Author: Admin
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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Transportation Infrastructure and Labor Market Integration: the Moscow Oblast Case
The model of city organization proposed by von Thünen in the beginning of the XIXth century, and then formalized by Alonso followed by Muth and Mills (see Ner (1986)), is one of the most “successful” models in economics in terms of practical applications. The model explains why the gradient of population density and land rents decline from the city center towards the periphery. In fact, almost all modern cities fit this pattern, i.e. the model invented two centuries ago is capable of describing today’s spatial structure of cities. Even though von Thünen’s original idea of a city center as a single “marketplace” is no longer realistic, a multitude of factors beyond this make central locations nevertheless attractive. If firms are located near each other, they can take advantage of a common labor pool, easier access to consumers and suppliers, shared infrastructure, and knowledge spillovers, to name but a few advantages. Access to the center brings tangible economic benefits to both labor and capital and these benefits exceed possible losses due to increased competition, and so the von Thünen mechanism still works today, albeit through different channels.
In cities, there are generally two types of spatial organizations possible with respect to household income. If the advantages of amenities in a city center are not very strong, rich people tend to choose to locate in suburbs in order to consume higher quality housing. Such patterns are typical in US cities. If the advantages of a center are strong, the rich choose to live in the center. (Brueckner et al. (1999)) Due to historical circumstances, such patterns are typical of European or Russian cities. In these cases we observe a declining gradient of income; the further we move from the center, the further residents’ average income falls.
There are two forces at work shaping this declining gradient of wage. First, poor people sort themselves into suburban locations. Second, residents of the suburbs who want to take advantage of the labor market in the center face a barrier involving commuting costs. Many of them forgo high-wage opportunities that require tedious everyday commuting and therefore remain poor as a consequence.
An apparent policy solution to reduce income inequality would be to reduce transportation costs. The higher transportation costs are, the steeper the gradient of income. Fast and convenient transportation promotes the integration of local labor markets, gives the residents of the suburbs more, and often better, job opportunities, and works toward equalization of income across the agglomeration. Moreover, as transportation costs decline, the geographic area of agglomeration grows, which opens new opportunities for real estate development as well as new possibilities for rural residents to commute and participate in large labor market.
We conducted a study at CEFIR (Mikhailova et al. (2012)) comparing the spatial patterns of average wages in the Moscow agglomeration with several agglomerations in Western Europe. We considered municipal-level data for Moscow Oblast and for 25 agglomerations in Sweden, Germany, and Netherlands. In the sample of municipalities that are served by suburban train system, we estimated how average wages in a given municipality respond to different lengths of travel times to the city center.
Figure 1 shows the estimated wage-travel time relationship for Moscow Oblast and Figure 2 for the selected European cities.
Figure 1. Average Wage and Travel Time to the City Center, Moscow 
The residents of the Moscow agglomeration are at a clear disadvantage according to the data shown above. Residents of Moscow Oblast, even those who live in relative proximity to the city, loose drastically in terms of average wage. Doubling the travel time (say, from 20 min to 40 min, which is the range most commuters fit into) results in a 25% drop in the average wage for residents in Moscow Oblast compared to only a 5% drop in Europe. The wage in a municipality, from which it would take 90 minutes to travel to the city center, is almost half of the average wage inside Moscow’s Ring Road whereas in Europe 90 minutes translates into a 10% loss of in average wages.
A 90 minutes travel time could be considered as a realistic limit to the size of an agglomeration. This is roughly the maximum distance over which a typical working commuter would be willing to travel each day in each direction. A 90 minute commute in Europe represents approximately a 100 kilometer distance. In Moscow Oblast, however, it is only 63 km. So, Moscow Oblast loses in the effective “reach” of suburban transportation: people who live further than roughly 60 km from the center cannot practically commute.
Even for the same commuting time, the difference in wages between center and suburban municipality is much smaller in Europe (see Figures 1 and 2). This means that a commute for the same time length (in terms of railroad transport) presents a larger barrier for the residents of Moscow Oblast. This is obviously an over simplification of the situation since taking into account only commuting times as the measure of costs we ignore many other critical factors such as price (relative to income), the convenience of schedule and travel comfort, alternative modes of transportation, etc. Suburban trains in Moscow Oblast run infrequently, they are overcrowded, and alternative transportation modes (car or bus) face considerable delays due to road congestion. All of these additional factors serve to reduce the labor market opportunities of the Moscow Oblast residents and make wage inequality even deeper.
Figure 3 presents wage-distance gradients for the Moscow agglomeration under different scenarios using a hypothetical “European” gradient to show what could be the case if changes were made to reduce barriers to transportation bringing the Moscow agglomeration in line with European standards. The graphs end at a distance that corresponds to a typical 90-minute commuting time under various scenarios ranging from the status quo to the best case, where Moscow Oblast replicates European standards. The red curve represents the upper bound estimate of the possible effect of investments to improve the transportation infrastructure to bring Moscow regional transportation network in line with the quality of a typical European agglomeration. The residents of Moscow region could gain up to 24% more in terms of current average wages if this were to take place. The purple curve, however, presents a more modest scenario assuming that the structure of Moscow regional transportation network remains the same, but the travel time were to be cut by 20%. Even in this case, the gains to Moscow Oblast residents are about 3% of wages which is very significant economically for an area populated by 5.5 million people.
Figure 3. Wage Distance Gradient 
Further, it is important to note that to take advantage of labor market integration residents do not necessarily all have to commute to work to the center. The mere possibility of commuting creates arbitrage opportunities in the labor market and puts upward pressure on wages. As a result, it is important for economic policy to constantly improve transportation infrastructure even if the private benefits of increased usage are modest.
In the end, our analysis did not touch on the other benefits from transportation infrastructure. Apart from labor market integration, improvements in transportation infrastructure promote real estate development (Baum-Snow (2007), Garcia-López(2012)) and expand the market for goods and services. We leave these questions for further research.
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References
- Baum-Snow, Nathaniel (2007) “Did Highways Cause Suburbanization?” The Quarterly Journal of Economics 122(2): 775-805
- Brueckner, Jan K., Jacques-François Thisse, and Yves Zenou (1999) “Why is central Paris rich and downtown Detroit poor?: An amenity-based theory.” European Economic Review 43.1: 91-107.
- Garcia-López, Miquel-Àngel (2012) “Urban spatial structure, suburbanization and transportation in Barcelona”, Journal of Urban Economics, Volume 72, Issues 2–3, September–November, Pages 176-190
- Mikhailova, T, V. Rudakov and N. Zhuravlyova (2012) “Economic effects from the Moscow Oblast suburban railroad infrastructure development” («Экономические эффекты от развития инфраструктуры пригородного железнодорожного сообщения в Московской области»), project report, CEFIR.
- Ner, J. B. (1986). The structure of urban equilibria: A unified treatment of the Muth-Mills model. Handbook of regional and urban economics: Urban economics, 2, 821.
And Then There Were Eighteen? Will Latvia Join the Euro Zone in 2014?
Latvia’s government is zealously preparing for accession to the Euro Zone. Prime Minister Valdis Dombrovskis is expected to request the European Central Bank (ECB) and European Commission (EC) prepare their respective convergence reports on Latvia’s readiness to enter Economic and Monetary Union (EMU) within the next two months. The expectation is that Latvia will join on 1 January 2014. Indeed, the three-party coalition government has long been readying for the technical changeover to the euro. The Cabinet of Ministers adopted a detailed national euro changeover plan in September 2012 and appointed a high-level steering committee to manage the process. The government has launched a controversial multi-million euro advertising blitz aimed at winning over Latvia’s skeptical public.[1] Parliament passed the law on euro adoption in a 52-40 vote on 31 January 2013.
