap observed in multinational companies can be explained by a stronger commitment penalty for women, mostly because of childcare. This asks for two potential policy interventions. First, the development of childcare could facilitate the reduction in the “commitment gap” that disrupts women’s careers. Second, institutions could support a more flexible repartition of childcare responsibilities. Note however that Estonia already has the longest duration of leave at full pay (85 weeks), and that this leave can be freely split between parents. As for the wealth gap at the top of the wealth distribution, it can to a large extent be explained by the entrepreneurship status. This difference could partly be explained by differences in preferences and risk-aversion, which would require long-run policies to be mitigated. But in the short run, there is room for specific policies supporting female entrepreneurship and removing barriers particularly affecting women, such as a tighter credit constraint.
References
- Aidis, R., Welter, F., Smallbone, D., & Isakova, N. (2007). Female entrepreneurship in transition economies: the case of Lithuania and Ukraine. Feminist Economics, 13(2), 157-183.
- Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. Journal of Economic perspectives, 14(4), 75-99.
- Bobilev, R., Boschini, A., & Roine, J. (2019). Women in the Top of the Income Distribution: What Can We Learn From LIS-Data?. Italian Economic Journal, 1-45.
- Boschini, A., Gunnarsson, K., & Roine, J. (2018). Women in Top Incomes: Evidence from Sweden 1974-2013. IZA Discussion Paper No. 10979 .
- Card, D., Cardoso, A. R., & Kline, P. (2015). Bargaining, sorting, and the gender wage gap: Quantifying the impact of firms on the relative pay of women. The Quarterly Journal of Economics, 131(2), 633-686.
- Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 104(4), 1091-1119.
- Meriküll, J., Kukk, M., & Rõõm, T. (2019). What explains the gender gap in wealth? Evidence from administrative data. Bank of Estonia WP No. 2019-04.
- Vahter, P., & Masso, J. (2019). The contribution of multinationals to wage inequality: foreign ownership and the gender pay gap. Review of World Economics, 155(1), 105-148.
The Dollar and the Global Monetary Cycle
The dominance of the dollar in international markets is at the heart of recent policy and academic debates at almost all conferences on international economics. Most recently, Bank of England Governor Mark Carney has suggested a new global electronic currency to reduce the dominance of the dollar (Carney 2019). What are the negative effects of the dollar’s dominance, and how can countries protect against its influence? We answer this and other related questions in our recent paper (Egorov and Mukhin 2019), which we summarize in this policy brief.
Stable prices
What are the sources of the dollar’s global powers? Ultimately, the dollar matters as long as it is used by private agents in their transactions. Recently, a lot of attention has been devoted to the role of the dollar in global financial markets, which gives rise to the so-called “global financial cycle” (Rey 2013). However, a growing literature (e.g., Gopinath et al. 2019) shows that the dollar also plays a central role in international goods markets with many exporters setting their prices in the U.S. currency. According to recent estimates, the share of goods with dollar prices is about 4-5 times larger than the share of the US in global trade (Gopinath 2016). That means many firms set prices in dollars even when they trade not with the US, but with other countries.
Even though this global invoicing role of the dollar may not seem important, many studies show that prices remain stable, or sticky, in the currency in which they are set. This means that in many countries, the prices of imported goods are almost fixed in dollars. Then movements in the dollar exchange rate immediately result in changes in the prices of these goods in the local currency. Of course, even dollar prices adjust occasionally, but recent empirical studies show that the dollar prices of imported goods remain pretty stable even two years after a change in the exchange rate (Gopinath et al. 2019).
Such stability of global prices in dollars has three important implications. First, the dollar exchange rate affects the volume of global trade. In any given country, appreciation of the dollar raises the local-currency prices of imported goods. Because of that, consumers switch from more expensive imported goods to cheaper domestic goods. The same happens in other countries, and thus all consumers buy fewer foreign goods, and the volume of global trade decreases.
Second, the dollar exchange rate affects world inflation and output. A rise in import prices after appreciation of the dollar increases inflation both directly and indirectly, through an increase in the costs to all domestic firms that use imported goods as inputs. The higher the costs, the more firms raise their prices, and the higher the inflation. Indeed, a recent empirical study shows that the dollar exchange rate is a good predictor of world inflation and the volume of global trade (Gopinath et al. 2019). Moreover, an increase in global inflation reduces consumers’ real income, and this leads to lower aggregate demand and thus to a reduction in world output. Therefore, dollar appreciation could trigger a world recession.
Third, we show that all countries find it optimal to partially peg their exchange rates to the dollar. Since changes in the dollar exchange rate could negatively affect output and inflation, all countries try to protect themselves from these external shocks. If it is not possible for a government to convince its private agents to stop using the dollar in their transactions, then the government could reduce the changes in the dollar exchange rate by pegging its currency to the dollar. Of course, this policy cannot address all issues, but at least the prices of imported goods can become more stable in the local currency.
Rigged system
What does this global use of the dollar imply for the US? First of all, it enables the US’s so-called “privileged insularity”. Since the prices of both local and imported goods in the US are stable in dollars, changes in exchange rates do not lead to inflation or expenditure switching between home and foreign goods. This gives rise to a significant asymmetry across countries: the dollar exchange rate has a substantial effect on other countries, but all other exchange rates have only a negligible effect on the US.
We show that the asymmetry in countries’ exposure to exchange rate shocks leads to an asymmetry in their monetary policy. All countries find themselves responding to US policy by partially pegging their exchange rates to the dollar. In contrast, due to its “privileged insularity”, the US can focus on its domestic targets, respond primarily to domestic shocks, and potentially achieve higher welfare than other countries, which are more exposed to foreign shocks.
So, when a local recession hits the US, the Fed stimulates the US economy regardless of the conditions of the world economy. Then all other countries stimulate their economies as well in order to keep their exchange rates more stable relative to the dollar. This creates what we call a “global monetary cycle”, where the whole world becomes more synchronized even when there are no global shocks common to all countries. The more prominent the role of the dollar is in the international goods market, the stronger this “global monetary cycle”. In fact, a recent empirical study confirms this prediction and shows that the higher the share of the dollar in the country’s import basket is, the stronger its peg to the dollar, and the more nominal interest rates follow the US interest rates (Zhang 2018).
Leveling the playing field
What can other countries do to diminish negative consequences from the “global monetary cycle”? One possible way to discourage firms from using the dollar could be the creation or expansion of a monetary union such as the Euro area. The larger the Eurozone is, the more countries within this area use the euro and not the dollar to trade with each other. Moreover, the Eurozone’s trading partners are more likely to use the currency of a larger monetary union (Mukhin 2018). If enough firms switch from the dollar to the euro, then we find that the Eurozone may gain the same advantage of “privileged insularity” as the US.
Another frequently mentioned policy to protect from the undesirable exchange rate effects is the use of capital controls, which are found to be effective in softening the “global financial cycle”. For example, a tax on borrowing in foreign currency can reduce the size of the foreign-denominated debt, so that depreciation does not lead to an increase in the nominal debt burden and start a recession. However, we find that under the “global monetary cycle” these measures turn out to be much less effective. Basically, capital controls primarily affect decisions in financial markets. But it’s the decisions of global exporters, that is decisions in international goods markets, that give rise to the “global monetary cycle”. And the effect of capital controls on exporters is much more subtle if present at all.
Conclusion
To sum up, we argue that as long as many firms continue to set prices in dollars, it is optimal for central banks to smooth movements in exchange rates in order to diminish the effects of the dollar on their economies. This partial peg to the dollar leads to the “global monetary cycle”. As a result, the US is free to implement a mostly independent monetary policy, while the rest of the world has to follow their lead.
References
- Carney, M., 2019. “The Growing Challenges for Monetary Policy in the Current International Monetary and Financial System”, Speech given at the Jackson Hole Symposium.
- Egorov, K., and D. Mukhin, 2019. “Optimal Monetary Policy under Dollar Pricing”, Working paper.
- Gopinath, G., 2016. “The International Price System”, Jackson Hole Symposium Proceedings.
- Gopinath, G., E. Boz, C. Casas, F. Diez, P.-O. Gourinchas, and M. Plagborg-Moller, 2019. “Dominant Currency Paradigm”, Working paper.
