Tag: Russia
Skill Structure of Demand for Migrants in Russia: Evidence from Administrative Data
Authors: Simon Commander (IE Business School, EBRD and Altura Partners) and Irina Denisova (CEFIR, NES).
Using Russian Ministry of Labor administrative data for all legal migrant applications in 2010 and matching the migrant to the sponsoring firm, we find that there is some – albeit limited – evidence of firms using migrants to address high skill shortages. However, the overwhelming majority of migrants are skilled or unskilled workers rather than qualified professionals; a reflection of the low underlying rates of innovation and associated demand for high skill jobs.
Migration policy continues to be a priority in Russian economic policy. This is driven both by a demand for labor – given the unfavorable demographic trends of the last decades – and the easily available supply from the CIS countries. It is still not clear, however, what is the skills structure of the demand for migrants. Relatively new administrative data on demanded permissions to employ migrants sheds however some light on the issue.
In particular, we use the 2010 nationwide dataset ‘Job positions filled by migrants’ published by the Russia Federal Employment Service. The dataset gives detailed information on the applications for permits for migrants, including the 4-digit occupation, firm ID and the offered wage. The Federal Employment Service’s role is to approve or reject an application. In almost all cases documented in this dataset, approval was granted. Moreover, in 99% of the cases, the duration of the permitted contract was one year.
The data allow us to study the skill composition of demand for migrants from the legal sector, with the sizeable illegal labor migration staying beyond the scope of the study. The total number of applications for all of Russia in 2010 was just over 890,000, of which nearly 250,000 or 28% originated from firms in Moscow. The analysis below uses the permission data for the 21 most developed Russian regions (a full version of the paper is available as Commander and Denisova, 2012).
A breakdown of the number of requests in 2010 by skill type using the one-digit ISCO-88 classification (Managers, High-level professionals, Mid-level professionals, Service worker, Skilled agricultural workers, Craft and trades workers, Plant and machine operators, Unskilled workers) shows that over 70% of the requests were for skilled and unskilled workers. At the same time, about 17% of the total migration requests were for higher-level professionals (7%) and managers (10%). Among managers, nearly nine out of ten requests were for production or department managers with no more than 12% of managerial migration requests being for top-level executives. Among the category of high-level professionals, architects and engineers accounted for over two-fifths of requests.
Is the situation any different in the main urban labor markets? In Moscow a lower proportion – around two thirds of the migrant applications – were for skilled and unskilled workers. The starkest difference was that professionals working in IT accounted for a minute share of total high-level skill applications in Russia, but nearly 9% in Moscow. Thus, while there are some differences in the migration profile between Moscow and the rest of the country, the broad picture that emerges is one where migration policy and practice seem to be responding mainly to the apparent bottlenecks at the lower-skill end of the labor market.
Legal requests for migrants are massively dominated by requests concerning low-skill groups; and illegal migrants, as shown by anecdotal evidence, are mainly low skilled. At the same time, there is a sizeable demand for qualified migrants, managers and professionals. There are two potential motives to issuing a request for a qualified migrant: to economize on the costs of labor by substituting a local laborer with a migrant; or to fill in the gap of the scarce qualification/skills hardly available domestically. The two motives could be distinguished by looking at the wage offers associated with the posted positions and comparing them with wages paid in comparable occupations in the same region. The aim of the exercise is to see – particularly within the categories of higher-skilled applicants – whether they command any wage premium that might reflect their scarcity value.
Figures 1-2 plot the reported (relative) wage offers for two migrant skill categories: Department Managers (ISCO code=122) and Computing Professionals (ISCO code=213). The figures depict distributions of relative (to the region average) wage in logs, thus implying that the points around 0 are the wage offers at the level of regional average, above 0 means positive wage premium, and below 0 means negative wage premiums (economizing on the costs). Each figure also gives the mean search wage from the EBRD survey of recruiting agencies in 2010 (relative to the regional average).
