Tag: Russia
Putting the “I” Back in Team: The Rise of International Teams in Science
In this policy brief, I discuss the increasing prevalence of international teams in the production of scientific knowledge. I outline several potential factors that may explain these trends and discuss recent evidence from an original survey of coauthors on scientific papers regarding their collaboration behavior. Finally, as a notable example of increased international collaboration, I discuss the increase in scientific collaboration between Russia and the US after the end of the Cold War.
The Increase in Collaboration and Internationalization of Teams
Teams are becoming more prevalent in science. Both the share of papers produced by teams and the number of scientists working on scientific papers has increased in recent decades (Wuchty, Jones and Uzzi, 2007). Economic theory suggests that scientific research is becoming increasingly collaborative since the frontier of scientific knowledge has become more complex and specialized so that more researchers are needed to combine their expertise to make advances (Jones, 2009). Team members are also becoming more geographically dispersed: the share of papers resulting from international collaborations has increased, and within the US, scientists today are more likely to have coauthors located in a different city than before (Freeman, Ganguli and Murciano-Goroff, 2014).
These trends can be seen clearly in the graph below from the National Science Board’s Science and Engineering Indicators 2012. It shows the share of both world papers and US papers from 1990-2010 that are coauthored, coauthored with domestic coauthors only, and coauthored with at least one international coauthor. Collaboration in general and international collaboration have been increasing steadily since 1990 both in the world and in the US. However, for the US, the share of domestic-only collaborations has plateaued, while it is increasing in the rest of the world. In a recent Nature article, Adams (2013) shows that this trend similarly holds for other Western countries (United Kingdom, Germany, France, the Netherlands, Switzerland), while for emerging economies (China, India, South Korea, Brazil, Poland), domestic collaborations are also increasing.
Figure 1. World and US Trends in Scientific Collaboration, 1990-2010
Source: From National Science Board (2012)
Why has Science Become More International?
There are many potential reasons for the recent increases in international collaboration. An important factor has likely been the spread of the scientific workforce and R&D activities throughout the world (Freeman, 2010). The growing number of science and engineering PhDs in developing countries, some of whom are international students and post-docs returning to their home countries has expanded the supply of potential collaborators around the world (Scellato, Franzoni, and Stephan, 2012). Another factor is funding that has shifted scientific production towards international teams, as increased government and industry R&D spending in developing countries and grant policies by the European Union and other countries have supported international cooperation.
The lower cost of travel and communication in recent decades has also reduced the cost of collaborating with people in different locations. For example, Agrawal and Goldfarb (2008) show how the expansion of Bitnet, the precursor to the Internet, led to increased collaboration between institutions within the US. Finally, the location of scientific equipment and materials, such as the CERN Large Hadron Collider, telescopes, or climatological data available only in certain parts of the world, have increased international collaboration, and in some fields, has made international collaboration a necessity.
Survey Evidence on Scientific Collaborations
In a recent paper, my coauthors and I present the results of an original survey we conducted of scientists regarding collaboration (Freeman, Ganguli and Murciano-Goroff, 2014). In August 2012 we conducted a web-based survey of the corresponding authors of scientific papers with at least one US coauthor published in 2004, 2007, and 2010 in the fields of Nanotechnology, Biotechnology, and Particle Physics.
We customized each survey to ask the corresponding author about the collaboration and individual team members. The survey questions asked about how the team formed, how it communicated and interacted during the collaboration, the contribution of each coauthor, types of research funding, and the advantages and disadvantages of working with the team. We received 3,925 responses, so that our response rate was approximately 20%.
The survey also asked the respondent which country each coauthor was “primarily based in during the research and writing” of the article. This gives us a more accurate measure of whether teams are international than can be typically gleaned from publication data, which are based on author affiliations at the time of publication. Defining international teams from author affiliations alone can produce errors if affiliations change between the time the research was undertaken and the time of publication, or because some people have affiliations from more than one country.
Our analysis of the survey data uses the respondents’ information to define US collocated, US non-collocated and international teams. One of our key results is that face-to-face meetings continue to play an indispensible role in collaborations: most collaborators first met while working in the same institution. Teams also reported that while carrying out the research, they communicated often through face-to-face meetings, even with coauthors from distant locations.
Figure 2 below displays how the corresponding author responded about how they first met their team members. It shows that former colleagues play a very important role in the formation of international teams, followed by former students, conferences and institution visits, which equally contribute. The graph also shows the similarity between international teams and US non-collocated teams in how coauthors met. For other survey questions, our analysis also shows similarities between international teams and US non-collocated teams, suggesting that the salient issues are more about geography in general rather than necessarily about national borders.
Figure 2. How Coauthors First Met
Source: From Freeman, Ganguli and Murciano-Goroff (2014)
Another key finding from our survey is that the main reason for most collaborations, whether domestic or international, is to combine the specialized knowledge and skills of coauthors. We also asked the corresponding authors their views of the advantages and challenges of their collaboration. The most often cited advantage for all types of collaborations was “Complementing our knowledge, expertise and capabilities” and “learning from each other”. For the challenges, US non-collocated and international teams tended to agree more that there was “Insufficient time for communication”, “Problems coordinating with team members’ schedules”, and “Insufficient time to use a critical instrument, facility or infrastructure”, but international teams did not report these problems more often than US non-collocated teams. Where international teams differed is that these teams were the most likely to agree that their “research reached a wider audience”.
International Collaboration After the End of the USSR
A small but significant part of the increase in international collaboration since the 1990s can be attributed to the end of the Cold War. In “Russian-American Scientific Collaboration” (Ganguli, 2012), I examine trends in international collaboration by Russian and US scientists since the end of the USSR. Given the nature of the Cold War and restrictions on travel and communication with the West, I show that there was a dramatic increase in the number of publications with at least one Russian and a US coauthor from 1985 to 2005.
In addition to the lifting of travel and communication restrictions, there are several factors that contributed to the surge in collaborations between American and Russian scientists after the end of the USSR. First, at the level of the Russian government, there was a switch to a more open and collaborative approach to science. Part of this effort included establishing international centers for research in Russia aimed at integrating Russia into the global science community. Another important factor facilitating collaborations with Western researchers were foreign grant programs. The large increase in the emigration of Russian scientists in the 1990s to the West also contributed to international collaboration. After emigrating, many Russian scientists maintained close links to their colleagues in Russia, and coauthored papers with their former colleagues, which are counted as internationally coauthored publications.
While many of these factors have aided international cooperation after the end of the USSR, there have also been significant challenges that made cooperation difficult. Some of these challenges in the early 1990s included the political instability, organizational turnover making long-term funding agreements difficult to implement, difficulty transferring funds due to the underdeveloped banking system, high taxation and customs duties, lack of effective intellectual property rights, poor infrastructure, lack of a shared language (both linguistic and cultural), and external regulations (see further discussion in OECD, 1994). However, many of these challenges have now been overcome, leading to the continued increase in international collaboration between Russian and US scientists.
My analysis in Ganguli (2012) shows that the increase in Russian-American collaboration was more pronounced in some fields of science versus others, particularly in Physics. Figure 3 shows that the bulk of the articles published with Russian and American coauthors were Physics articles, with a sharp increase occurring immediately after 1991.
Figure 3. Russia-United States Publications By Field, 1985-2005
Source: From Ganguli (2012)
While some of the differences across the fields can be attributed to the number of scientists active in these fields, there are also other potential contributing factors. For example, it may be that there was greater emigration of scientists from certain fields abroad, and links between emigrants and those who remained in Russia persisted. Graham and Dezhina (2008: 24) suggest that over 50 percent of emigrants were physicists and mathematicians. Another reason may be that international collaboration was more important in some fields due to the knowledge or resources needed to conduct research during the economic crisis of the 1990s. As Wagner Brahmakulam, Peterson, Staheli, and Wong (2002) point out, physics research received significant amounts of US government funding for international collaboration, partly because expensive equipment that is needed and through collaboration, countries could share costs. Also, physicists from many countries often meet and work together at international research centers like CERN. Moreover, in some fields, the US and Russian governments shared priorities in funding international cooperation, like biomedical and health sciences, energy, physics, while there were gaps in some areas where Russia devoted resources and the US did not, like chemistry (Wagner et al. 2002: 24). Graham and Dezhina (2008: 141) also discuss how Western colleagues benefited from working with Russians especially in fields like zoology, botany and the earth sciences, since the Russian colleagues provided access to data from unique regions not available previously.
Support for International Teams?
This policy brief has discussed some reasons for the increase in international scientific collaboration and related empirical evidence, including insights from collaboration after the end of the USSR. The growth in collaboration and the geographic dispersion of teams is likely to continue; the frontier of scientific knowledge will become more complex and specialized, so that an even greater numbers of researchers will be needed to combine their expertise, and they are likely to be spread across increasingly distant locations.
