Tag: Eastern Europe
Democracy in the Eye of the Beholder?
There is growing concern that democratic institutions in Eastern Europe are fragile. This brief compares two perspectives on the state of democracy: expert assessments and surveys of the general population. We show that while experts’ perception of some countries’ institutions has worsened in recent years, voters are increasingly satisfied with their own democracies. This trend is broad-based, encompassing almost all new EU member states and all age groups. We provide evidence that over time, survey respondents’ assessment of democracy has become more closely tied to the outcome of elections rather than actual institutional change. Where governments have imposed restrictions on media freedom or judicial independence, their supporters continue to report high levels of satisfaction with the way democracy works.
“Across the world, democracy is backsliding”
UN’s Secretary-General António Guterres, 2022
In recent years, the prevailing narrative around democracy in Eastern Europe has been negative. The reform momentum that propelled countries towards EU membership has not been sustained after accession. Discussions of global democratic backsliding frequently cite countries from the region as examples (Grillo and Prato, 2023; Chiopris et al., 2021; Mechkova et al., 2017). Following restrictions on judicial independence and media freedom, some new EU members have seen their ratings slide on indices that measure the quality of democratic institutions based on expert opinions. This brief contrasts these expert assessments with a different perspective on the state of democracy: that of the voters themselves.
Data from Eurobarometer surveys show that satisfaction with ‘the way democracy works in our country’ has been increasing in the new EU member states. This upward trend is visible for all age groups and in almost all countries – including those where experts’ assessment of democracy has worsened. We document patterns in the data that may help to explain this divergence. Survey responses increasingly reflect an instrumentalist view of democracy; respondents who are aligned politically with the winning party are more likely to feel that democracy is working well. This trend can be observed across the EU, but it is most pronounced in the new EU member states where the governing parties are right-of-centre.
Perceptions of Democracy
Expert Assessments
The quality of democracy is hard to measure. A range of indices classify countries by regime type or provide numerical ratings of institutional quality (the Polity, V-Dem, and Freedom House measures are among the most prominent). These indices have somewhat different objectives and methodologies, but they all rely on subjective judgements by expert coders.
Some academic research casts doubt on the prevailing narrative of a global phenomenon of democratic backsliding. For instance, Treisman (2023) and Lueders and Lust (2018) show that there is little consensus across indices, both in terms of individual countries and the global trend. A recent paper by Little and Meng (2023) contrasts subjective indices with more objective indicators of democratic health (e.g. the rate at which incumbents lose elections). The authors find no evidence for global democratic backsliding using the objective measures and suggest that the pessimistic narratives around democracy may have biased coders’ assessment.
There is less disagreement about the development of democracy in Eastern Europe. Treisman (2023) cites Hungary as the only example of a country that has recently been downgraded both from the status of “liberal democracy” by V-Dem and “free state“ by Freedom House. Little and Meng (2023) highlight three cases where both objective and subjective measures indicate backsliding: Hungary and Poland (as well as Venezuela). Further, Becker (2019) shows that downgrades to V-Dem democracy scores in Bulgaria, Czechia, Hungary, Poland, and Romania are relatively broad-based, driven by declines across multiple sub-categories including freedom of expression and constraints on the executive.
Surveys of Public Opinion
We use individual-level data from the Eurobarometer – a survey of public opinion in the EU Member States and candidate countries conducted by the European Commission. The surveys are conducted at an approximately monthly frequency and comprise of a representative sample (about 1000 face-to-face interviews) for each state. We combine data from 42 surveys, spanning 20 years (2002 to 2022), with a total of 1.3 million respondents. The main question we are interested in is: “On the whole are you very satisfied, rather satisfied, not very satisfied or not at all satisfied with the way democracy works in [our country]?”
At the beginning of the sample period in 2002, around a third of respondents in Eastern European EU countries were satisfied with their respective democracies compared to close to twice as many respondents in Western Europe (Figure 1). Over the past 20 years, the share of Eastern Europeans satisfied with their democracy has grown to around 50 percent, narrowing the gap with Western Europe. Figure 2 shows that this pattern is broad based across age groups. All cohorts of Eastern Europeans are more satisfied with democracy than earlier generations and among the youngest respondents, satisfaction is almost as high as in Western Europe.
Figure 1. Satisfaction with Democracy vs V-Dem Score.
Source: Eurobarometer, V-Dem and authors’ calculations.
Figure 2. Satisfaction with Democracy by Age Group.
Notes: Each point shows the sample mean for a single year cohort. 95 percent confidence intervals in grey.
Source: Eurobarometer, authors’ calculations.
Figure 1 also shows a stark divergence in expert assessment of the state of democracy in Eastern Europe compared to public opinion in the same countries. While the V-Dem democracy scores for Eastern Europe have declined rapidly since the mid-2010s, average satisfaction with the own country’s democracy has increased. A much smaller gap between these two measures has also started to open up in Western Europe over the past couple of years.
In Figure 3, we show the same patterns of satisfaction with democracy and expert opinions for individual countries. Satisfaction with one’s own democracy has increased in almost all Eastern European countries, including in Poland and Hungary which at the same time showed the largest declines in democracy scores.
Figure 3. Satisfaction with Democracy vs V-Dem Score by Country.
Source: Eurobarometer, V-Dem and authors’ calculations.
This divergence in individual survey responses and expert assessments is not altogether surprising. First, the Eurobarometer surveys a sample of the population in each country, while V-Dem (and most other similar democracy indices) relies on country experts. Another likely explanation for the difference is the interpretation of the question. Democracy ratings tend to emphasise institutional aspects of a democracy, for instance, the V-Dem liberal democracy index is designed to capture rule of law and checks on executive power (see, e.g., Becker, 2019). In contrast, the survey responses are likely to reflect both satisfaction with the state of democracy in a country, as well as the outcomes of that democracy.
Satisfaction with Democracy and Political Alignment
In this section, we investigate whether stated satisfaction with democracy depends on the outcomes of elections and the political ideology of the respondents. A common way of measuring political ideology is the placement on a right-left scale, where the right favours a free-market economy and traditional values while the left favours economic redistribution and socially progressive policies. We compare the right-left placement of each country’s governing party as coded by the Chapel Hill Expert Survey (CHES), with the self-identified right-left placement of Eurobarometer respondents. We calculate the ideological distance from the government as the absolute difference between these two scores.
Figure 4. Relationship Between Ideological Distance from Government and Satisfaction with Democracy.
Source: Eurobarometer, Döring, Huber and Manow (2022) and authors’ calculations.
Notes: Each point shows the coefficient from a separate regression of satisfaction with democracy on ideological distance from government, age, gender, year fixed effects and country fixed effects. 95 percent confidence intervals in grey. Coefficient estimates for Eastern and Western EU overlap on the chart for 2019 and 2020.
We find that people are on average less satisfied with their country’s democracy when they are ideologically further from the parties in government (Figure 4). This is consistent with prior evidence (Anderson and Guillory, 1997; Ezrow and Xezonakis, 2011). The alignment effect has become stronger over time – even when taking into account average satisfaction levels for each country and demographic characteristics of the respondents, such as their age and gender. In the past three years, political alignment with the government has become a major factor in explaining satisfaction with democracy, especially in Eastern Europe. Svolik (2019) suggests that voters trade off democratic principles and partisan interests. As political polarisation increases, voters become more willing to accept a government that undermines democratic institutions, as long as it is on ‘their side’ ideologically.
Figure 5. Satisfaction with Democracy and Political Ideology. Western Europe in the Left Panel and Eastern Europe in the Right Panel.