What could possibly go wrong? Although unlikely, a referendum or the collapse of the Dombrovskis coalition government could yet derail Latvia’s euro ambitions.
Latvia and Europe
All Latvian governments have steered a steady pro-Western course in the two decades since the fall of the Soviet Union. International recognition was followed by membership of the Council of Europe, World Bank and the other minor and major international organizations that make up the international community. However, the big attractions were the Western clubs – NATO and the European Union. Membership of both was achieved in the two ‘big bang’ enlargements of 2004. In all the giddy excitement of finally joining the Western world and seemingly slipping away from Russia’s bear-hug, Latvia initially aimed to quickly join the Euro Zone, setting a target of 1 January 2008.
However, the government proved half-hearted in its efforts, preferring to enjoy the low-hanging fruit of a cheap credit-driven booming economy rather than balance the budget. Both government and public entered a period of rabid consumption and spending that resembled nothing so much as sailors in a pub after a year at sea. Unsurprisingly, Latvia rapidly slipped far away from meeting the Maastricht criteria on inflation. Accession to the Euro Zone was quietly dropped from the political discourse.
However, euro adoption returned as a frontline government initiative after the dramatic economic collapse of 2008, and the advent to power of Valdis Dombrovskis, the Baltic Angela Merkel. Dombrovskis will soon have been in power for four years, a lifetime in Latvian politics where, prior to Dombrovskis, the average prime minister served for less than a year.[2] He has overseen harsh austerity measures of tax hikes and spending cuts, but remains surprisingly popular (not least because his party was in opposition during the post-2004 economic bubble years). He has twice been re-elected to office, proving once again that Latvians favour monochrome technocrats over colourful populists.
Despite a return to growth (in 2012 Latvia recorded the highest GDP growth in the EU), the government has maintained tight control over spending. Indeed, it has even perhaps been over-zealous, with both the IMF and EU recently chipping in with criticism of the social spending cuts that Latvia has made to its 2013 budget.[3] Nevertheless, Latvia is now applauded as a model of austerity and frequently used as a positive contrast to Greece.[4]
Moreover, Latvia is now on the cusp of meeting the Maastricht criteria for accession to the Euro Zone. A January 2013 IMF staff report argued that Latvia meets the public debt and budget deficit criteria, although inflation and interest rates may be a hurdle depending on the EU member states used for the reference value calculation (will Greece be treated as an outlier?).[5] The informal political signals from both the EC and ECB are clearly positive. However, euro accession could still be derailed by either a referendum or a change of government.
Let the People Decide?
The biggest potential hurdle remains the threat of a public referendum. The EC and ECB will not contemplate Latvia’s accession to the euro zone with the Damocles Sword of a referendum hanging over the process. Moreover, public support for the euro remains low, with just 8% of the public wanting the euro introduced quickly and 41% being absolutely opposed to the currency.[6] A vote would be a real throw of the dice.
A citizen’s initiative aiming to delay euro adoption, by demanding a vote on the timing of accession, was submitted to Latvia’s electoral authority (by the awkwardly named Latvia’s Social Democratic Movement for an Independent Latvia, a fringe party that has never been elected to parliament) in late 2012. The Central Election Commission must make a final decision on whether to allow the initiative to go ahead by February 3. However, the legal opinions provided by scholars, the Latvian ombudsman’s office and the Latvian parliament’s legal advisers indicate that the initiative is likely to be rejected because:
- Latvians effectively voted to join the euro when voting on accession in 2003;
- The Council of Ministers is the only institution authorized to choose the date of accession to the euro zone, thus any initiative specifying a date (or conditions that need to be met) is not legal;
- The text of the initiative conflicts with the constitution.[7]
While the ruling could be challenged in Latvia’s Constitutional Court or a reworded initiative submitted to the Central Election Commission, the weight of the legal opinions already delivered indicates that these efforts would be unlikely to succeed. At worst, the uncertainty could delay euro adoption past January 1, 2014 (and the Latvian legal system can certainly be ponderous at times). The same is true of any parliamentary attempt to initiate a referendum by having a one-third minority of deputies force the president to sit on the euro adoption law while citizens sign an initiative.[8] Indeed, legal opinions cited by the President state that because euro introduction is a treaty obligation, a majority of parliamentarians (51 of 100) would need to sign any initiative attempting to call a referendum. The opposition will not be able to rustle up a majority of parliamentary deputies (although the legal haggling could delay the date of euro adoption).
Coalition Collapse?
The other risk is a collapse of the government coalition. While the Reform Party and the prime minister’s Unity Alliance are firm supporters of euro adoption, the third coalition member – the radical right populist National Alliance is more torn. Its rank and file membership is largely against the euro, primarily for nationalist reasons (they see the Latvian Lat as a symbol of sovereignty and national identity). One NA parliamentarian even broke coalition ranks and voted against euro adoption. A motley conglomeration of far right radical groups and nationalist intellectuals has begun speaking out against the ‘commercialization’ and ‘westernization’ of Latvia, and sees the euro adoption battle as the opportunity to draw a final line in the sand. They are likely to put the National Alliance’s ministers and parliamentary deputies under severe pressure.
Indeed, the National Alliance already played the ‘euro card’ in November 2012, successfully extracting budgetary concessions for pet projects from Prime Minister Dombrovskis. They may well play it again, as they seek a greater number of ministerial portfolios. However, as Dombrovskis pointed out, opening up of the coalition agreement could well lead to the collapse of a government already creaking at the edges.
Conclusion: After Dombrovskis
There is strong political resolve to lever Latvia into the Euro Zone. Moreover, the unusual confidence emanating from both government officials and the Bank of Latvia indicates that certain reassurances have been made in Brussels and Frankfurt. Indeed, Latvia’s glowing current reputation as the poster child of austerity gives it a once-in-a-decade political momentum. Latvia’s entry into the euro on schedule on January 1, 2014 is more likely than not.
However, looking to the future, one pertinent question needs to be addressed. Which Latvia will we see in the Euro Zone? The grey, serious, disciplined almost Teutonic Latvia of Valdis Dombrovskis? Or the reckless drunken sailor, that has marked much of Latvia’s post-communist era?
Naturally, Dombrovskis holds the key to this question. He is expected to leave domestic politics after the October 2014 parliamentary election, probably to cash in his international political capital with a well remunerated European post (the timing is right for a 2014-2019 European Commissioner portfolio). At best, if re-elected, he might be persuaded to stay on to oversee Latvia’s presidency of the European Union in 2015. In any case, while Latvia has been reborn as a paragon of economic virtue under his watch, these assets have not been institutionalized. Dombrovskis will leave behind the same old fractured, frail and quarrelsome parties, politicians and oligarchs that he inherited. Recent international criticism of disequilibrium in government welfare and tax policies hints that political backsliding has already begun.
Latvia is at its strongest when its political, economic and administrative elite units in pursuit of some concrete target. Independence from the Soviet Union, then NATO and EU accession, followed by harsh austerity measures and now even Euro Zone accession were achieved far quicker than many observers had believed possible. International conditionality has made up for the absence of ideology and ideas as moral and political compasses in Latvian politics. However, when left to their own devices, Latvian politicians have tended to run amok. After Latvia enters the Euro Zone it will be left without an all-encompassing political plan. Quite frankly, that is rather worrying.
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References
- Aslund, Anders (2013) ‘Why austerity works and stimulus doesn’t’.
- DNB Banka (2012), ‘Latvijas Barometrs: Eiro ieviešana Latvijā’.
- Eglitis, Aaron (2013), ‘EU joins IMF in criticizing Latvian cuts to tax, social spending’. Bloomberg news.
