Project: FREE policy brief
Liquidity and Monetary Policy in Belarus
High inflation and devaluation expectations after the 2011 currency crisis force Belarusian monetary authorities to seek non-conventional policy measures. Instead of using the refinancing rate as an instrument on the money and credit markets, the National Bank of Belarus resorts to liquidity squeezes, which drive up the rouble interbank rates. The banks have to raise deposit and loan rates in response. As a result, households continue to keep savings in the national currency deposits, while firms struggle to keep up with the payments. This situation, however, will have to end soon.
Belarusian economy is characterized by state ownership domination and various (including political) constraints. This often makes it tempting for the Belarusian authorities to resort to untraditional policy measures, or use the conventional policies in unexpected ways. A good example is Belarusian monetary policy in 2012-2013. In 2011 Belarus experienced a severe currency crisis: the exchange rate of the Belarusian rouble (BYR) crumbled from 3011 BYR per USD in January 2011 to 8470 BYR in December 2011. Prices followed the currency and doubled: in 2011 the inflation rate was 108%. Due to high government influence on the labor market and competition from the Russian labor market, real incomes quickly recuperated (Bornukova, 2012). But the owners of the deposits in Belarusian roubles took a hit – their savings lost almost a half of real value. More and more people converted their deposits into USD or other foreign currency. Inflation and devaluation expectations were soaring (Kruk, 2012).
The National Bank of Belarus clearly realized that the proper response would be to increase the interest rates: this policy measure would partially compensate the losses of rouble deposit holders, make rouble deposits attractive again and curb the growth in lending, one of the major causes of the currency crisis.
However, there is a catch. Formally, the main monetary instrument of the National bank is the refinancing rate. Yet, despite the name, this is not the rate at which the National bank is refinancing the commercial banks. Officially, it is only a “basis for setting interest rates on the operations involving liquidity provision to banks”. The problem is that most of the floating rates, especially those on concessional loans, have the refinancing rate as its basis rate. Very high refinancing rate would hurt debt-financed organizations, in particular in agriculture and construction. And the National bank found a compromise: the refinancing rate would remain relatively low; but the National bank would regulate the money market through liquidity squeezes: it would offer liquidity to the commercial banks only at a much higher collateral loan and overnight rates. The lack of liquidity due to a squeeze would drive up the interest rates on the interbank market.
Figure 1: Main interest rates in Belarus in 2012-2014
Source: The National Bank of the Republic of Belarus.
Figure 1 shows the main interest rates in Belarus in 2012-2014. The refinancing rate was steadily decreasing throughout the whole period. The overnight rate (which moves together with the collateral loan rate), also set by the National bank, for some period was almost two times higher than the refinancing rate, reaching 70 percent at its peak. The overnight rates mostly exceeded the rate set in the interbank market. The interbank rate reflects the market price of liquidity. The National bank influences this rate by offering (or not) liquidity to the state-owned commercial banks.
The National bank has successfully used liquidity squeezes as an instrument of stabilization on the currency market. As Figure 2 shows, the two major spikes in the interbank rate coincided with the higher rates of currency devaluation. The first major devaluation episode began in the autumn of 2012. At that time the market reacted to the increased lending and the news about the ban on the exports of “solvents”, which meant Belarus would have to pay back to Russia the customs duties on oil. On the other hand, the periods of high liquidity and low interbank rates were usually followed by devaluation episodes.
Figure 2: Changes in the exchange rate and the interbank rate, 2012-2014
Source: The National Bank of the Republic of Belarus.
In the summer 2013 devaluation speeded up once again, fueled by the potassium scandal. The National bank responded with lower liquidity and higher rates, which reached peak values of 50% and higher in September 2013.
Of course, this policy had other effects besides calming the currency market. As Figure 3 demonstrates, deposit and credit rates mainly reacted to the changes in the interbank rate, with peaks in the autumn of 2012 and summer-autumn of 2013. Enormously high deposit rates (often higher than 40 percent) delivered a hefty real rate of return given inflation of 22 percent in 2012 and 16 percent in 2013. Rouble deposits were growing throughout the period. But someone had to pay those rates.
Figure 3. Short-run deposit and loan rates for firms and individuals
Source: The National Bank of the Republic of Belarus.
High real rates became a burden for firms and households. The commercial banks had to stop many of their long-term individual lending programs (mainly those financing housing purchases). Instead, the banks put their efforts into the development and promotion of short-term consumer credit, which was virtually non-existent just a couple of years before. Many firms switched to cheaper loans in U.S. dollar, but the National bank quickly shut down these practices by introducing restrictions on foreign currency loans. Credit growth slowed down, and did not decline only due to the government-sponsored lending programs and a boom in consumer credit.
High loan rates together with the growing wages and low sales suffocated the firms. Average profitability across the country is declining since summer 2012, reaching the record low profit margin and negative aggregate net profits in December 2013 (see Figure 4). The lack of liquidity lead to the crisis of payments: accounts receivable and accounts payable on the 1st of February 2014 were 24.7 and 31.6 percent higher than a year before.
Figure 4. Average profit margin in Belarus, 2012-2014
Source: The National Statistical Committee of the Republic of Belarus
Today Belarus experiences high pressure for devaluation. The international currency reserves are depleted; the current account balance is in the red for a long time. The exporting enterprises quickly lose competitiveness due to low productivity. For the first time since 2009 GDP growth is virtually non-existent (and even negative in the first months of 2014). Some of the main trading partners – Russia, Ukraine and Kazakhstan – have already devaluated their currencies and face uncertain prospects for growth. It looks like the successful practice of fighting devaluation with liquidity squeezes at the cost of the real economy will have to end soon.
References
- Kateryna Bornukova, 2012. “Devaluation of 2011 and real incomes in Belarus (in Russian),” BEROC Policy Paper Series 9, Belarusian Economic Research and Outreach Center (BEROC).
- Dzmitry Kruk, 2012. “Inflation Expectations and Probable Trap for Macro Stabilization”, FREE policy brief, http://freepolicybriefs.org/2012/02/27/inflation-expectations-and-probable-trap-for-macro-stabilization/
- National Bank of the republic of Belarus, Statistics. http://nbrb.by/engl/
- The National Statistical Committee of the Republic of Belarus. http://belstat.gov.by/homep/en/main.html
The crisis in Ukraine and the Georgian economy
We analyze how the crisis in Ukraine will likely impact the Georgian economy and distinguish between short-run and long-run effects. We argue that the short-run effects are transmitted through trade and capital flows and that they are rather negative for Georgia and can hardly be bolstered. In the long-run, however, the crisis could improve the competitiveness of the Caucasus Transit Corridor, an important trading route between Europe and Central Asia Georgia participates in. We give recommendations how political decision makers could support such a development in the wake of an impairment of the northern Ukrainian transit routes.
Introduction
When Ukrainian President Victor Yanukovich decided not to sign the association agreement with the European Union and instead opted for a Russian package of long-term economic support, many Ukrainians perceived this not to be a purely economic decision. Rather, they feared this to be a renunciation of Western cultural and political values, and – to put it mildly – were not happy about this development.
The Russian political system, characterized by a prepotent president, constrained civil rights, and a government controlling important parts of the economy through its secret service, is not exactly the dream of young Ukrainians. Russia can offer economic carrots, but these do not count much against the soft power of Europe that comes in the form of political freedom, good governance, and economic development to the benefit of not just a small group of oligarchs.
Hence, it was all but surprising when many young Ukrainians took their anger about Yanukovich to the streets. After protests that lasted for nearly three months, President Yanukovich fled the country, a temporary government took over, and chaos broke out on the Crimean peninsula.
The dispute about the Crimea has the potential to impede the relations between Russia and the West for a long time to come, in particular if Russia enforces an annexation of the territory. Moreover, the tensions could quickly turn into a military conflict. The aircraft carrier USS George H.W. Bush was moved into an operational distance to the Crimea, accompanied by 20 smaller U.S. warships, and 12 additional fighter planes will be stationed in Poland. Yet even if there will be no direct confrontation between official Russian and U.S. forces, Ukraine could become the battleground of a proxy war, a kind of conflict that was common in the Cold War era. In this respect, one can already read the writing on the wall: the new Ukrainian government begs the U.S. for supplying arms and ammunition, and while the Obama administration is still reluctant to give in to such requests, the call is supported by hawkish U.S. congressmen who might finally prevail.
Ukraine is a country that is geographically close to Georgia and, like Georgia, has vital economic stakes in the Black Sea area. Georgia will not be unaffected by whatever happens in Kiev and Simferopol. In this policy brief, we will inform policy makers about the likely short-run and long-run economic consequences of the turmoil in Ukraine, discuss the challenges and opportunities that may arise, and derive some policy recommendations.
Short-run economic consequences
The crisis in Ukraine will almost instantaneously affect trade and capital flows between Georgia, Ukraine, and Russia. The effects will likely be negative and hit Georgia in a situation of economic recovery.
The Georgian real GDP growth rates were 6.3% in 2010, 7.2% in 2011, and 6.2% in 2012, and the real GDP per capita evolved from about 2,600 USD to about 3,500 USD in this time, but the upsurge discontinued in 2013 (if no other source is mentioned, figures presented in this policy brief (including those in the graphs) come from the Georgian statistical office GeoStat). ISET-PI, in its February 2014 report on the leading GDP indicators for Georgia, estimates the GDP in 2013 to be 2.6%, while GeoStat, the statistical office of Georgia, believes it to be 3.1%.
The unsatisfactory performance of the Georgian economy in 2013 was arguably caused by political uncertainties resulting from the government change that took place in late 2012, and as these uncertainties are largely overcome, most economists believe that Georgia will get back to its remarkable growth trajectory in 2014. The IMF, in its Economic Outlook, predicts a real GDP Growth of 6% in 2014, and the government of Georgia expects this number to be 5%. With an escalating crisis in Ukraine, it is questionable whether these rosy forecasts are still realistic.
Effects on imports
In 2013, Ukraine and Russia were the 3rd and the 4th largest importers to Georgia, respectively. Graph 1 shows the top five importers to Georgia, which together make up about 50% of total imports. The imports from Ukraine and Russia are mainly comprised of consumption goods: of all goods that were imported between 2009 and 2013 from Ukraine and Russia, about 30% were foodstuff. The ten main import goods in this time (in order of monetary volume) were cigarettes, sunflower oil, chocolate, bread, cakes, meat other than poultry, poultry, and sugar.
If the supply of these goods would be reduced through a breakdown of production and logistics, roadblocks, damaged infrastructure etc., the consequences for Georgia would not be utterly severe. From Ukraine and Russia, Georgia receives few goods that are (1) needed for investment projects and (2) cannot be produced domestically (an example of sophisticated investment goods that need to be imported would be ski lifts for tourism projects). Moreover, as Ukraine and Russia supply primarily standard goods that are produced almost everywhere, it is unlikely that a cutback in their imports would lead to sharp price rises in Georgia. Very quickly, increased imports from other countries would close any supply gaps. In addition, many imported consumption goods, like Ukrainian orange juice, are but luxury for ordinary Georgians, who buy their food in cheap domestic markets that sell almost exclusively local products.