Source: Eurobarometer, Döring, Huber and Manow (2022) and authors’ calculations.
Notes: Respondents with the most left-leaning ideology are at the extreme left of the x-axis, those with the most right-leaning ideology are at the extreme right. The sample covers the period 2002 to 2022 and excludes observations where the government is coded as centrist (scores of 5-6 in the CHES data). 95 percent confidence intervals in grey.
In Figure 5, we break down the effect of political alignment on satisfaction with democracy according to individuals’ political leanings. On the x-axis is the respondents’ left-right placement and on the y-axis there are two series of dots showing satisfaction with democracy depending on whether the government is left of centre (lighter coloured dots) or right of centre (darker coloured dots). As before, being politically aligned with the government increases satisfaction, that is, to the left of the chart, the lighter coloured dots are placed higher than the darker coloured dots and vice versa for the right of the chart. The further from centre a person’s political leanings, the less satisfied they are with a government of the opposite ideology. There is also some evidence of asymmetry across the political spectrum in Eastern Europe, with respondents on the political right reporting much higher levels of satisfaction with right-wing governments compared to voters on the left under a left-wing government.
Conclusion
Over the past decade, there has been increasing concern over democratic backsliding in some of the Eastern European countries that are members of the EU. This is reflected in commonly used democracy indices whose country experts note the worrying trends in countries’ institutions – such as the reduction of freedom of expression, the strengthening of rule of law and constraints on the executive, all hallmarks of a liberal democracy. In this policy brief, we investigate whether this erosion of institutional safeguards affects people’s stated satisfaction with democracy in one’s respective country. We find a broad-based increase in satisfaction with democracy in the Eastern European EU countries, including in the countries that have seen some of the largest declines in liberal democracy ratings. We show that stated satisfaction with democracy reflects less the institutional changes in countries, but more the outcome of democratic elections. Voters who are politically aligned with their government are systematically more likely to report that they are satisfied with the state of democracy in their country. And this effect has become stronger in the most recent years, particularly in the Eastern European EU countries. We also find that this effect is not symmetric across the political spectrum. In the Eastern European EU countries, respondents on the political right are more satisfied with right-wing governments than those on the left are with left-wing governments.
The descriptive patterns outlined in this policy brief illustrate a worrying disconnect in the minds of many voters between institutions and outcomes of the democratic process. The threat of democratic backsliding in Europe and across the globe is predominantly not due to electoral democracies being replaced by autocratic regimes. Rather, genuinely popular (and often populist) governments are democratically elected and, once in power, proceed to undermine and dismantle liberal democratic institutions, such as a free press, an independent judiciary, and a fair electoral system. This process in turn makes it more difficult for opposition parties to win future elections, further cementing the power of the rulers of these illiberal democracies. While the electorate might support these governments now, voters need to be aware that these liberal institutions are designed to safeguard their democratic future.
References
- Anderson, C. J. and Guillory, C. A. (1997). Political institutions and satisfaction with democracy: A cross-national analysis of consensus and majoritarian systems. American Political Science Review, 91(1), pp.66-81.
- Becker, T. (2019). Liberal Democracy in Transition – The First 30 Years. FREE Policy Brief.
- Chiopris, C., Nalepa, M. and Vanberg, G. (2021). A wolf in sheep’s clothing: Citizen uncertainty and democratic backsliding. Working Paper.
- Döring, H., Huber, C. and Manow, P. (2022). ParlGov 2022 Release. Harvard Dataverse. https://doi.org/10.7910/DVN/UKILBE
- Eurobarometer (multiple waves: 2002-2022), European Commission. Brussels
- Ezrow, L. and Xezonakis, G. (2011). Citizen satisfaction with democracy and parties’ policy offerings. Comparative Political Studies, 44(9), pp.1152-1178.
- Grillo, E. and Prato, C. (2023). Reference points and democratic backsliding. American Journal of Political Science, 67(1), pp.71-88.
- Little, A. and Meng, A. (2023). Subjective and Objective Measurement of Democratic Backsliding. Available at SSRN 4327307.
- Lueders, H. and Lust, E. (2018). Multiple measurements, elusive agreement, and unstable outcomes in the study of regime change. The Journal of Politics, 80(2), pp.736-741.
- Mechkova, V., Luhrmann, A. and Lindberg, S. I. (2017). How much democratic backsliding?. Journal of. Democracy, 28, pp.162-169.
- Svolik, M. W. (2019). Polarization versus democracy. Journal of Democracy, 30(3), pp.20-32.
- Treisman, D. (2023). How great is the current danger to democracy? assessing the risk with historical data. Comparative Political Studies, https://doi.org/10.1177/00104140231168363.
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.
From East to West: A Paper Curtain in Swedish Foreign News Coverage?
How much a country is talked about in the media can determine its place in the public debate. In this brief, we collect data on the mentions of Eastern and Western European countries in the main Swedish newspapers over the past decades. We find consistently more coverage devoted to Western compared to Eastern Europe in the Swedish press. We investigate several factors that could explain this pattern. We find that while Eastern European countries are on average not more geographically distant from Sweden, Sweden tends to have closer trade links with Western European countries. Sweden is more culturally similar to the average Western European country in terms of language, religion and attitudes, cultural values and social norms. Trade relations and cultural proximity are associated with higher media coverage.
The media plays a vital role in modern societies by keeping the public informed and policymakers accountable. Whether and how events are covered by the news determines their relevance in the public debate. There is ample empirical evidence on the agenda-setting power of the news media. For example, Snyder and Strömberg (2010) show that local press coverage affects how informed US voters are about their representatives and in turn how much their politicians work in the interest of their constituencies. Eisensee and Strömberg (2007) find that news coverage affects how much disaster relief the US sends to foreign countries.
In this brief, we study the amount of news coverage devoted to European countries in the Swedish press. We document a systematic difference between Western and Eastern Europe and explore underlying factors that could be important in explaining this East-West divide.
The East-West Divide
We choose the four most widely read Swedish newspapers (Aftonbladet, Expressen, Dagens Nyheter, and Svenska Dagbladet) and use the newspaper database Retriever Research Media Archive to obtain statistics on the number of mentions of each country between 1995 and 2021. A country mention is an article in which the name of a country appears. Since two or more countries can be named in the same article, the total number of mentions does not correspond to the number of articles. As a percentage of all articles published by the four newspapers in 2021, roughly 20% mention at least one of these countries. While this simple measure of news coverage can be informative, it does not take into account many other aspects of a country’s prominence in the news, such as the length of articles, where articles appear, the tone of coverage, etc.
Figure 1 plots the sum of annual number of mentions by region over time. We see a clear difference in the amount of coverage devoted to Eastern and Western European countries. Over the entire time period, the 21 Western European countries were mentioned on average 2.7 times more than the 22 Eastern European countries.
While there does not appear to be a trend in relative coverage, there is considerable variation from year to year. The year when the relative difference in the number of mentions is smallest is 2014. The two most mentioned Eastern European countries in that year were Russia and Ukraine. Coverage likely increased due to the Crimean Crisis, when Russia invaded and annexed the Crimean Peninsula in Southern Ukraine. The relative difference was also low in 2008, coinciding with the Russo-Georgian war in August. In that year, other newsworthy events, such as the Global Financial Crisis or the UEFA European Football Championship, have a more ambiguous effect on relative media coverage.