- IMF Staff Report No. 13/28 (2013). Available at: http://www.imf.org/external/np/sec/pn/2013/pn1311.htm
- Pettai, Auers and Ramonaite (2011), ‘Political Development’ In Marju Lauristin (ed.), Estonian Human Development Report 2010/2011: Baltic Way(s) of Human Development: Twenty Years On. Tallinn: Eesti Koostoo Kogu. 144-163.
- Swedbank (2012). ‘Fulfilling the Maastricht Criteria – mission possible for Latvia and Lithuania?’.
[1] See the Latvia euro changeover site. Available at: http://www.eiro.lv
[2] Pettai, Auers and Ramonaite (2011), ‘Political Development’ In Marju Lauristin (ed.), Estonian Human Development Report 2010/2011: Baltic Way(s) of Human Development: Twenty Years On. Tallinn: Eesti Koostoo Kogu. 144-163.
[3] Aaron Eglitis (2013), ‘EU joins IMF in criticizing Latvian cuts to tax, social spending’. Bloomberg news.
[4] Anders Aslund, an ardent cheerleader of Latvia’s austerity programme, puts the country’s success down to ‘front loading’ reforms, particularly fiscal adjustment . See Anders Aslund (2013) ‘Why austerity works and stimulus doesn’t’.
[5] IMF Staff Report No. 13/28 (January 2013). Also see Swedbank Analysis (1 August 2012). ‘Fulfilling the Maastricht Criteria – mission possible for Latvia and Lithuania?’
[6] Although another 42% had a positive attitude towards the euro, but did not want to see it hurriedly introduced. See DNB Banka (November 2012), ‘Latvijas Barometrs: Eiro ieviešana Latvijā’.
[7] The legal opinions can be found on the Central Election Commission’s homepage.
[8] See Article 1, paragraph 3 in the law on referendums and initiatives.
Adapting to Capitalism
Author: Jenny Simon, SITE
When transitioning to a free-market economy, do people adapt to the new circumstances immediately? Undoubtedly, major shifts in the political system do not escape people’s notice. They often follow extended demonstrations, spectacular coups d’état or even violent uprising. However, the changes in economic institutions that go along with such transitions, and their implications for optimal economic behavior, although fundamental, may not be apparent immediately. The German reunification provides the opportunity to study this learning process.
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.
Latvian Unemployment is Cyclical
In terms of output decline and increase in unemployment, the economic recession in Latvia that started during the 2008-09 financial crisis was one of the most severe in the world. Using modern methods of statistical analysis, we demonstrate that the changes in unemployment should be attributed primarily to cyclical, rather than structural factors. This answer brings important implications for anti-crisis policy in Latvia and elsewhere in the world: it suggests that the surge in unemployment was largely a consequence of Latvia’s austerity policy, and that today, broader economic measures to support further economic recovery can be effective.
During the 2008-2009 recession Latvia experienced the EU’s largest and fastest increase in unemployment. This is illustrated in Figure 1 where it can be seen that the unemployment rate rose by approximately 14 percentage points from a low of 6.2% in early 2008 to 20.4% at the end of 2009. However, labour market recovery has not been equally rapid, with unemployment in 2011 and the first half of 2012 settling at around 16%. This corresponds to a decline of less than 5 percentage points from the peak. The most recent quarter has seen an improvement with the unemployment rate falling to 13.5%. Partly, the decline can be attributed to seasonal factors (seasonally adjusted unemployment rate declined by less; from 15.7% to 14.2%). However, if discouraged workers are counted, the reduction in unemployment was smaller and the rate of unemployment still stood at 16.8% in the 3rd quarter.
This observed persistence in unemployment is seen by many as a signal of the structural nature of the shocks that hit the economy during the recession and of the further intensification of structural problems.
Figure 1. Unemployment Rate (Age Group 15-74), Seasonally Adjusted, (%)[1] 
Note: Discouraged workers are those economically inactive who mentioned loss of hope to find a job as the main reason for not looking for a job.
Source: Central Statistical Bureau of Latvia, authors’ calculations.
For example, Krasnopjorovs (2012)[2] argues that there is a structural mismatch in the Latvian labour market, which mainly takes the form of a skills mismatch and concludes that the “employment rate now is similar to that observed in “normal times” of 2002-2004, [which] suggests a rather small [if any] negative output gap and a large share of structural unemployment in total unemployment”. Likewise, the Ministry of Finance of Latvia (2012)[3] argues that in the medium term, supply and demand mismatches will intensify. Thus, raising the risks of structural unemployment and, while not explicitly reporting their NAIRU estimates, the reported estimate for the output gap in 2012 is just -0.2% of potential GDP, but for 2013, a positive output gap of 0.7% is forecast.
The European Central Bank (2012)[4], when discussing inflation prospects in Latvia, identifies the situation in the labour market as a potential source of risk, as “labour shortages in certain sectors have appeared, suggesting that unemployment is likely to be close to its natural rate”. The European Commission’s (2012)[5] estimate for the NAIRU in 2012 is 14.6%, which is very close to the actual unemployment rate. The IMF (2012)[6] is the least categorical in characterising the nature of Latvian unemployment, arguing that “lack of skilled labor could become a constraint to growth and put pressure on wages unless the long-term unemployed re-enter the labor market”, at the same time forecasting that “[a] negative output gap and high unemployment should keep core inflation (…) low, and contribute to a gradual decline in headline inflation”.
Other commentators, e.g. Krugman[7] have argued that Latvian unemployment is largely explainable by cyclical factors.
Which explanation is correct is important both for current policy purposes and for the interpretation of past policy. Thus, “if cyclical factors predominate, then policies that support a broader economic recovery should be effective in addressing long-term unemployment as well; if the causes are structural, then other policy tools will be needed”.[8] On the other hand, “higher structural unemployment alters the role of short-run stabilization policies, including monetary policy, by increasing the possibility that expansionary policies will trigger inflation at higher rates of unemployment than otherwise”.[9]
In what follows, we evaluate the extent to which the recent evolution of Latvian unemployment can be interpreted as structural and provide some policy implications. We use three alternative approaches and all three point in the same direction: overwhelmingly both the increase in unemployment and its recovery are explainable by cyclical factors.
Decomposition of the Unemployment Rate into Structural and Cyclical Components
Our first approach is to directly decompose unemployment into structural and cyclical components. This is based on the following intuitive reasoning: when structural change occurs, unemployment is a result of changes in the composition of the labour market, i.e. the skill requirements of the jobs available today no longer match the skillset of the workers who are searching for jobs. On the other hand, when cyclical factors dominate, we would expect similar increases in unemployment across all sectors and locations. Using a formalised version of this approach, we conclude that changes in Latvian unemployment during the recession can be explained by changes in the unemployment rates in particular sectors and occupations, while the shares of the sectors and occupations in labour supply have been practically unchanged.
Following Lazear and Spletzer (2012)[10], we decompose the changes in the unemployment rate into structural and cyclical components, where the first component comes from changes in unemployment rates in a particular group assuming an unchanged structure, while the second component represents compositional changes in the structure of labour supply.
In order to implement this analysis, we use the most disaggregated categories of the sector of previous employment and occupations, which are obtainable from quarterly micro level LFS data. This covers 10 sectors of production and 9 occupations. We use a broad definition of unemployment and include discouraged workers to account for the nominal reduction in unemployment, which occurs just because people stop looking for a job. At the time of writing, data is only available for 2007-2011; hence, our analysis does not cover 2012.
Figures 2 and 3 show the decomposition of unemployment rate changes by sectors of production and by occupations.
Figure 2. Decomposition of Year-on-Year Changes in Unemployment Rate by Sectors of Production, Including Discouraged Workers, (% points)
Note: Includes only those unemployed who stopped working less than 8 years ago, for those who stopped working more than 8 years ago data on the previous sector of employment is not available; includes only those who indicated the sector of previous employment.
