Location: Eastern Europe

Addressing the Covid-19 Pandemic: Vaccination Efforts in Free Network Countries

COVID-19 mask and vaccine bottle representing vaccination efforts

COVID-19 vaccination efforts are now starting in several countries around the globe and many believe that this is the way out of the pandemic crisis. The Stockholm Institute of Transition Economics (SITE) in collaboration with the FREE Network is delighted to invite you to a webinar to share insights and knowledge about how countries in Eastern Europe and around the Baltics are handling the vaccination efforts against the COVID-19 crisis.

How Are Countries in Eastern Europe, Around the Baltic Sea, and in the Caucasus Managing Vaccination Efforts?

With the pandemic still ongoing around the world and in many cases having entered both a second and third wave of infections and deaths—vaccination is urgently needed. Since the first vaccines against COVID-19 were approved, governments around the world are now pushing forward with the vaccination efforts – all with different strategies and methods. How are countries in Eastern Europe, around the Baltic Sea region and in the Caucasus region managing vaccination efforts in their countries and what are the key factors of success and failure? How different are the strategies?

Since the FREE Network includes research and policy institutes in Belarus (BEROC)Latvia (BICEPS)Russia (CEFIR at NES)Poland (CenEA)Georgia (ISET PI)Ukraine (KSE) and Sweden (SITE) the upcoming webinar will provide a comprehensive regional perspective on the vaccination efforts of different strategies implemented in these countries. Furthermore, the webinar will also shed light on how people have responded to vaccination offers; how other countries are being portrayed in the national media; and what the current discussions focus on.

The webinar is part of a series of online discussions aiming to provide a regional overview updates as well as in-depth analysis of specific topics related to the COVID-19 pandemic.

Join the webinar, learn more about the vaccination efforts in FREE Network countries and ask questions directly to distinguished panelists and experts:

Speakers

  • Iurii Ganychenko, Senior researcher at Kyiv School of Economics (KSE/Ukraine)
  • Jesper Roine, Professor 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 MyckDirector of the Centre for Economic Analysis (CenEA/ Poland)
  • Natalya Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR at NES/ Russia)
  • Pavlo Kovtonyuk, Head of Health Economics Center at Kyiv School of Economics (KSE/Ukraine)
  • Sergejs Gubins, 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)

Chair/Moderator

  • Torbjörn Becker, Director of the Stockholm Institute of Transition Economics (SITE)

Register here

RSVP Date: Thursday, February 11, 2021, 10:00am – 12:00pm (CET, Sweden)

Location: Online. A link to the webinar will be sent to you 4-5 hours ahead of the start of the webinar.

Registration: Will remain open until the start of the webinar.

Pollution and the COVID-19 Pandemic: Air Quality in Eastern Europe

Factory with chimney smoke representing air-quality 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:

  1. How did air pollution in Eastern Europe compare to Western Europe prior to the pandemic?
  2. What are the main sources of air pollution in Eastern European cities and can they be addressed by policymakers?
  3. 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. ReutersThe 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 Impact of the COVID-19 Pandemic in Eastern Europe | Key Points From the 2020 SITE Development Day Conference

A black and white colour image with people walking through the tunnel wearing masks and representing COVID-19 in Eastern Europe

After having been relatively mildly affected in the first wave, Eastern Europe is currently in the midst of the second wave of the COVID-19 pandemic with much higher levels of infected and dead compared to the spring. This health crisis not only has economic consequences but also has contributed to political instability in parts of the region. This policy brief shortly summarizes the presentations and discussions held at the SITE Development Day 2020 Conference, focusing on the consequences of the COVID-19 pandemic in Eastern Europe. 

A Swedish Government Perspective

The conference started with the Swedish Minister of International Development Cooperation, Peter Eriksson, discussing the current situation in Eastern Europe with a particular focus on the partnership with Sweden.

According to Minister Eriksson, Swedish foreign policy in general, and foreign aid policy in particular, has historically paid too little attention to Eastern Europe. He has therefore emphasized that Swedish aid should be used to promote democracy and human rights in the region. As the pandemic has exacerbated global anti-democratic trends and intensified existing inequalities, international support and cooperation have become more essential than ever.