These trends raise many complex issues for policymakers. For some countries, international collaboration may be the only way to sustain the science sector as the frontier of knowledge becomes more complex and resource-intensive. For some, international collaborations may increase the emigration of home-grown talent to wealthier countries. To what extent international collaboration should be supported, and how, will be important policy questions going forward. Typically, funding for international projects has been the main policy lever, and the Russian experience suggests that grant programs did play a critical role in that case. As our survey evidence in Freeman, Ganguli and Murciano-Goroff (2014) suggests, face-to-face meetings are especially important in forming and sustaining international collaborations. Thus, funding mechanisms that include provisions for research stays and face-to-face meetings may be the most effective means for fostering international collaborations.
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References
- Adams, J. (2013). “Collaborations: The Fourth Age of Research.” Nature, 497(7451), 557-560.
- Agrawal A, Goldfarb A (2008). “Restructuring Research: Communication Costs and the
- Democratization of University Innovation,” American Economic Review, 98(4):1578-1590.
- Freeman, Richard B. (2010). “Globalization of Scientific And Engineering Talent: International Mobility of Students, Workers, and Ideas and The World Economy.” Economics Of Innovation And New Technology, Volume 19, issue 5, 201 pp. 393-406.
- Freeman, Richard B., Ina Ganguli and Raviv Murciano-Goroff (2014). “Why and Wherefore of Increased Scientific Collaboration,” NBER Working Paper No. 19819, Issued in January 2014.
- Ganguli, Ina (2012). “Russian-American Scientific Collaboration” in Y.P. Tretyakov (ed), Russian-Аmerican Links: Leaps Forward and Backward in Academic Cooperation. St. Petersburg, Russia: Nestor-Historia, pp. 120-135.
- Graham, Loren and Irina Dezhina (2008). Science in the New Russia: Crisis, Aid, Reform. Bloomington and Indianapolis: Indiana University Press, 2008.
- Jones, Ben (2009). “The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is
- Innovation Getting Harder?” Review of Economic Studies, 76:283-317.
- National Science Board (2012). Science and Engineering Indicators 2012. Arlington VA: National Science Foundation (NSB 12-01).
- National Science Board (2006). Science and Engineering Indicators 2006. Arlington VA: National Science Foundation (NSB 06-01).
- OECD (1994). Science, Technology, and Innovation Policies. Federation of Russia. Paris: Organisation for Economic Co-operation and Development, 1994.
- Scellato, G., Franzoni, C., & Stephan, P. (2012). “Mobile Scientists and International Networks,” NBER Working Paper 18613.
- Wagner, Caroline, Irene Brahmakulam, D.J. Peterson, Linda Staheli, and Anny
- Wong (2002). U.S. Government Funding for Science and Technology Cooperation with Russia.
- Santa Monica, CA: RAND Corporation, 2002.
- Wuchty, S., Jones, B. F., & Uzzi, B. (2007). “The Increasing Dominance Of Teams In Production Of Knowledge.” Science, 316(5827), 1036-1039.
Tajikistan Joining the Customs Union of Russia, Belarus and Kazakhstan: Pros and Cons
Authors: I.A. Densiova, A.M. Malokostov, and N.A. Turdyeva, CEFIR
In this brief we summarize the results obtained in a CEFIR research project on the economic impact of Tajikistan joining the Customs Union of Russia, Belarus and Kazakhstan conducted for the Eurasian Development Bank in 2013 (EBD, 2013). We argue that integration has to be comprehensive to be mutually beneficial: indeed, trade effects are marginal, and the highest stakes are at migration regulation in the CU member-countries and the investment opportunities in Tajikistan.
Integration Formations in the Monetary Sphere: the Possibility and the Necessity for Monetary Integration in the Post-Soviet Region
This policy brief addresses the possibility of monetary integration in the post-Soviet region. It provides a short overview of the literature devoted to the formation and development of the monetary unions, and argues that, based on this literature and real-world experiences, monetary integration can be of substantial value for the CIS states. However, such monetary union is not feasible in the near future due to weak economic integration of the national economies of the CIS countries, significant difference in their development level, and imbalances in allocation of bargaining power between the states. This policy brief suggests that a first step towards monetary integration could be an adoption of a supranational unit of account on the territory of the Customs Union between Russia, Belarus and Kazakhstan.
The modern world has observed formation of a number of economic and monetary integration communities. Their performance varies greatly: some of them are developing successfully, others, on the contrary, are stagnating. Questions concerning the possibility of economic and monetary integration in the post-Soviet space are constantly addressed both by policymakers and by academic economists. Taking into account theoretical concepts and international experience, this brief addresses the possibility and desirability of the integration of the monetary sphere of the post-Soviet region. Based on Luzgina (2013a,b), this brief proposes a form of representation of monetary integration on the early stages of its development. In this case, an early form of monetary integration may be achieved via adoption of a single supranational unit of account on the territory of (a subset of) countries; the national currencies would continue to coexist with the new supranational currency. This approach to integration would allow preserving the independence of economic policy for the involved member states. At the same time, countries would benefit from a reduction in transaction costs and increasing convergence of national economies.
Background: Theoretical Concepts and World Experience of Monetary Integration
Ideally, the monetary union should have the form of an optimum currency area (OCA), a territory of one-currency domination with high level of integration and unification in different economic spheres. Modern economic science provides two main approaches considering the possibility of constructing an optimal currency zone on the territory of several states. The first suggests that optimality should be determined on the basis of implementing a specific group of criteria by countries. Among the main criteria, freedom of goods movement, labor and capital, openness and diversification of the economy, the synchronization inflation rates as well as integration in the financial sector can be mentioned. The second approach is based on a comparison of the benefits and costs in terms of the monetary union formation of the country with the highest economic potential. In practice, when studying the effectiveness of monetary integration, a synthesized approach is used. It includes evaluating by criteria, as well as taking into account costs and benefits that a country accrues in case of entering a particular monetary group. The main benefits of a monetary union include a reduction of transaction costs, trade relations enlargement, improving the discipline in the monetary sphere, and a reduction of the rate of international reserve sufficiency for every country-member. At the same time, there are some negative aspects of deep integration, such as loss of monetary policy independence, economic imbalances in case of weak convergence of national economies, loss of (part of) seigniorage income, and a possible negative public reaction to the adoption of a single currency.
When discussing the concept of monetary integration, it is important to understand the distinction between a monetary union and an optimum currency area. A monetary union is one of the most developed forms of a currency area, which implies a rigid anchor of national currencies to each other with a possible further transformation into the currency of the leading country, or to a single supranational currency (as in the case of the European Union). In this case, a monetary union can be formed of asymmetrical economies. Instead, the optimum currency area requires mandatory implementation of the main convergence criteria, and thereby, more symmetry/alignment among the members. Thus, a monetary union does not necessarily have to be an optimum currency area, while the optimum currency area has every opportunity to be transformed into a full-fledged monetary union [1].
Historically, there have been several examples of monetary union formations. The Italian monetary union (1862-1905), which was formed through the merger of disparate Italian lands, is among them. We can also identify the Scandinavian Monetary Union, which united Norway, Denmark and Sweden (1875-1917). The Austro-Hungarian monetary union existed in the period from 1867 to 1914. Currently, we observe formations of monetary unions in Africa, Latin America and the Arab states.
Despite the implementation of a number of integration projects within the various groups of countries over the past century, only the European states were able to achieve the highest form of monetary integration. It took them more than 50 years to do this, and the integration processes in the economic and monetary fields are continuing with new Member States joining the European Union. However, despite the detailed development plans for the implementation of a monetary union, the Eurozone countries face a number of difficulties and obstacles on the path of economic development. European monetary integration brings not only benefits, but also some costs. For example, the loss of independence of monetary policy creates obstacles in regulations of economic processes.
This discussion suggests that an assessment of the potential formation of a monetary union – that is, of desirability, feasibility and level of monetary integration within a particular group of countries – should be based on relating theoretical concepts and features of the countries in question, as well as a in-depth research of the experience of other currency unions.
Integration Processes in the Post-Soviet Space
At the territory of the former Soviet Union, integration projects have been implemented for more than 20 years. After the collapse of the Soviet Union, such integration formations as the Commonwealth of Independent States and the Eurasian Economic Community were created. Belarus, Kazakhstan and Russia have built a Customs Union (CU) and a Common Economic Space (CES). There is also a possibility of making a transition to the highest form of integration – a monetary union. However, this raises a number of questions: which CIS countries should join a monetary union, when should this be done, and what is the optimal form of monetary union for integrating countries.