Figure 1. Relative Wage Distribution, Production and Operation Department Managers (ISCO-88 Code: 122)
Source: Authors’ calculations based on Rostrud 2010
It is clear from Figure 1 that the wage offers for migrants do not identify any clear positive selection effect, in that migrants’ wages mostly fall below the survey search mean comparators. In the majority of cases, the offered wages also fall below the regional average wage thus implying that the motive is to substitute for cheaper labor.
The demand for migrants with skills of IT professionals is more complicated: there are those who offer wages below regional average, but there is also a large group of those ready to pay a wage premium to attract migrants (with log wage above zero). The search through recruiting agencies (the survey wage) would still require offering higher wages.
Figure 2. Relative Wage Distribution, IT Professionals (ISCO-88 Code: 213)
Source: Authors’ calculations based on Rostrud 2010
For further analysis, the migration dataset was mapped to the ORBIS (a dataset assembled by Bureau van Dijk) firm observations using the unique national tax identification code (so called INN). The ORBIS data includes information on firms’ balance sheets and simple performance data such as output per employee.
When looking only at demand from firms that lie in the top 10-20% of the productivity distribution (productivity is calculated as output per worker in the narrowly defined industry), the picture looks somewhat different: wage offers tend to lie above the average (Figure 3). It is likely that the most productive firms tend to offer wages higher than both regional average for the occupation and the survey-based search wages. This implies that the scarcity of skills on the domestic labor market is one of the more important motives behind the demand for migrants from high-productivity firms.
Figure 3. Relative Wage Distribution, Production and Operation Department Managers (ISCO-88 Code: 122), 10% Most Productive Firms
Source: Authors’ calculations based on Rostrud 2010 and Orbis-Roslana
To control for other firm characteristics, we run regressions relating the relative wage of a migrant to a set of firm and region characteristics, including measures of size and ownership, a measure of recent growth in the region, as well as the level and change in foreign direct investment in a given region since 2007. We also control for the tightness of the local labor market, using a measure of search wages raised in the EBRD survey compared to average wages in a region. The estimates are run with and without region, industry and occupation controls. The results show that relatively high wages tend to be associated with large and/or foreign-owned firms. Growth in a region or the level of FDI per capita are not systematically associated with the relative wage once controls enter the regression, suggesting that the relative wage is largely determined by firm-level features. The measure of labor market tightness enters positively but is insignificant whencontrolling for industry, region and occupation.
Overall, the data from the Russian Ministry of Labor that documents all applications for migrants to Russia in 2010 and allows matching the migrant to the sponsoring firm, show that there is very limited evidence of firms using migrants to fill high-skill jobs. In fact, the overwhelming majority of migrants, skilled or unskilled workers, were mostly originating from other states of the CIS. Furthermore, most were hired at relatively low wages in comparison to the occupation/region averages or the wages reported in the EBRD survey of recruiting firms. At the same time, there is a sizeable portion of demand for skilled migrants, which are offered wage premiums. The demand originates mostly from highly productive firms. Migration policy should acknowledge these different motives behind the demand for migrants.
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References
- Simon Commander and Irina Denisova “Are Skills a Constraint on Firms? New Evidence from Russia”, IZA Discussion Paper No. 7041, November 2012
The crisis in Ukraine and the Georgian economy
We analyze how the crisis in Ukraine will likely impact the Georgian economy and distinguish between short-run and long-run effects. We argue that the short-run effects are transmitted through trade and capital flows and that they are rather negative for Georgia and can hardly be bolstered. In the long-run, however, the crisis could improve the competitiveness of the Caucasus Transit Corridor, an important trading route between Europe and Central Asia Georgia participates in. We give recommendations how political decision makers could support such a development in the wake of an impairment of the northern Ukrainian transit routes.
Introduction
When Ukrainian President Victor Yanukovich decided not to sign the association agreement with the European Union and instead opted for a Russian package of long-term economic support, many Ukrainians perceived this not to be a purely economic decision. Rather, they feared this to be a renunciation of Western cultural and political values, and – to put it mildly – were not happy about this development.