Effects on exports
A small anecdote may illustrate the status of Georgian products in the Russian market. In the late 1940s and early 1950s, Stalin used to invite his comrades to his Kuntsevo dacha almost every night. At these occasions, he drank only semi-sweet Georgian red wine. His clique, usually preferring Russian vodka, adopted this habit out of fear to displease the dictator. Yet the real highlight of these nightly gatherings took place after midnight, when an opulent feast began, featuring all the delicacies of the Georgian cuisine. Through Stalin (and the fact that Georgia was a preferred destination of Soviet tourism), Georgian food obtained an excellent reputation in most countries of the former Soviet Union, and, to the dismay of Georgians, some younger Russians even do not know that Khinkali is not an originally Russian dish.
As can be seen in Graph 2, Russia and Ukraine are among the top 5 destinations for Georgian produce, together absorbing about 14% of total Georgian exports in 2013. In 2006, two Georgian products that are traditionally highly popular in Russia, namely wine and mineral water (the famous “Borjomi” brand), were banned from the Russian market. Yet in the wake of the diplomatic thaw that set in after the new government assumed power last year, this ban was lifted, and in 2013, the export of these goods regained momentum. In 2013, 68% of all wine exported from Georgia was sold in Russia and Ukraine (44 and 24 percentage points, respectively). In both countries, Georgian wines are sold at the higher end of the price range and are typically consumed by people with middle and high income. It is likely that these exports, in particular those to Ukraine, will be affected considerably by the crisis. This may happen through decreased demand for luxury foods and through a possible depreciation of the Ukrainian hryvna and the ruble vis-à-vis the Georgian lari.
Another sector that may be affected by the situation in Ukraine is the car re-export business. Georgia imports huge numbers of used cars from the U.S., Europe, and Japan, and passes them on to countries in the region. While this business hardly yields potential for real economic progress, it accounts for roughly 25% of Georgian exports! Of these 25%, about 7 percentage points go to Russia and Ukraine. Moreover, many cars are imported to Georgia on the land route from Europe through Ukraine and Russia (often driven by private, small-scale importers). If it will become more difficult to cross the border between Russia and Ukraine, this business, providing income to many low-skilled Georgians, may be at risk.
It should also be noted that Ukrainians and Russians make up an ever-increasing share of the tourists coming to Georgia (though the biggest group of tourists are Israelis). Also through this channel, an economic downturn in Ukraine and Russia will have unpleasant consequences for Georgia.
Effects on capital flows
According to the National Bank of Georgia, in 2013 a total of 801 mln USD was flowing in from Russia (see Graph 3). Ukraine contributed 45 mln USD to the money inflows, still significant for an economy as small as Georgia’s. An economic downturn in Russia and Ukraine would hit many Georgian citizens, often pensioners and elderly people, who depend on remittances of their children and other family members sent from these countries. This may aggravate a trend that already exists: in January 2014, money inflows decreased by 4% from Russia and by 5% from Ukraine (compared to January 2013).
Long-run economic consequences
Most of the economic dynamics Georgia experienced since 2003 was “catch up growth”. A country permeated by corruption, with a dysfunctional police and judicial system, without protection of property rights and contract enforcement, will grow almost automatically when the government restarts to fulfill its basic functions. Yet once this phase of returning to normal economic circumstances is over (Georgia probably is already in this situation), high growth rates can hardly be achieved without a strong export orientation of the economy, in particular when an economy is as small as Georgia’s. Most economists concerned with Georgia are therefore struggling to identify economic sectors where Georgia is in a good position to develop export potential. The National Competitiveness Report for Georgia, written in 2013 by the ISET Policy Institute on behalf of USAID, therefore extensively discusses the question what Georgia can deliver to the world. Though not related to export in a classical sense, the report points out that one of the advantages Georgia has is its geographical location, providing for possibilities to transform Georgia into a logistics hub.
There are three main routes to transport goods from Europe to the Central Asian countries (e.g. from Hamburg to Taraz in Kazakhstan). One route goes via the Baltic ports of Klaipeda or Riga, and then through Ukraine and Russia, and another route goes overland through Ukraine. A third one, the so called Caucasian Transit Corridor, has the Georgian port city of Poti and Turkey as its Western connection points, then goes through Georgia, Azerbaijan, and the Caspian Sea, and further east it splits up into a Kazakhstan and a Turkmenistan branch.
According to the Almaty based company Comprehensive Logistics Solutions, the fastest and cheapest route is the one through the Baltic ports. The transport from Hamburg to Taraz takes around 33 days and costs 6,220 USD per standard container. The overland transport via Ukraine takes around 34 days and costs 7,474 USD. Finally, transport through the CTC currently takes the longest time, namely around 40 days, and costs 6,896 USD.
Unlike many other economic activities, competition for transportation is more or less a zero-sum game played by nations. If transport through Ukraine and Russia will be restrained due to closed borders and political and economic instability, the total transport volume will not change substantially. Rather, instead of going through the northern routes, the goods will flow through the CTC. A similar development could be observed when the embargo against Iran was tightened and shipping goods through Iranian ports became increasingly difficult for Armenia and Azerbaijan. As a result, Azerbaijan, traditionally importing through Iran and exporting through Poti, now facilitates both its imports and exports through Poti.
This is a great chance for Georgia if it wants to become serious about transforming into a logistics hub. In our policy recommendations, we will speak about how to utilize on this opportunity.
Policy recommendations
Georgia can do little to bolster the short-run effects that are transmitted through the trade and capital flow channels. Political decision makers should be aware of problems that might arise for particularly vulnerable groups in the population, like pensioners who lose income in case remittances from Russia and Ukraine run dry, and help out with social support if necessary.
Regarding the long-run impact, Georgia should use this opportunity for gaining ground in the competition with northern transit routes. The Caucasus Transit Corridor can become much faster and cheaper if (a) a deepwater port and modern port facilities with warehouses will be built in Poti, (b) the road and train infrastructure will be improved, and (c) it will be easier to bring cargo over the Caspian Sea. Regarding the latter point, it would be important to assist Azerbaijan in improving the port management at Baku (in particular reducing corruption), and in reforming the monopolistic Azerbaijani State Caspian Sea Shipping Company.
Azerbaijan invests 775 mln USD into the Georgian part of the Baku-Tbilisi-Kars railway, proving their serious interest to upgrade CTC. Given this impressive commitment of Azerbaijan, Georgia should not stand back.
Conclusion
The crisis in Ukraine yields short-run risks and long-run opportunities for the Georgian economy. While there is little that can be done about the risks, the opportunities call for courageous steps to improve the Caucasus Transit Corridor. If the countries that hold stakes in the CTC are now further reducing the cost of transportation and make the route faster and more customer-friendly, the CTC may establish itself as the main trading route connecting Europe and Central Asia. Once critical investments have taken place, CTC’s advantage could be sustained beyond the current crisis. It is a competitive route that simply needs upgrading, which can happen now as a fallout of the conflict between Ukraine and Russia.
References
- Leading GDP Indicators for Georgia, The ISET Policy Institute, February 2014, http://www.iset-pi.ge/index.php?article_id=711
- The National Competitiveness Report for Georgia, The ISET Policy Institute, 2013, http://www.iset-pi.ge/index.php?article_id=713
- World Economic Outlook, The International Monetary Fund, October 2013, http://www.imf.org/external/pubs/ft/weo/2013/02/
Macroeconomic Performance and Preferences for Democracy
This policy brief summarizes the results of our research on factors influencing preferences for democracy in transition countries. The aim of this work was to detect which macroeconomic and individual factors impact the choice of supporting democracy. The results showed that the performance of the country, described by level of GDP, unemployment, level of corruption and economic growth, has a serious impact on an individual’s perception of democracy. At the same time, individual factors like education and age also influence people’s choice of support of democratic authorities.
Individual perception of democracy is a question that attracts the attention of policymakers. The macroeconomic instability that has been observed worldwide lately is likely to impact individual attitude toward democratic values and political institutions. The recent economic crisis brought a deterioration of the economic situation around the world and provided new challenges to cope with. It is likely that macroeconomic indicators have an impact on how a person perceives democracy. Literature studying similar questions has shown that GDP growth, unemployment and inflation all affect personal attitude to democratic institutions (Clarke et. al., 1994; Barro, 1999; Papaioannou and Siourounis, 2008). As for individual characteristics, the level of education is revealed by the literature as a very important factor in the context of the individual’s propensity of democracy approval.
The literature on the determinants of political support and attitudes to democracy was mostly focusing on exploring stable world economies with long-formed and steady-functioning democracies. We tried to look at a similar question in the context of transition economies, where democratic institutions are still under development.
We intend to estimate individuals’ propensity to favor democratic values. The specification of our econometric model was based on the literature addressing the same topic. The estimation procedure used probit econometric techniques, which allows for the calculation of the propensities of interest while taking into account the influence of both macroeconomic factors and individual characteristics. The paper used two sources of data: macroeconomic information was collected from the World Development Indicators of the World Bank, and individual-level cross-sectional data was obtained from Life in Transition Survey (LITS) 2010, which initially covered 38864 individuals from 35 countries. However, as the paper focuses on countries in transition, the final set only included individuals from 30 countries, most from Eastern Europe, Baltics and CIS, and excluded representatives of Western Europe. This data allowed for substantial data variation in the context of economic development vs. perception of democratic values (Graph 1).
Figure 1. Support of Democracy and GDP Per Capita
Source: WDI and LITS 2010
Inclusion of different macroeconomic variables together with individual factors allowed for an evaluation of their importance and level of impact on the perception of democratic values (Table 1). The results show that GDP per capita has a positive and significant effect on individuals’ perception of democratic values, which is in line with the literature claiming that standard of living in countries with not so high level of GDP is positively correlated with satisfaction with their life and the political system (Easterlin, 1995; Clark et al., 2008; Stevenson and Wolfers, 2008). Inflation rates are not significant and do not influence individuals’ attitude to democracy. On the other hand, economic growth is strictly positive and significant, and an increase of the economic growth rate raises propensity of democratic support by around 1.6 percentage points. The possible explanation here is that the growth rate of GDP works as a proxy of expectations for improvements of the standard of living in the future.
Table 1. Influence of Macroeconomic and Individual Factors on Perception of Democracy
Unemployment works as an indicator of a country‘s economic performance and has an expected negative sign in terms of individuals’ satisfaction with life and political institutions, which is also in line with the results in the literature (Di Tella et al., 2001; Wagner and Schneider, 2006). Impact of unemployment was tested using a cross product of unemployment and the Freedom House Index (this latter indicator shows the level of political and civil rights from 1 (most free) to 7 (least free)). The sign on this cross product is positive, which captures their mutual positive impact on the support for democracy. Thus, the higher the unemployment in a country with a low level of democratization is, the larger the probability of democratic support by individuals in these countries is. The indicator for the level of corruption in a country was also taken into account, via the Corruption Perception Index. This index ranks countries on a scale from 0 (highly corrupt) to 10 (effectively, corruption-free). The results show that the less corrupt a country is, the higher the propensity that an individual in that country will support democracy is. In fact, one additional point in the index increases the propensity of support by almost 4 percentage points. Military expenditures negatively affect the support of democratic values, and so does the existence of oil in the country. Here, military expenditures may be seen as a proxy for a less democratic regime, so that the leaders there have higher incentives to rule using suppressive measures with a support of military force in the country (Mulligan, Gil and Sala-i-Martin, 2004).