Source: Central Statistical Bureau of Latvia, authors’ calculations.
The sectoral decomposition suggests that the increase in unemployment in 2009-2010 can be fully attributed to cyclical factors – the structural component was small and even negative. The negative structural component is explained mainly by a reduction in the share of industry and construction in labour supply, which were sectors characterised by relatively high rates of unemployment.
Figure 3. Decomposition of Year-on-Year Changes in Unemployment Rate by Occupations, Including Discouraged Workers, (% points)
Note: Includes only those unemployed who stopped working less than 8 years ago, for those who stopped working more than 8 years ago data on the previous occupation is not available; includes only those who indicated previous occupation.
Source: Central Statistical Bureau of Latvia, authors’ calculations.
The occupational decomposition also suggests that changes in the rate of unemployment have been largely cyclical. The positive structural component in 2010Q1 can be explained by an increase in the share of civil servants, service workers, as well as shop and market sales workers. The positive structural component in 2010Q4 and 2011Q2 is a result of an increased share of craft and related trades workers, and elementary occupations.
In sum, the shares of both sectors and occupations in the economy have remained largely unchanged with unemployment changes explained by sectoral or occupational changes in unemployment rates.
Evaluating mismatch
A second approach is to directly estimate labour-market mismatch. Structural unemployment is usually defined as resulting from a mismatch between the labour demand and the skillset and locations of those looking for jobs. “[M]ismatch is defined as a situation where industries differ in their ratio of unemployed to vacancies”.[11] Using this approach our estimates show no significant mismatch between available vacancies the skills of workers.
To assess changes in the matching during the crisis, we calculate relative standard deviation of the number of unemployed per vacancy across sectors:
where x(i) is number of unemployed per vacancy in sector[12] i (including discouraged workers) and x¯ is average number of unemployed per vacancy across sectors.
Figure 4. Relative Standard Deviation of Unemployed per Vacancy across Sectors
Source: Central Statistical Bureau of Latvia, authors’ calculations.
Figure 4 presents the results of the relative standard deviation estimation. RSD increased in the beginning of the recession, but it has been declining since early 2009 indicating no increase in the degree of mismatch.
Estimating the Beveridge Curve
The third method uses the search and matching approach as developed by Pissarides (2000)[13] where the emergence of structural unemployment is signalled by deterioration in the efficiency of labour-market matching. Again, the conclusion is that except during the boom, when matching appears to have improved, Latvian unemployment cannot be explained by changes in the efficiency of matching.
We follow the Beveridge curve approach proposed by Barlevy (2011)[14] who follows Petrongolo and Pissarides (2001)[15] in assuming that matches in the labour market can be described by a Cobb-Douglas function, in which the number of matches depends on the unemployment rate, the vacancy rate, the productivity of the matching process, and elasticity of the number of matches with respect to the unemployment rate. The flow into unemployment is defined by the separation rate into unemployment; while the flow out of unemployment is given by the matching function. Equating the two flows yields the Beveridge curve which, given a constant separation rate, defines a negative relationship between vacancies and the unemployment rate.
Figure 5 plots the Beveridge curve for Latvia over 2005 – 2012Q2. We first observe that the Beveridge curve appears to have shifted downwards in 2007, pointing to an improvement in matching (an increase in the productivity parameter) as the economy approached the top of the boom. This is consistent with the idea that employers facing labour shortage became less “picky” in their hiring decisions. Starting from 2010, as the unemployment rate gradually declined there appears to have been a movement back along the Beveridge curve though perhaps with a minor outward shift.
Figure 5. Unemployment Rate (incl. Discouraged Workers) vs. Vacancy Rate in 2005-2012q2, Seasonally Adjusted
Source: Central Statistical Bureau of Latvia, authors’ calculations.
Estimating the parameters of the Beveridge curve permits assessment of changes in matching. To estimate A, we divide the sample into three periods and fit the Beveridge curve for these three periods: 2005-2006 (beginning of the boom), 2007-2009 (the peak and the recession) and 2010-2012 (the period of gradual reduction in unemployment). Apart from data on unemployment and the vacancies, we need to know the separation rate. Barlevy (2011)[16] argues that the relevant separation rate is likely to be fairly stable over the cycle – he assumes a constant separation rate of 0.03 for the U.S. (one can think of this separation rate as the flow of people from employment to unemployment in “normal” times). In the absence of concrete evidence to the contrary, we also assume a constant separation rate. However, this assumption is not crucial for our analysis, since we are interested in the change in A and not the level of A.
Figure 6 shows the fitted Beveridge curves, as well as the seasonally adjusted data over the period ranging from 2005 up to the second quarter of 2012.
Figure 6: Fitted Beveridge Curves and Actual Unemployment Rate (incl. Discouraged Workers) vs. Vacancy Rate in 2005-2012q2, Seasonally Adjusted
Source: Central Statistical Bureau of Latvia, authors’ calculations.
Our estimates of the parameters are presented in Table 1. The results show that A declined in 2010-2012, suggesting a slight deterioration in matching, yet A estimated on 2010-2012 data is slightly higher than A estimated on 2005-2006 data, the period which probably comes closest to the definition of “normal” times in our sample.
Table 1. Estimated Parameters of the Beveridge Curve
Source: Authors’ calculations.
Using estimated and the formula for the steady-state vacancy rate, we are able to calculate implied changes in A over the whole period under consideration. To do this, we employ two alternative estimates of : (1) , the estimate on 2005-2006 data, which can be viewed as estimate for “normal” times and (2) , average of estimates for the three periods.
Figure 7 illustrates the results of the estimation. These suggest that A declined from its peak in the beginning of 2008, in turn suggesting that matching has deteriorated as compared to the boom years. However, A started to grow in the end of 2011 and is currently above its level in 2005-2006. More importantly, our results suggest that there was no notable deterioration in matching since mid-2009, i.e. neither the increase in unemployment in the recession nor the subsequent recovery have been accompanied by significant intensification of labour market mismatches.
Figure 7: Implied A estimate
Source: Authors’ calculations.
Finally, our estimates of the Latvian Beveridge curve imply that changes in matching efficiency have been practically absent (except in the boom). Hence, changes in unemployment can largely be explained by cyclical factors.
Conclusion
Our analysis indicates no significant change in structural unemployment in Latvia during the 2008-2009 recession and afterwards. First, decomposition of the unemployment rate into structural and cyclical components illustrates the dominant role of the cyclical component. Second, direct estimation of mismatches also shows no evidence to support a structural explanation of the change in the Latvian unemployment rate. Finally, our estimates of the Beveridge curve during the period suggest that the efficiency of matching did not deteriorate during the recession and afterwards.
Accordingly, we conclude that in the course of the crisis not only did Latvia fall well below its long-term output trend, but Latvia is still operating below potential. This has implications for the assessment of Latvia’s internal devaluation policy. To put it in Blanchard’s (2012)[17] words: “Is it a success? The economic and social cost of adjustment has been substantial. Output further contracted by 16% in 2009, and is still 15% below its 2007 peak. Unemployment increased to more than 20% and still stands at 16% today, far higher than any reasonable estimate of the natural rate. Was there another, less costly, way of adjusting, through floating, and a slower fiscal consolidation? The truth is we shall never know”. The evidence presented here does not directly help to evaluate alternatives – still, it confirms that the chosen course was extremely costly and that today broader economic measures to support further recovery can be effective.