The Russian political system, characterized by a prepotent president, constrained civil rights, and a government controlling important parts of the economy through its secret service, is not exactly the dream of young Ukrainians. Russia can offer economic carrots, but these do not count much against the soft power of Europe that comes in the form of political freedom, good governance, and economic development to the benefit of not just a small group of oligarchs.
Hence, it was all but surprising when many young Ukrainians took their anger about Yanukovich to the streets. After protests that lasted for nearly three months, President Yanukovich fled the country, a temporary government took over, and chaos broke out on the Crimean peninsula.
The dispute about the Crimea has the potential to impede the relations between Russia and the West for a long time to come, in particular if Russia enforces an annexation of the territory. Moreover, the tensions could quickly turn into a military conflict. The aircraft carrier USS George H.W. Bush was moved into an operational distance to the Crimea, accompanied by 20 smaller U.S. warships, and 12 additional fighter planes will be stationed in Poland. Yet even if there will be no direct confrontation between official Russian and U.S. forces, Ukraine could become the battleground of a proxy war, a kind of conflict that was common in the Cold War era. In this respect, one can already read the writing on the wall: the new Ukrainian government begs the U.S. for supplying arms and ammunition, and while the Obama administration is still reluctant to give in to such requests, the call is supported by hawkish U.S. congressmen who might finally prevail.
Ukraine is a country that is geographically close to Georgia and, like Georgia, has vital economic stakes in the Black Sea area. Georgia will not be unaffected by whatever happens in Kiev and Simferopol. In this policy brief, we will inform policy makers about the likely short-run and long-run economic consequences of the turmoil in Ukraine, discuss the challenges and opportunities that may arise, and derive some policy recommendations.
Short-run economic consequences
The crisis in Ukraine will almost instantaneously affect trade and capital flows between Georgia, Ukraine, and Russia. The effects will likely be negative and hit Georgia in a situation of economic recovery.
The Georgian real GDP growth rates were 6.3% in 2010, 7.2% in 2011, and 6.2% in 2012, and the real GDP per capita evolved from about 2,600 USD to about 3,500 USD in this time, but the upsurge discontinued in 2013 (if no other source is mentioned, figures presented in this policy brief (including those in the graphs) come from the Georgian statistical office GeoStat). ISET-PI, in its February 2014 report on the leading GDP indicators for Georgia, estimates the GDP in 2013 to be 2.6%, while GeoStat, the statistical office of Georgia, believes it to be 3.1%.
The unsatisfactory performance of the Georgian economy in 2013 was arguably caused by political uncertainties resulting from the government change that took place in late 2012, and as these uncertainties are largely overcome, most economists believe that Georgia will get back to its remarkable growth trajectory in 2014. The IMF, in its Economic Outlook, predicts a real GDP Growth of 6% in 2014, and the government of Georgia expects this number to be 5%. With an escalating crisis in Ukraine, it is questionable whether these rosy forecasts are still realistic.
Effects on imports
In 2013, Ukraine and Russia were the 3rd and the 4th largest importers to Georgia, respectively. Graph 1 shows the top five importers to Georgia, which together make up about 50% of total imports. The imports from Ukraine and Russia are mainly comprised of consumption goods: of all goods that were imported between 2009 and 2013 from Ukraine and Russia, about 30% were foodstuff. The ten main import goods in this time (in order of monetary volume) were cigarettes, sunflower oil, chocolate, bread, cakes, meat other than poultry, poultry, and sugar.