- Mukhin, D., 2018. “An Equilibrium Model of the International Price System”, Working paper.
- Rey, H., 2013. “Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence”, Federal Reserve Bank of Kansas City Econoic Policy Symposium.
- Zhang, T., 2018. “Monetary Policy Spillovers through Invoicing Currencies”, Working paper
The Georgian Tax Lottery of 2012 – A Quantitative and Qualitative Evaluation
This policy brief is based on preliminary findings of research that assesses the 2012 Georgian Tax Lottery by Larsen et al. (2019). Tax lotteries are seen as a way to relatively easily augment public revenue while also increasing compliance. Tax lotteries are constructed so that consumers are nudged to ask for a receipt when making a purchase. This receipt contains information which can also be used as a lottery ticket with the possibility of winning prizes. Such tickets also leave traces of transaction records that allow revenue authorities to audit vendors. Given this background, the aim of this paper is to provide a broad, multi-methodological and socio-economic assessment of Georgia’s tax lottery experience in 2012.
Introduction
A well-designed tax system improves economic efficiency, facilitates economic growth and social welfare, (Besley & Persson, 2013). Yet, curbing tax evasion remains one of the key challenges for policy makers, and institutions in charge of revenue administration are experimenting with diverse set of instruments to increase tax compliance and thus revenue.
In addition to the traditional audit-sanctioning mechanism, the taxation literature emphasizes the role of consumers in facilitating tax compliance of businesses. The government can create direct monetary incentives for consumers to request receipts. Turning a receipt into a lottery ticket with a chance of winning a pre-determined prize is an example of such an incentive. The tax lottery motivates and rewards those consumers who become part in the efforts to fight tax evasion by requesting receipts while making purchases. Given that audit-sanctioning mechanisms are very costly for the government, clever usage of a “zero cost policy”, such as tax lotteries, might be advisable (Fabbri & Hemels, 2013).
The aim of this paper is to provide an assessment of the Georgian tax lottery experience in 2012 using both quantitative and qualitative methodologies. The two methodological approaches complement each other and help to investigate the tax lottery from different angles.
The Georgian Tax Lottery
The Georgian Revenue Service (GRS) introduced a tax lottery starting in spring 2012, which was planned to run until January 1, 2013. The aim of the lottery was to popularize the already introduced General Packet Radio Services (GPRS) -based cash registers and make sure that they were used by vendors. Such registers would allow the GRS to gather information about business activities online daily. This, in turn, was due to an effort to fight the shadow economy and be able to audit business revenue, when payments were made by cash. The lottery would thus motivate consumers to ask for receipts. As a communicative resource, the lottery aimed to increase awareness of asking for receipts, as well as to develop a positive attitude in Georgian society towards GRS in the background of harsh fiscal reforms.
In order to participate, customers had to buy goods or services from a vendor who had a GPRS-based cash register. The receipt could be checked for win immediately by mobile phone. The Georgian Tax Lottery was a chance to win money for every customer purchasing anything from groceries, to shoes and hair care. The winning prizes were 10, 20, 50, 100, 10,000 and 50,000 GEL[1]. The 10,000 GEL prizes were awarded once a month while 50,000 GEL prizes were given quarterly.
The lottery ended prematurely on grounds of inefficiency on November 12, 2012 when a new government was elected.
Multi-Method Approach
For the assessment of the tax lottery in Georgia, we employed a multi-method approach combining a qualitative assessment built on an ethnographic approach with quantitative regression-based methods; following the ethnographic approach, we collected opinions, experiences, and views on the tax lottery from the perspective of participating and non-participating businesses, consumers as well as other stakeholders.
The quantitative assessment of the paper investigates whether the existence of the lottery affected businesses’ total revealed turnovers through the facilitation of a receipt-requesting norm. The data for the quantitative analysis conducted in this paper was provided by the GRS. The latter was collected from the daily reports of the GRS system, for two years, 2012 and 2013. The data includes variables, such as the unique cash register identifier, the year and the week of a purchase and address (city and municipality) and the total turnover of the cash register reported through GPRS. GRS also provided the dataset with detailed information on winning tickets. The latter includes daily information on the number of winning tickets and the aggregate daily monetary amount of the prizes.
Three different specifications of linear regression models were run separately on the aggregate country level data. The model-specifications differ in a way that each uses different dependent variables – aggregate weekly sales, average weekly sales per register and number of registers reporting any sales.
Preliminary Results
Table 1: Regression Results of the aggregated analysis on a country level
As may be inferred from the country level regression results reported in Table 1, for all the econometric specifications the ‘lottery’ variable is significant at 1% level. The regression results show that during the weeks of the lottery (weeks 16-46) the aggregate weekly sales are on average 33,363 GEL higher than in the non-lottery weeks (11% more than in non-lottery weeks, based on the log linear model). When looking at the year effect of 2012 in non-lottery weeks, the effects are positive, significant, and, on average, amount to 38,813 GEL. This means that aggregate weekly sales in the non-lottery weeks of 2012, exceed aggregate weekly sales in 2013, on average, by 38,813 GEL. While in this simple model we do not explicitly control for the macroeconomic environment, GDP in 2013 grew by 3.4% while inflation stood close to 0%. These macroeconomic outcomes strengthen predictions of the econometric analysis.
When looking at the average sales per register as the dependent variable instead of aggregate weekly sales, the results are compatible with the results of the first model. There is on average a 282 GEL (7.7%) increase in average turnover during the lottery weeks compared to the non-lottery weeks; and average weekly sales in non-lottery weeks of 2012 exceed average weekly sales in 2013 by 458 GEL, on average. In addition, the positive effect and significance of the year 2012 variable shows that controlling for the non-lottery weeks, something was still driving sales up. This could be the long-term effect of the lottery weeks that continued even after the termination of the lottery; hence some evidence of habit formation.
A similar regression is done with the weekly number of cash registers reporting their income as a dependent variable. The outcome illustrates that during the lottery weeks of 2012, the average number of reported cash registers is 3,199 units (4%) more than those in non-lottery weeks, which is quite compatible with the results reported by the first and second regressions.
Conclusion
Despite seemingly positive results, the lottery was prematurely terminated after parliamentary elections in November 2012. Interviews with stakeholders revealed that the public budget that was allocated for the lottery was deemed insufficient to keep the chances of winning high enough and therefore interest and participation from public had decreased significantly from around 2 mln out of 2.5-2.8 mln receipts checked daily in the first months of the lottery to only 300,000 by the end of the lottery. However, there was a lack of financial resources or interest from the new government to invest additional resources to increase the budget and effectiveness of the lottery.
Regardless of its premature termination lottery itself was thought to have influenced social norms and also started a discussion about tax compliance. The tax lottery also aimed to improve citizens’ attitude towards the GRS. A qualitative analysis, based on multi-ethnographic approach through which we have collected media articles, reports, and other materials expressing views on the Georgian tax lottery, however, showed that strategies of “love and fear” are difficult to make work in combination, and we find it hard to say that citizens’ views of the GRS improved due to the lottery itself. Perhaps even the contrary could be proposed. In terms of an increased trust to the GRS, we conclude with our methodological point that a tax lottery cannot be assessed as an isolated event. Previous and other activities that the revenue services engage in that have an impact on taxpayers and on societal tax, compliance have to be taken into consideration. Fear and unjust treatment especially linger in people’s perceptions.
References
- Besley, T., & Persson, T. (2013). Taxation and development. In Handbook of public economics (Vol. 5, pp. 51-110). Elsevier.
- Fabbri, M., & Hemels, S. (2013). ‘Do you want a receipt?’ Combating VAT and RST evasion with lottery tickets. Intertax, 41(8), 430-443.
- Larsen, L., Arakelyan, R., Gogsadze, T., Katsadze, M., Skhirtladze, S., & Muench, N. (2019). The Georgian Tax Lottery of 2012. A Multi-Methodological Assessment. International School of Economics at TSU, Tbilisi, Republic of Georgia.
- Marcus, G. E. (1995). Ethnography in/of the world system: The emergence of multi-sited ethnography. Annual review of anthropology, 24(1), 95-117.
[1] The exchange rate for a Georgian Lari, GEL, is about 3.0 GEL to 1 EUR.