Minister Eriksson mentioned several priority areas of Swedish aid policy in the region, such as the fight against corruption, economic reforms for poverty alleviation, gender equality, and media freedom. Emphasizing the importance of the latter, Minister Eriksson mentioned education for journalists and financial support for small independent media as important Swedish efforts in the region. He stressed that the protection of pluralistic media is also a military security matter, as countries like Georgia and Ukraine have been targets of foreign disinformation campaigns. The importance to support democracy and civil society was also illustrated by the case of Belarus, where all ongoing projects in partnership with the state or state-affiliated organizations have been suspended. The Swedish government has successfully implemented regional projects in energy efficiency and water purification, although Minister Eriksson underlined that the need for measures to slow down climate change is intensifying.  

The important role of European Union membership was also mentioned. Minister Eriksson argued that the incentives created by potential EU membership have been the main drivers of democratization, modernization, and poverty reduction as well as progress towards greener economies in the region.

In response to the pandemic, Sweden, as well as the European Union, have increased aid transfers to Eastern Europe. Minister Eriksson underlined, though, the need to not only support immediately affected sectors and outcomes, as the pandemic has many serious spillover effects in other areas already in need of help prior to the crisis.

The Economic Outlook for the Region

The second section of the conference provided a current account of the economic situation in the region by two speakers from different sectors.

Alexander Plekhanov, director for Transition Impact and Global Economics at the European Bank for Reconstruction and Development (EBRD), shared results from an EBRD survey on the impact of the pandemic. The survey was conducted in August and covered 8 emerging economies in Eastern Europe and 6 more advanced countries for comparison.

Analysis of the survey responses shows that the impact of the crisis is very broad. The share of respondents that had lost their job was 15% in emerging economies, and almost twice as high in advanced economies. Many factors contributed to this gap. One affected area was tourism, with international tourism being particularly important in many emerging economies, and hard to replace with increased domestic tourism. The outbound relative to inbound tourism for countries like Sweden and the UK equals a factor of 3 and 2 respectively, while the corresponding in emerging economies is often below 1.

Compared to the 2008 financial crisis, the economic impact over the first five months of the pandemic was at similar aggregate levels, but more unequal across socio-economic groups. For instance, job losses were higher among the young and those with lower income and with less education. Yet, the overall impact in emerging economies was 10% less unequal than in advanced economies due to differences in the structures of economies and the feasibility of working from home.

Fredrik Rågmark, the CEO of Medicover, a healthcare and diagnostics services provider operating in the region in the last 25 years, provided insights from a business perspective.

Similar to Minister Eriksson, Rågmark argued that, for Medicover, the biggest change in the region over recent years has been related to EU integration, and in particular to Poland becoming an EU Member. Rågmark noted that the change was not limited to Poland: all the countries in the region are on a trajectory of change but at different stages. In his mind, the biggest difference between the emerging Eastern Europe and the West is that people have higher expectations about the future in the East.

Rågmark recognized that corruption has been a major challenge for the region in attracting business and investors, but also that it has gotten significantly better in recent years. The EU integration process has been essential there, as membership and continued support relies on institutional reforms to improve governance and ensure political accountability. Recognizing the risk that governments lose incentives to continue reforms once membership is secured (currently exemplified by the policies in Hungary and Poland), Rågmark yet emphasized that the European Union has been extremely successful in improving the business climate in the region and should receive more recognition than it often does.

As for the COVID-19 crisis, Rågmark argued that Plekanovs description was very representative of what he has seen in Eastern Europe. Medicover experienced a drastic falloff in late March when people were not allowed to visit the hospital unless they had acute symptoms. When countries re-opened in the summer, the company had a strong rebound of replaced demand from the lockdown. Also, Medicover has contributed significantly to the testing effort across the region. Due to the challenges associated with the skyrocketing demand for PCR testing, many countries in Eastern Europe that previously only allowed the public sector to treat inpatient COVID-19 cases, have opened up ambulatory services to the private sector. In terms of scaling up testing capacity, the private sector has been very important. Medicover is now a major provider of PCR-testing in Ukraine and Poland, and the single largest provider in Romania.

Economic Policy Responses to the Crisis: Regional Experiences

In this section, experts from the FREE network provided brief overviews of the current situation in their respective countries, as well as the major developments during the year.