As for the individual factors, both secondary and higher education appear to be very important factors with a positive impact on the satisfaction with democracy. This finding follows the literature (Barro, 1999; Przeworski et al., 2000; Glaeser et al., 2004). In our results, people with secondary or higher education degree showed 10 and 18 percentage points higher propensity of support, respectively. Age also seem to matter: positive perception of democracy is specific to those aged 18-54, compared to the older generation, which goes in line with the explanation that senior citizens are more conservative than younger citizens. We also observe a negative significant coefficient on female gender, which may, perhaps, be related to women being more conservative than men.
Subjective relative income measure (answer to the question “to which income quintile do you think you belong to?”) has a positive impact on the support for democracy. Surprisingly, individuals from middle-income group have a more positive attitude than those who regard themselves as rich. Employment status is positively correlated with the support for democracy. Moreover, self-employment and employment in the public sector have a larger effect on the propensity of positive attitude to democratic values than employment in the private sector.
Divorced and widowed people expressed less support for democracy than single individuals, which might signal some dissatisfaction that impacts on personal attitude. Urban residency is positively correlated with the support of democracy. The same relationship is present for the risk tolerance of an individual. Finally, inclusion of a subjective measure of life satisfaction brought some changes to the general picture. It appeared that those who are satisfied with life strongly support the democratic values and such mentality raises the propensity of support by 7 percentage points. Moreover, inclusion of this variable makes the effect of being rich insignificant.
To sum up, the results showed that economic performance of the country described by various macroeconomic indicators has a serious impact on individual’s perception of democracy and, most probably, of other forms of government. At the same time individual factors also influence people’s satisfaction with the authorities. Thus, individual support of a political system is based on the results of performance of both the individual and the country.
References
- Barro R. 1999. “Determinants of Democracy.”Journal of Political Economy 107, #S6.
- Clark A. and Oswald A.J. 1994.“Unhappiness and Unemployment.”EconomicJournal104.
- Clark A., FrijtersP. and Shields M. 2008. “Relative Income,Happiness and Utility: An Explanation for the Easterlin Paradox and Other Puzzles.” Journal of Economic Literature46,# 1.
- DiTellaR., MacCulloch R.J., Oswald A.J. 2001. “Preferences over inflation and unemployment: Evidence from surveys of happiness.”American Economic Review91.
- Easterlin R. 1995. “Will Raising the Incomes of All Increase the Happiness of All?”Journal of Economic Behavior and Organization27, # 1.
- Glaeser E., La PortaR., Lopez-de-SilanesF. and ShleiferA. 2004.“Do Institutions Cause Growth?” Journal of Economic Growth.9, #3.
- Mulligan C.B., Gil R. and Sala-i-Martin X. 2004. “Do Democracies HaveDifferent Public Policies than Nondemocracies?” Journal of Economic Perspectives18, #1.
- Papaioannou, E. and Siourounis G. 2008.“Economic and Social Factors Drivingthe Third Wave of Democratization.” Journal of Comparative Economics36, #3.
- Prezworski A., Alvarez M., Cheibub J. and LimongiF. 1996. “WhatMakes Democracy Endure?” Journal of Democracy 7, #1.
- Stevenson, B. and Wolfers, J. 2008. “Economic Growth and SubjectiveWell-Being: Reassessing the Easterlin Paradox.” Brookings Papers on Economic Activity 1.
- Wagner A.F. andSchneider F. 2006. “Satisfaction with Democracy and the Environment in Western Europe: A Panel Analysis.” IZA Discussion Papers 1929, Institute for the Study of Labor (IZA).
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Charity of the Extremely Wealthy
Analyzing data from the Giving Pledge (a public pledge to give away at least half of one’s fortune during one’s lifetime, launched by Bill Gates and Warren Buffett in 2010) and the Forbes billionaires’ list, I find that self-made billionaires are substantially more likely to give away large amounts of money, than do billionaires who inherited their money. Policy makers in many emerging markets with ‘new’ billionaires thus better quickly modernize their charity laws.
In 2010, two billionaires Bill Gates and Warren Buffett launched the Giving Pledge, a public pledge to give away at least half of one’s fortune during one’s lifetime (http://givingpledge.org/), which by now has been signed by 114 people. 114 are not much, you might think, and you might want to add your own name to the list. But, unfortunately, not everybody is invited to make this pledge. Gates and Buffet focus only on the extremely wealthy people: 85 of the signatories of the pledge are among the 1426 billionaires identified by Forbes in 2013, and most of the others were on Forbes’ billionaire list in earlier years. Of these 1426, 135 billionaires come from Central and Eastern Europe or the Former Soviet Union (see table I)
Worldwide, about 6% of billionaires (85/1426) have made this pledge. Among the signatories is one Russian billionaire, Vladimir Putanin, and one Ukrainian billionaire, Victor Pinchuk, which makes Ukraine score above average, with one out of ten, or 10% of Ukrainian billionaires signing.
Table 1. Number of 2013 Forbes Billionaires from the Former Soviet Union|
# 2013 Forbes Billionaires |
# of Selfmade |
Giving Pledge |
Name of Signatory |
|
|
Russia |
110 |
110 |
1 |
Vladimir Potanin |
|
Ukraine |
10 |
10 |
1 |
Victor Pinchuk |
|
Kazakhstan |
5 |
4 |
0 |
|
|
Czech Republic |
4 |
4 |
0 |
|
|
Poland |
4 |
4 |
0 |
|
|
Romania |
1 |
1 |
0 |
|
|
Georgia |
1 |
1 |
0 |
In my most recent working paper, Claire Monteiro of Georgetown University and myself investigate whether it is possible to explain why these 6 % have signed, and the other 94% have not (yet) signed the Pledge. Or to put it in a more interesting way, why Putanin and Pinchuk signed but the other CEE/FSU oligarchs have not.
We investigate this question by analyzing whether generous billionaires have specific characteristics in common, characteristics that not so generous billionaires do not have. Doing this is possible because Forbes publishes not only a ranking of billionaires, it also provides background information about each billionaire like the billionaire’s education, age, how many children (s)he has and so on.
My analysis shows that three factors have a significant effect on the chance that a billionaire will be generous. First, a billionaire who is self-made is about three to four times more likely to sign than a billionaire who inherited his/her billion(s). This finding that how one earned one’s money affect how one spends this money is consistent with University of Chicago professor Richard Thaler’s ‘mental accounting’ theory and with earlier research showing that the propensity to consume is bigger if income received is framed as a bonus rather than if it is framed as a rebate, and the research showing that windfall gains (money won in a lottery) is more readily consumed than non-windfall gains (money for which one had to work). Note that all but one billionaire from the CEE/FSU are categorized by Forbes as self-made.
Second, billionaires with more money are more likely to sign the Giving Pledge and promise to give away half their fortune – for example, compared to an average billionaire who has about 4 billion dollar in estimated net worth (like Victor Pinchuk), a billionaire with an estimated net worth of about 15 billion dollars (like Vladimir Potanin) is roughly 50% more likely to promise to give away half of her/his fortune. Third, billionaires whose fortune comes from the technology/telecommunications industry are about twice as likely to announce that they will give away at least half of their fortune, compared to billionaires from other sectors.
The influence of other factors is small and less precisely estimated: older billionaires tend to be more likely to sign (possibly because being closer to the end of one’s life makes one think more about what one wants to leave behind), as do those who have more children (maybe because having more children makes it more likely that the inheritance will lead to fights among family members) or those having a Ph.D. Moreover, billionaires from the food and retail industry tend to be less likely to sign than those from the metallurgy industry.
Taken together my model predicts for Ukraine that Victor Pinchuk is the Ukrainian billionaire who is most likely to sign (4% probability), being 10 times more likely to sign than Yuriy Kosiuk (the Ukrainian billionaire who is least likely to sign with 0.4% probability). The difference in estimated net worth (3.8 billion versus 1.6 billion), age (52 versus 44), the number of children (4 versus 1) and education (Ph.D versus bachelor), and the sector in which they are active (metals and mining versus food and retail) explain this difference in probability. Victor Pinchuk is also about 30% more likely to sign than Rinat Akhmetov – while the latter has a higher estimated net worth (15.4 billion versus 3.8 billion), the effect of education (bachelor versus Ph.D), age (46 versus 52) and children (2 versus 4) play in favor of Victor Pinchuk, outweighing the wealth effect.
While it is definitely fun to do these kinds of computations, my research also has serious implications. The fact that inherited billionaires are much less charitable than the self-made billionaires means that academics should not assume that ‘all money is equal’ as they typically do – how you acquire money affects what you will do with it. It also implies that the countries from CEE/FSU with lots of ‘new’ wealth should modernize their charity laws quickly – once the self-made billionaires pass their wealth on to their children, it will become much more difficult to turn this massive wealth into charity.
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References
- Tom Coupé and Claire Monteiro, The Charity of the Extremely Wealthy, Kyiv School of Economics, Discussion Papers 51.
* A version of this policy brief has been published in Russian at Forbes.ua.
Putting the “I” Back in Team: The Rise of International Teams in Science
In this policy brief, I discuss the increasing prevalence of international teams in the production of scientific knowledge. I outline several potential factors that may explain these trends and discuss recent evidence from an original survey of coauthors on scientific papers regarding their collaboration behavior. Finally, as a notable example of increased international collaboration, I discuss the increase in scientific collaboration between Russia and the US after the end of the Cold War.
The Increase in Collaboration and Internationalization of Teams
Teams are becoming more prevalent in science. Both the share of papers produced by teams and the number of scientists working on scientific papers has increased in recent decades (Wuchty, Jones and Uzzi, 2007). Economic theory suggests that scientific research is becoming increasingly collaborative since the frontier of scientific knowledge has become more complex and specialized so that more researchers are needed to combine their expertise to make advances (Jones, 2009). Team members are also becoming more geographically dispersed: the share of papers resulting from international collaborations has increased, and within the US, scientists today are more likely to have coauthors located in a different city than before (Freeman, Ganguli and Murciano-Goroff, 2014).
These trends can be seen clearly in the graph below from the National Science Board’s Science and Engineering Indicators 2012. It shows the share of both world papers and US papers from 1990-2010 that are coauthored, coauthored with domestic coauthors only, and coauthored with at least one international coauthor. Collaboration in general and international collaboration have been increasing steadily since 1990 both in the world and in the US. However, for the US, the share of domestic-only collaborations has plateaued, while it is increasing in the rest of the world. In a recent Nature article, Adams (2013) shows that this trend similarly holds for other Western countries (United Kingdom, Germany, France, the Netherlands, Switzerland), while for emerging economies (China, India, South Korea, Brazil, Poland), domestic collaborations are also increasing.