Liberal Democracy in Transition – The First 30 Years
This year marks 30 years since the first post-communist election in Poland and the fall of the Berlin Wall. Key events that started a dramatic transition process from totalitarian regimes towards liberal democracy in many countries. This brief presents stylized facts from this process together with some thoughts on how to get this process back on a positive track. In general, the transition countries that joined the EU are still far ahead of the other transition countries in terms of democratic development.
The recent decline in democratic indicators in some EU countries should be taken seriously as they involve reducing freedom of expression and removing constraints on the executive, but should also be discussed in light of the significant progress transition countries entering the EU have shown during the first 30 years of transition. The brief shows that changes in a democracy can happen fast and most often happen around elections, so getting voters engaged in the democratic process is crucially important. This requires politicians that engage the electorate and have an interest in preserving democratic institutions. An important question in the region is what the EU can do to promote this, given its overloaded political agenda. Perhaps it is time for a Greta for democracy to wake up the young and shake up the old.
This brief provides an overview of political developments in transition countries since the first post-communist elections in Poland and the fall of the Berlin Wall 30 years ago. It focuses on establishing stylized facts based on quantitative indices of democracy for a large set of transition countries rather than providing in-depth studies of a small number of countries. The aim of the brief is thus to find common patterns across countries that can inform today’s policy discussion on democracy in the region and inspire future studies of the forces driving democracy in individual transition countries.
The first issue to address is what data to use to establish stylized facts of democratic development in the region. By now, there are several interesting indicators that describe various aspects of democratic development, which are produced by different organizations, academic institutions and private data providers. In this brief, three commonly used and well-respected data providers will be compared in the initial section before we zoom in on more specific factors that make up one of these indices.
The big picture
The three indicators that we look at first are: political rights produced by Freedom House; polity 2 produced by the Polity IV project; and the liberal democracy index produced by the V-Dem project. Figures 1-3 show the unweighted average of these indicators for two groups of countries. The EU10 are the transition countries that became EU members in 2004 and 2007 and include Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovakia, and Slovenia. The second group, FSU12, are the 12 countries that came out of the Soviet Union minus the three Baltic countries in the EU10 group, so the FSU12 group consists of Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.
Figure 1. Freedom House
Source: Freedom House and author’s calculations
Note: Scale inverted, 1 is best and 7 worst score
Figure 2. Polity IV project
Source: Polity IV project and author’s calculations
Note: Scale from -10 (fully autocratic) to 10 (fully democratic)
Figure 3. V-Dem
Source: V-Dem project and author’s calculations
Note: Scale from 0 to 1 where higher is more democratic
All three indicators convey the message that the democratic transformation in the EU10 group was very rapid in the early years of transition and the indicators have remained at high levels since the mid-90s only to show some decline in the most recent years for two of the three indicators. The FSU12 set of countries have made much less progress in terms of democratic development and remain far behind the EU10 countries in this regard. Overall, there is little evidence at the aggregate level that the democratic gap between the EU10 and FSU12 groups is closing. While the average EU10 country is more or less a full-fledged democracy, the average FSU12 country is at the lower end of the spectrum for all three democracy measures.
The average indicators in Figures 1-3 obviously hide some interesting developments in individual countries and in the following analysis, we will take a closer look at the liberal democracy index at the country level. We will then investigate what sub-indices contribute to changes in the aggregate index in the countries that have experienced significant declines in their liberal democracy scores.
For the first part of the analysis, it is useful to break down the democratic development in two phases. The first phase is from the onset of transition (1989, 1991 or 1993 depending on the specific country) to the time of the global financial crisis in 2009 and the second phase is from 2009 to 2018 (the last data point).
Figure 4. Liberal democracy, the first phase
Source: V-Dem project and author’s calculations
Figures 4 and 5 compare how the liberal democracy indicator changes from the first year of the period (measured on the horizontal axis) to the last year of the period (on the vertical axis). The smaller blue dots are the individual countries that make up the EU10 group while the red dots are the FSU12 countries. The 45-degree line indicates when there is no change between start and end years, while observations that lie below (above) the line indicate a deterioration (improvement) of the liberal democracy index in a specific country.
In the first phase of transition (Figure 4), all of the EU10 countries increased their liberal democracy scores and the average increase for the group was almost 0.5, going from 0.26 to 0.74. This was a result of many of the countries in the group making significant improvements without any countries deteriorating. The FSU12 group had a very different development with the average not changing at all since the few countries that improved (Georgia and Ukraine) were counterbalanced by a significant decline in Belarus and a more modest decline in Armenia.
Figure 5. Liberal democracy, the second phase
Source: V-Dem project and author’s calculations
The very rapid improvement in the liberal democracy index in the EU10 countries in the first phase of transition came to a halt and also reversed in several countries in the second phase of transition. Of course, as they had improved so much in the first period, there was less room for further positive developments, but the rapid decline in some of the countries was still negative news. However, it does point towards that reform momentum was very strong in the EU accession process, but once a country had entered the union, the pressure for liberal democratic reforms has faded.
Overall, the EU10 average fell by 0.1 from 2009 to 2018. This was a result of declining scores in several countries. The particularly large declines in this period have been seen in Hungary (-0.28), Poland (-0.27), Bulgaria (-0.14), the Czech Republic (-0.14), and Romania (-0.12). Again, the average FSU12 score did not change much, although Ukraine (-0.2) put its early success in reverse and lost as much in this period as it had gained earlier.
Country developments
Since much of the current discussion centers on how democracy is being under attack, the figures name the countries that have seen significant declines in the liberal democracy score in the first or second phase of transition. Figures 6 and 7 show the time-series of the liberal democracy index in the countries with significant drops at some stage of the transition process.
Figure 6. FSU12 decliners
Source: V-Dem project and author’s calculations
In many countries, the drop comes suddenly and sharply, with the first and most prominent example being Belarus. There, it only took three years to go from one of the highest ranked FSU12 countries to fall to one of the lowest liberal democracy scores. In Poland, Romania, Bulgaria and Armenia, the process was also very rapid and significant changes happened in 2-3 years.
Figure 7. EU10 decliners
Source: V-Dem project and author’s calculations
In the Czech Republic and Hungary, the period of decline was much longer and in the case of Hungary, the drop was the most significant in the EU10 group. Ukraine stands out as more of an exception with a roller-coaster development in its liberal democracy score that first took it up the list and then back down to where it started. For those familiar with politics in these countries, it is easy to identify the elections and change in government that have occurred at the times the index has started to fall in all of these countries. In other words, the democratic declines have not started with coups but followed election outcomes where in most cases the incumbent leaders have been replaced by a new person or party.
How democracy came under attack
We will now take a closer look at what has been behind the instances of decline in the aggregate index by investigating how the sub-indices have developed in these countries. The sub-indices that build up the liberal democracy index are: freedom of expression and alternative sources of information; freedom of association; share of population with suffrage; clean elections; elected officials; equality before the law and individual liberty; judicial constraints on the executive; and legislative constraints on the executive (the structure is a bit more complex with mid-level indices, see V-Dem 2019a).
Table 1 shows how these indicators have changed in the time period the liberal democracy indicator has fallen significantly (with shorter versions of the longer names listed above but in the same order). The heat map of decline indicated by the different colours is constructed such that positive changes are marked with green, smaller declines are without colour, declines greater that 0.1 but smaller than 0.2 are in yellow and larger declines in red. Note that the liberal democracy index is not an average of the sub-indices but based on a more sophisticated aggregation technique (see V-Dem 2019b). Therefore, the Czech Republic and Bulgaria can have a greater fall in top-level liberal democracy index that what is indicated by the sub-indices.
Table 1. Changes in liberal democracy indicators at times of democratic decline
Source: V-Dem project and author’s calculations
For the countries with the largest changes in the liberal democracy index, it is clear that both freedom of expression and alternative sources of information have come under attack together with reduced judicial and legislative constraints on the executive. Among the EU10 countries, Hungary and Poland stand out in terms of reducing freedom of expression, while Romania has seen most of the decline coming from reducing constraints on the executive. Not surprisingly, Belarus stands out in terms of the overall decline in liberal democracy coming from reducing both freedom of expression and constraints on the executive in the most significant way.