▪
References
- Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011
- Bernanke (2012), “Recent Developments in the Labor Market,” remarks to the National Association for Business Economics, March 26, 2012
- Blanchard (2012), “Lessons from Latvia”, June 2012
- Daly, Hobijn, Sahin, and Valletta (2012), “A Search and Matching Approach to Labor Markets: Did the Natural Rate of Unemployment Rise?,” Journal of Economic Perspectives 26(3), Summer 2012, pp. 3-26
- Daly, Hobijn, and Valletta (2011), “The Recent Evolution of the Natural Rate of Unemployment,” IZA Discussion Paper No. 5832, July 2011
- European Central Bank (2012), “Convergence report”, May 2012
- European Commission (2012), Autumn 2012 Forecast Exercise, Estimates of output gap and of potential output and their determinants, https://circabc.europa.eu, November 2012
- IMF (2012), “Republic of Latvia: First Post-Program Monitoring Discussions”, July 2012
- Krasnopjorovs (2012), “What is missing in Krugman’s structural unemployment story?”, blog on Bank of Latvia website, June 2012.
- Krugman, The Conscience of a Liberal, blog on New York Times, http://krugman.blogs.nytimes.com/?s=latvia
- Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012
- Ministry of Finance of Latvia (2012), “Convergence programme of the Republic of Latvia 2012-2015”, April 2012
- Petrongolo and Pissarides (2001), “Looking into the Black Box: A Survey of the Matching Function,” Journal of Economic Literature, 39(2), June 2001, pp. 390–431
- Pissarides (2000), Equilibrium Unemployment Theory (Second Ed.). Cambridge, MA: MIT Press
[1] Figure 1 uses data unadjusted for the results of the census carried out in Latvia in the first half of 2011 which showed that the population and the workforce was less than previously thought. This has implications for the calculation of all labour market statistics but the official statistics not yet been revised for years before 2011. Accordingly, for consistency over time, we use unadjusted data.
[2] Krasnopjorovs (2012), “What is missing in Krugman’s structural unemployment story?”, blog on Bank of Latvia website, June 2012
[3] Ministry of Finance of Latvia (2012), “Convergence programme of the Republic of Latvia 2012-2015”, April 2012
[4] European Central Bank (2012), “Convergence report”, May 2012
[5] European Commission (2012), Autumn 2012 Forecast Exercise, Estimates of output gap and of potential output and their determinants, November 2012
[6] IMF (2012), “Republic of Latvia: First Post-Program Monitoring Discussions,” July 2012
[7] Krugman, The Conscience of a Liberal, blog on New York Times
[8] Bernanke (2012), “Recent Developments in the Labor Market,” remarks to the National Association for Business Economics, March 26, 2012
[9] Daly, Hobijn, and Valletta (2011), “The Recent Evolution of the Natural Rate of Unemployment,” IZA Discussion Paper No. 5832, July 2011
[10] Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012
[11] Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012
[12] Here we use data on vacancies from the Central Statistical Bureau (data from enterprise surveys), since this data is more representative of the whole economy than the data on registered vacancies from the State Employment Agency. The latter is likely to be biased towards vacancies for low-qualified workers, as employers opt for different search methods for higher level positions. This is supported by the fact that, e.g. in 2012 vacancies for craft and related trades workers, plant and machine operators, and assemblers, as well as elementary occupations accounted for 50-60% of all vacancies registered with the State Employment Agency, while in the Statistical Bureau data these vacancies accounted for only about 20% of all vacancies.
[13] Pissarides (2000), Equilibrium Unemployment Theory (Second Ed.). Cambridge, MA: MIT Press
[14] Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011
[15] Petrongolo and Pissarides (2001), “Looking into the Black Box: A Survey of the Matching Function,” Journal of Economic Literature, 39(2), June 2001, pp. 390–431
[16] Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011
[17] Blanchard (2012), “Lessons from Latvia”, June 2012
Natural Resources, Intangible Capital and Sustainable Development in a Small, Oil-Rich Region
“Where scientific enquiry is stunted, the intellectual life of a nation dries up, which means the withering of many possibilities of future development.” – Albert Einstein, 1934 The rampant unemployment rates and the general contraction of economic activity in many western countries rekindled the fear of emigration and brain drain, which for a while seemed to be exclusively a developing-world problem. This brief illustrates a potential new approach to the issue, through a recent experience in a small but oil-rich region of Southern Italy.
Economic Growth and Brain Drain
Since the times of Solow, economic theory represents growth as the result of a process not unlike some sort of portfolio management. Just like any individual investor, countries own and need to manage certain assets, characterized by different properties and returns: some are exhaustible, others are renewable or living, and ensure a sustained stream of income. In the original formulations, the economy’s productive assets were identified in land, capital and labor, to which human capital was soon added. In 2006, the World Bank published estimates of 120 countries’ total wealth, in an attempt to introduce a broader view of what these assets really are [1]. The report classified a country’s capital into three main types: natural, produced (physical) and intangible. A striking pattern emerged. While the share of produced assets in total wealth is virtually constant across income groups of countries, the share of natural capital tends to fall with income, and the share of intangible capital rises. This means that rich countries are largely rich because of the skills of their populations and the quality of the institutions supporting economic activity.
There is an important relation between the different types of assets. In order to avoid illusory and temporary growth based on consuming the readily available natural capital, efficient management through saving and investment can transform one type of asset into another, achieving sustainability over time. Although this may sound as no big news, the analysis of the actual savings and rates of growth in the different form of capital reveals far from ideal situations all over the world. In many resource-rich developing countries, savings rates have been negative for many decades, meaning that resource rents have been at best used for consumption. In the worst cases, they have fueled corruption and private enrichment of small elites, as highlighted by the extensive literature on the “resource curse”.
Also, renewable natural resources are often exploited in an unsustainable fashion. One case in point is the thorny issue of fish stocks, but many more examples are discussed in the literature on ecosystem services. Even the intangible capital is under stress in many places. In the wording of the 2006 World Bank report, “intangible assets include the skills and know-how embodied in the labor force; social capital, that is, the trust among people in a society and their ability to work together for a common purpose; all those governance elements that boost the productivity of labor: an efficient judicial system, clear property rights, and an effective government.” Probably the first component in the list, what is traditionally indicated with the term human capital, is the most tangible, observable and relatively controllable part of it.
Controlling the Brain Drain?
Although there are many arguments in favor of international careers and general workforce mobility,[2] some regions experienced negative and prolonged net outflows – emigrants minus immigrants – to the extent that they now face a real risk of hold ups in their economic development. This, due to shortages of vitally needed high-skilled personnel. Even the economic sustainability of many basic services and businesses is in doubt due to the shrinking customer base.
Southern Italy is one of these regions. The net outflow of people with a bachelor or higher degree is negative[3] even at the national level, -2% over the latest ten years. In southern Italy, with a population of just above 13 million, the net balance of emigrants and immigrants over the same period amounts to -630,000. 70% of these people are aged between 15 and 34, and 25% hold at least a bachelor degree. To this figure, which is based on changes in official residence and therefore grossly underestimates the real size of the phenomenon, must be added the 150,000 that on average every year join the flow of internal migrants or long-distance commuters from the south to Northern Italy. Among these people, 47% are aged between 15 and 34, and almost 30% hold a bachelor or higher degree. The reason for these massive outflows can be identified in the labor market dynamics. If we break down the average 22% decline in job creation for youth between 2008 and 2011, new hires declined by 30% for youth with a bachelor degree and 14% for higher degrees, against 11% decline for youth with only secondary education.[4]
As opposed to physical capital, recent research shows that loss of human capital can have long lasting crippling consequences for economic growth (Waldinger, 2012). Among the policies that have been tried in order to stop or counterbalance the brain drain, a first set targets human capital as embodied in the workforce, i.e. tries to attract highly trained people. Probably the most popular are economic incentives in the form of tax rebates, higher wages or other job-related benefits and amenities. This kind of incentive regime exists in Italy since December 2010, though only targeting Italian nationals. However, for many high-skilled professionals, the important factors are others, such as a generally innovative and creative environment, a network with a critical mass, a transparent and competitive labor market not contaminated by politics, high quality support services, and other conditions that are not as easy and cheap to modify. Some countries have played the card of instead attracting prestigious foreign schools to their national territory to prevent their brilliant youth from leaving in the first place. Many famous western universities have already initiated partnerships with or lent their names to schools and universities in these countries and even built replicas of themselves – mostly in Asia – so as to get a toehold in the world’s largest education market, or in the Gulf States, where financial resources abound. There are successful examples of such partnerships in Italy, too.