Figure 1. World and US Trends in Scientific Collaboration, 1990-2010
Source: From National Science Board (2012)
Why has Science Become More International?
There are many potential reasons for the recent increases in international collaboration. An important factor has likely been the spread of the scientific workforce and R&D activities throughout the world (Freeman, 2010). The growing number of science and engineering PhDs in developing countries, some of whom are international students and post-docs returning to their home countries has expanded the supply of potential collaborators around the world (Scellato, Franzoni, and Stephan, 2012). Another factor is funding that has shifted scientific production towards international teams, as increased government and industry R&D spending in developing countries and grant policies by the European Union and other countries have supported international cooperation.
The lower cost of travel and communication in recent decades has also reduced the cost of collaborating with people in different locations. For example, Agrawal and Goldfarb (2008) show how the expansion of Bitnet, the precursor to the Internet, led to increased collaboration between institutions within the US. Finally, the location of scientific equipment and materials, such as the CERN Large Hadron Collider, telescopes, or climatological data available only in certain parts of the world, have increased international collaboration, and in some fields, has made international collaboration a necessity.
Survey Evidence on Scientific Collaborations
In a recent paper, my coauthors and I present the results of an original survey we conducted of scientists regarding collaboration (Freeman, Ganguli and Murciano-Goroff, 2014). In August 2012 we conducted a web-based survey of the corresponding authors of scientific papers with at least one US coauthor published in 2004, 2007, and 2010 in the fields of Nanotechnology, Biotechnology, and Particle Physics.
We customized each survey to ask the corresponding author about the collaboration and individual team members. The survey questions asked about how the team formed, how it communicated and interacted during the collaboration, the contribution of each coauthor, types of research funding, and the advantages and disadvantages of working with the team. We received 3,925 responses, so that our response rate was approximately 20%.
The survey also asked the respondent which country each coauthor was “primarily based in during the research and writing” of the article. This gives us a more accurate measure of whether teams are international than can be typically gleaned from publication data, which are based on author affiliations at the time of publication. Defining international teams from author affiliations alone can produce errors if affiliations change between the time the research was undertaken and the time of publication, or because some people have affiliations from more than one country.
Our analysis of the survey data uses the respondents’ information to define US collocated, US non-collocated and international teams. One of our key results is that face-to-face meetings continue to play an indispensible role in collaborations: most collaborators first met while working in the same institution. Teams also reported that while carrying out the research, they communicated often through face-to-face meetings, even with coauthors from distant locations.
Figure 2 below displays how the corresponding author responded about how they first met their team members. It shows that former colleagues play a very important role in the formation of international teams, followed by former students, conferences and institution visits, which equally contribute. The graph also shows the similarity between international teams and US non-collocated teams in how coauthors met. For other survey questions, our analysis also shows similarities between international teams and US non-collocated teams, suggesting that the salient issues are more about geography in general rather than necessarily about national borders.
Figure 2. How Coauthors First Met
Source: From Freeman, Ganguli and Murciano-Goroff (2014)
Another key finding from our survey is that the main reason for most collaborations, whether domestic or international, is to combine the specialized knowledge and skills of coauthors. We also asked the corresponding authors their views of the advantages and challenges of their collaboration. The most often cited advantage for all types of collaborations was “Complementing our knowledge, expertise and capabilities” and “learning from each other”. For the challenges, US non-collocated and international teams tended to agree more that there was “Insufficient time for communication”, “Problems coordinating with team members’ schedules”, and “Insufficient time to use a critical instrument, facility or infrastructure”, but international teams did not report these problems more often than US non-collocated teams. Where international teams differed is that these teams were the most likely to agree that their “research reached a wider audience”.
International Collaboration After the End of the USSR
A small but significant part of the increase in international collaboration since the 1990s can be attributed to the end of the Cold War. In “Russian-American Scientific Collaboration” (Ganguli, 2012), I examine trends in international collaboration by Russian and US scientists since the end of the USSR. Given the nature of the Cold War and restrictions on travel and communication with the West, I show that there was a dramatic increase in the number of publications with at least one Russian and a US coauthor from 1985 to 2005.
In addition to the lifting of travel and communication restrictions, there are several factors that contributed to the surge in collaborations between American and Russian scientists after the end of the USSR. First, at the level of the Russian government, there was a switch to a more open and collaborative approach to science. Part of this effort included establishing international centers for research in Russia aimed at integrating Russia into the global science community. Another important factor facilitating collaborations with Western researchers were foreign grant programs. The large increase in the emigration of Russian scientists in the 1990s to the West also contributed to international collaboration. After emigrating, many Russian scientists maintained close links to their colleagues in Russia, and coauthored papers with their former colleagues, which are counted as internationally coauthored publications.
While many of these factors have aided international cooperation after the end of the USSR, there have also been significant challenges that made cooperation difficult. Some of these challenges in the early 1990s included the political instability, organizational turnover making long-term funding agreements difficult to implement, difficulty transferring funds due to the underdeveloped banking system, high taxation and customs duties, lack of effective intellectual property rights, poor infrastructure, lack of a shared language (both linguistic and cultural), and external regulations (see further discussion in OECD, 1994). However, many of these challenges have now been overcome, leading to the continued increase in international collaboration between Russian and US scientists.
My analysis in Ganguli (2012) shows that the increase in Russian-American collaboration was more pronounced in some fields of science versus others, particularly in Physics. Figure 3 shows that the bulk of the articles published with Russian and American coauthors were Physics articles, with a sharp increase occurring immediately after 1991.
Figure 3. Russia-United States Publications By Field, 1985-2005
Source: From Ganguli (2012)
While some of the differences across the fields can be attributed to the number of scientists active in these fields, there are also other potential contributing factors. For example, it may be that there was greater emigration of scientists from certain fields abroad, and links between emigrants and those who remained in Russia persisted. Graham and Dezhina (2008: 24) suggest that over 50 percent of emigrants were physicists and mathematicians. Another reason may be that international collaboration was more important in some fields due to the knowledge or resources needed to conduct research during the economic crisis of the 1990s. As Wagner Brahmakulam, Peterson, Staheli, and Wong (2002) point out, physics research received significant amounts of US government funding for international collaboration, partly because expensive equipment that is needed and through collaboration, countries could share costs. Also, physicists from many countries often meet and work together at international research centers like CERN. Moreover, in some fields, the US and Russian governments shared priorities in funding international cooperation, like biomedical and health sciences, energy, physics, while there were gaps in some areas where Russia devoted resources and the US did not, like chemistry (Wagner et al. 2002: 24). Graham and Dezhina (2008: 141) also discuss how Western colleagues benefited from working with Russians especially in fields like zoology, botany and the earth sciences, since the Russian colleagues provided access to data from unique regions not available previously.
Support for International Teams?
This policy brief has discussed some reasons for the increase in international scientific collaboration and related empirical evidence, including insights from collaboration after the end of the USSR. The growth in collaboration and the geographic dispersion of teams is likely to continue; the frontier of scientific knowledge will become more complex and specialized, so that an even greater numbers of researchers will be needed to combine their expertise, and they are likely to be spread across increasingly distant locations.
These trends raise many complex issues for policymakers. For some countries, international collaboration may be the only way to sustain the science sector as the frontier of knowledge becomes more complex and resource-intensive. For some, international collaborations may increase the emigration of home-grown talent to wealthier countries. To what extent international collaboration should be supported, and how, will be important policy questions going forward. Typically, funding for international projects has been the main policy lever, and the Russian experience suggests that grant programs did play a critical role in that case. As our survey evidence in Freeman, Ganguli and Murciano-Goroff (2014) suggests, face-to-face meetings are especially important in forming and sustaining international collaborations. Thus, funding mechanisms that include provisions for research stays and face-to-face meetings may be the most effective means for fostering international collaborations.
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References
- Adams, J. (2013). “Collaborations: The Fourth Age of Research.” Nature, 497(7451), 557-560.
- Agrawal A, Goldfarb A (2008). “Restructuring Research: Communication Costs and the
- Democratization of University Innovation,” American Economic Review, 98(4):1578-1590.
- Freeman, Richard B. (2010). “Globalization of Scientific And Engineering Talent: International Mobility of Students, Workers, and Ideas and The World Economy.” Economics Of Innovation And New Technology, Volume 19, issue 5, 201 pp. 393-406.
- Freeman, Richard B., Ina Ganguli and Raviv Murciano-Goroff (2014). “Why and Wherefore of Increased Scientific Collaboration,” NBER Working Paper No. 19819, Issued in January 2014.
- Ganguli, Ina (2012). “Russian-American Scientific Collaboration” in Y.P. Tretyakov (ed), Russian-Аmerican Links: Leaps Forward and Backward in Academic Cooperation. St. Petersburg, Russia: Nestor-Historia, pp. 120-135.
- Graham, Loren and Irina Dezhina (2008). Science in the New Russia: Crisis, Aid, Reform. Bloomington and Indianapolis: Indiana University Press, 2008.
- Jones, Ben (2009). “The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is
- Innovation Getting Harder?” Review of Economic Studies, 76:283-317.
- National Science Board (2012). Science and Engineering Indicators 2012. Arlington VA: National Science Foundation (NSB 12-01).
- National Science Board (2006). Science and Engineering Indicators 2006. Arlington VA: National Science Foundation (NSB 06-01).
- OECD (1994). Science, Technology, and Innovation Policies. Federation of Russia. Paris: Organisation for Economic Co-operation and Development, 1994.
- Scellato, G., Franzoni, C., & Stephan, P. (2012). “Mobile Scientists and International Networks,” NBER Working Paper 18613.
- Wagner, Caroline, Irene Brahmakulam, D.J. Peterson, Linda Staheli, and Anny
- Wong (2002). U.S. Government Funding for Science and Technology Cooperation with Russia.
- Santa Monica, CA: RAND Corporation, 2002.
- Wuchty, S., Jones, B. F., & Uzzi, B. (2007). “The Increasing Dominance Of Teams In Production Of Knowledge.” Science, 316(5827), 1036-1039.
Academic Inbreeding in Ukraine
In Ukraine, having a university degree only provides a noisy signal of one’s productivity, which means social ties and personal relations play a relatively more important role in the Ukrainian economy in general. Therefore it should not come as a surprise that inbreeding is very common in Ukrainian academia; for example, about 50% of faculty obtained their university degree from the university that employs them. Given the absence of clear “quality signs” for fresh university graduates, inbreeding can be viewed as a second-best option for hiring decisions. Our econometric analysis shows that inbred faculty does not differ in its (observable) quality from non-inbred faculty. At the same time, ceteris paribus, inbred faculty has somewhat lower salaries. We also find that the extent of inbreeding is slightly higher in universities with a “national” status and lower in very small universities (of less than 1000 students).