Figure 1. Country mentions in Swedish newspapers
Note: Countries included in Eastern Europe: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Latvia, Lithuania, Moldova, Montenegro, North Macedonia, Poland, Russia, Serbia, Slovakia, Slovenia, Ukraine. Countries included in Western Europe: Andorra, Austria, Belgium, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Switzerland, United Kingdom.
What Explains This Discrepancy Between East and West?
There are a number of potential reasons why some countries systematically receive more attention in the press. In this section, we correlate the mean annual mentions of each country between 2019 and 2021 with different aspects of that country’s relationship with Sweden.
Distance and Population
Figure 2 shows how news coverage of a country depends on its geographic distance to Sweden and its population size. Overall, the further a country is from Sweden, the less that country is covered in the Swedish press. On average, Eastern European countries (in yellow) are covered less than Western European countries (in blue), for a given distance to Sweden. For example, Poland and Germany are both around 1000km away from Sweden, but Germany is mentioned almost twice as often in the Swedish press. As we measure the distance between the most populous city of each country and Stockholm, some of this difference in coverage is driven by the fact that countries sharing a border with Sweden receive extensive coverage. For instance, Denmark, Finland, and Norway are on average covered more than six times as much as Latvia.
Population also plays a role, that is, larger countries (e.g., Germany, Russia, Spain, and Poland) receive more coverage than smaller countries (e.g., Lithuania, Ireland, and Estonia). As Eastern European countries have on average smaller populations than Western European countries, population can partly explain the East-West difference in news coverage. One counterexample is Russia, which has more than twice as many people as France or the UK, but receives less coverage in the Swedish press.
Figure 2. Geographical distance and population
Note: Geodesic distances are calculated between the latitudes and longitudes of the most populous city of each country and Stockholm. Marker sizes are weighted by population averaged over 2019-2021, and fitted line is unweighted. Source: CEPII’s GeoDist dataset (Mayer and Zignago, 2006) and the World Bank. See Figure 1 for a list of countries included.
Trade and GDP
Figure 3 shows that Sweden’s economic relationship with a country affects how much the country features in Swedish news. We find a strong positive correlation of 0.8 between a country’s total trade volume with Sweden and country mentions in Swedish newspapers. As Sweden’s largest trading partners tend to be in Western Europe, this partly explains the relative coverage of East and West. Another factor is the overall size of a country’s economy (as measured by its GDP). Swedish newspapers more commonly mention countries with higher GDP, and these are more likely to be in Western than Eastern Europe.
Figure 3. Trade and GDP
Note: Trade data are from 2019. Marker sizes are weighted by national GDP, and fitted line is unweighted. GDP figures are averaged over 2019-2021 and measured in current prices, PPP adjusted, international dollars. Source: The World Bank’s WITS database and the IMF World Economic Outlook, October 2021. See Figure 1 for a list of included countries.
Culture
There is a large literature documenting the link between cultural factors and the economic relationship between nations. For instance, studies show that similarities in ancestry, language, religion, norms and values can influence bilateral trade (Melitz, 2008; Guiso et al., 2009) and the diffusion of technology (Spolaore et al., 2009). In this section, we show how the amount of press coverage correlates with differences in language, religion, and values and norms using cultural distance data from Spolaore and Wacziarg (2016).
Figure 4.a shows that Swedish newspapers are more prone to cover countries whose languages are similar to Swedish. The language similarity measure originally developed by Fearon (2003) is based on the prevalence of languages within a country and distance between languages. The distance measure is calculated using linguistic trees provided in Ethnologue. It ranges from 0 (close) to 1 (distant) and reflects the expected number of common linguistic nodes between two randomly chosen individuals from each country and takes into account that countries can be linguistically heterogeneous (for more details, see Fearon 2003). Norway and Denmark are linguistically closest to Sweden, however, these are also two neighboring countries with which Sweden conducts extensive trade. On average, Eastern European countries are more linguistically distant from Sweden, although some Western European countries (such as France and Spain) are as linguistically distant from Sweden as many of the Eastern European countries and receive considerably more press coverage.
The religious distance measure by Spolaore and Wacziarg (2016) is calculated analogously to the linguistic distance measurement. It is based on the prevalence of different religions within a country and the distance between religions. Figure 4.b shows that countries that are religiously different from Sweden receive less coverage in the Swedish media. With the exception of the three Scandinavian countries, Eastern and Western European countries have similar levels of religious distance to Sweden. Based solely on this metric, the Swedish press mentions Eastern European countries less (and Western European countries more) than their religious distance to Sweden would predict.
Figure 4.c shows an index of a country’s cultural proximity to Sweden, that is, its distance in terms of cultural values, attitudes and norms based on average responses to the World Value Surveys from 1981 to 2010 (see Spolaore and Wacziarg, 2016). This cultural proximity index aggregates the Euclidian distances in survey responses between each country and Sweden. The index is standardized so that 0 shows the average country’s cultural distance to Sweden and negative (positive) values indicate above (below) average cultural similarity. Western European countries are significantly closer to Sweden than Eastern European countries based on this measure. As Swedish press coverage is on average declining in a country’s cultural distance to Sweden, this difference in country’s values and attitudes can explain some of the East-West difference in media coverage.
Figure 4. Cultural distance
Panel a. Linguistic distance
Note: We use the indicator of tree-based weighted linguistic distance from Spolaore and Wacziarg (2016) and originally developed in Fearon (2003). This measure is an estimate of the expected or weighted number of common linguistic nodes between two randomly chosen individuals from each country. The data on language prevalence is compiled from a number of different sources and assembled in Fearon (2003). Countries included in Eastern Europe: Albania, Armenia, Azerbaijan, Belarus, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Latvia, Lithuania, Moldova, Poland, Russia, Slovakia, Slovenia, Ukraine. Countries included in Western Europe: Austria, Belgium, Denmark, Finland, France, Germany (average between East and West Germany), Ireland, Italy, Netherlands, Norway, Portugal, Spain, Switzerland, United Kingdom
Panel b. Religious distance
Note: We use the tree-based weighted religious distance from Spolaore and Wacziarg (2016). This measure is an estimate of the expected distance between the religions of two randomly chosen individuals from each country. See Figure 4.a for a list of included countries.
Panel c. Distance in cultural values, attitudes, and norms
Note: We use the distance in cultural norms and values from Spolaore and Wacziarg (2016). This measure is based on all value-related questions from the World Values Survey Integrated Questionnaire from 1981–2010. The mean distance across countries is standardized to zero. See Figure 4.a for a list of countries included.
Conclusion
As the public and policymakers primarily receive information from the mass media, news coverage can have profound effects on public debate and policy decisions. Using data on the content of the four most widely read Swedish newspapers over the past decades, we measure how much the Swedish press covers Eastern and Western European countries. We find that over the past 25 years, there have been 2.7 times more mentions of Western than Eastern European countries. We find that the Swedish press is more likely to mention countries that are geographically closer, more populous, have a larger GDP and more trade with Sweden. Cultural proximity (as measured by language, religion and values, attitudes and social norms) also correlates with higher coverage. These factors are of course not independent from each other. For instance, the other Scandinavian countries with whom Sweden shares a border and a history, are culturally similar to Sweden and some of Sweden’s most important trading partners. They are also some of the countries that are most covered by the Swedish press. Some of these factors, such as sharing similar values, appear to explain the gap in coverage between East and West, while others, such as geographic distance, do not. More recently, concerns over energy security in the EU (see e.g., Le Coq and Paltseva, 2022) and the rise in military tension between Russia and Ukraine illustrate how developments in Eastern Europe can directly affect life here in Sweden. Perhaps it is time for Sweden to pay more attention to her eastern neighbours?