On a more general level, the attack on democracy does differ between the countries, but in the cases where serious declines can be seen, the attack has been particularly focused on information aspects and constraints on the executive. At the same time, all countries let all people vote (suffrage always at 1) and let the one with the most votes get the job (elected officials).
Policy conclusions
This brief has provided some stylized facts on the first 30 years of liberal democracy in transition and some details on how democracy has come under attack in individual countries. It leaves open many questions that require further studies and some of these are indeed ongoing in this project and will be presented in future briefs and policy papers here.
Some observations have already been made here that can inform policy discussions on liberal democratic developments in the region. The first is that changes can happen very rapidly, both in terms of improvements but also in terms of dismantling important democratic institutions, including those that provide constraints on the executive or media that provides unbiased coverage before and after elections. What is also noteworthy is that these changes have almost always happened after an election where a new person or party has come to power, so the democratic system is used to introduce less democracy in this sense.
It is also interesting that in all of the countries, the most easily observed indicators of democracy such as suffrage and having the chief executive or legislature being appointed by elections are given the highest possible scores. In other words, even the most autocratic regime wants to look like a democracy; but as the old saying goes, “it is not who votes that is important, it is who counts”.
The regime changes at election times that have led to declining liberal democracy scores have also in many cases come as a result of the incumbents not doing a great job or voters not turning up to vote. It was enough for Lukashenko in Belarus to promise to deal with corruption and rampant inflation that was a result of the old guard’s mismanagement to turn Belarus into an autocracy. In Hungary, the change of regime came after the Socialist leader was caught on tape saying he had been lying to voters. While in Romania, only 39% voted in the 2016 election. And in Bulgaria, around half of the voters stayed at home in the presidential election the same year.
In sum, both incompetent and corrupt past leaders and disengaged or disillusioned voters are part of the decline in a liberal democracy that we have seen in recent years. It is clearly time for policy makers that are interested in preserving liberal democracy in the region and elsewhere to think hard about how democracy can be saved from illiberal democrats. Part of the answer clearly will have to do with how voters can be engaged in the democratic process and take part in elections. It also involves defending free independent media and the thinkers and doers that contribute to the liberal democracy that we cherish. The question is if the young generation will find a Greta for democracy that can kick-start a new transition to liberal democracy in the region and around the world.
For those readers that want to participate more actively in this discussion and have a chance to be in Stockholm on November 12, SITE is organizing a conference on this theme which is open to the public. For more information on the conference, please visit SITE’s website (see here).
References
- Freedom house data downloaded on Oct 4, 2019, from https://freedomhouse.org/content/freedom-world-data-and-resources
- Freedom house methodological note available at https://freedomhouse.org/report/methodology-freedom-world-2018
- Polity IV project data downloaded on Oct 4, 2019, from http://www.systemicpeace.org/inscrdata.html
- Polity IV project manual available at http://www.systemicpeace.org/inscr/p4manualv2018.pdf
- V-Dem project data downloaded on Sept 24, 2019, from https://www.v-dem.net/en/data/data-version-9/
- Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Anna Lührmann, Kyle L. Marquardt, Kelly McMann, Pamela Paxton, Daniel Pemstein, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Steven Wilson, Agnes Cornell, Lisa Gastaldi, Haakon Gjerløw, Nina Ilchenko, Joshua Krusell, Laura Maxwell, Valeriya Mechkova, Juraj Medzihorsky, Josefine Pernes, Johannes von Römer, Natalia Stepanova, Aksel Sundström, Eitan Tzelgov, Yi-ting Wang, Tore Wig, and Daniel Ziblatt. 2019a. “V-Dem [Country-Year/Country-Date] Dataset v9”, Varieties of Democracy (V-Dem)
- Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2019b. “The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data”, V-Dem Working Paper No. 21. 4th edition. University of Gothenburg: Varieties of Democracy Institute.
How to Intensify and Diversify Ukrainian Exports? The Case of Bilateral Trade with Germany
This policy brief focuses on trade relations between Ukraine and Germany. In particular, it analyses bilateral trade in goods and examines the possibilities for increasing Ukrainian exports to Germany, in both the extensive and the intensive margins. The brief identifies prospective product groups for such increases and discusses potential obstacles to trade intensification. Finally, it provides recommendations for the further trade development.
German-Ukrainian Trade
Germany has recently become one of the most important trading partners for Ukraine. In 2018, Germany was fifth in terms of Ukrainian export destinations and third in terms of its import source countries. While Ukraine, not surprisingly, is less important for German international trade (in 2018, Ukraine ranked 42nd in terms of Germany’s export and 45th in terms of its import), bilateral trade between Ukraine and Germany showed positive dynamics over the last five years.
Since Germany is a member of the European Union, its trade relations with Ukraine are regulated by legislation common for all EU member states. The EU’s political and economic cooperation with Ukraine is stipulated by the Association Agreement (AA). The AA is a comprehensive agreement provisioning the Deep and Comprehensive Free Trade Area (DCFTA) between Ukraine and the EU. While the provisional application of the AA began in the fall of 2014, the document fully entered into force on September 1, 2017. The abovementioned intensification of trade relations between Ukraine and Germany was to a significant extent driven by the signing of the DCFTA and a loss of a significant share of the Russian market.
The main Ukrainian exports to Germany include ignition wiring sets used in vehicles, aircraft and ships; low erucic acid, rape or colza seeds, iron ores agglomerated, maize, electrical switches etc. (see Table 1). Together, the top-15 product groups at a 6-digit level of the Harmonised System (HS) give 57% of the total exports from Ukraine to Germany.
Table 1. Top-15 Ukrainian product groups by export to Germany as of 2018
Source: UN Comtrade
This brief argues that both countries are likely to gain additional benefits from further intensifying bilateral trade relations. It summarizes the results of the research (Iavorskyi P. at al., 2019) on how to further expand and diversify Ukrainian exports to Germany, it identifies the prospective product groups and obstacles to their exports, and provides policy recommendations for trade development.
Promising Products
In order to find the most promising ways for increasing Ukrainian exports to Germany, this study employs a two-step approach. First, using a normalized revealed comparative advantage (NRCA) index (Run Yu et al, 2009) we distinguish goods, which Ukraine has world-wide comparative advantage in and Germany does not. A positive (negative) NRCA indicates that country’s actual share of a product in national exports is higher (lower) than the world average, – so that the country has a comparative advantage (disadvantage) in this commodity. According to this criterion, product groups with a negative NRCA for Germany and a positive NRCA for Ukraine were selected.
At the second stage, for the goods identified during the first step, a gravity model was estimated. A gravity model predicts bilateral trade flows based on the size of the economy and trade costs between them (such as distance, cultural differences, free trade agreements, tariffs, etc.). Being a general equilibrium model, it captures not only immediate impact of economic and political changes on trade between two countries, but also how it influences trade with other countries. A gap between current and potential export volumes predicted by the model is a potential for exports increase (which we refer to as undertrade).
The gravity model estimates the total undertrade between Ukraine and Germany at $ 500 million in 2016, or 35% of the total exports from Ukraine to Germany in the same year. Moreover, Ukraine has the potential to increase trade in both goods already exported to Germany as well as goods not yet supplied by Ukrainian companies to this market.
As for the structure of our findings, agricultural and mining commodities, as well as products of traditional Ukrainian export industries, such as metallurgy, are widely represented on the top of the undertraded commodity list. For example, more than a half of the estimated undertrade falls on primary food and primary industrial supplies, such as soybeans, barley, tomatoes, grain sorghum, iron ore, zirconium ores, etc. These categories already account for a large share of the current exports composition, and production in these sectors provides for a significant share of employment. Foreign currency inflow stipulated by exporting these products is also important for the Ukrainian economy.
At the same time, the undertrade in categories of final consumption, capital goods and transport is much lower. However, these product groups are important for exports diversification. These, for example, include liquid dielectric transformers, refrigerator cabinets, telescopes, tugs and pusher craft in capital goods, rail locomotives, railway cars, gas turbine engines in transport; automatic washing machines, electric space heaters, fans, coffeemakers, synthetic curtains, and leather apparel in consumer goods. Despite the complex regulation and relatively small amount of estimated undertrade, export diversification from primary to manufactured goods is important for overcoming export instability and long-term economic growth (Cadot at al. 2013), which is why promotion of trade in such areas is important.