Academic inbreeding is the practice of universities hiring their own graduates to academic positions. Inbred faculty is thus faculty employed at the same university from which they graduated. Inbreeding implies a low level of competition for faculty vacancies possibly resulting in low quality hires. However, inbred faculty can be cheaper, reduce the chance of a mismatch between university and faculty member, and can be better “tailored” to the needs of a certain university or discipline. For some specific narrow disciplines inbreeding can be the only way to hire faculty (for example, if only one university in a region provides courses in a certain discipline, teachers of that discipline most probably will be inbred). In research, inbreeding can help to pass on tacit knowledge but it can also prevent “fresh blood” and new ideas from entering into the university. In developed countries, universities usually try to limit inbreeding in order to first, “disseminate” their graduates and earn a good reputation, and second, hire the best graduates on the market through an open competition. In less developed countries, inbreeding is more common because of the higher role of personal relations in hiring decisions in general.
Although very widespread, academic inbreeding in Ukraine has received little or no attention from researchers or policy makers. Data on inbred faculty is similarly scarce. There is only one recent exception – in the summer of 2013, the Centre for Social Research surveyed about 400 university professors. The survey contains information on a wide range of aspects of faculty employment, such as working hours, publications, participation in conferences, income size etc., including the question on whether a person works at the same university from which (s)he graduated. We used this data to do an econometric analysis of the factors that determine inbreeding and the impact of inbreeding. We complemented the survey data by data from an online questionnaire we distributed among KSE graduates whom we know work in academia, their acquaintances and among the network of KSE partners who work in academia (a total of 59 responses).
Causes of Inbreeding
Besides providing a person with knowledge and skills necessary for a white-collar job, education has several other functions. One of them is signaling, i.e. people who successfully graduate from an educational institution should have higher abilities (ceteris paribus) than those with lower grades or dropouts. This function of education is almost entirely lost in Ukraine because of widespread corruption. In Ukraine, good students can obtain good skills and knowledge together with good grades. However, “bad” students can obtain the same grades for money: besides paying professors for exam grades, students can buy a course paper, a diploma thesis and even a doctoral dissertation. Cheating and plagiarism are also very widespread; not only in students’ work, but also in academic research. Hence, based on the diploma alone, a potential employer will have difficulties telling apart a “good” student from a “bad” one. Therefore, other screening mechanisms are relatively important in Ukraine.
Many private-sector employers, for example, will pay more attention to previous work experience and personal recommendations than formal education. For example, the ULMS-2007 survey shows that from 48% to 68% of people found a job through relatives or friends, which is comparable to the extent of inbreeding found by this study in academics (48.6% in the CSR-2013 survey, 68% in our online survey). This situation pushes students, who do not expect to be hired by relatives or friends, to find a full-time job already in the first or second year of studies, providing them with both incentives and funds to “buy” a diploma. This creates a “vicious circle” – the low value of a diploma makes employers looking at previous work experience, and the need to gain that experience further devalues diplomas.
For universities, “previous work experience” is the student’s performance during their studies. Hence, by inbreeding their own students, universities reduce uncertainty, which they would be facing if they looked for needed candidates on an open market. As the academic career of a person develops, (s)he can develop additional signals of his/her “quality”; first of all, scientific degrees (Candidate of Sciences, Doctor of Sciences) and/or ranks (Docent or Professor) and connected to them publications in Ukrainian and foreign journals (with the last ones being much more valuable). Therefore, as we show, younger and less distinguished faculty (with shorter teaching experience and without a Doctor degree or Professor rank) is more likely to work at a university from which they graduated.
Estimation Results
Our econometric estimation showed that the extent of inbreeding does not depend on the quality of a university as measured by its rank in Ukraine. Inbreeding is less common in very small universities (of less than 1000 students), and is independent of the university size after this threshold. Universities with a “national” status have slightly higher level of inbreeding.
We also show that inbred faculty does not differ in “quality” (measured as the number of publications in Ukrainian and foreign journals and the probability to get a foreign fellowship) from other faculty, although, ceteris paribus, inbred faculty do get lower salaries.
Results from both the CSR-2013 survey and our online questionnaire indicate that personal connections are very important both for entering a university and for further promotion. Usually an academic career starts when a person begins his/her Ph.D. studies; at the same time, (s)he starts working as an assistant or a lecturer (when admitting students to Ph.D. studies, universities prefer their own MA graduates). To move up the career ladder, a person should earn scientific degrees or ranks, have certain duration of teaching experience and a minimal required number of publications (all the formal requirements for certain academic positions are stipulated in a Decree of the Cabinet of Ministers). According to the law, currently there is no tenure system, and faculty is hired with one- three- or five-year contracts (the longest contracts can last up to seven years, but only in the universities with a “national” status).
Hiring Procedures at Universities
When a vacancy is open (e.g. a contract expires), a university should make an announcement in a pedagogical journal and/or on its website; then candidates should be interviewed at a chair meeting, and a selected candidate should be approved by the faculty dean. A candidate should have a required teaching experience and publications. There are about 1500 journals on the list of Higher Attestation Commission (the body that organizes the dissertations defense), which means that practically all universities issue at least one journal, and very few of them are refereed. This means that publishing in the home university’s journal is the cheapest and easiest way for a faculty member to get the needed number of publications. Therefore, publications are very often of very poor quality and do not contain any real research, especially in social sciences. To mitigate this problem, the Ministry of Education and Science introduced a new requirement for scientific degrees – since 2013, 20% of publications should be in foreign-refereed journals.
When hiring, all formal requirements and procedures are typically observed – a competition is announced, the chair meeting held, the candidate has the required duration of work experience and the number of publications (their quality is discussed above). However, in reality there is very often just one candidate “for” whom the vacancy is opened, and outside people, even if they apply for a vacancy, are ignored. Usually a chair meeting supports the opinion of a chair head, but either way, a dean could overturn a chair meeting decision, so despite seemingly open procedures, in reality a person’s employment depends on his/her relations with a chair head and/or a faculty dean. Studying at a university is the most common but not the only way to establish these relations. A person can get acquainted with a chair head or a faculty dean at a conference, be his/her relative or friend, or be recommended by his/her relative or friend.
Such a widespread reliance on personal connections is a legacy from the Soviet times when personal ties replaced market mechanisms, and students were allocated to their first workplaces rather than hired on a competitive basis. Since universities were situated in cities, staying at a university implied a better living environment, and salaries were also good. Therefore many students tried to stay at their alma mater by establishing good relations with a chair head or a faculty dean. Nowadays, university salaries are not competitive so students staying at universities are not necessarily the best ones. However, they are not the worst ones either because otherwise they would not be offered a position.
Concluding Remarks
In Ukraine, academic inbreeding provides universities with a relatively cheap and well-prepared workforce. On the other hand, it also fosters isolation of universities and conservation of existing “traditions” – whether good or bad. Given low academic mobility of both students and professors, this situation prevents dissemination of knowledge and lowers competition, which necessarily leads to degradation.
Currently, inbreeding is not on the agenda of either researchers or policy makers. In fact, no one seems to have considered it as a problem. Perhaps, it will not be discussed as a problem any time soon because there are many other “bigger” problems in Ukrainian higher education. To name a few, these are:
- high centralization and insufficient level of university autonomy;
- low salaries and high teaching workload of professors;
- low extent of university research and very low quality of the existing research, especially in humanities and social sciences;
- high corruption and low standards of studying and research work (ubiquitous cheating and plagiarism);
- low sensitivity of educational programs to the needs of modern economy.
Perhaps, introduction of formal limits on inbreeding (setting a quota for both MA graduates admitted to Ph.D. programs and for Ph.D. graduates hired to teaching positions at the same university) could bring some “fresh air” into the system. This measure would extend the pool of candidates available to a university and introduce an element of competition between them. It would also create incentives both for universities to improve their Ph.D. programs and for students to put greater effort into studies.
References
- Bilyk, Olga and Iuliia Sheron (2012) Do Informal Networks Matter in the Ukrainian Labor Market? EERC Working paper No 12/11E.
- Coupe, Tom and Hanna Vakhitova (2010). Recent Dynamics of Returns to Education in Transition Countries, KSE/KEI Working paper.
- Osipian, Ararat (2009). Corruption and Reform in Higher Education in Ukraine, Canadian and International Education, vol. 38, pp. 104-122.
- Shaw, Marta, Chapman, David and Nataliya Rumyantseva (2011). The Impact of the Bologna Process on Academic Staff in Ukraine, Higher Education Management, vol. 23, pp. 71–91.
- Stephens, Jason, Romakin, Volodymyr and Mariya Yukhymenko (2010). Academic Motivation and Misconduct in Two Cultures: A Comparative Analysis of US and Ukrainian Undergraduates, International Journal for Educational Integrity, vol. 6, pp. 47–60.
Increasing Resources for Families with Children Through the Tax System: Recent Reform Proposals from Poland
This brief discusses the consequences of a recent reform proposal that aims to redistribute resources to low-income families with children through the income tax system in Poland. The proposed reform replaces the current child tax credit with additional amounts of the universal tax credit, and by changing the sequence in which tax deductions are accounted for, it increases resources of low-income families with children by about 1.7 billion PLN per year (0.4 billion EUR). The brief examines four possible ways of additional tax system modifications that would make the reform package neutral for the public finances, and presents distributional implications of the reforms.
The level and structure of financial support for families with children has become an important policy focus in Poland; a country that faces high levels of child poverty and one of the lowest fertility rates in Europe (Immervoll et al., 2001; Haan and Wrohlich, 2011; Eurostat, 2013). In this brief, we outline recent tax reform proposals that aim to increase financial support for low-income families with children through the tax system. A range of such potential reforms has been examined in Myck et al. (2013b); a report prepared for the Chancellery of the President of the Republic of Poland. One of the options became the key element of the President’s family support program Better climate for families proposed in May 2013. Below we discuss its main features and various options for financing the proposals.
The proposed modification of financial support for families would replace the current child tax credit with additional amounts of the universal tax credit conditional on the number of children, and increase tax advantages for families by changing the sequence in which tax credits are accounted for in a way that is favorable for families with children (Chancellery of the President of Poland, 2013). The main beneficiaries of this reform would be low-income families with children whose income is too low to take full advantage of the current child-related advantages. The overall cost of the reform would amount to about 1.7 billion PLN (0.4 billion EUR). In the final section of the brief we discuss potential ways of making the reform budget neutral.
The analysis has been conducted using CenEA’s micro-simulation model SIMPL on reweighted and indexed data from the 2010 Household Budget Survey (HBS) collected annually by the Polish Central Statistical Office (see Morawski and Myck, 2010, 2011; Myck, 2009; Domitrz et al., 2013; Creedy, 2004).