Belarus

The Academic Director of BEROC, Kataryna Bornukova, provided an alarming description of recent developments in Belarus. Even before 2020, the prospects of the Belarussian economy did not look great. As relations with Russia started to worsen, the year began with shortages in the oil supply which contributed to GDP contraction already in the first quarter. When the pandemic hit Belarus in the spring the government neglected its severity. Initially, no measures of economic relief were introduced and there are valid suspicions that the official COVID-19 statistics were inaccurate. Eventually, the government created incentives for state-owned companies to keep up output, slowing down the GDP contraction in the second quarter. However, these measures are now a source of financial risk for the whole country as the state has accumulated huge inventories and substantially increased public debt. Unfortunately, during the second wave, policy responses are still lacking and the ongoing political crisis worsens the situation as it hampers economic development through increased uncertainty and lowered public trust.

Poland

As for Poland, Michal Myck, director of CenEA, argued that development during the crises has been mixed both in terms of the pandemic itself and government response.

While infections were at low levels during the first wave in April, they increased sharply during the second wave at the end of October. Similar to Belarus, there have been significant political developments over the year such as the presidential election campaign and the “Women’s Strike”. Myck suggested that these events have complicated a clear strategic response to the virus. During the summer, the government shifted its attention away from preparations for the second wave, towards the July elections. The first wave was met by fiscal and monetary stimulus packages. Although employment and growth have not fallen that much relative to neighboring countries, Myck argued that Poland will be left with a significantly higher level of public debt and other challenges when the pandemic is over. 

Georgia

Giorgi Papava, Center Head at ISET-PI, explained that the Georgian government declared a state of emergency and lockdown in March, despite the low number of infections at the time. From April to June, the economy then experienced a 13% drop in GDP. After the economy re-opened at the end of June, it has shown a slight recovery over the summer. Unfortunately, it was followed by a sharp increase in infections in the autumn. This second wave was not met by similar restrictions until after the elections at the end of November, again suggesting the role of politics in the pandemic response in the region. In terms of economic impact, the most severe blow for Georgia was the sharp decline in tourism affecting many sectors including hospitality and food services, construction, arts, entertainment, and recreation. 

Ukraine

Olena Sholomytska, Senior Researcher at KSE, explained how Ukraine, like most other countries in the region, experienced low reported infection rates in the spring, though high detection rates and low levels of testing may suggest that real infection rates were higher. The summer was followed by a sharp increase in infections and the situation has worsened since then. The economy saw a 7.5% drop in GDP in the second quarter, partly due to a strict lockdown policy, followed by a slight recovery in the third. The Ukrainian government has introduced various monetary and fiscal measures for both households and firms including cash allowances for self-employed, small firms, and people with temporary pay cuts, as well as long-term financing for banks up to 5 years. Currently, the government is reluctant to enforce stricter measures to prevent the second wave of infections mainly for political reasons. Ukrainians are becoming less afraid of the virus and more discontent with the restrictions, so the government is concerned about taking an unpopular decision.

Russia

Natalya Volchkova, Director at CEFIR at NES, explained how Russia, after a relatively calm summer, was hit by the second wave in October as the number of infections and COVID-19 deaths reached their highest levels since the onset of the pandemic. As far as economic performance is concerned, monthly indicators of economic activity show a sharp decline at the beginning of March and a slight recovery since then. However, when looking at month-on-month comparisons, economic performance is significantly lower in every month throughout 2020 compared to 2019.

The support measures introduced during the spring and summer constituted 3.7% of GDP. While most stimulus was allocated to the corporate sector (2.1%) households also received a significant amount of support (1.6%). The measures targeted to help household income included: cash transfers to families with children; increased unemployment benefits; 2019 tax-return for self-employed; extra payments to medical specialists; and credit restructuring and penalty-free payment deferrals for COVID-19 infected. The support dedicated to the business sector included: tax and credit payment deferrals; bankruptcy moratorium for 6 months; reduction in property tax: and subsidies to backbone enterprises. The support measures are expected to increase GDP growth by 1.8 percentage points by boosting household consumption, corporate inventory, and investments.