Figure 1. Estimated undertrade according to broad economic categories
Source: Own calculations based on UN Comtrade data
Obstacles to Trade
Following the abolition or reduction of EU import duties between Ukraine and the EU under the DCFTA, tariffs do not significantly restrict exports of Ukrainian goods to the EU. Instead, technical regulations, sanitary and phytosanitary measures, geographical indications, licensing, etc. create significant barriers to bilateral trade. Thus, “non-tradability” can be explained, for instance, by the negative effects of various non-tariff barriers (both at European and national levels) or other factors, such as low competitiveness (in terms of price or quality) of Ukrainian goods compared to similar goods supplied by other countries, taste preferences of German consumers, peculiarities of importers’ associations, specific requirements of retailers, etc. Thus, harmonization of Ukrainian regulations with those of the European Union in accordance with the AA will help reduce customs barriers and existing divergences in regulations, and thus simplify the export of Ukrainian goods to the EU and Germany in particular.
Policy Recommendations
Based on the findings of the qualitative and quantitative research carried out, Ukrainian policy makers are advised to:
- Timely and effectively align Ukrainian legislation, standards and practices with those of the EU, in line with the Action Plan and Commitments undertaken by Ukraine under the DCFTA within the framework of the AA with the EU, in particular in such areas as technical barriers to trade, sanitary and phytosanitary measures, customs, and protection of intellectual property rights.
- Accelerate preparations for the signing of the ACAA (the Agreement on Conformity Assessment and Acceptance for Industrial Products) for the top three priority sectors of Ukrainian industry, which Ukrainian authorities agreed with European side, namely in the areas of low-voltage equipment, electromagnetic compatibility and machine safety, which will boost industrial technological exports to the EU and other countries.
- Conduct government level negotiations with the EU and Germany regarding the removal of those barriers to the single market faced by the promising Ukrainian goods that will not be lifted as a result of harmonization of regulations with the European ones.
- Take advantage of the Regional Pan-Euro-Mediterranean Preferential Rules of Origin Convention (the Pan-Euro-Med Convention), which establishes identical rules of origin for goods between its member-states under free trade agreements, and will facilitate the opening of new production facilities and involvement in regional and international value chains.
- Provide information and consulting support to local manufacturers and exporters regarding the most promising destination markets, help them find partners on such markets, advise on the best ways to penetrate such markets by organizing trade missions, etc.
Another push to the German-Ukrainian trade promotion may arise from facilitating German FDIs to Ukraine. German entrepreneurs and investors are interested in localizing German production facilities in Ukraine and establishing joint German-Ukrainian enterprises, STIs, in particular in such areas as agriculture, light industry (including textiles), civil engineering, renewable energy, and circular economy (GTAI 2018a, 2018b, 2018c). This form of cooperation also boosts Ukrainian exports, since such enterprises often produce intermediate inputs for German production. In order to promote joint enterprises setup Ukraine should:
- Establish effective mechanisms for protecting foreign investments, including export-oriented ones.
- Ensure the rule of law and effective protection of property rights.
- Create favorable macroeconomic conditions to ensure access to financing for both Ukrainian and foreign businesses.
References
- Cadot O., Carrère C., and V. Strauss‐Kahn, 2013. Trade Diversification, Income, and Growth: What Do We Know? Journal of Economic Surveys 27(4): 790-812
- Germany Trade & Invest (GTAI) (2018a). Branche kompakt: Ukrainischer Maschinenbau profitiert von steigenden Investitionen. Accessed online October 14, 2019.
- Germany Trade & Invest (GTAI) (2018b). Ukraine hat hohen Bedarf an moderner Landtechnik. Accessed online October 14, 2019.
- Germany Trade & Invest (GTAI) (2018c). Ukrainischer Markt für Windenergie im Aufwind. Accessed online October 14, 2019.
- Iavorskyi P. at al., 2019. “How to grow and diversify Ukrainian exports to Germany? Analysis and Recommendations” (in Ukrainian). Working paper
- Yu, R., Cai, J. & Leung, P. 2009. Ann Reg Sci, 43: 267. https://doi.org/10.1007/s00168-008-0213-3
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Russian Food Embargo: Five Years Later
In this brief, we report the results of a quantitative assessment of the consequences of counter-sanctions introduced by the Russian government in 2014 – Russian food embargo. We consider several affected commodity groups: meat, fish, dairy products, fruit and vegetables. Applying a partial equilibrium analysis to the data from several sources, including Rosstat, Euromonitor, UN Comtrade, industry reviews etc. as of 2018, we obtain that consumers’ total loss amounts to 445 bn Rub, or 3000 Rub per year for each Russian citizen. This is equivalent to a 4.8% increase in food expenditure for those who are close to the poverty line. Out of this amount, 84% is distributed towards producer gains, 3% to importers, while the deadweight loss amounts to 13%. Based on industry dynamics, we identify industries where import substitution policies led to positive developments, industries where these policies failed and group of industries where partial success of import substitution was very costly for consumers.
The full text of the underlying paper is forthcoming in the Journal of the New Economic Association in October 2019.
In August 2014, in response to sectoral sanctions against Russia, the national government issued resolution No. 778, which prohibited import of processed and raw agricultural products from the United States, the EU, Ukraine and a number of other countries (Norway, Canada, Australia, etc.). The goal was to limit market access for countries, which supported sectoral sanctions. The other rhetoric of the counter-sanctions was to support domestic producers via trade restrictions, or by other words – import substitution.
This brief provides an update of welfare analysis of counter-sanctions based on partial equilibrium model of domestic market. The initial estimations based on 2016 data can be found in another FREE Policy Brief here. This time we compare the consumption, outputs and prices of the counter sanctioned goods as of 2018 relative to 2013. The estimated consumer surplus changes, producer gains and prices are reported in Table 1.
Table 1. Welfare effects of counter-sanctions in 2018 relative to 2013.
Data sources: Rosstat, Euromonitor, UN COMTRADE
* Negative losses correspond to gains
** Negative gains correspond to losses
Green color was used to mark the commodity groups with a noticeable consumption growth in 2013-2018 and red color those with consumption decrease.
Effect on production
From the point of view of price dynamics, on the one hand, and consumption and output, on the other, the studied products can be divided into three groups.
The first group which we call “Success of import substitution” includes goods for which real prices (in 2013 level) increased by 2016 but afterwards, the growing domestic production ensured that by 2018 prices fell below the level of 2013 with a corresponding increase in consumption. This group includes tomatoes, pork, poultry and, with some reservation, beef. For beef, growing domestic production pushed prices down after 2016, but the level of consumption and prices have not yet reached the pre-sanction level.
For the second group, import substitution has not resulted in a price decrease, we call this group “Failure of import substitution”. For products in this group, the initial increase in prices by 2016 was not reverted afterwards. Their consumption decreased significantly compared to 2013, and domestic production either continued to fall after 2016, or its growth turned out to be fragile. This group includes apples, cheese, fish, as well as condensed milk and processed meat.
We call the third group “Very expensive import substitution”. It includes fromage, sour milk, milk and (to a lesser extent) butter. This group is characterized by increase in consumption and output in the period 2016–2018, but real prices over this period still remain very high.
Effect on consumers
By comparing the losses and gains of consumers in different categories of goods due to changes in real prices and real consumption, our analysis provides the following monetary equivalents. For all considered counter-sanctioned product groups, with the exception of poultry, pork and tomatoes, consumer losses are around 520 billion rubles per year (in 2013 prices). In three product groups (poultry, pork, tomatoes), in which there was a decrease in prices and a significant increase in consumption, the consumer gains are equivalent to 75 billion rubles per year. Thus, the total negative effect from counter-sanctions for the consumers amounted to 445 billion rubles a year, or about 3000 rubles for a person per year.
Given the cost of the minimum food basket, defined in Russia as 50% of the subsistence level, the impact of counter-sanctions on the budgets of Russian consumers can be estimated as follows. 3000 rubles account for approximately 4.8% of the annual cost of the minimum food basket. The minimum food basket is a set of food products necessary to maintain human health and ensure its vital functions that is established by law. In other words, one can say that 3000 rubles a year are equivalent to a 4.8% increase in food expenditure for those who are close to the poverty line.