Financial Support for Polish Families in 2013
In Poland, financial support for families with children depends on the level of family income and the demographic structure of the household. The system consists of two main elements – family benefits on the one hand, and tax preferences for families with children on the other. Following Myck et al. (2013a), we define financial support for a family j (FSFj) as the sum of family benefits received by the family (FBj), and tax preferences that families with children collect in the PIT system is defined as the difference in the level of tax liabilities and health insurance contributions paid by the family (PITHIjD0 – PITHIjDn) supposing they have no children (D0) and on condition them having n number of dependent children (Dn):
FSFj = FBj + (PITHIjD0 – PITHIjDn) [1]
Figure 1a presents the current level of the financial support for single-earner married couples and Figure 1b presents the same for single parents with one and three children in relation to the level of gross earnings.
Family benefits
Family benefits, which include family allowance with supplements, childbirth allowance and nursing benefits, are means-tested and related to the number and age of dependent children in the family and specific family circumstances. Family benefits are granted only to low-income families and are subject to point withdrawal once the family crosses the income eligibility threshold (539 PLN of net income per person). For example, the stylized married couples in Figure 1 lose family benefits when their monthly gross income exceeds 2,060 PLN if they have one child and 3,435 PLN if they have three children (for single parents these thresholds equal 785 PLN and 1,825 PLN respectively).
Figure 1. Monthly level of financial support received by families with one and three children dependent on their age and family gross income in 2013 (PLN/month) (a) Married couple with one spouse working b) Single parent working
Note: FB – family benefits; CTC – child tax credit; joint taxation preferences: UTC – additional amount of universal tax credit; IB – shift of tax income bracket. In case of the single parent alimonies from the absent parent are assumed at the median value from 2010 data, which is 410.50 PLN for 1 child and 724.67 PLN for 3 children. Gross income of the single parent includes income from work only. Alimonies are taken into account for FB income means testing. Source: Myck et al. (2013a).
Tax preferences
Taxpayers with children can deduct a non-refundable child tax credit (CTC) from the accrued tax, with the maximum values of the CTC related to the level of universal tax credit available to all tax payers (UTC is 46.37 PLN per month). For each of the first two children in the family, taxpayers can deduct up to two values of the UTC (92.67 PLN per month), for the third child up to three values (139.00 PLN per month) and for the fourth and following children up to four values of the UTC (185.34 PLN per month). The CTC is not available for high-income parents with one child (whose annual taxable income exceeds 112,000 PLN per year).
Further tax advantages are available for single parents through joint taxation, which translates into substantial gains in particular for high-income parents. As Figure 1 shows, single parents whose gross income exceeds the second tax income bracket (15,745 PLN per month) gain up to 1,044.19 PLN per month if they have one child and 1,368.54 PLN if they have three children. With the same income levels, the system grants nothing to married couples if they have one child and 324.34 PLN if they have three.
In the current system, the CTC can be deducted from the accrued tax only after the full amount of UTC and the tax-deductible part of health insurance (HI) contributions have been exhausted. As a consequence, there is a large group of low-income families whose income is too low to take full advantage of the CTC. As Figure 2 illustrates, the higher the number of children is in a family, the lower is the proportion of families who take full advantage of the credit. Although the percentage of those using the full CTC is 76.1% for families with one child, it decreases to 67.6% for those with two children and is as little as 30.8% for families with three or more kids. Over 40% of the latter use only half of the CTC they are entitled to.
Figure 2. Use of maximum amount of CTC by number of children
Recent Reform Proposals
In a recent report for the Chancellery of the President of Poland, we have analyzed several options for the reform of the family-related elements of the tax system (Myck et al., 2013b). One of these has become the key element of the presidential reform proposal (Chancellery of the President of Poland, 2013). The reform assumes that the CTC is replaced with the amounts of the Universal Tax Credit conditional on the number of children in the family in such a way as to maintain the current maximum advantages offered to families through the CTC system. The main purpose of the reform is to reverse the tax deduction sequence so that tax advantages related to having children are deducted from the accrued tax before considering credits related to health insurance contributions. Such construction would enable low-income families to make greater use of child-related tax advantages, while leaving the situation of higher-income families unchanged.
Figure 3. Monthly tax advantages from the reform among families with 1-4 children (PLN/month) 
Figure 3 presents monthly levels of tax advantages resulting from the proposed reform conditional on the number of children in the family and the level of gross income. We note that families with children gain from the reform if their income exceeds 735 PLN per month. Tax advantages resulting from the proposed modifications are exhausted at different levels of gross income depending on the number of children (from 2,630 PLN for families with one child to 8,010 PLN for those with four children). The higher the number of children is, the greater is also the potential maximum gain – for example, families with four children and income of 4,010 PLN per month would gain up to 311.35 PLN per month.
The results of the analysis show that, overall, 2 million households with children would benefit from this reform (below referred to as System 1). The total annual change in households’ disposable income (equivalent to the total cost for public finances) would amount to 1.69 billion PLN (see Table 1 below).
Table 1. Average annual change in households’ disposable income by number of children in Systems 1-5 (billion PLN)|
No children |
1 child |
2 children |
3+ children |
Total |
|
| System 1 |
0,00 |
0,39 |
0,60 |
0,70 |
1,69 |
| System 2 |
-0,45 |
-0,20 |
0,04 |
0,55 |
-0,08 |
| System 3 |
-0,65 |
-0,09 |
0,17 |
0,59 |
0,02 |
| System 4 |
-0,66 |
-0,15 |
0,23 |
0,59 |
0,01 |
| System 5 |
-0,86 |
-0,04 |
0,31 |
0,63 |
0,04 |
Table 1 shows that most of the resources would be beneficial for families with three or more children (0.7 billion PLN per year), while families with one or two children would benefit about 0.39 billion PLN and 0.6 billion PLN per year, respectively.
The distribution of total income gains by income deciles is presented in Figure 4. The gains are clearly focused in the lower part of the income distribution. For example, families with children in the second income decile would receive a total of 0.4 billion PLN, while those in the bottom and third decile would recieve approximately 0.25 billion PLN. Only 0.04 billion PLN of the total cost would be distributed to families in the top income decile.
Figure 4. Distribution of total annual gains in households’ disposable income by deciles: Systems 1-5 (billion PLN) 
Potential Ways of Financing the Reform
Concerns about the state of public finances naturally imply questions related to the potential ways of financing any additional tax giveaways. Myck et al. (2013b) presents four alternative modifications of the tax system that make the entire package of reforms neutral for the public finances. These are:
- System 2 – CTC reform + limitations on joint-taxation preferences for married couples (both with or without children) and single parents;
- System 3 – CTC reform + reduction of tax income threshold from 85,528 to 68,000 PLN per year;
- System 4 – CTC reform + reduction of tax revenue costs from 1,335 to 475 PLN per year;
- System 5 – CTC reform + reduction of tax-deductible part of health insurance from 7.75% to 7.45%.
The overall total outcomes of these proposals for household disposable income are illustrated in Table 1 and Figure 4. The implications in terms of the redistribution of the packages – with losses among childless households and gains among those with children – are clear under all of the proposed packages, although all of the reform combinations imply small losses also for families with one child. Total disposable income of childless households falls by 0.45 PLN per year under System 2 and by as much as 0.86 billion PLN under System 5. By shifting the majority of the costs to households without children, the latter is simultaneously the most generous for families with children since income of those with two children grows on average by 0.31 billion per year, while of those with more children see a growth of 0.63 billion PLN per year.
Figure 4 illustrates that in all of the revenue neutral reform packages, the households from the highest two deciles are the biggest losers. That the financing of the shift of resources to low-income families falls on households from the top income decile is particularly evident in the case of Systems 2 and 3 where total disposal income for these households fall by 1.64 billion PLN and 1.52 billion PLN, respectively. Since changes to revenue costs and deduction of HI contributions apply to almost all taxpayers, Systems 4 and 5 are less favorable for households from the lower deciles and generate losses for the upper part of the income distribution. However, a large part of cost is also born by households from the tenth decile (0.26 and 0.39 billion PLN, respectively).
While the combinations of tax changes presented above would be neutral with respect to the current system of taxes in Poland, it is worth noting that the policy of tax increases through the tax-parameter freezing implemented in 2009 has increased taxes by far more than the cost of the Presidential reform proposal. As we showed in Myck et al. (2013c), this policy increased taxes by 3.71 billions PLN per year, of which 2.21 billions was paid by families with children. The recent proposal could thus be thought of as a way of redistributing these resources back to families with children.
Conclusions
Financial support for families with children is an important element of government policy with implications for child poverty, labor-market participation among parents, as well as fertility (Immervoll et al., 2001; Haan and Wrohlich, 2011). In this brief, we outlined the results of a recent analysis of direct financial consequences of modifications in the Polish system of support for families through the tax system with the focus on a reform proposal presented by the Polish President in the program Better climate for families. The reform would benefit lower-income families with children at the cost of about 1.7 billion PLN. As a result, annual income of the families from the three bottom deciles would grow by 0.93 billion PLN. A high proportion of the gains (0.7 billion PLN) would go to families with three or more children.
We also presented four additional modifications of the tax system that would make the CTC reform revenue neutral. Reform packages that withdraw joint-taxation preferences and decrease the threshold of the income tax to a higher rate would be most effective in ensuring redistribution of support for low-income households. It is worth noting though, that the recent approach of the Polish government to the tax system has implied substantial increases in the level of income taxes through the freezing of income tax parameters, and these alone would be more than sufficient to finance the proposed tax changes.
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References
- Creedy J. (2004). Reweighting Household Surveys for Tax Microsimulation Modelling: An Application to the New Zealand Household Economic Survey. Australian Journal of Labour Economics 7 (1): 71-88. Centre for Labour Market Research.
- Domitrz A., Morawski L., Myck M., Semeniuk A. (2013). Dystrybucyjny wpływ reform podatkowo-świadczeniowych wprowadzonych w latach 2006-2011 (Distributional effect of tax and benefit reforms introduced from 2006-2011). CenEA MR01/12; Bank i Kredyt 03/2013.
- Chancellery of the President of Poland (2013). Dobry klimat dla rodziny. Program polityki rodzinnej Prezydenta RP. (Better climate for families. Family support program of the Polish President.)
- Eurostat online database 2013 – epp.eurostat.ec.europa.eu. Date of access: 28.11.2013.
- Haan P., Wrohlich K. (2011) Can Child Care Encourage Employment and Fertility? Evidence from a Structural Model. Labour Economics 18 (4), pp. 498-512.
- Immervoll H., Sutherland H., de Vos K. (2001). Reducing child poverty in the European Union: the role of child benefits. In: Vleminckx K. and Smeeding T.M. (eds.) Child well-being, Child poverty and Child Policy in Modern Nations. What do we know? The Policy Press: Bristol.
- Morawski L., Myck M. (2010).‘Klin’-ing up: Effects of Polish Tax Reforms on Those In and on Those Out. Labour Economics 17(3): 556-566.
- Morawski L., Myck M. (2011). Distributional Effects of the Child Tax Credits in Poland and Its Potential Reform. Ekonomista 6: 815-830.
- Myck M. (2009). Analizy polskiego systemu podatkowo-zasiłkowego z wykorzystaniem modelu mikrosymulacyjnego SIMPL (Analysis of the Polish tax-benefit system using microsimulation model SIMPL). Problemy Polityki Społecznej 11: 86-107.