References
- Eisensee, T., & Strömberg, D. (2007). “News droughts, news floods, and US disaster relief”. The Quarterly Journal of Economics, 122(2), 693-728.
- Fearon, J. (2003) “Ethnic and Cultural Diversity by Country”, Journal of Economic Growth, 8, 195–222.
- Guiso, L., Sapienza, P., & Zingales, L. (2009). “Cultural biases in economic exchange?”. The Quarterly Journal of Economics, 124(3), 1095-1131.
- Le Coq, C. & Paltseva, E. (2022). “What does the Gas Crisis Reveal About European Energy Security?” FREE Policy Briefs.
- Mayer, T. & Zignago, S. (2006). “GeoDist: The CEPII’s Distances and Geo-graphical Database” MPRA Paper No. 31243.
- Melitz, J. (2008). “Language and foreign trade”. European Economic Review”, 52(4), 667-699.
- Snyder, J. M., & Strömberg, D. (2010). “Press coverage and political accountability”. Journal of Political Economy, 118(2), 355-408.
- Spolaore, E., & Wacziarg, R. (2009). “The diffusion of development”. The Quarterly Journal of Economics, 124(2), 469-529.
- Spolaore, E., & Wacziarg, R. (2016). “Ancestry, language and culture”. In The Palgrave Handbook of Economics and Language (pp. 174-211). Palgrave Macmillan, London.
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.
Addressing the COVID-19 Pandemic: Vaccination Efforts in FREE Network Countries
There are great expectations that vaccinations will enable a return to normality from Covid-19. However, there is massive variation in vaccination efforts, vaccine access, and attitudes to vaccination in the population across countries. This policy brief compares the situation in a number of countries in Eastern Europe, the Baltics, the Caucasus region, and Sweden. The brief is based on the insights shared at a recent webinar “Addressing the COVID-19 pandemic: Vaccination efforts in FREE Network countries” organized by the Stockholm Institute of Transition Economics.
Introduction
As of February 16, 2021, the total number of confirmed COVID-19 deaths across the globe has reached 2.45 million according to Our World in Data (2021). Rapid implementation of vaccination programs that extend to major parts of the population is of paramount importance, not only from a global health perspective, but also in terms of economic, political, and social implications.
Eastern Europe is no exception. Although many countries in the region had a relatively low level of infections during the first wave of the COVID-19 pandemic in the spring of 2020, all have by now been severely affected. Vaccination plays a key role for these economies to bounce back, especially as many of them depend on tourism, trade, and other sectors that have been particularly hurt by social distancing restrictions.
Figure 1. Cumulative confirmed COVID-19 cases (top panel) and deaths per million (bottom panel) in the FREE Network region
Source: John Hopkins University CSSE COVID-19 visualizations: Ourworldindata.org/coronavirus
Against this background, the Stockholm Institute of Transition Economics invited representatives of the FREE Network countries to discuss the current vaccination efforts happening in Eastern Europe, the Baltics, and the Caucasus (the represented countries were Belarus, Georgia, Latvia, Poland, Russia, Sweden, and Ukraine). This brief summarizes the main points raised in this event.
Vaccination Status
In Latvia, Poland, and Sweden, the second wave of infections started to pick up in November 2020 and peaked according to most COVID-19 impact measures in early 2021. As all three countries are members of the EU and take part in its coordinated efforts, they have all received vaccines from the same suppliers (i.e. Astra/Zeneca, Moderna, and Pfizer/BioNTech).
Latvia had problems early on with getting the vaccination process off the ground. The health minister was blamed for the slow start since he declined orders from Pfizer/BioNTech in the early stages, and was forced to resign. As of February 16, two doses per 100 people have been distributed primarily to medical staff, social care workers, and key-state officials.
Figure 2. Cumulative COVID-19 vaccination doses per 100 people
Source: Our world in data, last updated February 24th, 2021. This is counted as a single dose, and may not equal the total number of people vaccinated. Visualizations: Ourworldindata.org/coronavirus
With the first phase starting in late December, Sweden has by February 16th, 2021, fully vaccinated 1,05% of the population while experiencing serious problems with delivery and implementation. As planning and delivery of vaccines are centralized while the implementation is decided regionally, there have been some unclarities regarding who stands accountable for issues that emerge. Guidelines, issued by the Public Health Agency of Sweden, for how to prioritize different groups have been changed a couple of times. Currently, the (non-binding) recommendation is to prioritize vaccinating people living in elderly care homes, as well as personnel working with this group, followed by those above 65 years of age, health care workers, and other risk groups.
Looking at regional statistics there are significant differences in vaccinating people across regions with an average of 70% usage rate of delivered vaccines, and with lows at 40-60%, see figure 3. Reasons for this remain unclear.
Figure 3. Distributed relative to delivered vaccines across counties (län) in Sweden.
Source: Authors’ calculations based on data collected by the Public Health Agency of Sweden. Last updated February 14th, 2021.
Poland has so far been somewhat more efficient than Sweden in its vaccination efforts. Despite turbulent political events over the last couple of months, it has managed to distribute 5.7 doses per 100 people. The country has just finished the first phase of the national vaccination plan, which focused on vaccinating healthcare personnel, and has now entered the second phase with a shifted focus towards elderly care homes, people above 60 years of age, military, and teachers.
Among the countries that are not members of the EU, and thus, not taking part in its coordinated vaccination efforts, the vaccination statuses are more diverse.
Russia was fast in developing and approving the Sputnik V vaccine. The country started vaccinating in early December, although only people in the age of 18-60 in prioritized occupations such as health care workers, people living and working in nursing homes, teachers, and military. At the start of 2021, the program extended to people above 60 and, on January 16, all adults were given the possibility to register themselves and get vaccinated within one week. There are no precise data at the moment, but the fraction of the population vaccinated is likely to be higher than 1%.
Others in the region have faced greater challenges in signing contracts with vaccine suppliers. Georgia and Ukraine are still waiting to secure deliveries and have not yet started to vaccinate. Being outside the EU agreements and with public and political mistrust towards Sputnik V and Russia alternatives are being explored. Georgia has ordered vaccines through the COVAX platform (co-led by Gavi, the Coalition for Epidemic Preparedness Innovations (CEPI) and WHO) but there are concerns about potential delays in deliveries. In terms of prioritizing groups once vaccinations can start, both Ukraine and Georgia have set similar priorities as other countries, with extra focus on health-care and essential workers, age-related risk groups, and people with chronic illnesses.
While Belarus’ official figures on the death toll have been widely perceived as unrealistic from the beginning, the most accurate and recent data shows an excess deaths rate of about 20% in July. The country has no precise data on vaccinations, but some reports have emerged based on interviews with government officials in the Belarusian media. These suggest that around 20,000 imported doses of Sputnik V have been distributed mainly to medical professionals and an additional 120,000-140,000 doses have been promised by Russia.
Main Challenges
The discussion during the Q&A session at the webinar concerned the economic and political implications of vaccinations in the region.
Pavlo Kovtoniuk, the Head of Health Economics Center at KSE in Ukraine, stressed the importance of a coordinated vaccination effort in Europe with regards to geopolitics. There is a clear EU vs Non-EU divide in the vaccination status across European countries. The limited vaccine availability in Non-EU countries such as Ukraine, Georgia, and Belarus offers opportunities for more influential nations like Russia and China to pressure and affect domestic policy in these countries.
Also highlighting the fact that no one is safe until everybody is safe, Lev Lvovskiy, Senior Research Fellow at BEROC in Minsk, noted that vaccination efforts in Europe are important for recovery in small open economies like Belarus as many of its trade partners currently have imposed temporary import restrictions.