A different approach has been taken by the new government, with the realization that the country can benefit from the pool of expatriated talents without moving them permanently back. A program of facilitation for visiting scholars and exchange students was thus launched in September 2012. But a step even further is actually possible. A network of scholars and high-skilled professionals that want to contribute to the development of a particular country or region, for example their place of origin, does not require physical presence on the territory, and not even any formal or institutional bond. The only needed ingredient is the Internet. Not removed from the environment and the conditions where they achieved success, these people can actually contribute even more. This is the idea behind, for example, Innovitalia.net and other smaller independent initiatives inspired by the concept of crowd-sourcing.[5]
The Experience of Basilicata
I recently witnessed (what I hope is) the birth of one such network in the region where I am from. Basilicata, also known as Lucania, is a small, poor region of less than 600,000 inhabitants scattered across 131 different municipalities on a territory of barely 10,000 squared kilometers, between the heel and the toe of the boot that the Italian peninsula resembles. Here, the crisis hit especially hard and migration outflows are since then even stronger, especially among youths. According to SVIMEZ (a think tank focused on entrepreneurship and economic activity in Southern Italy), Basilicata has lost 10% of its regional GDP since 2007, much more than the national average of -4.6%. Compared to other large European economies, Spain is currently at -2.7, while Germany and France, notwithstanding the low annual growth rates, are now back at the same level as in 2007. The youth employment rate (with the generous definition of 15-34) is alarmingly low at 30%, down by 15% since 2007, and only 24% for women. As a result, the consumption level of 27.5% of families is now below the poverty threshold, compared with 11% of families at the country level.[6]
Enter Europe’s largest onshore oil and gas reservoir; about 150,000 oil barrels are extracted in Basilicata every day, covering 12% of the national oil demand. The exploitation started in the late 1990s, although the reservoir has been known since at least the 1970s. It is expected that these oil fields will be operational until 2022, but at least one more reservoir with about the same estimated capacity remains unexploited. The regional government has for the time being blocked any new concession, hoping perhaps to negotiate better conditions. The truth is, there have been strong concerns – related to lack of transparency and in some cases to alleged corruption – voiced at the actual quantities of extracted oil and what is a fair distribution of revenues. After more than 10 years, it is hard to claim any major social impact of the project: there is a clear lack of funds to invest in local small and medium size businesses and, as observed above, unemployment in the area remains a problem while the regional population has plummeted.
Is this a case of “resource curse”? Not really. There is no clear evidence of corruption, or elite capture – the problem seems to be mostly poor management and a lack of ideas, mixed with the deeply rooted penchant of local politics for populism and the clientela system (patronage). To give an idea, creativity in using the oil money did not go much beyond the restoration of many of the small town’s pavements and facades. In 2009, in line with the so called “Development Action Plan” of the Berlusconi government, an 80 euro lump sum was distributed to all residents. After the crisis hit harder, the royalties have also been used to cover holes here and there in the current account. Data from the Ministry for Economic Development shows that capital investment in the region went down by 8.5% per year between 2008 and 2011, while current expenditure went up by 3%. Going back to the importance from the growth perspective of savings and investment versus consumption, it is worth remarking that current expenditure is (in most part) consumption.
Can this bounty instead become an answer to Basilicata’s troubles? This was the question driving the first Sustainable Development School, held at the end of October in Viggiano, a small town in the center of the oil field, hosting 23 oil wells. Sponsored by a number of institutions and associations, local or national,[7] the event attracted a group of 45 economists, sociologists, managers and entrepreneurs, engineers and culture sector specialists, in most part born in Basilicata and working or studying abroad. Seven of these participants were instead citizens of various countries in the Middle East and North Africa region, working or studying in Basilicata. This heterogeneous group worked together for two days on concrete proposals to be put on the administrator’s tables, in five main areas: Regional Economy in the new Euro-Mediterranean context, Energy and natural resources, Environmental protection, Infrastructure for environmental protection, Promotion of the historical, cultural and social heritage. Given the context, most projects focused on alternative proposals for how to use the royalties. The keyword was, however, sustainability. Everybody was well aware of the fact that for them to last longer than oil itself, these resources must be saved and earmarked to some productive use that, leveraging on other locally abundant resources, can start off a process of self-sustained development. The projects highlighted the stimulation of local small-scale entrepreneurship and the creation of employment opportunities as necessary ingredients for a fairer sharing of the revenues but most importantly for long-term sustainability.
Many local resources, not fully utilized at present, were brought in as examples: the abundant wood, the underexploited waterways, even the wastewater from bigger agricultural and animal farms, connected to the potential for small-scale generation of energy from renewable sources. On a slightly different note, the list continued with the historical and cultural heritage, natural beauty and the religious and culinary traditions that could support a much more developed tourism industry than what it does today. All of this, in the proposals of the participants, has the potential to support profitable businesses that bring employment to the community. This ingredient is considered crucial, in the perspective that the long-term survival of any (business) initiative requires tying its success to the welfare of the local communities. The focus was thus overwhelmingly on private initiative, with the public confined to the role of investing partner and provider of supportive infrastructure (material and immaterial) and services.
Overarching is undeniably the question of institutional quality, needed as the underlying canvas to support whatever initiative we hope to see blooming. A proposal that did not make it to the finals, though, involved the creation of a stable watchdog, either on local policies in general (and in particular on the use of the royalties) or more specifically focused on the environmental and health impact of the extractive activity. According to the more politically experienced participants, no administration would agree to finance an independent body with the explicit mandate to criticize them. Never mind that this type of institutions is common in other places. In Italy, the one body that currently operates with a watchdog function on the public administration, although limited to the financial aspect,[8] is facing threats of limitations of its powers. A lot remains to be learned. However, the perhaps most valuable outcome of this experience was, if not yet policy change at least a promising method to produce change, by mobilizing a latent ‘local’ resource and really transform oil rents in durable intangible capital.
References
- Where Is the Wealth of Nations? Measuring Capital for the 21st Century. Washington, DC: The World Bank, 2006
- The brain drain in Spain is mainly to Spain’s gain, The Economist, April 2012
- The Inclusive Wealth Report 2012, Cambridge University Press, 2012
- Rapporto sull’economia del Mezzogiorno, SVIMEZ, 2012
- Peer effects in science: evidence from the dismissal of scientists in Nazi Germany, Waldinger, F., The Review of Economic Studies, 2012
[1] Updates on these figures for a subset of 20 countries can be found in the newly released Inclusive Wealth Report 2012 , sponsored by a number of UN agencies, the first of what is intended to be an annual report looking at a broad measure of wealth. From the report: “Wealth is the social worth of an economy’s assets: reproducible capital; human capital; knowledge; natural capital; population; institutions; and time.”
[2] The Economist recently pointed out that “[w]hat some call “brain-drain” may in fact be a win-win situation for Europe’s economies. […I]n the short run, migration takes away pressure from budgets as the unemployed don’t claim benefits but move [abroad] instead. In the long run, there is a pool of highly skilled workers who have not fallen victim to hysteresis effects and can be re-activated for the [home] economy once the crisis is over.” However, it is not at all obvious that this migration is short-run, i.e. that these high-skilled workers will eventually go back. A survey of Italian scientists working aboard reveals, for instance, that the overwhelming majority excludes ever going back to Italy.