- Myck M., Kundera M., Oczkowska M. (2013a). Finansowe wsparcie rodzin z dziećmi w Polsce w 2013 roku (Financial support for families with children in Poland in 2013). CenEA MR01/13.
- Myck M., Kundera M., Oczkowska M. (2013b). Finansowe wsparcie rodzin z dziećmi w Polsce: przykłady modyfikacji w systemie podatkowym (Financial support for families with children in Poland: examples of modifications in the tax system). CenEA MR02/13.
- Myck M., Kundera M., Najsztub. M, Oczkowska M. (2013c). Ponowne „mrożenie” PIT w kontekście zmian podatkowych od 2009 roku (PIT freezing in the context of tax reforms since 2009). Komentarze CenEA: 06.11.2013.
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* This brief draws on recent research at the Centre for Economic Analysis in the projects financed by the Chancellery of the President of the Republic of Poland and the Batory Foundation (project no: 22078). The analysis has been conducted using CenEA’s micro-simulation model SIMPL based on the 2010 Household Budget Survey data collected annually by the Polish Central Statistical Office (CSO). The CSO takes no responsibility for the conclusions resulting from the analysis. Any views presented in this brief are of the authors’ and not of the Centre for Economic Analysis, which has no official policy stance.
Can Public Enforcement of Competition Policy Increase Distortions in the Economy?
Authors: Vasiliki Bageri, University of Athens, Yannis Katsoulacos, Univeristy of Athens, and Giancarlo Spagnolo, SITE.
Competition law has recently been introduced in a large number of developed and emerging economies. Most of these countries adopted the common practice of basing antitrust fines on affected commerce rather than on collusive profits, and in some countries caps on fines have been introduced based on total firm sales rather than on affected commerce. Based on recent research, this policy brief explains how a number of large distortions are connected to these policies, which may facilitate competition authorities in their everyday job but at the high risk of harming the consumer and distorting industrial development. We conclude by discussing the possibility to depart from these distortive rules-of-thumb opened by recent advancements in data availability and econometric techniques, as well as by the considerable experience matured in estimating collusive profits when calculating damages in private antitrust litigation.
Competition policy has become a prominent policy in many developing economies, from Brazil to India. Indeed, the available evidence suggests that in countries where law enforcement institutions are sufficiently effective, a well designed and enforced competition policy can significantly improve total and labor productivity growth.
It is already well known that the private enforcement of competition policy can give rise to large distortions: since competition law is enforced by Judges and not by economist, it is easy for firms to strategically use the possibility to sue under the provision of competition law to protect their market position rather than the law being used to protect competition.
It is somewhat less known that a poor public enforcement of Competition Law by publicly funded competition authorities can also end up worsening market distortions rather than curing them. In the reminder of this policy brief we explain why, according to recent research, a mild and suboptimal enforcement of antitrust provisions – in the sense of fines that are too low to deter unlawful conduct (horizontal agreements and cartels in particular) and fines which are based on firm revenue rather than on the extra profits generated by the unlawful conduct, could significantly harm social welfare, even if we abstract from the direct cost the public enforcement of competition law imply for society.
Current Practice in Setting Fines
A very important tool for the effective enforcement of Competition Law is the penalties imposed on violators by regulators and courts. In this policy brief, we uncover a number of distortions that current penalty policies generate, we explain how their size is affected by market characteristics such as the elasticity of demand, and quantify them based on market data.
In contrast to what economic theory predicts, in most jurisdictions, Competition Authorities (CAs), but also courts where in charge, use rules-of-thumbs to set penalties that – although well established in legal tradition and in sentencing guidelines and possibly easy to apply – are hard to justify and interpret in logical economic terms. Thus, antitrust penalties are based on affected commerce rather than on collusive profits, and caps on penalties are often introduced based on total firm sales rather than on affected commerce.
A First Well Known Distortion Due to Legal Practice
A first and obvious distortive effect of penalty caps linked to total (worldwide) firm revenue is that specialized firms which are active mostly in their core market expect lower penalties than more diversified firms that are also active in several other markets than the relevant one. This distortion – why for God’s sake should diversified firms active on many markets face higher penalties than more narrowly focused firms? – could in principle induce firms that are at risk of antitrust legal action to inefficiently under-diversify or split their business to reduce their legal liability.
In a recent paper published in the Economic Journal, we examine two other, less obvious, distortions that occur when the volume of affected commerce is used as a base to calculate antitrust penalties.
A Second Distortion: Poorly Enforced Competition Law May Increase Welfare Losses from Monopoly Power
If expected penalties are not sufficient to deter the cartel, which seems to be the norm given the number of cartels that CAs continue to discover, penalties based on revenue rather than on collusive profits induce firms to increase cartel prices above the monopoly level that they would have set if penalties were based on collusive profits. Intuitively, this would be done in order to reduce revenues and thus the penalty. However, this exacerbates the harm caused by the cartel relative to a monopolized situation with similar penalties related to profits, or even relative to a situation with no penalties due to the distortive effects of the higher price and, in comparison to a situation with no penalties, the presence of antitrust enforcement costs.
A Third Distortion: Firms at the Bottom of the Value Chain May Pay a Multiple of the Fine Paid by Firms at the Top for an Identical Infringement
Firms with a high revenue/profit ratio, e.g. firms at the end of a vertical production chain, expect larger penalties relative to the same collusive profits that firms with a lower revenue/profit ratio would get. Our empirically based simulations suggest that the welfare losses produced by these distortions can be very large, and that they may generate penalties differing by over a factor of 20 for firms that instead should have faced the same penalty.
Note that this third distortion takes place also when at least for some industries fines are sufficiently high to deter cartels. This distortion means that competition is only enforced in industries that happen to be in the lower end of the production chain, and not in industries where the lack of competition is producing larger social costs. Note also that our estimation is based only on observed fines, i.e. on fines paid by cartels that are not deterred. Since cartels tend to be deterred by higher fines, this suggest that if we could take into account the fines that would have been paid by those cartels that were deterred (if any), the size of the estimated distortion would likely increase!
Concluding remarks
We argue that if one wants to implement a policy, one must be ready to do it well otherwise it may be better to not do it at all. This is particularly relevant for countries with weaker institutional environments where it is likely that political and institutional constraints will not allow for a sufficiently independent and forceful enforcement of the Competition Law.
It is worth noting that – in particular in the US but also increasingly so in the EU – the rules-of-thumb discussed above do not produce any saving in enforcement costs because the prescribed cap on fines requires courts to calculate firms’ collusive profits anyway. Furthermore, the distortions we identified are not substitutes where either one or the other is present. Instead, they are all simultaneously present and add to one another in terms of poor enforcement.
Where there are sufficient resources to allow for a proper implementation and where enforcement of Competition Law is available, developments in economics and econometrics make it possible to estimate illegal profits from antitrust infringements with reasonable precision, as regularly done to assess damages. It is time to change these distortive rules-of-thumb that make revenue so central for calculating penalties, if the only thing the distortions give us is savings in the costs of data collection and illegal profit estimation.
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Managed Competition in Health Insurance Systems in Central and Eastern Europe
This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.
A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).
This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.
The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.
Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia
At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).
The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).
However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).
In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).
Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions) 
This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.
Data and Results
In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model. The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).
The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).
Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).
Table 1. Factors leading to decreased infant and under-five mortality in Russia
Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.
To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)
In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.
Discussion
The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.
In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.
Summary and Policy Implications
The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.
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References
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- Baranov IN, Sklyar TM. 2009. Problemy strakhovoi modeli zdravookhraneniya na primere Moskwy i Sankt-Peterburga (Problems of insurance model in health care: the example of Moscow and Saint Petersburg). In X International Conference on the Problems of Development of Economy and Society, Yasin E.G (ed), Moscow: Higher School of Economics, vol.2.
- Besstremyannaya GE. 2013. Razvitie systemy obyazatelnogo meditsinskogo strakhovaniya v Rossijskoi Federatsii (Development of the Mandatory Health Insurance system in the Russian Federation) Federalizm 3: 201-212
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- Culyer AJ (2005) The Dictionary of Health Economics, Edward Elgar.
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Some More Reflections on RCTs
In preparation of next year’s elections, the Swedish government chose recently to replace the Minister for International Development Cooperation. During her long mandate, former Minister Gunilla Carlsson championed the importance of aid evaluation and result focus, and managed to move aid from a quiet consensus to become a hotly debated topic. She also closed down the aid evaluation agency SADEV, following the publication of critical reviews about the work of the agency. Now, an expert group is in charge of rethinking and redesigning development policy evaluation and planning. One of the tools under consideration is randomized control trials (RCTs). This is an area in which Swedish development cooperation has no previous experience. Here are some reflections on RCTs.
In recent years, the methods of development economics have been crucially altered by the introduction of randomized control trials (RCTs). The idea behind RCTs is that development policies can be evaluated similarly to clinical trials in medicine, where subjects are randomly assigned to receive a treatment or to function as a reference or control group. The main benefit of this approach is that the random assignment allows for an estimation of the effect of the treatment (that is, the policy in question), while avoiding unobservable confounding factors or selection issues (see more about the advantages of the method in Banerjee et al. (2008)).
The diffusion of experimental methods in development economics has undoubtedly been a revolution in the academic and, if not yet fully, in the policy world. In the blogosphere there has even been talk of awarding Sveriges Riksbank’s Prize in Economic Sciences in Memory of Alfred Nobel, informally called the Nobel Prize of Economics, to the MIT couple Banerjee – Duflo. Due to their young age and the closeness in time of their contribution, this would be a ”shock” prize meant to give a strong signal. Their creation, the Abdul Latif Jameel Poverty Action Lab (J-PAL), stands for a new approach to both scientific and policy work in development that is a fantastic contribution, and definitely has the connotation of seminal.
However, it might be too early for the profession to sanction a method that has much good to show for, but also potentially undesired consequences. In the camp of critics there are heavy weights such as Angus Deaton and Dani Rodrik of Princeton, and the World Bank’s Philip Keefer and Martin Ravallion. The core of their position is of course not to deny the merits of RCTs, but to advocate their use in the right way and, in particular, as one tool among many others, with important complementarities to the others.
Some points in this context are often made, well understood and widely accepted: the limits of the approach per se, in particular the problem of external validity (the question of how generally applicable are the findings from such studies); the conflict between short-run and long-run implications, especially with respect to some policy areas (support to institution-building among others), and the incentives of policy actors. Another brief in this series by Anders Olofsgård spells out these points very clearly and references to further readings for those interested.
One aspect I find to be missing in the debate is a reflection on what impact this new method has on the three main actors involved, namely the researchers and practitioners in development and their way of working, and the people living in the countries and regions where these studies take place. This will therefore be the focus of this brief.