Consumer surplus losses were significantly redistributed in favor of domestic production, totaling 374 billion, or 2500 rubles per year per person. Another 56 billion rubles (or 390 rubles per person) correspond to the deadweight loss, i.e., reflect the inefficiency increase of the Russian economy, and 16 billion rubles (110 rubles per person) is the equivalent of redistribution in favor of foreign producers, who get access to Russian market with higher priced products than before counter-sanctions.
Effect on foreign partners
As a result of the selective embargo, the geography of Russian imports of the affected goods has changed. Traditional suppliers of these goods, primarily from Europe, were replaced by suppliers from other countries due to trade diversion. Given the changes in the composition of importers after the imposition of sanctions, we single out countries that have lost and countries that have gained access to the Russian market. We use the change in trade volumes from the respective countries as indicators of growth and decrease in share of these importers in the Russian market. Below we consider in detail the three groups of goods with the largest gains for importers in 2018 compared with 2013: cheese, apples, butter.
Cheese imports decreased significantly after the imposition of counter-sanctions, in 2018 accounting for only 42% of their dollar value in 2013. The total gain of importers due to the growth of domestic prices in 2013-2018 amounted to 17.3 billion rubles (Table 1) and was distributed among following importing countries: Belarus (78%), Argentina (6%), Switzerland (4%), Uruguay (3%), Chile (3%), other countries (6%). Countries that lost their shares of the Russian cheese market included Ukraine, Holland, Germany, Finland, Poland, Lithuania, France, Denmark, Italy and Estonia. As mentioned earlier, domestic production and Belarusian imports were not able to fully compensate for imports from countries on the counter-sanctions list, and in 2016-2018 cheese consumption in Russia decreased significantly.
Apple imports after the initial drop in 2016 partially recovered in 2018, amounting to 66% of their dollar volume in 2013. The total gain of importers in 2018 compared to 2013 amounted to 15.0 billion rubles (Table 1); it was distributed between Serbia (22%), Moldova (19%), China (13%), Turkey (10%), Iran (10%), Azerbaijan (7%), South Africa (4%), Chile (3%), Brazil (3%) and other countries (9%). Poland suffered the most from the ban on apple imports; it accounted for about 80% of all losses. Other losers from counter-sanctions include Italy, Belgium and France. The reorientation of trade flows did not completely replace Polish imports, so apple consumption in 2016-2018 was significantly lower than in 2013.
Imports of butter in 2018 was also below the level of 2013 (67% of dollar value). The gain of importers in 2018 compared to 2013 amounted to 11.2 billion rubles and was distributed among the following trading partners: Belarus (90%), Kazakhstan (4%), Kyrgyzstan (3%) and other countries (3%). Among the countries bearing most of the negative burden of the diversion of trade, one should mention Finland and Australia.
Conclusions
Five year after counter-sanctions were put in place Russian consumers continue paying for them out of their pockets. While few industries have demonstrated a positive effect of import substitution policies, most are not effective enough to revert the price dynamics.
References
- Kuznetsova, Polina; and Natalya Volchkova, 2019. “How Much Do Counter-Sanctions Cost: Welfare Analysis”, Journal of New Economic Association, N3(43), pp 173-183. (in Russian)
Short-Run and Long-Run Effects of Sizeable Child Subsidy: Evidence from Russia
How to design the optimal pro-natalist policy is an important open question for policymakers around the world. Our paper utilizes a large-scale natural experiment aimed to increase fertility in Russia. Motivated by a decade-long decrease in fertility and population, the Russian government introduced a sequence of sizable child subsidies (called Maternity Capitals) in 2007 and 2012. We find that the Maternity Capital resulted in a significant increase in fertility both in the short run and in the long run. The subsidy is conditional and can be used mainly to buy housing. We find that fertility grew faster in regions with a shortage of housing and with a higher ratio of subsidy to housing prices. We also find that the subsidy has a substantial general equilibrium effect. It affected the housing market and family stability. Finally, we show that this government intervention comes at substantial costs.
In all European and Northern American countries the fertility is below the replacement level (United Nations, 2017). Following this concern, most of the developed countries have implemented various large scale and expensive pro-natalist policies. Yet, the effectiveness of these policies is unclear, and the design of the optimal pro-natalist policy remains a challenge.
There are several important open research questions on the evaluation of these programs. The first is whether these programs can induce fertility in the short-run and/or in the long-run horizon. Indeed, very few of these expensive and large-scale policies are proved to be an effective tool to increase fertility (Adda et al, 2017). The next set of questions deals with further evaluation of the programs: What are the characteristics of families that are affected by this policy? How costly is the policy, i.e. how much is the government paying per one birth that is induced by the policy? Finally, what are the non-fertility related effects of these policies? While most of the studies that analyze the effect of pro-natalist policies concentrate on fertility and mothers’ labor market outcomes, these, usually large-scale, policies may have important general equilibrium and multiplier effects that may affect economies both in the short run and long run (Acemoglu, 2010).
In our paper we utilize a natural experiment aimed to increase fertility in Russia to address these questions.
Motivated by a decade-long decrease in fertility and depopulation, the Russian government introduced a sizable conditional child subsidy (called Maternity Capital). The program was implemented in two waves. The first wave, the Federal Maternity Capital program, was enacted in 2007. Starting from 2007, a family that already has at least one child, and gives birth to another, becomes eligible for a one-time subsidy. Its size is approximately 10,000 dollars, which exceeds the country’s average 18-month wage and exceeds the country’s minimum wage over a 10-year period. The recipients of the subsidy can use it only on three options: on housing, the child’s education, and the mother’s pension. Four years later, at the end of 2011, Russian regional governments introduced their own regional maternity programs that give additional – on the top of the federal subsidy – money to families with new-born children.
In our paper, we document that the Maternity Capital program results in a significant increase in fertility rates both in the short run (by 10%) and in the long run (by more than 20%). This effect can be seen from both within-country analysis and from comparing the long-term growth of fertility rates in Russia with Eastern and Central European countries that face similar economic conditions and had similar pre-reform fertility trends. Like Russia, Eastern European countries experienced a drop in fertility rates right after the collapse of the Soviet Union and had similar trends in fertility up until 2007. Our results show that while having similar trends in fertility before 2007, afterward Russia significantly surpassed all the countries from this comparison group.
Figure 1 illustrates the effect of the Maternity Capital on birth rates. The top two panels show monthly birth rates (simple counts and de-seasoned); the bottom panels show total fertility rates in Russia versus Eastern European countries, and versus the European Union and the US.
Figure 1. Total Fertility Rate, Russia, Eastern European countries, USA and EU.
Source: Sorvachev and Yakovlev (2019), and http://www.fertilitydata.org/.
The effects of the policy are not limited to fertility. This policy affects family stability: it results in a reduction in the share of single mothers and in the share of non-married mothers.
Also, the policy affects the housing market. Out of three options (education, housing and pension), 88% of families use Federal Maternity Capital money to buy housing. We find that the supply of new housing and housing prices increased significantly as a result of the program. Confirming a close connection between the housing market and fertility, we find that in regions where the subsidy has a higher value for the housing market, the program has a larger effect: the effect of maternity capital was stronger, both in the short run and long run, in regions with a shortage of housing, and in regions with a higher ratio of subsidy to price of apartments (i.e. those regions where the real price of subsidy as measured in square meters of housing is higher).
Figure 2 below shows the effect of Federal Maternity Capital on birth rates in different regions. It shows no effect on fertility in Moscow, small effect in Saint-Petersburg; whereas the sizable effect of maternity capital in other Russian regions.
Figure 2. Effect of Federal Maternity capital, by regions
Source: Sorvachev and Yakovlev (2019), and http://www.gks.ru/.
These results suggest that cost-benefit analysis of such policies should go beyond the short-run and long-run effects on fertility. Ignoring general equilibrium issues may result in substantial bias in the evaluation of both short-run and long-run costs and benefits of the program.