[3] The “import” of such people generally more than compensates the “export” in other big European countries.
[4] Source: SVIMEZ, 2012.
[5] A recent paper analyzing the experience of New Zealand (Davenport, 2040) reviews the waves of brain-drain response policies and calls this latest generation diaspora policies: “Diaspora policies are based on an assumption that many expatriates are not likely to return, at least in the short term, but represent a significant resource wherever they are located. This resource is not just embodied in the individual expatriate but also potentially includes their socio-professional networks. A key advantage of any diaspora option is that such connectivity initiatives do not require a large infrastructural investment in order to potentially mobilize this latent ‘national’ resource.”
[6] Source: ISTAT.
[7] Sponsors and partners included the municipal and regional administration, the Italian Institute for Asia and Mediterranean (ISIAMED) and its local branch, CeBasMed, the Val d’Agri National Park, the Regional Environmental Protection Agency, SVIMEZ and the University of Basilicata.
[8] The Corte dei Conti tribunal.
For Some Mothers More Than Others: How Children Matter for Labor Market Outcomes When Both Fertility and Female Employment Are Low
Authors: Krzysztof Karbownik and Michal Myck, CenEA.
Wide spread entry of women into the labor force has been one of the most pronounced socio-economic developments in the 20th century, and high levels of female employment are crucial from the point of view of continued economic growth and financial stability of many welfare systems (Galor and Weil, 1996). At the same time, demographic changes determined by the current and future fertility levels will play a vital role in shaping these developments and will affect the costs of social programs. Given the potentially strong link between female employment and family size, it seems that understanding the relationship between the two ought to be at the heart of policy discussions, especially in countries that are characterized by both low fertility and low female employment. In particular, in light of rising unemployment in low-fertility countries, which have been most severely affected by the economic crisis such as Greece, Spain and Latvia, our findings may serve as a guide with respect to the relationship between fertility and labor supply in an environment, which will be more common in Europe in the near future.
Becoming Entrepreneur in Belarus: Factors of Choice
This policy brief summarizes two papers by Maryia Akulava on entrepreneurship development in Belarus and outlines which factors affect the choice of becoming self-employed in Belarus. While one of the papers, “Choice of Becoming Self-Employed in Belarus: Impact of Monetary Gains”, focuses on the role of pecuniary benefits, the other paper, “Portrait of Belarusian Entrepreneur”, adopts a broader perspective by accounting for individual, sociological, and institutional factors.
Although the Belarusian government has repeatedly declared the importance of private entrepreneurship for the national economy, its role remains rather modest. In terms of private sector development, Belarus lags severely behind other post-socialist countries. Yet, over the last decade, some positive dynamics have been recorded. In particular, the number of small and medium enterprises (SMEs) per 1,000 people increased from 2.5 in 2003 to 7.2 in 2010. Still, this ratio is rather small in comparison with other post-socialist economies (Table 1) [3; 4; 5; 6].
Table 1. Number of Small Enterprises (SEs) per 1,000 People
| Number of SEs per 1000 people | |
| Belarus | 7.2 |
| Russia | 11.3 |
| Ukraine | 17 |
| Kazakhstan | 41 |
| United Kingdom | 46 |
| Germany | 37 |
| Italy | 68 |
| France | 35 |
| EU countries | 45 |
| United States | 74.2 |
| Japan | 49.6 |
Regarding the growth rates of SEs and individual entrepreneurs (IEs), the numbers leave much to be desired. Specifically, in 2009, the number of SMEs and IEs amounted to 62,700 and 216,000 respectively, while in 2011 – to 72.200 and 232,000. Therefore, despite the efforts of the authorities to encourage the development of private initiative, the number of SEs and IEs only increased by 15.2 and 7.4%, respectively.
Next, private sector employment remains rather low. It amounts to approximately 13%, while in the developed economies this figure varies between 60 and 70%. For instance, in the U.S., it amounts to 60%, in Germany and in France – around 65-70%, and in Japan – 85%. On the other hand, transition economies have smaller shares, including Russia – 17%, Kazakhstan – 20.6%, and Ukraine – up to 28.8%, [7].
Some important indicators are provided in Table 2 [8].
Table 2. Share of Small and Medium Business in Economic Indicators of Belarus
| Share of small sector | 2003 | 2008 | 2009 | 2010 |
| GDP | 8.2 | 11.2 | 11.4 | 12.4 |
| Volume of industrial production | 8.4 | 8.3 | 9.2 | 9.4 |
| Exports | 18.2 | 31.4 | 34.3 | 38.9 |
| Retail trade turnover | 9.2 | 27.8 | 29.5 | 28.2 |
| Economically active labor force | 13 | 13 | 13 | 13.1 |
Table 2 reveals an increased contribution of private entrepreneurs to the national economy. At the same time, the share of labor employed in the private sector remains unchanged at the level of 13%. This fact suggests that self-employment remains relatively unattractive for salaried workers.
So, what are the drivers of people’s choice? On the one hand, people might be reluctant to become entrepreneurs because of the prevailing social and cultural attitudes, or the lack of necessary experience. Post-socialist economies all share the legacy of planning and suppression of private initiative. On the other hand, government’s policies and regulations might ‘cool down’ enthusiasm or people simply have had or heard of some bad experiences. Thus, it is important to think of the reasons behind people’s choice and formulate policies to encourage entrepreneurship development in Belarus.
Who Is a Belarusian Entrepreneur?
In Belarus, entrepreneurs are active mainly in the non-manufacturing sector, including trade (30% of all entrepreneurs), provision of different services (16.5%), construction (13%), logistics (7%), and real estate (7%). The most common reasons to start your own business include a sudden, but attractive, business opportunity (66%), and the availability of funding for project implementation (33%).
As for the gender and age profiles of Belarusian entrepreneurs, 64% are men and 36% are women, with an average age of around 40-42 years. The majority of entrepreneurs is religious (54%), married (69%), and has children (75%). Around 65% have higher education, and about one third of them were among the top 10% students of their classes. Entrepreneurs report a good health status: 64% of them consider themselves as ‘healthy’. This is not surprising, given that entrepreneurship in Belarus is ‘survival for the fittest’. An entrepreneur has to be ready to take risks, be energetic, active and to continuously search for new business opportunities. Moreover, entrepreneurs are optimists, who evaluate themselves as successful (77%) and happy (81%) people.
Sociological characteristics reveal strong reliance on social networks. In general, the number of relatives or friends involved in the business activities is about two times larger than for salaried workers. Besides that, a much larger share of entrepreneurs consider their parents wealthy and successful (45% and 82%), compared with employees (34% and 37%, respectively).
Belarusian entrepreneurs stay in business because they like what they do (53%), and think that their work is important for society (29%). Profits and income remain a strong, but are not a decisive reason (25%).
Although entrepreneurs and employees do not differ substantially in terms of their attitudes towards family, friends, health, financial stability, religion, and so on, there is still a notable distinction. Specifically, entrepreneurs tend to praise work, power and influence over other people, and also like political freedom. In addition, they value their function of a service provider to other people.
Moreover, entrepreneurs have more trust to colleagues, other business people and subordinates than salaried workers. This is not surprising, given the importance of horizontal networks mentioned above. It is important to note that more than 30% of respondents expressed their trust to political authorities despite the government-induced difficulties for entrepreneurship development in Belarus.