Luzgina (2013b) shows that, within the framework of the CIS countries, that there are significant differences in many of the macroeconomic indicators. Countries differ in terms of GDP and the growth rates of investment and prices. For example, Belarus has the highest inflation in the post-Soviet region. The source of growth also differs: for example, a number of countries, such as Azerbaijan, Russia and Kazakhstan, owe a significant part of their economic growth to the availability of natural resources, but this is not universally true within the CIS. Dynamics of population income is also significantly different among the countries. Here, Russia occupies the leading position with its average wage at the beginning of 2012 reaching 780 USD. At the same time, in Tajikistan, the average wage amounts to only 110 USD.
Another concern is that the formation of an economic and monetary union implies free movement of labor and capital. However, at this stage of development, it can lead to some negative consequences. Free movement of labor could involve a massive flow of labor from depressed areas to regions where incomes are much higher. This may create pressure on health and social services in the latter regions. In turn, free movement of capital may cause speculative attacks on the financial markets. At the same time, the CIS countries, except Russia, Kazakhstan and Ukraine, do not have large gold reserves. Therefore, the free movement of capital flows without additional support may cause a crisis within the national financial systems. Out of all the gold reserves of the CIS countries, more than 85% of the total volume is owned by Russia. In the case of an abolition of restrictions on capital flows, countries that are exposed to speculative attacks are likely to ask Russia for help. Such a situation would require Russia to use its own financial resources, which would create an additional pressure on its international reserves.
Table 1. International reserves in the CIS countries, (million US dollars)|
Country |
2008 |
2010 |
2012 |
|
Azerbaijan |
6467,2 |
6409,1 |
11277,3 |
|
Armenia |
1406,8 |
1865,8 |
1799,4 |
|
Belarus |
3063,2 |
5025,4 |
8095 |
|
Kazakhstan |
19883,1 |
28264,7 |
28299,4 |
|
Kirgizstan |
1225,1 |
1720,4 |
2066,7 |
|
Moldova |
1672,4 |
1717,7 |
2515 |
|
Russia |
426278,8 |
479222,3 |
537816,4 |
|
Tajikistan |
163,5 |
403,1 |
630,7 |
|
Ukraine |
31543,3 |
34571,3 |
24552,8 |
Russia is leading among the CIS countries in terms of population and territory, with other countries lagging substantially behind. For example, Belarus owns less than 1% of the total territory of the CIS countries and less than 4% of the population.
Relying on the above quantitative indicators it is natural to expect that in case of a formation of a monetary union with a single emission center, the distribution of votes in the decision-making of the development and implementation of monetary policy is likely to be unequal. The leading role would likely belong to Russia, which has the largest economic potential. However, other countries in this case may be in a less advantageous position as Russia’s decisions may lead to undesirable consequences for the economies of other countries, given the lack of a sufficient degree of synchronization of national economic systems.
Thus, a weak degree of economic integration of the national economies of the CIS countries, different levels of development, as well as the superiority of the economic potential of Russia over the other states gives reason to argue for a non-feasibility of monetary integration within the CIS countries in the short term.
On the other hand, it may be reasonable to consider the possibility of integration in the monetary sphere on the basis of the most economically integrated countries, namely Russia, Belarus and Kazakhstan. These countries have created a Customs Union and are implementing a project of forming a Common Economic Space. There are plans of creating the Eurasian Economic Union. In addition, based on the experience of European countries, it might be easier to start the integration within a limited number of participants, which satisfy the required convergence criteria. Later, more countries may enter the monetary union.
Prospects for Monetary Integration of Belarus, Kazakhstan and Russia
Taking into account the experience of the European Union, we note the need for close trade and technological relations, as well as a market type of economy, and unification of the legislation in the economic sphere. Some of these elements of monetary integration are observed within the CU. After the collapse of the Soviet Union, economies of the former Soviet states switched to paths of market reforms. In addition, the CU countries have rather close trade relations; they have restored the old and created new means of communication. At the same time, there is a weak degree of diversification of exports and imports. A large part of export and import are represented by raw materials.
The second important point of the monetary integration is the comparability by size of the emerging economies. In the framework of the Customs Union, Russia is the only leader. Harmonization of relations between the alliance partners would be easier in the case of smaller countries coordinating their efforts, which would allow them to defend their interests along with the large member-states.
Finally, obligatory condition of monetary integration is the fulfillment of convergence indicators (certain values of macroeconomic indicators) by all association members. In Luzgina (2013b), we compare a range of such indicators, as based on the experience of the European Union. We use indicators such as the inflation rate, public debt, budget deficit, and the dynamics of exchange rates for comparison. The study reveals that the main differences lie in the monetary indicators, namely the rate of inflation and exchange rate. In addition, there are certain differences in the structure of the economy and the share of private ownership in GDP.
Figure 1. Exchange Rate (average for a year), as % of the previous year
Figure 2. Industrial Producer Price Index (average for a year), as % of the previous year
Source: Data of the Interstate Statistical Committee of the Commonwealth of the Independent State
The persistence of significant differences in the values of convergence indicators at the macro level makes a full-fledged monetary union highly unlikely in the short term, even within the framework of the three most economically integrated states. At the same time, it is appropriate to consider the option of monetary integration in its mild form, i.e. in the form of monetary integration on the basis of a single unit of account. A single unit of account is usually calculated on the basis of the basket of national currencies, and is mostly used for international payments and credits.
The attractiveness of monetary integration in the form of monetary union on the basis of a supranational unit of account is motivated; first of all, by the preservation of the economic sovereignty of all countries. Circulation of the unit of account would take place in parallel with national currencies. Member states would retain the possibility of implementation of independent monetary and fiscal policies. Furthermore, the unit of account may fulfill the role of a training tool. The supranational payment unit can be used on the national level. Using this unit of account, legal entities may carry out transactions and individuals may hold their savings. It can also be actively implemented in the inter-state calculations. A part of gold and forex reserves of member countries can be held in the supranational unit of account. Inter-state loans can be issued in this unit as well. This type of monetary union would reveal the feasibility of further deepening of integration in the monetary sphere and determine the timing of the formation of a full-fledged monetary union. In case of serious problems, the dismantling of the currency union will not cause major adverse changes in national economies, unlike in the case of a collapse of a monetary union with a single currency. In addition, the operation of a single unit of account allows for the anticipation of potential problems associated with the functioning of economies under a single monetary system, and a solution before the introduction of a supranational currency.
Last, but not least, this form of integration seems to be a relatively feasible option as the process of convergence on the territory of the CU countries in the monetary sphere has already begun. There is an increased use of national currencies in bilateral trade, harmonization of national legislation is taking place in the monetary sphere, and international agreements in the monetary sphere are ratified. These activities are gradually building a base for the realization of the monetary integration project of the union countries.
Conclusions
Economic and monetary integration allows the countries to get the maximum benefit from mutual cooperation. However, the deepening of the integration process is usually accompanied by certain difficulties. Convergence of economic systems requires transformation of economic institutions, changes in legislation and principles of management, all of which are costly to achieve. The better the preliminary harmonization is performed, the easier the process of adaptation of national economies to function within a particular economic and monetary union will be.
The post-Soviet countries are implementing several projects of economic integration. However, their economies have major differences according to a number of macroeconomic indicators. The greatest degree of convergence is reached only by three CIS states, namely Belarus, Russia and Kazakhstan. Rather high level of economic integration, as well as a continuation of the process of unification and harmonization of national economies allows us to study the feasibility of realizing the lightweight form of a monetary integration based on a single supranational unit of account on the territories of Belarus, Kazakhstan and Russia.
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References
- Butorina O.V. International currencies: integration and competition / O.V. Butorina.- Мoscow.: Publishing house “Delovaia literatura”, 2003.- 368 p.
- Chapligin V.G. Theory and methodology of currency alliance formation/ V.G. Chapligin – St. Petersburg.: Publishing house SPbGUAF, 2003.- 193 p.
- Drobishevski S.M., Polevoi D.E. The problems of creating a single monetary zone in the CIS countries / S.M Drobishevski, D. I. Polevoi – Мoscow.: EAPP,- 2004. – 152 p.
- Euro – a baby of Mandell? The theory of optimum currency areas: collection of papers: translation from English.- Мoscow.: Delo, 2002.- 368 p.
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- Eurasian Economic Community on-line database [Electronic resource]- Moscow.- 2005.- Mode of access: www.evrazes.com.- Date of access: 17.02.2012
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[1] Chapligin V.G. Theory and methodology of currency alliance formation/ V.G. Chapligin – St. Petersburg.: Publishing house SPbGUAF, 2003.- 193 p.
Managed Competition in Health Insurance Systems in Central and Eastern Europe
This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.
A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).
This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.
The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.
Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia
At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).
The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).
However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).
In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).
Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions) 
This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.
Data and Results
In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model. The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).
The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).
Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).
Table 1. Factors leading to decreased infant and under-five mortality in Russia
Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.
To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)
In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.
Discussion
The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.
In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.
Summary and Policy Implications
The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.
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References
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- Baranov IN, Sklyar TM. 2009. Problemy strakhovoi modeli zdravookhraneniya na primere Moskwy i Sankt-Peterburga (Problems of insurance model in health care: the example of Moscow and Saint Petersburg). In X International Conference on the Problems of Development of Economy and Society, Yasin E.G (ed), Moscow: Higher School of Economics, vol.2.
- Besstremyannaya GE. 2013. Razvitie systemy obyazatelnogo meditsinskogo strakhovaniya v Rossijskoi Federatsii (Development of the Mandatory Health Insurance system in the Russian Federation) Federalizm 3: 201-212
- Besstremyannaya GE. 2010. Essays in Empirical Health Economics. PhD thesis. Keio University (Tokyo).
- Besstremyannaya GE. 2009. Increased public financing and health care outcomes in Russia. Transition Studies Review 16: 723-734.
- Blam I, Kovalev S. 2006. Spontaneous commercialization, inequality and the contradictions of the mandatory medical insurance in transitional Russia. Journal of International Development 18: 407–423.
- Culyer AJ (2005) The Dictionary of Health Economics, Edward Elgar.
- Danishevski K, Balabanova D, McKee M, Atkinson S. 2006. The fragmentary federation: experiences with the decentralized health system in Russia. Health Policy and Planning 21: 183–194.
- Gordeev VS, Pavlova M, Groot W. 2011. Two decades of reforms. Appraisal of the financial reforms in the Russian public healthcare sector. Health Policy 102(2-3): 270-277.
- Hussey P, Anderson GF. 2003. A comparison of single- and multi-payer health insurance systems and options for reform. Health Policy 66: 215-228.
- Jacobs R, Goddard M. 2002. Trade-offs in social health insurance systems. International Jthenal of Social Economics 29(11): 861-875.
- Lawson C, Nemec J, Sagat V. 2012. Health care reforms in the Slovak and Czech Republics 1989-2011: the same or different tracks? Ekonomie a management 1, 19-33.
- Lawson C, Nemec J. 2003. The political economy of Slovak and Czech health policy: 1989-2000. International Political Science Review 24(2): 219-235.
- Medved J, Nemec J, Vitek L. 2005. Social health insurance and its failures in the Czech Republic and Slovakia: the role of the state. Prague Economic Papers 1:64-81.
- Praznovcova L, Suchopar J, Wertheimer AI. 2003. Drug policy in the Czech Republic. Jthenal of Pharmaceutical Finance, Economics and Policy 12(1): 55-75.
- Preker AS, Jakab M, Schneider M. 2002. Health financing reforms in Central and Eastern Europe and the former Soviet Union, in Funding Health Care: Options for Europe, Mossalos E., Dixon A., Figueras J., Kutzin J. (Eds.), European Observatory on Health Care Systems Series: Open University Press, 2002.
- Rokosova M, Hava P, Schreyogg J, Busse R. 2005. Health care systems in transition: Czech Republic. Copenhagen, WHO Regional Office for Europe on behalf of the European Observatory on Health Systems and Policies.
- Sheiman I. 1991. Health care reform in the Russian Federation. Health Policy 19: 45–54.
- Sheiman I. 2006. O tak nazyvaemoi konkurentnoi modeli obyazatelnogo meditsinskogo strahovaniya (On so-called competitive model of mandatory health insurance). Menedzher Zdravoohraneniya 1: 52-58.
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- Sinuraya T. 2000. Decentralization of the health care system and territorial medical insurance coverage in Russia: friend or foe? European Jthenal of Health Law 7:15–27.
- Sparling AS. 2008. Income, drug, and health: evidence from Russian elderly women. PhD dissertation. University North Carolina at Chapel Hill, UMI Dissertations Publishing.
- Tompson W. 2007. Healthcare reform in Russia: problems and perspectives. Working Papers 538, OECD Economics Department
- Tragakes E, Lessof S. 2003.Russian Federation, Health Care Systems in Transition, The European Observatory, WHO, Europe.
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The Customs Union Between Russia, Belarus and Kazakhstan: Some Evidence from the New Tariff Rates and Trade Flows
Author: Arevik Mkrtchyan, European University Institute.
This brief addresses the Customs Union between Russia, Belarus and Kazakhstan that was established in 2010. It argues that the external tariff schedule reflects a compromise between the interests of its members rather than simple expansion of Russian influence on the CU partners, and that the reduction in trade costs due to elimination of internal borders, benefits both the members of the CU and their external trade partners. Moreover, the impact of alleviated non-tariff trade costs on trade flows is strong and significant, while the tariff impact is insignificant for all members.
Optimal Economic Policy and Oil Price Shocks in Russia
Significant oil price fluctuations are an important factor influencing real economic variables, especially in the countries with large dependency on export of natural resources. Under such fluctuations, it is natural to consider the possibility of economic policy to fine tune the real economy, achieve inflation stability, and to weaken the negative influence of oil price shocks. In terms of monetary policy, authorities realize the existence of many channels through which oil market is related to the real sectors and inflation. The Central Bank of Russia should analyze the necessity to react to oil prices and to change the effect of them on the real economic variables.
The most typical way of reaction to oil prices in the Russian Federation is accumulation of reserves at the Reserve Fund. The Stabilization Fund (was later in 2008 separated into the Reserve Fund and the National Welfare Fund) was created in 2004 based on the initiative of Mr. Alexey Kudrin, who was a Minister of Finance at the time. The idea of the fund is to direct the revenue from oil export to the budget, but only when the price of oil does not exceed a pre-specified level, and the residual income should be accumulated in the fund.
In addition, the Central Bank of Russia may respond with its refinancing rate to the changes of the oil price via an augmented oil price Taylor rule or indirectly without inclusion of a commodity quota into the monetary policy rule.
We consider whether the Central Bank of Russia should formally establish the policy of responding to the changes of the oil price. The key evaluation criterion for selecting the optimal response is the minimization of inflation and GDP fluctuations.
Taking into account the results of an applied Dynamic Stochastic General Equilibrium model estimated for the Russian economy, we suggest that the Central Bank, optimally, should include the oil price in its interest rate Taylor monetary rule. That is, it should react to oil price quotas but only in the case of stabilization fund absence. This suggested optimal monetary policy implies a positive direct response to oil price shocks; a 1% oil price increase (decrease) should trigger CBR to raise (decrease) the refinancing rate by 0.1%. In the case of stabilization fund presence, there is no need to respond to changes in the oil price since the former stabilizes the situation when the oil price fluctuates too much.
The main potential limitation of this study is the problem of model quality against the real data. In addition, other monetary policy instruments may be tested against the reaction to changes in the oil price.
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Accountability in Russia
This policy brief summarizes two recent research papers that are related to obstacles to political accountability in modern Russia and potential ways to overcome these obstacles. The first paper provides a rigorous assessment of the extent of electoral fraud in Moscow city during the parliamentary elections held on December 4, 2011. Using random assignment of independent observers, we estimate the actual share of votes for the incumbent United Russia party to be at least 11 percentage points lower than the official count (35.6 percent instead of 46.5 percent). A less rigorous, but more realistic estimate is 21 percentage points. These results suggest that electoral accountability in Russia is limited. The second paper demonstrates that even in an environment with low electoral accountability and limited freedom of media, alternative accountability mechanisms may emerge. In particular, anti-corruption campaigns in social media may affect the valuation of state-controlled companies, so that market forces put a disciplining effect on the managers of SOEs. We study consequences of blog postings of a popular Russian anti-corruption blogger and shareholder activist Alexei Navalny on the stock prices of state-controlled companies. In an event-study analysis, we find a negative effect of company-related blog postings on both daily abnormal returns and within-day 5-minute returns. We use the incidence of distributed denial-of-services (DDoS) attacks to show that the effect is not driven by the endogenous timing of blog postings. We also show that there are long-term effects of certain types of posts on stock returns, trading volume, and volatility. Overall, our evidence implies that blog postings about corruption in state-controlled companies have a negative causal impact on stock performance of these companies.