Similar to the political crisis happening alongside the pandemic in Belarus, the challenges we see in Poland – protests against the recent developments regarding abortion rights and attempts by the government to limit free media – have deflated the urgency to vaccinate in terms of its future economic and political implications, according to Michal Myck, director of CenEA in Szczecin.
Looking forward, another major challenge for the region is vaccine skepticism. Not only do many countries have to build proper infrastructure that can administer vaccines at the required scale and pace, but also make sure that people actually show up. In Latvia, Poland, Georgia, Russia, and Ukraine, polls show that less than 50% of the population are ready to vaccinate. Sergejs Gubin, Research Fellow at BICEPS in Riga, highlighted that there can be systematic variation in the willingness to vaccinate within countries as e.g. Russian-speaking natives in Latvia have been found to be less prone to vaccinate on average. Also, most of the skepticism in Georgia has been more directed towards the Chinese and Russian vaccine than towards those approved by the EU, according to Yaroslava Babych who is lead economist at ISET in Tbilisi.
Even though vaccine skepticism is an issue in Russia too, Natalya Volchkova, Director of CEFIR at New Economic School in Moscow, pointed to the positive impact of “bandwagon effects” in vaccination efforts. When one person gets vaccinated, that person can spread more accurate information about the vaccine to their social circle, resulting in fewer and fewer people being skeptical as the share of vaccinated grows. In such a scenario vaccine skepticism can fade away over time, even if initial estimates suggest it is high in the population.
Concluding Remarks
Almost exactly a year has passed since Covid-19 was declared a pandemic. The economic and social consequences have been enormous. Now vaccines – developed faster than expected – promise a way out of the crisis. But major challenges, of different types and magnitudes across the globe, still remain. As the seminar highlighted, there are important differences across transition countries. Some countries (such as Russia) have secured vaccines by developing them, but still face challenges in producing and distributing vaccines. Others have secured deliveries through the joint effort by the EU, but this has also had its costs in terms of a somewhat slower process (compared to some of the countries acting on their own) and sharing within the EU. For some other countries, like Belarus, Ukraine, and Georgia, the vaccination is yet to be started. All in all, the choice and availability of vaccines across the region illustrates how economic and geopolitical questions remain important. Finally, for many of the region countries vaccine skepticism and information as well as disinformation are important determinants in distributing vaccines. Summing up, the combination of these factors once again reminds us that how to best get back from the pandemic is truly a multidisciplinary question.
List of Participants
- Iurii Ganychenko, Senior researcher at Kyiv School of Economics (KSE/Ukraine)
- Jesper Roine, Professor at Stockholm School of Economics (SSE) and Deputy Director at the Stockholm Institute of Transition Economics (SITE/ Sweden)
- Lev Lvovskiy, Senior Research Fellow at the Belarusian Economic Research and Outreach Center (BEROC/ Belarus)
- Michal Myck, Director of the Centre for Economic Analysis (CenEA/ Poland)
- Natalya Volchkova, Director of the Centre for Economic and Financial Research New Economic School (CEFIR NES/ Russia)
- Pavlo Kovtoniuk, Head of Health Economics Center at Kyiv School of Economics (KSE/Ukraine)
- Sergej Gubin, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS/ Latvia)
- Yaroslava V. Babych, Lead Economist at ISET Policy Institute (ISET PI/ Georgia)
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.
Video of the FREE Network webinar “Addressing the Covid-19 Pandemic: Vaccination Efforts in Free Network Countries“
Pollution and the COVID-19 Pandemic: Air Quality in Eastern Europe
The COVID-19 pandemic has drawn attention to a pre-existing threat to global health: the quality of air in cities around the world. Prolonged exposure to air pollution has been found to increase the mortality rate of COVID-19. This is a particular concern for much of Eastern Europe, where emissions regularly exceed safe levels. This policy brief analyses recent data on air quality in the region and the factors that explain a persistent East-West divide in pollution in Europe. It concludes by evaluating to what extent lockdowns in 2020 provided a temporary respite from pollution in the region.
Introduction
The WHO estimates that air pollution causes seven million premature deaths every year (WHO 2018). COVID-19 has further amplified these health risks, as air pollution can increase both the chance of catching respiratory diseases and their severity. At the same time, the pandemic has resulted in lockdowns and a general slowdown in economic activity which are widely perceived as having led to a temporary improvement in air quality.
This brief provides an overview of recent trends in air quality in Eastern European cities using data from the World Air Quality Index. It addresses three questions:
- How did air pollution in Eastern Europe compare to Western Europe prior to the pandemic?
- What are the main sources of air pollution in Eastern European cities and can they be addressed by policymakers?
- Was there a significant improvement in air quality in 2020 as a result of COVID-19?
Air Pollution in Eastern Europe
Most measures of air quality in Europe show a stark East-West divide. Map 1 plots the share of days in 2019 where air pollution, as measured by PM 2.5 (fine particulate matter), exceeded levels classified as unhealthy for the general population. On average, cities to the east of the former Iron Curtain experienced over 100 such days, compared to an average of 20 days in Western Europe. These averages mask significant variation within both regions; Tallinn was among the best performing cities while Naples was among the worst.
Map 1
Source: Author’s calculations based on data from the World Air Quality Index COVID-19 dataset. Above the threshold AQI of 150, PM 2.5 levels are classified as unhealthy to the general population by the US EPA.
The gap in air quality between Eastern and Western Europe has been linked to differences in health outcomes for decades. Shortly after the fall of the Soviet Union, Bobak and Feachem (1995) found that air pollution accounted for a significant share of the Czech Republic and Poland’s mortality gap with respect to Western Europe. The European Environment Agency’s 2020 report provides estimates for ‘years of life lost’ attributable to different pollutants. Figure 1, which plots these estimates for PM 2.5, highlights the fact that Eastern European countries, in particular those in the Balkans, continue to experience significantly higher mortality related to pollution, as compared to their Western European counterparts.
Figure 1
Source: estimates from EEA Air Quality in Europe report 2020
Sources of Air Pollution
A number of factors contribute to the pattern of pollution shown on Map 1, not all of which are under policymakers’ direct control. For example, two of the cities on the map with the unhealthiest air – Sarajevo and Skopje – are surrounded by mountains that prevent emissions from dissipating.
In addition to immutable geographic factors, policies elsewhere may also be contributing to pollution in the region. Stricter regulations in Western Europe can have adverse effects if they result in polluting industries migrating eastwards. Bagayev and Lochard (2017) show that as EU countries adopt new air pollution regulations, the share of their imports from Eastern Europe and Central Asia in pollution-intensive sectors increases. Stricter rules can also result in outdated technology being exported to other countries. A Transport & Environment report found that over 30,000 high-emission diesel cars were exported from Western Europe to Bulgaria in 2017 and argued that such flows will continue as Western European cities impose Low Emission Zones and diesel bans (Transport & Environment 2018).
Power generation, and in particular coal power, is likely to be the single most important determinant of the gap in air quality between Eastern and Western European cities. Coal power accounts for over 60% of electricity production in Poland, Serbia, Bosnia Herzegovina, and North Macedonia, and remains an important energy source in the majority of Eastern European countries (BP 2020). Many of the coal power plants in the region have been operating for decades and are not equipped with modern desulphurisation technology that would help to reduce their emissions. A report by the Health and Environment Alliance found that 16 coal power plants in the Western Balkans collectively produce more emissions than the 250 power plants in the European Union, while only being able to generate 6% of the power (Matkovic Puljic et al. 2019).