While there are many benefits of the program, we show that this government intervention comes at substantial costs: the government’s willingness to pay for an additional birth induced by the program equals approximately 50,000 dollars.[1]
For more detailed evaluation of the results see Evgeny Yakovlev and Ilia Sorvachev, 2019, “Short-Run and Long-Run Effects of Sizable Child Subsidy: Evidence from Russia”, NES working Paper # 254, 2019.
References
- Acemoglu, Daron 2010 “Theory, General Equilibrium, Political Economy and Empirics in Development Economics”, Journal of Economic Perspectives, 24(3), pp. 17-32. 2010
- Adda, Jérôme, Christian Dustmann and Katrien Stevens 2017. “The Career Costs of Children”. Journal of Political Economy, 125, 2, 293-337.
- Ilia Sorvachev and Evgeny Yakovlev, 2019, “Short-Run and Long-Run Effects of Sizable Child Subsidy: Evidence from Russia”, NES working Paper #254 and LSE IGA Research Working Paper Series 8/2019
[1] Roughly, the WTP (US$50,000) exceeds nominal US$10,000 subsidy because the government pays for all (100%) families that give birth to a child to induce additional (20%) increase in fertility. See paper for more accurate elaboration.
The Gender Wage Gap in Belarus: State vs. Private Sector
This brief is based on research that studies gender difference in wages in Belarus using survey data from 2017. According to the results, the unconditional gender wage differential equals 22.6%. The size of the wage gap is higher in the state sector than in the private sector. Additionally, it increases in the state sector throughout the wage distribution and accelerates at the top percentiles, indicating the presence of a strong glass ceiling effect.
Introduction
The causes and consequences of the gender wage gap in the labor market, that is the difference between the wages earned by women and men, continue to attract increasing attention in empirical studies worldwide.
Belarus’ labor market is not an exception and faces the problem of wage inequality like other neighboring and transition countries. According to the National Statistical Committee of the Republic of Belarus (Belstat), the average gender wage gap in terms of monthly wages was 19% in 2000, it increased up to 23.8% in 2015, and reached 25.4% in 2017.
In this regard, this brief updates the estimates of the gender wage gap in Belarus. And it summarizes the results of the study on what the role of the state and private sectors are in the distribution of gender wage differences in Belarus (Akulava and Mazol, 2018).
Data and methodology
The data used in the research is from the Generations and Gender Survey (GGS) conducted in Belarus in 2017. This survey is a nationally representative dataset that is based on interviews of about 10,000 permanent residents of Belarus, aged 18–79, covering the whole country disaggregated by regions. The GGS contains information on a range of individual (age, gender, marital status, educational attainment, employment status, hours worked, wages earned etc.) and household-level characteristics (household size and composition, land holding, location, asset ownership etc.).
The analysis is based on the typical Mincer model of earnings that estimates individual wage income as a function of various influencing factors using the OLS approach (Mincer, 1974). Specifically, the Mincerian wage equation is defined where the log of the hourly wage rate is regressed on a set of male and female workers’ personal and job characteristics (educational level, working experience, occupational type, organization type, family characteristics, and region).
Next, we use the Oaxaca-Blinder (OB) methodology (Oaxaca, 1973; Blinder, 1973) to identify and quantify the contribution of personal characteristics and the unexplained component (which is referred to as differences in returns) to the wage difference between males and females.
Finally, we apply the Machado-Mata (MM) technique (Machado and Mata, 2005) to look into the nature of the wage gap at various points of the income distribution and also to test the difference for individuals employed in the state or private sectors. For the Machado-Mata procedure, we estimate our specifications at the 10th, 25th, median, 75th and 90th percentiles of the wage distribution.
Results
The analysis shows that women’s wages are lower than men’s wages all over the wage distribution. The average raw gender wage gap equals 22.6% and it increased substantially compared with 9.0% in 1996 and 17.8% in 2006, the numbers obtained in the study conducted by Pastore and Verashchagina (2011).
Figure 1. Gender differential by quantile of the wage distribution
Source: Authors’ estimates based on GGS.
The level of female earnings is lower than the male regardless of the occupational type, educational background, work experience and organizational type. Moreover, the underpayment of women is lower for low earning workers, but increases up to the end of the wage distribution (see Figure 1).
The OB decomposition shows that female educational attainment and job-related experience help to decrease the level of the wage gap slightly (see Table 1).
Table 1. Oaxaca-Blinder decomposition results
Source: Authors’ estimates based on GGS.
However, the occupational choice is leading to an expansion of the difference in earnings. However, its effect is also small, indicating that occupational segregation plays a minor role in explaining the gender wage gap. The major share of the gender wage gap is formed by the unexplained part, which is likely to be attributed to discrimination.
Next, the level of remuneration is higher among private companies. However, contrary to other countries in transition, the average gender wage gap in Belarus in the private sector is lower than in the public sector.
Moreover, the MM decomposition estimates presented in Table 2 demonstrate that the gender wage gap in the state sector shows evidence of the glass ceiling effect (the size of the total wage gap expands at the top of the wage distribution), while no evidence of either glass ceiling or sticky floor (the size of the total wage gap increases at the bottom of the wage distribution) in the private sector.
The negative coefficient near the characteristics part in the private sector shows that female endowments outweighs their male counterparts. Thus, controlling for personal characteristics, if the labor market rewards males and females equally, the wages of females in the private sector should be substantially higher (see Table 2).
Table 2. Machado-Mata decomposition of the observed gender wage gap by organization type
Source: Authors’ estimates based on GGS.
Finally, the results also suggest that female workers are better off being in the private sector at the lowest and the highest percentiles (i.e. the size of the gender wage gap is lower there compared to the 25th and 50th percentile).
A possible explanation for all the above is that institutional differences seem to play a crucial role here. First, Belarusian private firms work under stronger regulation than in other transition economies which makes it harder for them to set low wages. Second, they also operate under stronger competition (compared to state companies), which force them to identify individual productivity more correctly, narrowing the gender difference in pay. In contrast, the paternalistic attitude to women left as a legacy from the Soviet Union further increases the gender wage gap in the public sector.
Conclusion
In this brief, we present new evidence on the existence of a gender wage gap in the Belarusian labor market and analyze the differences in its distribution between the state and private sectors.
Our results show that the unconditional gender wage gap in terms of hourly wages equals 22.6%. Thus, jointly with a previous study (see Pastore and Verashchagina, 2011) and recent official indicators, all these indicate that the pace towards gender equality in Belarus seems to be sluggish. For the moment, all institutional changes accomplished by the Belarusian government to reduce gender discrimination are not enough and require additional efforts to cope with that problem.
However, the gender wage gap is shown to be much wider in the public sector than in the private sector. At the same time the private sector appears to be more attractive than the public sector in the country in terms of the level of remuneration. Therefore, additional structural shifts of the economy accompanied by the growth of competition are needed to induce a further reduction of the gender wage gap.
References
- Akulava, M. and A. Mazol. (2018). What Forms Gender Wage Gap in Belarus? BEROC Working Paper Series, WP no. 55.
- Blinder, A. (1973). Wage Discrimination: Reduced Form and Structural Estimates. Journal of Human Resources, 8, 436-455.
- Machado, J., and J. Mata. (2005). Counterfactual Decomposition of Changes in Wage Distributions Using Quantile Regression. Journal of Applied Econometrics, 20(4), 445‑465.
- Mincer, J. (1974). Schooling, Experience, and Earnings. New York: Columbia University.
- Oaxaca, R. (1973). Male-Female Wage Differentials in Urban Labor Markets. International Economic Review, 14(3), 693-709.
- Pastore, F., and A. Verashchagina. (2011). When Does Transition Increase the Gender Wage Gap? An application to Belarus. The Economics of Transition, 19(2), 333-369.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Social Media and Xenophobia
We study the causal effect of social media on hate crimes and xenophobic attitudes in Russia, using variation in social media penetration across cities. We find that higher penetration of social media leads to more ethnic hate crimes, but only in cities with a high baseline level of nationalist sentiment prior to the introduction of social media. Consistent with a mechanism for the coordination of crimes, the effects are stronger for crimes with multiple perpetrators. We show that social media penetration also had a persuasive effect on young and uneducated individuals, who became more likely to have xenophobic attitudes.