Analysis of institutional infrastructure for doing business detects a negative relationship between a publicly-stated favorable attitude of authorities towards entrepreneurs and their decision to work in the private sector. This can be explained in following way: a priori, the government’s stance on entrepreneurship is evaluated positively, or at least considered as not harmful. Moreover, a person considers himself as being too small to attract the ‘extractive attention’ of the authorities. However, a posteriori, entrepreneurs revise their initial views. Their experience tells us that the government’s attitude is far from welcoming.
As for corruption, the attitude is ambiguous. On the one hand, entrepreneurs generally disfavor corruption. On the other hand, those who seek to expand their businesses consider corruption a way to avoid ‘unnecessary troubles’ and to overcome barriers created by the excessive ‘red tape’ in the economy.
What Are The Obstacles For Doing Private Business In Belarus?
Belarusian entrepreneurs consider the following factors as barriers to business development: (i) inflation and macroeconomic instability (55%), (ii) lack of financing (31%), (iii) high taxes (27%) and complexity of tax system (18%), (iv) legal vulnerability (23%), and (v) toughness of state administrative regulation inspections, licensing and certification requirements (19%). These barriers are largely of macroeconomic and regulatory nature. Moreover, authorities conduct a policy of close-to-full formal employment. This policy is aimed at securing jobs for people even at loss-making and poorly performing companies, which are kept afloat by subsidizes and directed loans. As a result, employees prefer to trade risks of working in the private sector, for a stable employment in the sector of state-owned enterprises.
As for the main barriers, which impede business start ups financial constraints are the most common factor (33%), followed by high risks (25%), the lack of necessary business skills, a clear understanding what to do in the market (15% and 13% respectively), and unwillingness to work a lot (16%). In other words, financial constrains along with the lack of business education are the two most important domestic barriers.
These findings correspond to the results of the research on the impact of pecuniary benefits on entrepreneurs. In that study, education does not appear to have a significant influence on the level of earnings by entrepreneurs. The latter are ‘self-trained’ by the experience of starting a business in the uncertain environment of the 1990s and matured in the course of doing their business in unfriendly conditions. However, as the economy evolves, activities and contracts become more sophisticated. To survive in the changing environment, entrepreneurs have to acquire new skills and learn new methods and concepts of doing business.
So far, it appears that the quality of education obtained by the entrepreneurs does not match the skills required in the Belarusian economy. Thus, it is important to organize seminars, to hold training and to run business education programs for the future and current entrepreneurs in order to upgrade their skills and thus to contribute to their improved performance on the market.
Conclusion
An efficient development of the private sector in Belarus requires a drastic improvement of the domestic business environment. In order to encourage domestic entrepreneurship, the authorities should improve macroeconomic management and cut much of the ‘red tape’. Entrepreneurship possesses a great potential to contribute to growth and development. Surveys reveal that government policies constrain the development of the domestic private sector. Moreover, the high tax burden should be reduced, and some fiscal ‘sweeteners’ could be offered for business startups. In addition, a somewhat higher priority should be given to the improvement of the quality of business education, and make it more accessible for the current and future business people. If implemented, all these measures would supposedly have a fostering impact on the development of a dynamic private sector in Belarus.
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References
Akulava M. 2012. “Choice of Becoming Self-Employed in Belarus: Impact of Monetary Gains”.
Akulava M. 2012. “Portrait of Belarusian Entrepreneur”. Work in progress.
Djankov S., Miguel E., Qian Y., Roland G. and Zhuravskaya E. 2005. “Who are Russia’s Entrepreneurs?” Journal of the European Economic Association, MIT Press. Volume 3 (2-3), 04/05.
Djankov S., Miguel E., Qian Y., Roland G. and Zhuravskaya E. 2006. “Entrepreneurship in China and Russia Compared” Journal of the European Economic Association, MIT Press. Volume 4 (2-3), 04/05.
http://netherlands.mfa.gov.by/_modules/_cfiles/files/sme_belarus_2011_1670.pdf
http://www.tambov-rosnou.ru/monograf/files/ind4.htm
http://www.erce.ru/internet-magazine/magazine/27/389/
http://www.mspbank.ru/files/documents/Ukraine.pdf
Sulakshin S. “State Economic Policy and Economic Doctrine of Russia. To Smart and Ethic Economy”. Т. II.
http://netherlands.mfa.gov.by/_modules/_cfiles/files/sme_belarus_2011_1670.pdf
Recent Dynamics of Returns to Education in Transition Countries
While, in an international comparison, transition countries spend a relatively large share of their GDP on education, and the population in transition countries is fairly highly educated, the returns to education in transition countries have been found to be relatively low, especially in comparison to other developing countries. In our paper, ‘Recent Dynamics of Returns to Education in Transition Countries’, we investigate whether the economic boom that transition countries experienced up to the 2008 financial crisis, increased the returns to education in these countries. Theories of skilled-biased technical change typically predict that periods of fast economic growth go together with an increase in the relative demand for skilled labor and hence an increase in the returns to education.
Using data from the 2007 wave of the International Social Survey Program (ISSP), the estimated return to an additional year of schooling in transition countries varied between a low 5.2 percent in Ukraine to a high of about 10 % in Poland (see Figure 1). Returns in transition countries were relatively low compared to developing countries in the ISSP sample, and on average not unlike OECD countries.
Figure 1. Returns to Education by Countries, 2007 Wave – Basic Specification
Note: Coefficients of the years of schooling variable in earning regressions. Dependent variables are monthly earnings. Specification includes: potential experience (linear and squared), dummy for gender. Source: Ukraine – ISSP 2008, all other countries – ISSP 2007.
The estimated dynamics in returns to education in the period 2002-2007 further suggest that the economic boom that took place in that period did not affect people with different amounts of education in different ways. Returns to education increased slightly in some transition countries and decreased slightly in others, but overall returns to education remained relatively moderate. More specifically, from table 2 we can see a decrease in returns in Bulgaria, Latvia and Poland, and an increase in the Czech Republic, Russia, Slovakia and Slovenia. Both increases and decreases are small in size however.
Table 1. Dynamics of Returns, Basic Specification
Note: Coefficients of the years of schooling variable in earning regressions with few controls as specified in the text.Source: Estimates for 1991-2002 are from Flabbi et al. (2008); estimates for 2007 and for Ukraine are by the authors.
A more detailed analysis for Ukraine using data from the Ukrainian Longitudinal Monitoring Survey, confirmed that economic growth did not have a major impact on the returns to education. The analysis for Ukraine however does suggest that, while in 2003 a secondary degree resulted in a somewhat higher wage, just having secondary education was no longer a differentiating factor in 2007.Moreover, only academic education made a difference, possibly because less and less people were paid very small wages (i.e. less than the official minimum wage).
The relatively limited importance of education for success on the labor market does not only show itself in the low estimated returns to education, it is also clear from the opinions people express about the factors that are important to get ahead. Table 3 gives the percentage of people who say a given factor is essential, important or fairly important to get ahead in a given country (based on the 2009 ISSP).
Table 2. To get ahead, it is essential, important or fairly important to
In most transition countries in the sample, most people think that hard work and ambition is the key to get ahead. Ukraine is no exception with hard work being thought to be essential, important or fairly important by about 94 percent of the respondents. Having a good education is thought to be at least fairly important by only about 73 percent of the respondents, with four other factors, besides hard work, scoring better on this criterion: having political connections, having ambition, having a wealthy family and knowing the right people. Also for the other transition countries in our sample, good education ranks only 5th, 6th or 7th.
Optimists could interpret these results as implying that at least education does not create the same social inequalities in the transition countries as it does in some other countries. Pessimists, on the other hand, who see education as an important driver of economic growth, will argue that low returns to education mean there is a low incentive for people to invest in education and that it is better to have education as a source of inequality rather than political or social connections, or having a wealth family.
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