Countries in the region are taking steps to reduce their dependence on coal power. In September 2020, the Polish government struck an agreement with labour unions that would see coal phased out by 2049. Coal accounts for 75% of Poland’s current electricity and Map 1 shows that air in the Upper Silesian Coal Basin, in the south of the country, is particularly polluted. Despite such commitments, Western European countries have in recent years been faster at transitioning away from coal. If this trend continues, the gap in air quality may even increase in the short run.
Did COVID-19 Improve Air Quality?
Last spring, a number of headlines from around the world featured the phrase “A breath of fresh air” (e.g. Reuters, The Economic Times, EUIdeas). These articles described measurable improvements in air quality in cities with government-mandated lockdowns. Recent academic publications have confirmed these reports in a variety of settings including the US (Berman and Ebisu 2020), China (Chen et al. 2020), and Korea (Ju et al. 2020).
While Eastern Europe was less affected by the initial wave of COVID-19 than Western Europe, most countries imposed lockdowns and social distancing measures that can be expected to have affected air quality. Figure 2 uses daily data from the World Air Quality Index for 221 European cities to compare average air pollution in 2020 to 2019. Overall, these plots suggest that air quality did improve in Eastern European cities relative to the previous year. However, not all types of pollutants declined and the declines are slightly smaller on average than in Western European cities. Panels A, B, and C plot air quality indices for fine particulate matter (PM 2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) respectively. Dots below the line represent cities where the average air quality index was lower (indicating less pollution) in 2020 than in 2019. The declines are largest for NO2 – a gas that is formed when fuel is burned. The reduction in traffic and transportation in all European cities is likely to have contributed to this drop. By contrast, there were no statistically significant declines in SO2. This may be due to the fact that power generation, which is the source of most SO2 emissions, was less affected by lockdowns than transportation.
Figure 2
Panel A
Panel B
Panel C
Source: Author’s calculations based on the World Air Quality Index COVID-19 dataset. Each marker represents a city. Markers below the 45-degree line represent cities where emissions for the respective category of pollutant were lower in 2020 than in 2019. For reasons of presentation, outliers were excluded from panels B and C.
The variation in COVID-19 prevalence over the course of 2020 is visible when tracking pollution over time. Figure 3 shows that average daily NO2 emissions in Western European cities dropped most from March to June of 2020, during the first wave of the pandemic. NO2 levels were comparable to the previous year in July and August when case numbers fell and restrictions were lifted. In the last months of the year, as the second wave hit, NO2 emissions once more dropped below the previous year’s average. This pattern is similar for Eastern European cities but the decline in NO2 in the first half of the year is less pronounced.
Figure 3
Source: Author’s calculations based on the World Air Quality Index COVID-19 dataset. Lines show the seven day moving average of the ratio between average NO2 emissions in 2020 and 2019.
Conclusion
The COVID-19 epidemic has highlighted the health costs of air pollution. The preliminary evidence suggests that long-term exposure to pollution increased COVID-19 mortality rates (Cole et al. 2020, Wu et al. 2020). This is a particular concern for countries across Eastern Europe which – at the time of writing – are still grappling with the second wave of the pandemic in Europe. Many people in this region have been exposed to polluted air for decades.
The pandemic has also demonstrated that air quality can improve relatively quickly when human behaviour changes. The data described in this brief suggest that Eastern Europe was no exception in this regard, although the declines were confined to some categories of pollutants. Achieving a more general, and sustained improvement in air quality will require a shift from coal power towards cleaner forms of energy.
Stimulus packages aimed at a post-pandemic economic recovery can provide an opportunity for policy to reorient the economy and accelerate such a shift. The consultancy Vivid Economics, which rated G20 member countries’ proposed stimulus packages in terms of their environmental impact, found that the ‘greenest’ stimulus proposals are those of the European Commission, France, UK, and Germany. Russia is one of the worst performers on this index (Vivid Economics 2020). Whether governments in Eastern Europe are able to take advantage of this opportunity will depend on their respective fiscal space and whether they make improving air quality a priority.
References
- Bagayev, Igor, and Julie Lochard, 2017. “EU air pollution regulation: A breath of fresh air for Eastern European polluting industries?.” Journal of Environmental Economics and Management 83: 145-163.
- Berman, Jesse D., and Keita Ebisu. 2020 “Changes in US air pollution during the COVID-19 pandemic.” Science of the Total Environment 739: 139864.
- BP 2020 “Statistical Review of World Energy – all data, 1965-2019“
- Bobak, Martin, and Richard GA Feachem. 1995. “Air pollution and mortality in central and eastern Europe: an estimate of the impact.” The European Journal of Public Health , no. 2: 82-86.
- Cole, Matthew, Ceren Ozgen, and Eric Strobl, 2020. “Air pollution exposure and COVID-19.”.
- Chen, Kai, Meng Wang, Conghong Huang, Patrick L. Kinney, and Paul T. Anastas, 2020. “Air pollution reduction and mortality benefit during the COVID-19 outbreak in China.” The Lancet Planetary Health 4, no. 6: e210-e212.
- European Environment Agency 2020. “Air Quality in Europe – 2020 report“, EEA Report No 9/2020
- Matkovic Puljic, V., D. Jones, C. Moore, L. Myllyvirta, R. Gierens, I. Kalaba, I. Ciuta, P. Gallop, and S. Risteska. 2019. “Chronic coal pollution–EU action on the Western Balkans will improve health and economies across Europe.” HEAL, CAN Europe, Sandbag, CEE Bankwatch Network and Europe Beyond Coal, Brussels.
- Ju, Min Jae, Jaehyun Oh, and Yoon-Hyeong Choi. 2020. “Changes in air pollution levels after COVID-19 outbreak in Korea.” Science of The Total Environment 750: 141521.
- Transport & Environment, 2018. “Briefing: Dirty diesels heading east”
- Vivid Economics, 2020. “Greenness of Stimulus Index” December 2020 update
- World Air Quality Index, 2021. “Worldwide COVID-19 dataset“
- World Health Organization, 2018. “WHO Global Ambient Air Quality Database (update May 2018)”
- Wu, Xiao, Rachel C. Nethery, Benjamin M. Sabath, Danielle Braun, and Francesca Dominici, 2020. “Exposure to air pollution and COVID-19 mortality in the United States.” medRxiv
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 Political Economics of Long Run Development in Eastern Europe: Insights from the 2019 SITE Academic Conference
Thirty years after the fall of communism, many assume that the economic transition of Eastern Europe and the former Soviet States towards a system of market economy is complete. But the region faces new challenges, of both economic and political kind, which renders a thorough understanding the past even more important. This policy brief is based on the scientific contributions presented at the 7th SITE Academic Conference held at the Stockholm School of Economics from December 16th to December 17th, 2019. Organized by the Stockholm Institute of Transition Economics (SITE), the conference brought together academics from all over Europe and the United States to share and discuss their research on economic and political development in Eastern Europe.
The Imperial and Soviet Periods
In the first section of the conference, papers with a focus on the long-term history of Eastern Europe and its implications for more recent events were presented. Marvin Suesse presented his research on how the Russian State Bank financed Tsarist Russia´s belated industrialization, a question that had been discussed by historians, but never thoroughly analyzed quantitatively. By geo-coding historical manufacturing censuses around the turn of the century and using distance between bank branches and factory location, the causal impact of the expansion of the State Bank is estimated, revealing large effects on firm revenues and productivity. These effects are largest in areas where alternative means of financing were least available and where human capital was more abundant.