To study the extent of electoral fraud we employ data from a large-scale field experiment that allows us to estimate the amount of electoral fraud in the city of Moscow during Russian parliamentary elections in December 2011. In particular, we exploit randomized assignment of independent observers to polling stations. Prior to the parliamentary elections the independent NGO Citizen Observer (Grajdanin-nabludatel) trained more than 500 volunteer observers in the city of Moscow. The observers were sent to 156 randomly selected polling stations. The polling stations were selected using a systematic sampling technique. In particular, polling stations were divided by electoral districts. Within each district, polling stations were sorted according to their official number assigned by Central Election Committee. Every 25th polling station within electoral district starting from the 1st was assigned for observation, resulting in a sample of 185 polling stations. The Citizen Observer’s network recruited enough observers to cover 156 of the 185 polling stations, which corresponds to 4.9 percent of the 3,164 ordinary polling stations in Moscow.[1] To make sure that this procedure does not lead to a biased sample because of some hidden periodicities we check that in the previous parliamentary elections in 2007 polling stations selected using a similar procedure were not different from other polling stations.
Comparison of the share of votes received by different parties and the turnout between polling stations with independent observers from Citizen Observer (treatment group) and without observers (control group) is presented in Figure 1. The results indicate that the presence of observers led to a decrease in the share of votes for United Russia of 10.8 percentage points and the turnout at the polling stations with observers was lower by 6.5 percentage points.
Figure 1. Vote Shares in 2011 
Notes: The figure is reproduced from Enikolopov, Ruben, Vasily Korovkin, Maria Petrova, Konstantin Sonin, and Alexei Zakharov (forthcoming) “Electoral Fraud in Russian Parliamentary Elections in December 2011: Evidence from a Field Experiment.” Proceedings of the National Academy of Sciences.
The above results are likely to provide a lower bound on the extent of the electoral fraud, since the presence of observers at the polling stations did not fully prevent fraud. To provide more information on the extent of the fraud, we divide all treatment stations into three groups: those in which observers reported no serious violations (75 polling stations), those in which serious violations were reported, but the observers received the final protocol (43 polling stations), and those in which all observers were not able to get the official protocol of the vote count (38 polling stations), which happened if the observers were dismissed from the polling station or the heads of electoral commissions illegally refused to give a signed copy of the protocol.
Figure 2 shows the distribution of vote shares for United Russia at polling stations from these three groups. For observations in the control group the distribution seems to be bimodal with two peaks – one around 25 percent of votes and another one around 55 percent of votes. The distribution for the precincts with observers also has two peaks, with the first one around 25 percent of votes. Note, however, that the second mode of this distribution, around 50 percent of votes, is noticeably smaller as compared with the control group. Moreover, for the polling stations in the treatment group in which observers reported no serious violations the distribution becomes unimodal with the peak around 25 percent of votes for United Russia. Thus, the results are consistent with the following hypothesis: the distribution of vote shares for United Russia in the control group is simply a mixture of two distributions that correspond to polling stations without large electoral fraud (for which the distribution is centered around 25 percent of votes) and polling stations with substantial electoral fraud (for which the distribution is centered around 55 percent of votes). Note also that a similar pattern is observed for the distribution of turnout across three groups of precincts, but not for the distribution of vote shares for other parties.
Figure 2. Distribution of votes for United Russia 
Notes: The figure is reproduced from Enikolopov, Ruben, Vasily Korovkin, Maria Petrova, Konstantin Sonin, and Alexei Zakharov (forthcoming) “Electoral Fraud in Russian Parliamentary Elections in December 2011: Evidence from a Field Experiment.” Proceedings of the National Academy of Sciences.
To assess the overall influence of the electoral fraud in Moscow on the outcome of Russian parliamentary elections, we also estimate the total number of votes that United Russia received due to electoral fraud. As both vote share of a ruling party and turnout were affected by electoral fraud, we look at the number of votes for each party as a share of registered voters in precincts with and without observers. Based on these numbers, our conservative estimate of the number of votes, which United Russia received at the ordinary precincts in Moscow due to electoral fraud, is equal to 635,000. This is a lower bound for the size of electoral fraud as it assumes that the presence of observers fully prevented any fraud, and at least anecdotal evidence suggests that it is not always the case. If we use results from the polling stations in which observers report no serious violations as an alternative estimate, the number of stolen votes increases up to 1,090,000.
The results presented above indicate that because of electoral fraud, voting does not constitute an efficient mechanism to replace those in power, and, therefore, electoral accountability in Russia does not work to discipline politicians in the office. Other means to hold politicians and public officials accountable are also limited, since traditional media is often censored and politics is generally not competitive. We ask the question whether in such environment there is any alternative ways to hold public officials accountable, and, in particular, if new media, such as blogs, can make a difference. Specifically, we study whether blog postings of a popular Russian blogger, shareholder activist, and, subsequently, one of the leaders of emerging opposition to President Putin’s regime, Alexei Navalny, have had an impact on stock performance of the companies whose wrongdoings he uncovered and made public.
First, we show that daily abnormal returns of the companies Navalny wrote about were significantly lower after Navalny’s posts about them. The results hold if we control for mentions of these companies in other types of media (business newspapers, online newspapers, and blogs) and for company-year and year-month fixed effects. In addition to looking at daily abnormal returns, we show similar results for 5-minute abnormal returns even controlling for trading-day fixed effects (see Figure 3). The magnitude of this effect is quite sizable with a daily decline of 0.5 p.p. after an average blog posting, and a daily decline of 0.9 p.p. after an important blog posting.
Figure 3. 5-minute Abnormal Returns and Navalny’s Blog Postings, Non-Trading Time (Evenings and Weekends) Excluded
We also provide evidence that the impact of blogging on stock performance is causal. Although the results described above are consistent with the negative impact of blogging, they could be explained, e.g., by selective exposure. To identify the causal effect of blog postings we use an external variable, distributed denial-of-service (DDoS) attack on a blog service, as a source of exogenous variation. During the period under study (between January 2008 and August 2011), these DDoS attacks, allegedly, were not specifically targeting the Navalny’s blog, but they affected the accessibility of the whole blog platform, and the Navalny’s blog was also affected. As a result, DDoS attacks either prevented Navalny from writing a post or prevented his readers from reading his blog, but there was no obvious reason why they might influence fundamental determinants of stock prices of the companies Navalny wrote about.
In a reduced form model, we find significant positive effect of DDoS attacks on daily abnormal returns of the companies Navalny wrote about. This effect is stronger for the companies Navalny was more focused on (the latter result holds even with DDoS attack fixed effects). Quantitatively, the effect of DDoS attack is similar to the absence of the post or to the presence of the post with no information about the company in question. We also show that though DDoS effect is increasing in Navalny’s attention to the companies he was writing about, it is not increasing in the amount of general news attention to these companies.
Finally, in addition to the short-term effects we just described, we look at the longer-term one-month effects of blog postings. We find that although there were no long-term effects of the ordinary postings, there were negative and significant long-term effects of the most important postings, as proxied by at least 5 mentions of a company in the post. In addition, during the month after a blog posting, there was a larger volatility of stock returns and a larger trading volume. It appears that the number of transactions, controlling for trading volume, was significantly larger in both the short-term and longer-term perspective. Smaller average transactions are consistent with more individual, in contrast to institutional trading, which suggest that short-run effects of blog posting are driven by attention effects, rather than provision of new information. Overall, all our results are consistent with a negative causal impact of blog postings on stock performance of state-controlled companies, and imply that potentially there is a disciplining effect on the behavior of public officials who manage these companies. Thus, our results suggest that posting in online social networks can affect the stock performance of state-controlled companies, and, as a result, can become an unusual alternative mechanism to putting additional checks on the behavior of government officials even if political competition remains limited, and traditional media remain controlled.
The report is based on two papers: Enikolopov, Ruben, Vasily Korovkin, Maria Petrova, Konstantin Sonin, and Alexei Zakharov (2012) “Electoral Fraud in Russian Parliamentary Elections in December 2011: Evidence from a Field Experiment.” Proceedings of the National Academy of Sciences, 109 (52); Enikolopov, Ruben, with Maria Petrova and Konstantin Sonin “Do Bloggers Have any Real Influence? Event Study of Blog Postings by a Russian Activist Shareholder and Blog Service DDoS Attacks,” CEPR Working Paper.
[1] The sample excludes 210 precincts that had a special status, as they were located in hospitals, military units, or pre-trial detention facilities. These polling stations were excluded from the analysis since sending observers there was not always possible, and it was not clear if these polling stations were sufficiently similar to each other to use randomization. The number of votes cast at these polling stations, however, stood at only 1.8 percent of total votes in Moscow.
The Eurasian Customs Union among Russia, Belarus and Kazakhstan: Can It Succeed Where Its Predecessor Failed?