Latvia

Sergej Gubin, Research Fellow at BICEPS, described the epidemiological impact of the pandemic in the spring as hardly noticeable in Latvia. Although, the country currently has the 3rd lowest COVID-19 mortality rate in the EU, infections and mortality have increased quite dramatically during the fall.

While the restrictions introduced in the spring did not include a strict lockdown or a mandatory mask policy, the government closed borders, schools, and kindergartens. Following the second wave, the restrictions adjusted to including a mask policy, open borders, and 5-12 graders on distance learning.

The economic policy response has included downtime benefits for employees of firms with a reduction in turnover of 30% or more, temporary tax reliefs, and sick leave benefits for parents with young children on distance learning. The drop in GDP for 2020 is projected to be 7% and unemployment is expected to increase by 7.7%.

The Implications of the Pandemic for Gender Inequality

It is widely known that the pandemic has had catastrophic consequences for health and economic activity. Many experts, though, have also expressed concerns about its impact on gender equality and the welfare of women. On the health side, men and women have been shown to be equally susceptible to infection, however among those that get infected women have significantly lower mortality rates than men. Monika Oczkowska, Senior Researcher at CenEA, showed that about 40 % of deaths in Poland were women, which is very similar to Western European countries, whereas excess mortality has been particularly high among men in older age groups.

The pandemic has also impacted gender inequality through the labor market. In countries like Ukraine and Georgia, the pandemic has significantly worsened pre-existing inequalities. In the latter, the number of registered unemployed increased by 16 000 in the second quarter, and among them, 90% were women, according to Yaroslava Babych, Policy Center Head at ISET-PI. Also, among the 44 000 workers that lost their employment during lockdown in the spring a vast majority were women. Partly, the reason for this is that the restrictions affected sectors that were predominantly female such as restaurants, cafés, and retail, as well as arts and entertainment.

In Belarus, a country with relatively high female labor force participation, the impact on gender inequality changed over time. In the Belarussian labor market, women are highly concentrated in the hospitality and public sector, and men in the industrial sector. After the first wave in the spring, women were worst affected, both in terms of unemployment and loss of income, which was largely driven by the impact on the hospitality industry. Over time men became more affected as the industrial sector took a hit, whereas women benefitted from steady employment within the public sector. The gender distribution in the Ukrainian labor market is similar to the Belarusian. Women are concentrated in sectors that are economically vulnerable to the crisis but also in those that are critical for everyday life such as the health and education sectors. In other words, in these countries some women are at high risk of losing their job while others, that are less at risk of an economic shock, often are particularly likely to be exposed to health shocks.

From a more positive perspective, the crisis has also brought about structural changes to the labor market that could potentially improve gender equality. In Russia, workplaces have started to provide more flexible working conditions which have enabled more women to work remotely from home.

One serious consequence of the crises is an increase in domestic violence as the pandemic has exacerbated things that are known to increase conflict and violence within households. Maria Perrotta Berlin, Assistant professor at SITE, argued that mobility restrictions have increased the time spent with family members, increased isolation from social networks and support organizations, and increased stress caused by economic insecurity. According to the international ombudsman of Russia, the number of distress calls relating to intimate partner violence has increased by 150% during the pandemic, compared to an estimated average increase of 60% in Europe during the same time.

Political Implications in the Region with a Special Focus on Belarus and Russia

The final section of the day focused on political developments in Russia and Belarus in the times of the COVID-19 pandemic, two countries with close historical, political and economic ties. SITE invited two experts on the politics in respective countries: Elena Panfilova, Founder of the Center for Anti-corruption Research and former Chair of Initiative Transparency International – Russia, and Artyom Shraibman, founder of Sense Analytics, a political consultancy in Minsk and nonresident scholar at the Carnegie Moscow Center.

Panfilova gave a comprehensive narrative of the recent political developments in Russia related to the onset of the pandemic. Panfilova argued that the political response to the pandemic in Russia changed over time. In the spring, the government and political elites had a relatively active response and clear communication with the public. However, when the second wave started in September the government largely stayed silent. According to Panfilova, the reason for this is that Russian politicians started to anticipate the important 2021 regional elections and that they found it hard to communicate with the public without challenging their future political interests as the crisis response had been met with much discontent. This discontent, Panfilova argued, had to do with Russia’s vertical system of accountability being very ineffective in dealing with a horizontal problem such as COVID-19. The response system would have needed help across the political spectrum and would have benefited from more transparency to fight the pandemic; instead, the government continued to restrict political freedom and civil rights.