Natalya Naumenko presented her findings on the economic consequences of the 1933 Soviet famine, which in terms of casualties was extremely devastating. She uses the meteorological conditions a year earlier as an instrumental variable and finds that the famine, which was mostly a rural phenomenon, had a persistent negative effect on the urban population while the rural population recovered relatively quickly.
Gerhard Toews discussed the long-term consequences on regional development of the displacement of an estimated 3 million “enemies of the people”, political prisoners typically belonging to the elite of the society, into the gulags in the early years of the Soviet Union. Using archival data, he has constructed a large database describing the gulag population in terms of the shares of “enemies” relative to other prisoners and taking into account their socio-economic characteristics i.e. the much higher levels of education of the former group. Exploiting variation within gulags, the results suggest that a historically higher density of “enemies” means higher economic prosperity today as measured by nightlight intensity.
Taking another angle, Christian Ochsner investigated the effects of the Red Army´s occupation on post-war Europe, using the demarcation line crossing the Austrian state of Styria as a natural experiment. His conclusion is that even the temporary occupation affected the region’s long-term development, the main channel being age-specific migration.
Finally, Andreas Stegman offered an analysis of the effects of the 1972 East German Extended Visitors Program. The program reduced travel restrictions for West German visitors traveling to certain districts of East Germany. Using a geographic regression discontinuity design comparing similar districts with and without the program, he shows that included districts indeed received much more visits from West Germany and that their citizens were more likely to protest against the Communist government and less likely to vote for the ruling party. This suggests that face-to-face interaction can influence beliefs and attitudes in non-democratic regimes, in turn influencing individual behavior and societal outcomes during transition.
Corruption, Conflict and Public Institutions
Another topic of the conference was the current role of corruption, conflict, electoral fraud and public sector effectiveness for the region. Scott Gehlbach presented his most recent research on the ownership patterns and strategies of Ukrainian oligarchs before and after the Orange revolution. By mapping oligarchs to changing political leadership, he shows how firm owners in Ukraine take actions to protect their property depending on their connections with the current government. He finds that obfuscation of ownership behind holding companies and complicated structures is a potentially valuable strategy in this environment in general but becomes particularly important when an oligarch loses direct connections to the ruling regime.
Likewise, Timothy Frye analyzed election subversion by employers in Russia, Argentina, Venezuela, Turkey and Nigeria. He finds that in Russia, public sector employers and especially state-owned firms are more likely to influence their employees’ decision to vote than private companies. Furthermore, work place mobilization by employers in Russia is clearly negatively associated with the freedom of the press. Election subversion is more likely to be successful when the degree of dependence of the employee is high and the employer’s potential threats are credible. Among Russian firm officials, the most frequently named motivations for them to practice election subversion are the desire to improve their relationship with the authority and the intention to help their party.
Michal Myck studied the impact of the transition experience on economic development around the Polish-German border. Polish communities close to the border were economically backward at the beginning of the transition but could potentially benefit from trade opportunities with an opening towards the West. Using similar methods to those of Stegman above, and nightlight intensity as a measure of economic activity as for instance Toews, Myck finds significant evidence for economic convergence both between Germany and Poland, and between Polish border regions and the rest of Poland.
Vasily Korovkin presented his research on the impact of the conflict in Eastern Ukraine on trade in non-conflict areas in Ukraine, hypothesizing that the conflict may cause a trade diversion away from Russia, particularly so in areas with many ethnic Ukrainians. Using variation in the share of the Russian speaking population at the county level as well as detailed firm level export and import data, he finds that the decrease in trade with Russia is negatively correlated with the share of the Russian speaking population. Potential mechanisms include a decline in trust at the firm level and changes in local attitudes including consumer boycotts.
Finally, Tetyana Tyshchuk analyzed the effects of a Ukrainian public sector reform on civil servants’ capacity and autonomy. The reform created public policy directorates parallel to the regular bureaucracy in 10 ministries. Members of the directorates were hired based on a different procedure and different merits relative to regular public servants and received significantly higher salaries. Tyshchuk finds that the better paid civil servants indeed score higher on many, though not all, indicators of capacity and autonomy.
Information, Populism and Authoritarianism Today
The final important theme of the conference was the role of information and media, old and new, in today’s politics. In the event´s first keynote speech, Ruben Enikolopov analyzed the political effects of the Internet and social media whose low entry barriers and reliance on user-generated content make them decisively different from traditional media channels. On the one hand, this represents a chance for opposition leaders and whistleblowers to make their voice heard and may improve government accountability. On the other, these media may also become a platform for extremists. Enikolopov presented some of his work analyzing to what extent social media has contributed to fighting corruption in Russia. Using the timings of blog posts by the famous Russian opposition leader Alexei Navalny on corporate governance violations in state-owned companies, he shows that revelations resulted in an immediate drop in the price of the traded shares of the respective companies. He also finds evidence suggesting that Navalny´s blog posts resulted in management changes in these companies. In related papers, he exploits the spread of VKontakte (VK), the Russian version of Facebook, to better understand the influence of social networks on political activism, voting and the occurrence of hate crime. He finds that the spread of VK is indeed causally related to political protests, though not because it nurtures opposition to the government, but rather because it facilitates protest co-ordination. With respect to hate crime, he finds that social media only has an effect in areas where it falls on fertile grounds and where there already are high levels of nationalism. The tentative conclusion is that in Russia – as in Western countries – social media seems to have increased political polarization.
On a similar topic but taking a more theoretical approach, Galina Zudenkova investigated the link between information and communication technologies (ICT), regime contestation and censorship. In a game theoretical framework, where citizens use ICT both to learn about the competency of the government and to coordinate protests, governments can use different tools to censor information to increase their chances of survival. Zudenkova finds that less competent regimes are more likely to censor coordination, whereas intermediate regimes are more likely to focus on censoring content. These theoretical predictions are then tested using country level data.
The targeted use of information has also played a key role in Putin’s Russia according to Daniel Treisman. In his keynote speech, he argued that while the 20th century dictatorships were mainly based on violence and ideology, the 21st century has been characterized by a sizeable shift towards what he calls “informational autocracy”. Constructing a dataset on the methods used by authoritarian regimes to maintain power between 1946 and 2015, he shows that the use of torture and violence peaked among those dictators who took power in the 1980s and has declined since. Furthermore, he highlights a remarkable shift from topics of violence towards topics of economic competency in dictators’ speeches. However, Treisman finds that by instrumentalizing information, dictators fool the public “but not the elite”. In democratic regimes, those with tertiary education tend to rate their political leaders higher than people without tertiary education. In the new informational authoritarian regime, the opposite seems to be the case. According to Treisman, this is because the “informed elite” has a better understanding of the political reality in places where the media is censored, Putin’s Russia being a good example. Treisman concluded that this new model of authoritarianism has become the prevalent model outside of Europe and today also has its advocates inside the European Union.
The conference ended with a final keynote speech by Sergei Guriev on the political economy of populism. Using existing definitions, he first confirmed that Europe has seen a rise in right-wing populism in the last 20 years. Secular trends, such as globalization and new communication technology, but also the recent global financial crisis, are driving factors behind the rise of populist parties. For instance, analyzing regional variation in voting patterns suggests that the Brexit vote was primarily driven by economic motives rather than by anti-immigrant sentiments. Ironically, though, most evidence suggests that populist governments have a below-average economic performance once in office, the US and Poland being notable exceptions. A key point of Guriev’s presentation was that populism seems to be a good method to obtain power, but, once in power, populists tend to be less successful in promoting citizen welfare. These findings seem to be of high importance given the increasing public support for populist parties around the world and in parts of Eastern Europe
The conference was very well received and on behalf of SITE, the authors would like to express their appreciation to all speakers and participants for sharing their knowledge and to Riksbankens Jubileumsfond for financial support. For those interested to learn more about the papers summarized very briefly above, please visit the conference website and the presenters’ websites as indicated in the text and here below.