If the supply of these goods would be reduced through a breakdown of production and logistics, roadblocks, damaged infrastructure etc., the consequences for Georgia would not be utterly severe. From Ukraine and Russia, Georgia receives few goods that are (1) needed for investment projects and (2) cannot be produced domestically (an example of sophisticated investment goods that need to be imported would be ski lifts for tourism projects). Moreover, as Ukraine and Russia supply primarily standard goods that are produced almost everywhere, it is unlikely that a cutback in their imports would lead to sharp price rises in Georgia. Very quickly, increased imports from other countries would close any supply gaps. In addition, many imported consumption goods, like Ukrainian orange juice, are but luxury for ordinary Georgians, who buy their food in cheap domestic markets that sell almost exclusively local products.
Effects on exports
A small anecdote may illustrate the status of Georgian products in the Russian market. In the late 1940s and early 1950s, Stalin used to invite his comrades to his Kuntsevo dacha almost every night. At these occasions, he drank only semi-sweet Georgian red wine. His clique, usually preferring Russian vodka, adopted this habit out of fear to displease the dictator. Yet the real highlight of these nightly gatherings took place after midnight, when an opulent feast began, featuring all the delicacies of the Georgian cuisine. Through Stalin (and the fact that Georgia was a preferred destination of Soviet tourism), Georgian food obtained an excellent reputation in most countries of the former Soviet Union, and, to the dismay of Georgians, some younger Russians even do not know that Khinkali is not an originally Russian dish.
As can be seen in Graph 2, Russia and Ukraine are among the top 5 destinations for Georgian produce, together absorbing about 14% of total Georgian exports in 2013. In 2006, two Georgian products that are traditionally highly popular in Russia, namely wine and mineral water (the famous “Borjomi” brand), were banned from the Russian market. Yet in the wake of the diplomatic thaw that set in after the new government assumed power last year, this ban was lifted, and in 2013, the export of these goods regained momentum. In 2013, 68% of all wine exported from Georgia was sold in Russia and Ukraine (44 and 24 percentage points, respectively). In both countries, Georgian wines are sold at the higher end of the price range and are typically consumed by people with middle and high income. It is likely that these exports, in particular those to Ukraine, will be affected considerably by the crisis. This may happen through decreased demand for luxury foods and through a possible depreciation of the Ukrainian hryvna and the ruble vis-à-vis the Georgian lari.
Another sector that may be affected by the situation in Ukraine is the car re-export business. Georgia imports huge numbers of used cars from the U.S., Europe, and Japan, and passes them on to countries in the region. While this business hardly yields potential for real economic progress, it accounts for roughly 25% of Georgian exports! Of these 25%, about 7 percentage points go to Russia and Ukraine. Moreover, many cars are imported to Georgia on the land route from Europe through Ukraine and Russia (often driven by private, small-scale importers). If it will become more difficult to cross the border between Russia and Ukraine, this business, providing income to many low-skilled Georgians, may be at risk.
It should also be noted that Ukrainians and Russians make up an ever-increasing share of the tourists coming to Georgia (though the biggest group of tourists are Israelis). Also through this channel, an economic downturn in Ukraine and Russia will have unpleasant consequences for Georgia.
Effects on capital flows
According to the National Bank of Georgia, in 2013 a total of 801 mln USD was flowing in from Russia (see Graph 3). Ukraine contributed 45 mln USD to the money inflows, still significant for an economy as small as Georgia’s. An economic downturn in Russia and Ukraine would hit many Georgian citizens, often pensioners and elderly people, who depend on remittances of their children and other family members sent from these countries. This may aggravate a trend that already exists: in January 2014, money inflows decreased by 4% from Russia and by 5% from Ukraine (compared to January 2013).
Long-run economic consequences
Most of the economic dynamics Georgia experienced since 2003 was “catch up growth”. A country permeated by corruption, with a dysfunctional police and judicial system, without protection of property rights and contract enforcement, will grow almost automatically when the government restarts to fulfill its basic functions. Yet once this phase of returning to normal economic circumstances is over (Georgia probably is already in this situation), high growth rates can hardly be achieved without a strong export orientation of the economy, in particular when an economy is as small as Georgia’s. Most economists concerned with Georgia are therefore struggling to identify economic sectors where Georgia is in a good position to develop export potential. The National Competitiveness Report for Georgia, written in 2013 by the ISET Policy Institute on behalf of USAID, therefore extensively discusses the question what Georgia can deliver to the world. Though not related to export in a classical sense, the report points out that one of the advantages Georgia has is its geographical location, providing for possibilities to transform Georgia into a logistics hub.