Reacting to the introduction by Panfilova, Shraibman argued that there is no historic example of a situation where the response to similar situations have differed so much between the Belarusian and Russian governments. The Belarusian regime’s response, in contrast to the Russian, was close to non-existent in the first wave and this continued up until the autumn when the government started to introduce restrictions in response to the second wave of infections.

The pressure of the pandemic has revealed the weaknesses and flaws of governments around the world and not least in Belarus. Although there are several reasons for the political crisis such as the stagnation of the Belarus economy, Shraibman argued that the mismanagement of the pandemic became the tipping point.

Shraibman explained how the Belarus regime has always tried to sell a paternalistic identity and has presented itself as a stable and fair welfare system that cares for the poor and the vulnerable. The mishandling of the COVID-19 pandemic shattered this identity in the eyes of the public. The rhetoric and state-level deception during the first wave irritated a lot of people as the state-owned media outlets often accused the sick of being weak and ridiculed people for wearing masks. As many Belarusians saw relatives die and doctors started to contradict the narrative of the state, people were reminded of the Soviet government’s concealment of the Chernobyl disaster.

These developments created stress on the Belarusian society right before the presidential elections in August since the frustration that had been accumulated was channeled into political activity. During the pandemic, people learned how to organize and coordinate crowdfunding initiatives to support doctors and similar initiatives. This self-organization infrastructure transferred to the opposition campaign and is now used to support victims of political repression.

During the second wave, the government started exploiting the crisis to restrict political freedom. For instance, independent observers were not allowed to observe electoral polls, and political prisoners were not allowed to meet with lawyers. These and similar actions have further aggravated the political discontent with the regime in the country. Shraibman concluded that groups in society that previously have been apolitical now have become politicized, as they have personally experienced the repressive measures previously targeted primarily to the Belarusian opposition.

Concluding Remarks

As in previous years, the Development Day conference offered us an opportunity to invite a diverse group of experts, politicians, and practitioners to discuss a current and important topic in the area of development and transition. The different perspectives highlighted the multifaceted impact of the COVID-19 pandemic on Eastern Europe, as well as the continued engagement of Swedish society in the region. Unfortunately, the pandemic also prevented us from meeting in person this time, but we hope that next year we will be able to meet again at the Stockholm School of Economics.  

List of Participants

  • Peter Eriksson, Minister for International Development Cooperation, Sweden.
  • Alexander Plekhanov, director for Transition Impact and Global Economics, EBRD.
  • Fredrik Rågmark, CEO Medicover, Sweden.
  • Kataryna Bornukova, Academic Director BEROC, Minsk, Belarus.
  • Michal Myck, Director CenEA, Szczecin Poland.
  • Giorgi Papava, Center Head at ISET-PI, Tbilisi, Georgia.
  • Olena Sholomytska, Senior Researcher KSE, Kyiv, Ukraine.
  • Natalya Volchkova, Director CEFOR at NES, Moscow, Russia.
  • Sergej Gubin, Research Fellow BICEPS, Riga, Latvia.
  • Lev Lvovskiy, Research Fellow BEROC, Minsk, Belarus.
  • Monika Oczkowska, Senior Research Economist CenEA, Szczecin, Poland.
  • Yaroslava Babych, Head of Macroeconomic Policy Research Center ISET-PI, Tbilisi, Georgia.
  • Aleksandr Grigoryan, Associate Professor American University of Armenia, Yerevan, Armenia.
  • Olga Kupets, Policy Professor KSE, Kyiv, Ukraine.
  • Maria Perrotta Berlin, Assistant Professor SITE, Stockholm, Sweden.
  • Artyom Shraibman, founder of Sense Analytics and nonresident scholar at the Carnegie Moscow Center.
  • Elena Panfilova, Founder of the Center for Anti-corruption Research and former Chair of Initiative Transparency International – Russia.

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.

Public Healthcare Expenditures in Transition Countries: Does Government Spending Respond to Public Preferences?