In 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union and imposed the Russian tariff as the common external tariff of the Customs Union. This resulted in almost doubling the external average tariff of the more liberal Kazakhstan. Russia has benefited from additional exports to Kazakhstan under the protection of the higher tariffs in Kazakhstan. However, estimates reveal that the tariff changes have resulted in substantial transfers from Kazakhstan to Russia since importers in Kazakhstan now purchase lower quality or higher priced Russian imports which are protected under the tariff umbrella of the common external tariff. Transfers from the Central Asian countries to Russia were the reason the Eurasian Economic Community (known as EurAsEC) failed, so this bodes badly for the ultimate success of the Eurasian Customs Union. What is different, however, is that the Eurasian Customs Union and its associated Common Economic Space aim to reduce non-tariff barriers and improve trade facilitation, and also to allow the free movement of capital and labor, liberalize services, and harmonize some regulations. Estimates by my colleagues and I show that if substantial progress could be made in trade facilitation and reducing non-tariff barriers, this could make the Customs Union positive for Kazakhstan and other potential Central Asian members. Unfortunately, so far the Customs Union has made these matters worse. On the other hand, Russia’s accession to the World Trade Organization will eventually substantially reduce the transfers from Kazakhstan to Russia, but this will need a strong political commitment from Russia which we have not yet seen. If that Russian political leadership is forthcoming, the Eurasian Customs Union could nonetheless succeed where its predecessor has failed.
In January 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union. Two years later, the three countries agreed to even closer economic ties, by signing the agreement to form a “common economic space.” Regarding tariffs, the key change was that the three countries agreed to apply the tariff schedule of the Customs Union as their common external tariff for third countries. With few exceptions, the initial common external tariff schedule was the Russian tariff schedule. Kazakhstan negotiated exceptions from the common external tariffs for slightly more than 400 tariff lines, but was scheduled to phase out the exceptions over a period of five years (World Bank, 2012). In addition, the members agreed to have the Customs Union determine the rules regarding sanitary and phyto-sanitary standards (SPS) and standards on good. Fearing transshipment of goods from China through Kazakhstan and from the European Union through Belarus, Russia negotiated and achieved agreement on stricter controls on the origin of imports from countries outside of the Customs Union. The common economic space (CES) stipulates that, in principle, there will be free movement of labor and capital among the countries, there will be liberalization of services on the CES and coordination of some regulatory policies such as competition policy.
In February 2012, the Eurasian Economic Commission began functioning. It is intended to act as the regulatory authority for the Customs Union in a manner similar to the European Commission for the European Union.
The Economics of Tariff Changes — Gains for Russia and Losses for Kazakhstan
Some proponents of the Eurasian Customs Union have argued that as a result of the Customs Union firms in the three countries will have improved market access through having tariff free access to the markets in all three countries. Prior to 2010, however, along with other countries in the Commonwealth of Independent States (CIS), the three countries had agreements in place that stipulated free trade in goods among them. Thus, the Customs Union could not provide improved market access due to reducing tariffs on goods circulating among the three countries.
Since the common external tariff was essentially the Russian tariff, there was little change in incentives regarding tariffs in Russia. The big change occurred in Kazakhstan, who had a much lower tariff structure than Russia prior to implementing the Customs Union tariff. Despite the exemptions, Kazakhstan almost doubled its tariffs in the first year of the Customs Union (see World Bank, 2012). The increase in tariffs on many items which were not produced in Kazakhstan but produced in Russia, led to a substantial increase in imports from Russia and displacement of imports from Europe. Many of Russia’s manufacturing firms, which were not competitive in Kazakhstan prior to the Customs Union, were now able to expand sales to the Kazakhstani market. This represents gains for Russian industry. Given the deeper manufacturing base in Russia compared with most of the CIS countries and the resulting uneven benefits of the common external tariff in favor of Russia, acceptance of the common external tariff has been a fundamental negotiating position of Russia regarding acceptance of members in the Customs Union.
Some cite the expanded Russian exports in Kazakhstan as evidence of success of the Customs Union. But the displacement of European imports, to higher priced or lower quality imports from Russia, represents a substantial transfer of income from Kazakhstan to Russia and is an example of what economists call “trade diversion”. Moreover, it is the reason the World Bank (2012) has evaluated the tariff changes of the Customs Union as a loss of real income for Kazakhstan.
Furthermore, the three countries together (and even a broader collection of CIS countries) constitute too small a market to erect tariff walls against external competition. They would lose the benefits of importing technology from advanced countries and would rely on high priced production from within the Customs Union. Some would argue that there are political benefits of trade to be taken into account, but experience has shown that when a customs union is inefficient and the benefits and the costs of the customs union are very unequal, the customs union can inflame conflicts (see Schiff and Winters, 2003, 194-195).
Non-Tariff Barriers — Extremely Costly Methods of Regulating Standards Worsened by the Customs Union
Non-tariff barriers, in the form of sanitary and phyto-sanitary (SPS) conditions on food and agricultural products and technical barriers to trade (TBTs) on goods, are a very significant problem of the Customs Union. There are standards based trade disputes between Belarus and Russia on several products, including milk, meat, buses, pipes and beer (see Petrovskaya, 2012). Anecdotal evidence indicates that Kazakhstani exporters complain bitterly regarding the use by the Russian authorities of SPS and TBTs measures, either to extract payments or for protection.
If the Customs Union could make substantial progress on reducing these barriers, it would be a significant accomplishment. My colleagues and I have estimated that progress on the non-tariff barriers and trade facilitation could outweigh the negative impact of the tariff changes for Kazakhstan (see World Bank, 2012). Unfortunately, so far the Customs Union has taken a step backward on both non-tariff barriers and trade facilitation.
A big problem in reducing standards as a non-tariff barrier is that standards regulation, in all three countries, is still primarily based on the Soviet system. As a holdover from the Soviet era, mandatory technical regulations are employed where market economies allow voluntary standards to apply. This regulatory system makes innovation and adaption to the needs of the market very costly as firms must negotiate with regulators when they want to change a product or how it is produced. Legislation in both Russia and Kazakhstan calls for conversion to a system of voluntary standards, but this is happening too slowly in all three countries. The problem is that the Customs Union has worsened the situation. Technical regulations are now decided at the level of the Customs Union, so firms that previously negotiated with their national standards authority, have had to now get agreement from the Customs Union. This has reportedly caused further delays, impeding innovation and the ability of firms to meet the demands of the market.
A second problem with efforts to reduce the non-tariff barriers is that the Customs Union is trying to harmonize standards of the three countries by producing mandatory technical regulations. The alternative is to use Mutual Recognition Agreements (MRAs). Experience has shown that no customs union has been able to broadly harmonize standards based on mandatory technical regulations, with the exception of the European Union. In fact, even in the European Union, they have had to use MRAs and only harmonized technical regulations after decades of work. While each member of the Customs Union is expected to create a system of mutual recognition of certificates of conformity, these certificates are not presently recognized in the other countries of the Customs Union. There is little hope for a significant reduction in standards of non-tariff barriers unless the system of mutual recognition is more widely recognized and adopted.
Trade Facilitation —Participation in International Production Chains Made More Difficult by the Customs Union
Customs posts between the member countries have been removed and this has reduced trade costs for both exporters and importers in the three countries. Russia’s concerns regarding transshipment have, however, led to an opposite impact on trade with third countries, i.e., the costs of trading with countries outside the Customs Union have increased. Participation in international production chains has become a key feature of modern international production and trade. If goods cannot move easily in and out of the country, multinational firms will look to other countries to make their foreign direct investment and for international production sharing. Addressing this significant problem will take a change of emphasis on the part of Russia.
Russian WTO Accession —Liberalization That Will Significantly Reduce Transfers to Russia
It has apparently been agreed by the Customs Union members that the common external tariff of the Customs Union will change to accommodate Russia’s WTO commitments. As a result, the applied un-weighted average tariff will fall in stages from 10.9 percent in 2012 to 7.9 percent by the year 2020 (see Shepotylo and Tarr, forthcoming).[1] This will have the effect of lowering the trade diversion costs of Kazakhstan. In addition, the Customs Union will be expected to adapt its rules on standards to conform to commitments Russia made as part of its WTO accession commitments. In the case of Belarus, it remains to be seen if it will implement the changes, as this will increase competition for its industries.