In recent years, the world has witnessed a large increase in expressions of hate, particularly of xenophobia. Candidates and platforms endorsing nationalism and views associated with intolerance toward specific groups have also gathered increased popular support both in the U.S. and across Europe. There is a lot of speculation about the potential drivers of this increase in the expression of hate. In our recent paper (Enikolopov et al, 2019) we study the role of social media in this process. This brief introduces the topic and offers a short outline of our findings.
Conceptually, social media could foster hate being expressed through different channels. First, social media reduces the cost of coordination. For example, there is evidence that it facilitates political protest (Enikolopov, Makarin, Petrova, 2018). Coordination facilitated through social media might be particularly relevant for illegal and stigmatized activities, such as hate crime: social media might make it easier to find like-minded people (through targeted communities and groups); it might also reduce the cost of asking or exposing oneself by providing a more anonymous forum for social interactions. Social media might also influence people’s opinions: tolerant individuals might be more exposed to intolerant views, while intolerant individuals might end up in an “echo chamber” (Sunstein 2001, 2017, Settle 2018) that make their views even more extreme. In our paper, we study the causal effect of social media exposure on xenophobic crimes and xenophobic attitudes in Russia and provide evidence on the particular mechanisms behind these effects.
The challenge in identifying a causal effect of social media is that access and consumption of social media are not randomly assigned. To surmount this challenge, we follow the approach of Enikolopov et al. (2018) and exploit a feature of the introduction of the main Russian social media platform – VKontakte (VK). This social media, which is analogous to Facebook in functionality, was the first mover on the Russian market and secured its dominant position with a user share of over 90% by 2011. VK was launched in October 2006 by Pavel Durov, its founder, who at that time was an undergraduate student at St Petersburg State University (SPbSU). Initially, users could only join the platform by invitation, through a student forum of the University, which was also created by Durov.
As a result, the vast majority of the early users of VK were students of SPbSU. This, in turn, made their friends and relatives more likely to open an account. And since SPbSU attracted students from around the country, this sped up the development of VK in the cities, from which these students were coming from. Network externalities magnified these effects and, as a result, the idiosyncratic variation in the distribution of the home cities of Durov’s classmates had a long-lasting effect on VK penetration. Following this logic, we use fluctuations in the distribution of student of SPbSU across cities as an instrument for the city-level penetration of VK. We then evaluate the effect of higher VK penetration on hate crimes and hate attitudes, combining data on hate crimes for the period between 2007 and 2015 collected by a reputable Russian NGO SOVA with survey data on hate attitudes.
Previous findings indicate that whether information from media induces people to be involved in the active manifestation of xenophobic attitudes or not depends on predispositions of the population. For example, Adena et al (2015) demonstrate that radio propaganda by the Nazis in the 1930’s was effective only in areas with a historically high levels of anti-Semitism. The role of the underlying level of nationalism is likely to be even stronger for social media, in which the content of the media itself directly reflects the attitudes of the population. This is particularly relevant for hate crimes committed by multiple perpetrators, in which social media can facilitate the coordination of such crimes.
Thus, we test whether the effect of social media depends on the pre-existing level of nationalism. To get at this underlying sentiment, we break cities by their level of support for the Rodina (“Motherland”) party, which ran in the national 2003 elections (the last parliamentary elections before the creation of VK) on an explicit nationalistic, xenophobic platform.
We find that penetration of social media leads to more ethnic hate crimes, but only in cities with a high baseline level of nationalist sentiment prior to the introduction of social media. For example, in cities with a maximum level of support of Rodina an increase in the number of VK users by 10% lead to an increase in ethnic hate crimes by 20%, while it had no significant effect on hater crime in cities with minimal support of Rodina. There is also no evidence that future social media penetration is related to ethnic hate crimes before the creation of social media, regardless of the level of pre-existing nationalistic attitudes.
Further evidence is consistent with social media playing a coordination role in hate crimes. The effect of social media is stronger for crimes perpetrated by multiple individuals (as opposed to crimes committed by a single person), where coordination is more important. These heterogeneous effects are also not consistent with results being simply driven by a higher likelihood of hate crime in places with higher social media penetration, unless this effect were present precisely in cities with higher support for Rodina and for crimes with multiple perpetrators, for example – which we find unlikely.
Having found evidence of a causal effect of social media on ethnic hate crimes, consistent with a mechanism of coordination, we turn next to the impact of social media on xenophobic attitudes. We designed and organized an online survey, and launched it in the summer of 2018, reaching 4,327 respondents from 64 cities. To measure xenophobic attitudes, we examined answers to the question “Do you feel irritation of dislike for individuals from some other ethnicities?” Note that, unlike the coordination of hate crimes, the persuasive effects of social media are not necessarily expected to be strongest in cities with higher baseline nationalistic sentiment since individuals on social media can get as easily connected to people outside their city. In fact, it is conceptually possible that the persuasion would be stronger in cities with lower baseline nationalistic sentiment: individuals might have previously been less aware of and less exposed to these types of views before the introduction of social media.
Since there might be a stigma in reporting xenophobic attitudes even in anonymous surveys, we use a “list experiment” to approximate “truly-held” xenophobic attitudes. In particular, the list experiment works as follows: first, respondents are randomly assigned either into a control group or a treatment group. Respondents in all groups are asked to indicate the number of policy positions they support from a list of positions on several issues. Support for any particular policy position is never indicated, only the total number of positions articulated on the list that a respondent supports. In the control group, the list includes a set of contentious, but not stigmatized, opinions. In the treatment group, the list includes all the contentious opinions from the control list, but also adds the opinion of interest, which is potentially stigmatized. The degree of support for the stigmatized opinion can be assessed by comparing the average number of issues supported in the treatment and control groups. The question of interest, randomly added to half of the questionnaires, was “Do you feel irritation of dislike for individuals from some other ethnicities?”.
The results indicate that the average share of people who agree with the statement is 37%. While there is no significant effect of social media penetration on xenophobic attitudes for the whole sample, there is a significant effect for important subsamples, which are at a higher risk of being involved in hate crime, such as respondents with lower levels of education or young respondents. Of course, the individuals that became more likely to engage in hate crime are not necessarily the same that have been persuaded to have more xenophobic attitudes (especially given the question used to assess attitudes) – though it is possible that some individuals who would have been close to committing crimes in the absence of social media might have been persuaded enough to switch their behavior in the presence of social media.
At the same time, we do not find that social media leads to an increase in xenophobic attitudes when measured with a direct question. The results are confirmed if we use a much larger, nationally representative survey of more than 30,000 respondents conducted by one of the biggest Russian survey companies FOM in 2011. In principle, it is possible that social media not only changed real attitudes but also the perception of the social acceptability of expressing these attitudes. However, we do not find any evidence that social media reduces the stigma of admitting xenophobic attitudes. The fact that we find the effect of social media on actual attitudes, but not on the expressed ones suggests, that if anything the stigma increased, at least for the respondents who acquired xenophobic attitudes as a result of social media influence. This highlights the importance of using a survey method that reduces concerns with social acceptability, such as list experiments.
Overall, our results indicate that social media lead to an increase in both ethnic hate crimes and xenophobic attitudes in Russia. However, the effect on hate crime is observed only in cities in which there was already a high level of nationalism. Additional evidence indicates that this effect is driven both by facilitating the coordination of nationalists and by persuading people to become more xenophobic. These findings contribute to a growing body of evidence that social media is a complex phenomenon that has both positive and negative effects on the welfare of people (see also Allcott et al, 2019), which has to be taken into account in discussing policy implications of the recent changes in media technologies.
References
- Allcott, H., Braghieri, L., Eichmeyer, S., Gentzkow, M. (2019) “The Welfare Effects of Social Media”, Working paper.
- Burzstyn, L., Egorov, G., Enikolopov, R., Makarin, A. (2019) “Social Media and Xenophobia: Evidence from Russia”, Working paper.
- Enikolopov, R., Makarin, A., Petrova, M. (2018) “Social Media and Protest Participation: Evidence from Russia“, Working paper.
- Settle, J. E. (2018) Frenemies: How Social Media Polarizes America. Cambridge University Press.
- Sunstein, C. (2001) Republic.com. Princeton University Press.
- Sunstein, C. (2017) Republic: Divided Democracy in the Age of Social Media. Princeton University Press.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.