An image of surgery room with two doctors in green protection gear representing public healthcare expenditures

The transition from centrally planned to free-market economies in 1989 initiated a period of social and economic upheaval in post-communist countries, which affected healthcare quality, expenditures, and outcomes. We use data from the Life in Transition Survey (LiTS) to demonstrate that in spite of improvements across various measures of these facets of the healthcare system, it remains the first choice for additional government spending among the public in all countries of the region included in this study. Preferences in priorities for extra budget spending were similar among men and women in respective countries, but the preference for additional healthcare spending was stronger among women than men. The transition countries are compared with Germany and Italy – two Western European LiTs survey participants, countries with higher spending, and better healthcare outcomes.

Introduction

Across the globe, the outbreak of the COVID-19 pandemic has brought a new spotlight to the preparedness of healthcare systems for profound shocks (Anser et al, 2020). Critical care is a particularly costly element of healthcare provision, and thus, under-resourced systems are uniquely susceptible to spikes in mortality resulting from an oversaturation of intensive care units during an epidemiological crisis of this sort. (Fowler et al, 2008; Mannucci et al, 2020) Considering the widespread discussion surrounding health system capacity and the necessity for implementing economically painful lockdowns when those limits are reached, pressure from society to increase public spending may grow even further. With these developments in mind, in this policy paper, we confront past expressions of preferences regarding public expenditures with changes in government spending on healthcare between 2006 and 2017. The analysis draws on the one hand on the data from the Life in Transition Survey (LiTS), and on the other on publicly available data on government expenditures and outcomes.

In the context of preferences for additional public spending, we present a descriptive summary of trends in government expenditures on healthcare in Armenia, Belarus, Estonia, Georgia, Latvia, Lithuania, Moldova, Poland, Russia, and Ukraine. We include Italy and Germany as wealthier Western benchmarks, for which the data became available in the second wave of the survey in 2010. Data on public healthcare spending shows that despite a clear and strong public preference for increased investment in healthcare provision, additional spending as a proportion of total government expenditures between 2006 and 2017 has been moderate in most countries, and even negative in some. It must be underlined that expenditures are not always reflected in healthcare outcomes, quality, and coverage. Issues of efficiency, system design, and underlying health conditions of the population play a significant role in the returns on investment. For instance, the United States has spent drastically more per capita on healthcare than any other country and yet ranked lowest in the Healthcare Access and Quality (HAQ) Index among comparable countries (Fullman et al, 2016). However, due to the focus of the survey on government spending, we emphasize government expenditures on healthcare as a pertinent measure, especially in relation to overall GDP, per capita spending, and the public budget as a whole.

There is mounting evidence that one of the most important elements in the mitigation of COVID-19 mortality is the ability to expand system capacity and acquire the necessary equipment (e.g. respirators, ventilators) while ensuring that there is equitable access to measures for spread prevention (e.g. testing) (Khan et al, 2020; Ranney et al, 2020; Wang and Tang, 2020). The increasing pressure on healthcare systems, coupled with the additional fiscal strain resulting from the economic fallout of the pandemic, could lead to further divergence between public preferences and government spending on healthcare.

Healthcare Systems During the Transition

The ability of transition countries to absorb the risks and short-term economic shocks associated with pivoting from a centrally planned to a free-market economy has had dramatic implications for healthcare systems. Although countries in this region were divergent in terms of underlying health conditions, levels of expenditures, and health outcomes, most of them fell victims to deficient funding and additional health risks associated with the initial increases in poverty that were commonplace (Adeyi et al, 1997)

Compared to other transition countries, Georgia and Armenia faced a sharper economic collapse as well as armed conflicts, which caused scarcity in the availability of public healthcare providers and spikes in out-of-pocket expenses. Belarus was slower in the implementation of economic reforms and faced issues of fiscal sustainability further down the line (Balabanova et al, 2012). However, following this short tumultuous period, countries transitioning away from centrally planned economies have generally invested heavily in healthcare since the early 1990s. In many cases, these investments were facilitated by rapid GDP growth and accompanied by significant improvements in life expectancy. For example, between 1989 and 2012, Latvia, Lithuania, and Poland increased their per capita healthcare expenditures by more than 1,000 PPP per year, with an increase in life expectancy ranging from 1.7 years in Lithuania to 5.8 years in Poland (Jakovljevic et al, 2015). Despite heterogeneous and extensive reforms in many of these countries, as well as mixed results in measurements of efficiency and outcomes, healthcare expenditures consistently rank as the top priority for further government spending among both men and women in each country. This consistency lends itself to further policy considerations.