Conclusion — the Need to Russia to Exercise Political Leadership for Standards and Trade Facilitation Reform for Success of the Customs Union
In 1996, the same three countries formed a customs union. Later the same year, they were joined by Kyrgyzstan, then by Tajikistan and in 2005 by Uzbekistan. As Michalopoulos and I (1997) anticipated, the earlier Customs Union failed because it imposed large costs on the Central Asian countries, which had to buy either lower quality (including lower tech goods) or higher priced Russian manufactured goods under the tariff umbrella. The present Customs Union also started with the Russian tariff, which protects Russian industry and suffers from the same problem that led to the failure of the earlier Customs Union. Nonetheless, the present Customs Union could succeed. Crucially, due to Russia’s accession to the WTO, the tariff of the Customs Union will fall by about 40 to 50 percent.[2] This will make the Customs Union a more open Customs Union, very significantly reduce the transfers from Kazakhstan to Russia, and thereby reduce the pressures from producers and consumers in Kazakhstan on their government to depart from enforcement of the tariffs of the Customs Union. Further, the present Customs Union aims to reduce non-tariff barriers and improve trade facilitation, as well as it has “deep integration” on its agenda, i.e., services liberalization, the free movement of labor and capital and some regulatory harmonization. Although, to date, the Customs Union has moved backwards on non-tariff barriers and trade facilitation, one could optimistically hope for substantial progress. In the important area of non-tariff barriers, given the common history of Soviet mandatory standards, Russia will have to take the lead in moving the Customs Union toward a system of voluntary standards where no health and safety issue are involved, and toward a system of mutual recognition agreements and away from commonly negotiated technical regulations. On trade facilitation, Russia will have to reverse its pressure and find a way to allow the freer movement of goods with third countries while addressing its transshipment concerns.
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References
- Michalopoulos, Constantine and David G. Tarr (1997), “The Economics of Customs Unions in the Commonwealth of Independent States,” Post-Soviet Geography and Economics, Vol. 38, No. 3, 125-143.
- Petrovskaya, Galina (2012), “Belarus, Rossia, Ukraina. Obrechennye na torgovye konflikty” (Belarus, Russia, Ukraine. Doomed for trade conflicts), Deutsche Welle, June 14. www.dw.de/dw/article/0,,16023176,00.html.
- Schiff, Maurice and L. Alan Winters (2003), Regional Integration and Development, Washington DC: World Bank and Oxford University Press.
- Shepotylo, Oleksandr, and David G. Tarr (2008), “Specific tariffs, tariff simplification and the structure of import tariffs in Russia: 2001–2005,” Eastern European Economics, 46(5):49–58.
- Shepotylo, Oleksandr, and David G. Tarr (forthcoming), “Impact of WTO Accession on the Bound and Applied Tariff Rates of Russia,” Eastern European Economics.
- Shymulo-Tapiola, Olga (2012), “The Eurasian Customs Union: Friend or Foe of the EU?” The Carnegie Papers, Carnegie Endowment for International Peace, October. Available at: www.CarnegieEurope.eu,
- World Bank (2012), Assessment of Costs and Benefits of the Customs Union for Kazakhstan, Report Number 65977-KZ, Washington DC, January 3, 2012. Available at: http://documents.worldbank.org/curated/en/2012/01/15647043/assessment-costs-benefits-customs-union-kazakhstan
[1] The final “bound rate” of Russia is higher at 8.6 percent on an un-weighted average basis; but there are about 1,500 tariff lines where the applied rate of Russia is below the bound rate. The applied weighted average tariff will fall from 9.3 percent in 2012 to 5.8 percent in 2020.
[2] Russian tariffs fall more on an un-weighted average basis than they do on a weighted average basis. See Shepotylo and Tarr (forthcoming).
Inter-Regional Convergence in Russia
There was no inter-regional convergence in Russia during the 1990s but the situation changed dramatically after 2000. While interregional GDP per capita gaps still persist, the differentials in incomes and wages decreased substantially. Interregional fiscal redistribution has never played a major role in Russia, so understanding interregional convergence requires an analysis of internal capital and labor mobility. The capital market in Russia’s regions is integrated in a sense that local investment does not depend on local savings. Also, the barriers to labor mobility have come down. The situation is very different from the 1990s when many poor Russian regions were in a poverty trap: potential workers wanted to leave those regions but could not afford to finance their move. After 2000 (especially later in the first decade), these barriers were no longer binding. Overall economic development, as well as the development of financial and real estate markets, allowed even the poorest Russian regions to grow out of the poverty trap. This resulted in some convergence in the Russian labor market; the interregional gaps in incomes, wages and unemployment rates are now comparable to those in Europe.
Russia’s Regions are Finally Converging
Large interregional differences have always been an important feature of Russia’s transition to a market economy. This has been explained by the pre-transition geographical allocation of population and of physical capital that was determined by non-market forces. Soviet industrialization policies often pursued political or geopolitical goals. Even when they reflected economic realities, the economic decision-making was distorted substantially by central planning, price-setting and subsidies. In addition, the allocation of production was intended to serve a different country – the Soviet Union (or even the whole Council for Mutual Economic Assistance countries) rather than Russia alone. Moreover, believing in economies of scale rather than in competition, Soviet planners created many monotowns.[1] These towns, cities or even regions relied on a single industry. Therefore economic restructuring and inter-sectoral reallocation implied not only moving workers or capital between employers in one town, but also required moving workers or capital between cities.
Despite the need for geographical reallocation during the transition to a market economy, the differentials between Russian regions remained high (and even increased!) throughout the 1990s. However, after 2000 (especially later in the first decade) there was substantial convergence in incomes and wages (Figure 1). By 2010, this resulted in reduction of the inter-regional differences in incomes in line with European levels. In Figure 2, while inter-regional differences in Russia are still substantially above those in the US and Western Europe, they are comparable to those in the EU.
Figure 1. Differences among Russian Regions in Terms of Logarithms of Real Incomes, Real Wages, Unemployment, Real GDP Per Capita
Source: Guriev and Vakulenko (2012). Note: All variables measured as population-weighted standard deviations.
Figure 2. Income Differentials in Russia, Europe and the US
Interestingly, despite income convergence, there was no convergence in GDP per capita among Russia’s regions. Inter-regional dispersions in GDP per capita remain high not only by European standards, but also by standards of less developed countries. Indeed, in Figure 3, Russia is placed in the international context using the data recently developed by Che and Spilimbergo (2012).
Che and Spilimbergo calculate interregional differences for 32 countries in a compatible way and plot them against GDP per capita (averaged out for 1995-2005, in real PPP-adjusted dollars). Their main finding is that that there is a negative correlation between interregional differences and GDP per capita.
Since Russia was not in Che and Spilimbergo’s dataset, Guriev and Vakulenko (2012) reproduced their calculations for Russia, both for the 1995-2005 average (as they do for the other countries) but also for the individual years 1995, 2000, 2005 and 2010. It turns out that while Russia was “abnormally uniform” in the early 1990s, it did experience substantial divergence in the late 1990s. There was continuing, albeit weaker, divergence even in the early 2000s – so Russia became “abnormally unequal” given its GDP level. Even though there was some convergence late in the first decade, Russia is still “abnormally unequal”. Given the fast economic growth since 2000, Russia should have become substantially “more uniform” – at least given the downward-sloping relationship between income and inter-regional inequality in Che-Spilimbergo’s data.
Source: Che and Spilimbergo (2012). Note: The trend line is calculated without Russia.
Why didn’t income convergence happen in the 1990s and only start after 2000? Why hasn’t GDP convergence taken place? Large interregional differences are consistent with reduced income, wage, and unemployment differentials if the factors of production (labor and capital) have become more mobile while the productivity differences (due to geography, political and economic institutions, and inherited differences in infrastructure) remain in place. Therefore, in order to understand income convergence, an understanding of labor and capital mobility is needed.
Interregional Labor Mobility in Russia
Andrienko and Guriev (2004) studied internal migration flows in Russia in the 1990s and showed that the lack of convergence was explained by a “poverty trap”. In general, Russians did move from poorer to richer regions. However, in Russia’s very poor regions (in about 30% of the regions hosting about 30% of Russia’s population) the potential outgoing migrants wanted, but could not afford, to leave; so for these regions, an increase in income would have resulted in higher rather than lower outmigration.
What changed since 2000? Why did barriers to mobility come down? There are multiple potential explanations: (i) economic growth simply allowed most of Russia’s regions to grow out of the poverty trap; (ii) the development of financial and real estate markets reduced the transactions costs of moving therefore reducing the importance of the poverty trap; (iii) the development of capital markets increased capital mobility; (iv) federal redistribution reduced interregional differences.
According to Guriev and Vakulenko (2012), federal redistribution played a very minor role, while the other three explanations are consistent with the data. Our analysis of capital flows is, however, limited by the lack of detailed data, but our study of panel data on net capital inflows and investment shows that, first, capital does flow to regions with higher returns to capital and with lower wages and incomes, thus contributing to convergence. Second, investment in Russia’s regions is not correlated with savings which suggests that Russia’s capital market is not regionally segmented. As our data on capital are limited to the period after 2000, we cannot compare the recent years to those during the 1990s, but at least we can argue that recently, the capital market was functioning well and was contributing to convergence.