There are three main routes to transport goods from Europe to the Central Asian countries (e.g. from Hamburg to Taraz in Kazakhstan). One route goes via the Baltic ports of Klaipeda or Riga, and then through Ukraine and Russia, and another route goes overland through Ukraine. A third one, the so called Caucasian Transit Corridor, has the Georgian port city of Poti and Turkey as its Western connection points, then goes through Georgia, Azerbaijan, and the Caspian Sea, and further east it splits up into a Kazakhstan and a Turkmenistan branch.
According to the Almaty based company Comprehensive Logistics Solutions, the fastest and cheapest route is the one through the Baltic ports. The transport from Hamburg to Taraz takes around 33 days and costs 6,220 USD per standard container. The overland transport via Ukraine takes around 34 days and costs 7,474 USD. Finally, transport through the CTC currently takes the longest time, namely around 40 days, and costs 6,896 USD.
Unlike many other economic activities, competition for transportation is more or less a zero-sum game played by nations. If transport through Ukraine and Russia will be restrained due to closed borders and political and economic instability, the total transport volume will not change substantially. Rather, instead of going through the northern routes, the goods will flow through the CTC. A similar development could be observed when the embargo against Iran was tightened and shipping goods through Iranian ports became increasingly difficult for Armenia and Azerbaijan. As a result, Azerbaijan, traditionally importing through Iran and exporting through Poti, now facilitates both its imports and exports through Poti.
This is a great chance for Georgia if it wants to become serious about transforming into a logistics hub. In our policy recommendations, we will speak about how to utilize on this opportunity.
Policy recommendations
Georgia can do little to bolster the short-run effects that are transmitted through the trade and capital flow channels. Political decision makers should be aware of problems that might arise for particularly vulnerable groups in the population, like pensioners who lose income in case remittances from Russia and Ukraine run dry, and help out with social support if necessary.
Regarding the long-run impact, Georgia should use this opportunity for gaining ground in the competition with northern transit routes. The Caucasus Transit Corridor can become much faster and cheaper if (a) a deepwater port and modern port facilities with warehouses will be built in Poti, (b) the road and train infrastructure will be improved, and (c) it will be easier to bring cargo over the Caspian Sea. Regarding the latter point, it would be important to assist Azerbaijan in improving the port management at Baku (in particular reducing corruption), and in reforming the monopolistic Azerbaijani State Caspian Sea Shipping Company.
Azerbaijan invests 775 mln USD into the Georgian part of the Baku-Tbilisi-Kars railway, proving their serious interest to upgrade CTC. Given this impressive commitment of Azerbaijan, Georgia should not stand back.
Conclusion
The crisis in Ukraine yields short-run risks and long-run opportunities for the Georgian economy. While there is little that can be done about the risks, the opportunities call for courageous steps to improve the Caucasus Transit Corridor. If the countries that hold stakes in the CTC are now further reducing the cost of transportation and make the route faster and more customer-friendly, the CTC may establish itself as the main trading route connecting Europe and Central Asia. Once critical investments have taken place, CTC’s advantage could be sustained beyond the current crisis. It is a competitive route that simply needs upgrading, which can happen now as a fallout of the conflict between Ukraine and Russia.