The Impact on the Scholarly Profession
The creation of experimental infrastructures and the popularity of the RCT methodology have rubbed off on the rest of the empirical practice in development economics and beyond, with ever-increasing demands and expectations on the econometric identification of new studies. However, when it comes to what is possibly the main weakness of RCTs as compared to most observational studies, namely external validity, the corresponding demands and expectations on how this is dealt with seem to fall behind. As pointed out in Rodrik (2008), it is enough to compare the number of pages spent on describing the identification in an average observational study to that on external validity in an average RCT-based paper. If the purpose is to learn “what works in development”, as opposed to “what worked once for a set of 25 primary schools in Uttar Pradesh faced with high drop out rates” [1], it is natural to expect the researcher that really wants to serve this purpose to provide for a desired generality of her findings. With no generality, the findings may be of limited practical use to politicians and practitioners who need to choose a policy tool or make a decision in conditions, which are likely to differ from the exact setting of the study.
During a recent presentation by one of the most active and prominent RCT researchers, the researcher clearly stated at some point that: “[t]his intervention was never thought for scaling up as a policy.” That made me pause. But what is the purpose, then? In my meaning, these studies should fit into a “bigger-picture” understanding, or at least hypothesizing on how development works, what the binding constraints and open challenges are, what might contribute to overcoming them, and how do we proceed from there. Once some candidates are identified, RCTs might, depending on the setting, be used to evaluate and compare before and after the preferred policy is implemented. Unfortunately, this attitude is far from common, beyond what has become the standard of the ‘Introduction paragraphs’.
Quite often RCT studies are extremely precise and accurate on “the impact of X on Y”, even in cases of very small effects, and can be perhaps a bit vague or face bigger uncertainties on the ‘bigger’ question. This means that many, more general (and very relevant) questions are not addressed by development economists just because a RCT is not feasible. An example mentioned in a recent keynote lecture by David Laitin is the BetterBirth Project. This is a WHO program that seems to be making a big difference for infant and maternal health in India’s poorest states through a list of 29 easy, low-cost, low-technology and well-known practices. The main lesson drawn by observers at the Harvard School of Public Health is that people follow the list more accordingly when it is spread through ”human contact”. No mass media advertisement campaign, no punishment or incentive schemes, just ”nice” people visiting, explaining, and demonstrating the list, while – in the words of an interviewed nurse – ”smiling a lot”. At first sight, this seems like something that could be randomized. However, the treatment is so diffuse and fuzzy that the practical implementation would be very challenging. If it is the case that the person meeting the clinics’ personnel and spreading the information has to be somewhat of a mentor in order for the transition to happen, to be kind and pedagogic, repeat the visits indefinitely to make sure that the practices have been adopted, and do whatever else it takes to make them learn, this is very hard to observe with precision. To simply define X as ”presentation of the list in person”, to be compared to, for example, the ”diffusion of the list through an information campaign” would probably run the risk of severely underestimating the impact. This would be because it would bundle together different types of informers and different levels of human interaction. This means that there would be a high risk of zero or insignificant results from such a study. A RCT would need to be complemented by other investigations, for example surveys, in order to find out if there really was an effect and how it came about. All of the above is likely to undermine the publication chances for an academic paper on the issue, thereby discouraging development scholars to study this program.
There are two main ways of augmenting the RCT methodology in the direction of generalizability and external validity: the elbow-grease approach of replication and the resuscitation of the concern for theoretical mechanisms. Replication studies are not very appealing in the perspective of a scholar that aspires academic publications. Besides completely new clever designs that establish a link of causation in a specific case – and possibly for each of these corresponding studies that establishes the absence of such a link in different settings – journals have little interest in publishing more variations on the same theme. Replications with small variations should instead be highly attractive for development institutions and practitioners, precisely for the reason, mentioned above, that they want to learn about effectiveness of alternative strategies in as many different specific contexts as possible. [2] In an ideal world, development institutions and aid bureaucracies would work in close cooperation with universities and academic institutions, involving young researchers before their career-concern-stress phase (perhaps Ph. D. students?) in the design and evaluation of as many of their planned interventions as possible. Moreover, in an ideal world this would be enough reward for the young researchers. This wealth of replications would then favor the possibility of “taking stock” and really learning about some general truth. I do not, however, have a good recipe for making this happen.
Luckily, some scholars are in the meanwhile working on making the pendulum swing back from the purest empiricism to the involvement with theory. Here is a list of possibilities that are important to reflect about, starting from a given RCT:
– The macro problem. How does the found effect compare to the “bigger issue”, the one that most likely set the scene in the ‘Introduction paragraph’ of the study? Few studies go back to this point, after presenting their results. Numerical simulations or structural estimation of theoretical models might help answering this question. (See some examples in Buera et al. (2011) and Kaboski et al. (2011)).
– The alternative hypothesis. What is the particular intervention compared against? If the set of circumstances or policy-relevant parameters that might be varied are too big or too dense for replications, maybe a theoretical model can help to vary them in a smooth and continuous way?
– The strategic reaction. How are the involved economic agents likely to respond in case of an expansion in space, time or both, of the intervention? How would they have responded in the absence of the intervention?
The Impact on Development Practices
As stated above, RCTs may be a powerful tool for the learning and decision-making in development institutions, public or private. However, this assumes a seldom-questioned willingness to learn and change practices on their part. Brigham et al. (2013) show, through a RCT, that these organizations might be subject to confirmation bias. Brigham et al. sent out an invitation to microfinance institutions, offering partnership to evaluate their programs, randomly accompanying it with a survey of previous studies finding positive impact of microcredit, or a survey of studies finding no impact. The second treatment elicited barely half as many responses as the first one, which suggests that at least this type of organizations might not be so interested in learning whether what they do is effective or can be improved. Coupled with the mentioned publication bias, this might skew the distribution of reported, published and established findings even further.
The Impact on the Local Context
Individual studies can of course be affected by the so-called Hawthorne effect or experimenter effect. The phenomenon, by which the act of being experimented upon changes a subject’s behavior, was first observed and got its name in the 1920s in industrial psychology. Although it is clearly hard to establish, it has for decades been a central criticism of the ”participant observation” methodology in anthropology and ethnography. Also behavioral economists, that more recently started using experiments both in labs and in the field, are explicitly careful about it.
Depending on the definition of causality that the researcher has in mind, the fact that having knowledge about being treated impacts outcomes, might not be an issue at all for the measurement of the overall effect of an intervention. The overall effect should include also the (optimal) reaction of the agents (for example a change in behavior, the adoption of other complementary inputs, etc.) and this is actually considered one of the advantages of the method. However, this raises problems for the interpretation of the size of the effect and the analysis of the channels that bring it about. This point is made very clearly by Bulte et al. (2012), who compare a double-blind RCT with a regular one. If all or most of the effect simply comes from the participants knowing to be ”treated” and reacting to it, is the effect still going to be there when the intervention becomes a regular policy? The majority of both authors and critics mostly ignore this important question.
Beyond the perspective of a single study, a different concern comes to mind when considering how a substantial number of RCT studies are clustered geographically. The map below shows a snapshot of the J-PAL interventions in Africa and Asia, which are only a fraction, albeit substantial, of the total.
Figure 1. J-PAL Interventions in Africa and Asia
Reading study after study set in Kenya, or some Indian state, I wonder if people there are starting to get used to private organizations going around giving away assets, or used to temporary local government programs with funky benefit schemes. To my knowledge, no study has yet reflected upon the aggregate impact of experiments and randomized interventions in an area that has many. Might it be the case that exposure to many conditions eventually results in ”experimental fatigue”, or practice effects, which may influence the results of the studies and make the interpretation of the findings difficult?
Even more worrisome, given the frequency of and the resources involved in these interventions, perhaps we should expect an impact on the local political economy. As a parallel, I think about the agrarian reform and the later establishment of the welfare state in post-war Italy, and how they gave major local actors the ability to uphold their clientelistic systems. The newly established rights and entitlements, the various benefits and redistribution programs, were ”filtered” by the local elites and channeled through the traditional ties of family, kinship, friendship and neighborhood. According to comparative analyses of European welfare regimes, clientelism exists, in different forms and intensities, in all Mediterranean welfare states, and it appears to be linked to the process of political mobilization and the establishment of welfare state institutions in these nations.
A recent study by Ravallion et al. (2013) finds that unemployed fail to act on information about the National Employment Guarantee Scheme (NEGS) in India. They hypothesizes that the bottleneck lies with the local government institutions (Gram Panchayats). The GP are supposed to receive the applications and apply for central government resources for planning and implementation of projects, so as to guarantee 100 days of work per year to all adults from rural households who are willing to do unskilled manual labor at the statutory minimum wage. But perhaps – argue the authors – given the strict controls on corruption, the GP officials do not find anything in it for themselves, and hence do not proceed. Of course this is just one of the possible explanations, and moreover the NEGS is not a RCT. But in general the involvement of local official or unofficial power structures in contexts where this type of interventions are increasingly common could be interestingly related to the hypothesis on the ”Mediterranean welfare state” outlined above. The idea definitely deserves investigation.
Conclusions
The popularity of RCTs among development scholars is finally spreading to practitioners. This is mostly good news, there is much to gain and learn from this approach, especially in contexts where it is grossly underexploited, as has been the case in Sweden. However, a near-monopoly of this approach is though not granted, given its non-negligible limitations, often belittled in light of its numerous strengths. Spurring development “one experiment at a time” might take unnecessary extra time and efforts, and bring about other undesirable consequences. Both development scholars and practitioners should not forget the other arrows in their quiver.
References
- Bannerjee, A. and E. Duflo (2008), “The Experimental Approach to Development Economics”, NBER Working Paper 14467.
- Brigham, Matthew, Michael Findley, William Matthias, Chase Petrey, and Daniel Nelson. ”Aversion to Learning in Development? A Global Field Experiment on Microfinance Institutions”. Technical Report, Brigham Young University March 2013.
- Buera, F. J., J. P. Kaboski, and Y. Shin (2011). ”The macroeconomics of microfinance.”
- BREAD working paper.
- Bulte, E., Pan, L., Hella, J., Beekman, G. and S. di Falco (2012). ”Pseudo-Placebo Effects in Randomized Controlled Trials for Development: Evidence from a Double-Blind Field Experiment in Tanzania.” Working Paper.
- Kaboski, J. P. and R. M. Townsend (2011, July). ”A structural evaluation of a large-scale quasi-experimental microfinance initiative.” Econometrica 79, 1357–1406.
- Olofsgård, A. ”What Do Recent Insights From Development Economics Tell Us About Foreign Aid Policy?” FREE Policy Brief Series, October 3, 2011.
- Ravallion, M., et al. ”Try Telling People their Rights? On Making India’s Largest Antipoverty Program work in India’s Poorest State.” Department of Economics, Georgetown University, Washington DC (2013).
- Rodrik, D. (2008). ‘The New Development Economics: We Shall Experiment, but How Shall We Learn?’. Harvard Kennedy School Working Paper No. RWP08-055.▪
[1] The example is fictitious. Any resemblance to real studies is unintended and purely coincidental.
[2] At least in theory – this point is discussed more in the next section.