Speakers at the Conference
Andreas Stegman, briq – Institute on Behavior and Inequality
Christian Ochsner, CERGE-EI and University of Zurich
Daniel Treisman, University of California, Los Angeles
Galina Zudenkova, TU Dortmund University
Gerhard Toews, New Economic School Moscow
Marvin Suesse, Trinity College
Michal Myck, CenEA
Natalya Naumenko, George Mason University
Ruben Enikolopov, New Economic School Moscow
Scott Gehlbach, University of Chicago
Sergei Guriev, Sciences Po Paris
Tetyana Tyshchuk, Kyiv School of Economics
Timothy Frye, Columbia University
Vasily Korovkin, CERGE-EI
Old-Age Poverty and Health – How Much Does Income Matter?
The question concerning the material situation of older people and its consequences for their wellbeing seems to be more important than ever. This is especially true given rapid demographic changes in the Western World and economic pressures on governments to reduce public spending. We use data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to examine different aspects of old-age poverty and its possible effects on deterioration in health. The data contains information on representative samples from 12 European countries including the Czech Republic and Poland. We use the longitudinal dimension of the data to go beyond cross sectional associations and analyze transitions in health status controlling for health in the initial period and material conditions. We find that poverty matters for health outcomes in later life. Wealth-defined and subjective poverty correlates much more strongly with health outcomes than income-defined measure. Importantly subjective poverty significantly increases mortality by 58.3% for those aged 50–64 (for details see Adena and Myck, 2013a and 2013b).
Measuring Poverty
When measuring poverty, the standard approach is to define the poverty threshold at 60% of median equalized income. This standardized measure offers some advantages, such as simplicity and comparability with already existing studies. However, there are valid arguments against its use when analyzing old-age poverty. The permanent-income theory provides arguments against current income as a major determinant of quality of life of older people. Moreover, poverty defined with respect to current income while taking account of household size through equalization, ignores other important aspects of living costs such as disability or health expenditures. Additionally, most analysis using income-poverty measures ignore such aspects as housing ownership and housing costs.
Our analysis examines different aspects of poor material conditions of the elderly. The first poverty definition refers to respondents’ wealth as an alternative to income-defined poverty. Poor households, defined with reference to wealth (“wealth poverty” – WEALTH), are those that belong to the bottom third of the wealth distribution of the sample in each country. For this purpose, household wealth is the sum of household real assets (net of any debts) and household gross financial assets. Secondly, we compare the above poverty measures to a subjective measure of material well-being. This measure is based on subjective declarations by respondents, in which case (“subjective poverty” – SUB) individuals are identified as poor on the basis of a question of how easily they can make ends meet. If the answer is “with some” or “with great” difficulty, individuals in the household are classified as “poor”.
One reflection of potential problems with the standard income poverty measure becomes visible when it is compared with the subjective measure. The graph below shows the differences in country rankings when using one or the other poverty measure. The country with the greatest disproportion is Czech Republic. While being ranked as second according to the income measure, it is ninth according to the subjective measure.
Figure 1. Country Ranks in Old-Age Poverty According to an Income versus a Subjective Measure
Even more striking is the fact that the differences between ranks are not because of over or under classification of individuals as poor, but rather because of misclassification. Figure 2 shows that there is little overlap between different poverty measures. The share of individuals classified as poor according to all three measures is only 7.95%, whereas it is 60% according to at least one of the measures.
Figure 2. Poverty Measure Overlap
Measuring Well-Being
We examine three binary outcomes measuring the well-being of the respondents – two reflecting physical health, and one measuring individuals’ subjective health. The two measures of physical health are generated with reference to the list of twelve symptoms of bad health and the list of twenty-three limitations in activities of daily living (ADLs). In both cases, we define someone to be in a bad state if they have three or more symptoms or limitations. The two definitions are labelled as: “3+SMT” (three or more symptoms) and “3+ADL” (three or more limitations in ADLs). Subjective health “SUBJ” is defined to be bad if the subjective health assessment is “fair” or “poor”. Finally, we also analyze mortality as an “objective” health outcome.
Poverty and Transitions in Well-Being and Health
There is some established evidence in the literature that poverty negatively affects health and other outcomes at different stages of life.[1] At the same time, there is little evidence on how the choice of the poverty measure might result in under- or over-estimation of the effects of poverty. We address this question by examining different poverty measures as potential determinants of transitions from good to bad states of health.
The results confirm that living in poverty increases an individual’s probability of deterioration of health. In a compact form, Figure 3 presents our results from 12 separate regressions (4 outcomes, three poverty measures). Here we report the odds ratios related to the respective estimated poverty dummies. Individuals classified as poor according to the income measure are 37.7% more likely to report bad subjective health in a later wave of the survey than their richer counterparts; they are 4.5% more likely to suffer from 3 or more symptoms; 18.7% more likely to suffer from 3 or more limitations; and 5% more likely to die. The last three effects, however, are not statistically significant.
In contrast, the effects of wealth-defined poverty and subjectively assessed poverty are 2-8 times stronger than those of income poverty, and they are also significant for all outcomes but death. Overall, wealth-defined poverty and subjective assessment of material well-being strongly correlate with deterioration in physical health (exactly the same goes for improvements in health, see Adena and Myck 2013b).
Figure 3. Poverty and Transitions from Good to Bad States Overlap
Poverty and Mortality in the Age Group 50-64
Our analysis reveals differences between age groups and confirms the decreasing importance of income (and thus income defined poverty) with age. As compared to the average effects presented in Figure 3, for the younger age group 50–64 income poverty proves more important as a determinant of bad outcomes, with transition probabilities between 20 and 40% for all outcomes (see Figure 4). The magnitudes are closer to those of other poverty measures, but still lower in all cases. Importantly, we find that wealth-defined and subjective poverty is an important determinant of death in the age group 50–64.
Figure 4. Poverty and Transitions from Good to Bad States 50-64
Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).
Conclusions
The role of financial conditions for the development of health of older people significantly depends on the measure of material well-being used. In this policy brief, we defined poverty with respect to income, subjective assessment, and relative wealth. Of these three, wealth-defined poverty and subjective assessment of material well-being strongly and consistently correlate with deterioration and improvements in physical and subjective health. We found little evidence that relative income poverty plays a role in changes in physical health of older people. This suggests that the traditional income measure of household material situation may not be appropriate as a proxy for the welfare of older populations, and may perform badly as a measure of improvements in their quality of life or as a target for old-age policies. To be valid, such measures should cover broader aspects of financial well-being than income poverty. They could incorporate aspects of wealth and the subjective assessment of material situations as well as indicators more specifically focused on the consumption baskets of the older population.
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References
- Adena, Maja and Michal Myck (2013a): “Poverty and transitions in key areas of quality of life”, in: Börsch-Supan, Axel, Brandt, Martina , Litwin, Howard and Guglielmo Weber (eds.) “Active Ageing and Solidarity between Generations in Europe – First Results from SHARE after the Economic Crisis.”
- Adena, Maja and Michal Myck (2013b) Poverty and Transitions in Health, IZA Discussion Paper 7532, IZA-Bonn.