References
- Leading GDP Indicators for Georgia, The ISET Policy Institute, February 2014, http://www.iset-pi.ge/index.php?article_id=711
- The National Competitiveness Report for Georgia, The ISET Policy Institute, 2013, http://www.iset-pi.ge/index.php?article_id=713
- World Economic Outlook, The International Monetary Fund, October 2013, http://www.imf.org/external/pubs/ft/weo/2013/02/
The Application of Composite Leading Indicators on the Single Economic Space Economies
This brief is based on a CEFIR research project aimed at the short-term forecasting of socio-economic development of the member-countries of the Single Economic Space (SES), conducted for the Eurasian Economic Commission in 2013. This project focused on compiling composite leading indicators that could allow policymakers to identify phases of a business cycle and to forecast its turning points. We suggest a methodology for the selection of components of the Composite Leading Indicators (CLIs) for industrial production, and apply this methodology to predict industrial production in SES member states. Our methodology performs well for Russia and Kazakhstan, and slightly less so for Belarus.
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.
▪
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.
- European monetary union: transition, international impact and policy options/ edited by Paul J.J. Welfens.- Berlin.- Springer.- 1997.-470 p.
- Eurasian Economic Community on-line database [Electronic resource]- Moscow.- 2005.- Mode of access: www.evrazes.com.- Date of access: 17.02.2012
- Evstigneev V.R. Currency and finance integration in EU and CIS. Comparative semantic analysis. /V.R. Evstigneev -М.: Наука.- 1997.—271 p.
- International monetary fund on-line database [Electronic resource] – Washington.- Mode of access: www.imf.org.- Date of access: 07.11.2012
- Kondratov D.I. Finantial integration: international experience and perspectives of CIS countries development/D.I. Kondratov// Economic Journal of HSE.- 2012.- №1.- p. 105-142.
- Luzgina A.N. Prospects of economic and monetary integration of the CIS member states/ A.N. Luzgina // Bank Bulletin Magazine. – 2013a.-№ 19 (600).- p. 21-26.
- Luzgina A.N. Model of monetary integration involving the Republic of Belarus / A.N. Luzgina // Bank Bulletin Magazine. – 2013b.-№ 20 (601).- p. 39-46.
- Mandell R. A theory of optimum currency areas/ R. Mundell// Interntional economics [Electronic resource].- New York: Macmillan.- 1968.- Mode of access: http://www.columbia.edu/~ram15/ie/ie-12.html. – Date of access: 23.05.2013.
- Monetary unions: theory, history, public choice/ edited by Forrest H. Capie and Geoffrey E. Wood.- London: Routledge, 2003.- 198 p.
- Statistical Committee of CIS on-line database [Electronic resource] – Мoscow, 2013.- Mode of access: www.cisstat.com.- Date of access: 03.09.2012
- Struk T. Concepts of reforming the world currency system/ Т. Struk// Bank Bulletin Magazine- 2012.-№16 [561].- p.7-14.
- World Bank on-line database [Electronic resource].- 2013.- Mode of access: http://worldbank.org.- Date of access: 27.06.2013
[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
- Balabanova D, Roberts B, Richardson E, Haerpfer C, McKee V. 2012. Health Care Reform in the Former Soviet Union: Beyond the Transition. Health Services Research 47(2): 840-864.
- 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.
- Sheiman I. 1997. From Beveridge to Bismarck: Health Financing in the Russian Federation’. In Innovations in Health Care Financing, Schieber G. (ed.), Discussion Paper 365, 1997, Washington DC: The World Bank.
- 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.
- Twigg J. 1999. Obligatory medical insurance in Russia: the participants’ perspective. Social Science and Medicine 49: 371–382.
- Twigg, JL. 2001. Russian healthcare reform at the regional level: status and impact. Post-Soviet Geography and Economics 42: 202–219.
- Zaborovskaya AS, Chernets VA, Shishkin SV. 2005. Organizatsiya upravleniya i finansirovaniya zdravoohraneniyem v subjektah Rossijskoi Federatsii v 2004 godu (Organization of management and finance of healthcare in Russian regions in 2004)
- Zweifel P, Breyer F. The economics of social health insurance. In The Elgar Companion to Health Economics, Jones A. (ed.), Edward Elgar, 2006.
- Wagstaff A. 2010. Social health insurance reexamined. Health Economics 19: 503–517.
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.