It is striking to what extent the poverty trap and liquidity constraints used to be, but are no longer, binding for labor mobility. Figure 4 is a graphical illustration of the poverty trap. Based on a semiparametric estimation with region-to-region fixed effects it shows the relationship between income in the origin region and migration (both in logarithm). Each dot on this graph represents migration from one region to another in a given year (during 1995-2010). As discussed above, the relationship is non-monotonic. If the sending region is poor, an increase in income results in higher out-migration; for richer regions, a further increase in income results in lower migration. The peak is at log income equal to 8.7 which amounts to average income equal to exp(8.7) ≈ 6003 in 2010 rubles and 1.02 of the Russian average subsistence levels in 2010. The regions to the left of the peak are in the poverty trap while the regions to the right are in a “normal mode” where liquidity constraints are not a substantial barrier to migration.
While in the 1990s tens of regions were below this threshold (and therefore were locked in the poverty trap), by 2010 only one region was below this threshold. In this sense, overall economic growth allowed Russian regions to overcome liquidity constraints by simply growing out of the poverty trap. We ran additional tests to show that financial development also contributed to relaxing liquidity constraints.
Figure 4. Income in the Origin Region and Migration[3]
What Next?
Should we be worried about high interregional differentials in GRP per capita? Not necessarily. In order to ensure inter-regional convergence in incomes and wages, convergence in GDP per capita is not required. As long as barriers to labor and capital mobility are removed, mobility (or even a threat of mobility) protects workers. Therefore, the very fact of remaining large inter-regional dispersion in GDP per capita should not serve by itself as a justification for government intervention (e.g. region-specific government investment).
As reducing barriers to mobility is important for convergence, this is exactly where policies can contribute the most. Developing financial and housing markets and improving investor protection are better policies for reducing inter-regional differences in income; these factors have already reduced income differentials among Russian regions.
We should, however, provide an important caveat. Our analysis was done at the regional level. We therefore do not address the sub-regional level and have nothing to say on the need for town-level government interventions. There may well be many cases where individual towns (e.g. so called mono-towns) are locked in poverty traps. In those cases government intervention may be justified and desirable. Our results show that poverty traps did exist in Russia in the 1990s at the regional level. These may well still exist at the town level even now. We cannot extrapolate the quantitative value of the income threshold we identified for the poverty traps from regional level to the town level but our analysis provides very clear qualitative criteria for government intervention. If the average citizen of a town would benefit from moving out but cannot finance the move (e.g. because his/her real estate is worthless), then the government can and should step in through supporting financial intermediaries that could finance the move. Therefore our analysis is fully consistent with the rationale for the government’s mono-towns restructuring program.
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References
- Andrienko, Yuri, and Sergei Guriev (2004). “Determinants of Interregional Mobility in Russia: Evidence from Panel Data.” Economics of Transition, 12 (1), 1-27.
- Che, Natasha, and Antonio Spilimbergo (2012). “Structural reforms and regional convergence.” CEPR Discussion Paper No. 8951.
- Guriev, Sergei and Elena Vakulenko (2012). “Convergence among Russian regions.” Background paper for the World Bank’s Eurasia Growth Project.
[1] Russian law defines monotowns as town where at least 25% employment is in a single firm. Even now, the Russian government’s Program for the Support of Monotowns lists 335 monotowns (out of the total of 1099 Russia’s towns and cities) with the total of 25% of Russia’s urban population. [2] EU (19): Belgium, Czech Republic, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Latvia, Lithuania, Netherlands, Austria, Poland, Portugal, Slovakia, Finland, Sweden, United Kingdom. For EU (19) we consider only those NUTS-2 units for which there is data for each year. Western Europe: Austria, Belgium, Germany, Ireland, Greece, France, Italy, Netherlands, Norway, Portugal, Finland, Sweden, United Kingdom. [3] The graph shows the relationship between the logarithm of the real income in the sending region and the logarithm in migration controlling for income in the receiving region, unemployment and public goods in both sending and receiving, year dummies and other factors influencing migration. Moscow and Saint Petersburg are excluded.
Putin and the Modernization of Russia – a Chimera?
Vladimir Putin is once more the Russian President and a new government has been formed consisting of most of the same faces and mentality. Putin’s victory looks complete – yet there is a very real risk that it will be Pyrrhic. Even if the ‘managed’ political and economic system – rooted in a lack of competition and openness – that has been his defining project can remain stable, it will continue to sap the country’s vitality. In the election campaign, even Putin acknowledged the country’s lack of modern and competitive industries, as well as a business environment plagued by corruption, cronyism and excessive regulation. Yet, in calling for further modernisation of the economy, Putin has also called for more of the same policies, notably a central role for the Russian state in supporting new industries and technological leadership; a newly established State Corporation for Siberia and the Far East is a case in point.
However, this very model has so far achieved very limited results. Oil and gas still account for nearly 70% of total merchandise exports and around half of the federal budget. While relying on publicly funded and managed entities – such as Rusnano – to shepherd the economy into more diversified and more productive spaces, particularly in high-tech activities, has also yielded a relatively meagre harvest. Rusnano itself has already acknowledged the limited portfolio of innovative projects to fund.
In the arena that provides the most compelling metric of competitiveness – export markets – relatively few Russian firms compete in international markets and very few do in higher value added trade. Ricardo Hausmann (2007) has argued that the products that a country exports also reflect the proximity of products and their reliance on similar sets of inputs, such as physical assets and knowledge or skills. Near the start of Russia’s transition it has been calculated that Russia had comparative advantage in only 156 out of 1242 product lines when using a 4-digit SITC classification. Most were natural resources. In contrast, China had comparative advantage in 479 product lines. And as regards proximity, few of Russia’s export products were closely connected to other products, meaning that there was limited scope for enhancing exports. Yet, by 2010 our research shows that there has been an increased concentration on natural resource exports. The contraction of manufacturing has, further, been associated with a fall in the number of Russian product lines with comparative advantage to 103. In contrast, the number for China increased in 2010 to 513. So, despite Putin’s rhetoric, the Russian export basket has become even more concentrated since the mid-1990s. Moreover, the ability to shift into proximate products, as well as diversify into new ones, remains very restricted. This is due to several factors.
A common diagnosis is that failings in the business environment are to be blamed. This is not a new complaint. While the options for limiting these constraints may not be straightforward but the broad policy direction and options are well understood. The challenge is in enforcement. In this – as also with improving governance and further reducing the role of public ownership – improvement is only likely to start with serious political commitment. That is still lacking.
But modernising the economy depends on much more than a good business climate. Critically, it depends on what sorts of skills and knowledge are available to the economy. Yet, even here where many have believed that Russia is relatively favourably situated, on closer inspection, the situation turns out to be far more problematic. In fact, our evidence indicates deterioration in the quality of both skills and education over time, including limitations on the supply of high quality management. Evidence from surveys suggests that Russian firms face problems in finding workers with the appropriate skill profile. While this may be the situation for existing firms, it seems likely that potential entrants to new, diversified activities may, if anything, face even steeper constraints. To understand whether this is indeed the case, the leading – 270 – recruitment firms in Russia were surveyed using face-to-face interviews in 23 locations in Russia, including Moscow and St. Petersburg. This included a small experiment looking at skills availability for work in more innovative activities, such as web technology aimed at social networking and marketing. The aim was to see whether innovative activities faced more binding constraints when trying to hire.
The results of this survey are unequivocal. Not only are there widespread skill gaps for all types of skills, but it takes firms a much longer time to fill vacancies for skilled personnel. This is particularly true for relatively innovative activities. Recruiting managers or high level professionals in the major Russian cities on average takes 3-5 times longer for innovative activity. Even in Moscow, recruiting a manager or high level professional would take between 3-4 times longer; the gap was yet greater in the Urals, Siberia and the Far East.
Moreover, looking at the sorts of skills that are lacking for each type of potential recruit (e.g., a manager); recruiters also report an absence of basic or essential skills. For example, lack of problem solving and management skills were overwhelmingly the most commonly cited limitations for managers, with high level professionals most commonly lacking both problem solving and practical skills. Among the consequences, many firms decide to postpone launching new products and/or modernizing plant.
In short, our evidence shows not only widespread skill shortages but also major barriers on the availability of personnel for firms wishing to establish new or relatively innovative activity. At the same time, anecdotal evidence also suggests that among the thin layer of top talent – likely to be essential for high tech and other innovative activities – many prefer to emigrate. In contrast, Russia fails to attract talent from other countries, not least because of a restrictive migration regime.
The last decade has seen an emphasis on modernising and diversifying Russia. The results have been depressingly limited. Yet Putin and his government propose more of the same. In effect, they are continuing to take a huge gamble by relying on a mix of energy prices and publicly funded industrial policy to paper over the structural weaknesses of the economy. As this article has shown, what Russia currently produces and exports – and the underlying skills and knowledge – provide a very weak base for achieving the goals of modernisation.
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References
- Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
- Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
- Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011