Preferences for Government Spending in Transition Countries

As is demonstrated by Figure 1, in 2016, healthcare was the most common answer to the question – “Which field should be the first priority for extra government spending?”- for all ten post-transition countries included in our analysis (the other options were: education, housing, pensions, assisting the poor, public infrastructure, the environment, and other). The survey was carried out on a representative sample that covers approximately 1,000+ respondents from each of the 29 countries in wave I and up to 1,500+ respondents from each of the 34 countries in wave III (EBRD: LiTS, 2020). Despite intercountry differences, in 2016 healthcare persisted as the top priority for both men and women in every transition country we studied apart from Belarus. While healthcare remained the top priority on average, men expressed a higher preference for additional investment in education. In the countries where preferences for health were particularly strong, healthcare was the first priority for as many as 53.5% of Latvians, 47.7% of Poles, and 43.9% of Moldovans (Figure 1a). Notwithstanding some fluctuations in scale, these preferences were not only common across countries but also across time, with people expressing very similar preferences in the first two waves of the survey in 2006 and 2010. (See Annex Figure A1 and Figure A2). While healthcare remained a popular choice in Germany and Italy, spending on healthcare as a percentage of GDP was nearly twice that of any transition country in Germany. There, education outweighed healthcare among men and women in both available waves (II and III), while pensions surpassed healthcare among men in the latter wave. In Italy, despite a more comparable level of healthcare spending relative to the transition countries, a drastic shift took place as healthcare fell from being the first priority by a large margin of 24.9 percentage points (pp) in 2010 to becoming the second priority after pensions in 2016. This can likely be attributed to the prominence of pensions as a major political campaign issue following the austerity-driven reforms of 2011 (Alfonso and Bulfone, 2019).

 

Figure 1: 1a (left) : Preferences for additional government spending, 2016. / 1b (right): Preferences for additional healthcare spending by gender, 2016

Source: LiTS Wave III data (2016). Notes: Figures show proportions of declared preferences as replies to the question: “Which field should be the first priority for extra government spending?” For clarity of exposition the category ‘social assistance’ aggregates first priority choices of ‘assisting the poor’ and ‘housing’; the category ‘other’ also includes the least popular choices ‘public infrastructure’ and ‘environment’.

Moreover, it is evident that men and women within countries have rather similar preferences, as far as extra government spending is concerned. Not only is healthcare the first priority in all ten transition countries, but their second, third, and fourth choices are also very similar. When digging deeper into the differences that do exist, in every country except for Georgia women had a stronger preference for healthcare than men, and by as much as 8.8 pp, 8.4 pp, 7.8 pp, and 7.9 pp in Latvia, Germany, Belarus, and Russia respectively (Figure 1b). Conversely, in every case except for Georgia and Ukraine, men had a stronger preference for additional spending on education than women, most notably in Armenia – by 7.8 pp, Germany – by 5.7 pp, Lithuania – by 4.6 pp and Poland – by 3.9 pp. It is apparent that despite rapid investment in healthcare over the first two decades of the transition, there remains a widespread desire for further expansion of expenditures in this area.

Trends in Government Expenditures, 2006-2017

Considering the primacy of healthcare as the priority for additional government spending in all ten studied transition countries, we look at trends in aggregate statistics on government expenditures on healthcare over the surveyed period to explore the extent to which these preferences have been reflected in government spending. Taking the most basic measure into account in Figure 2a, i.e. public health expenditures as a percentage of GDP, among the transition countries only Georgia and Estonia have significantly increased their healthcare expenditures, by 1.6 pp and 1.2 pp, respectively. Lithuania, Poland, and Russia saw more moderate increases in the range of 0.6 pp and 0.2 pp. Other countries have remained essentially stagnant, apart from Moldova and Ukraine which saw a notable drop of 0.8 pp.  Considering that this measure is sensitive to fluctuations in GDP growth, we also consider public health spending as a proportion of all government expenditures (see figure A3 in the Annex), which is a better indicator of government priorities for additional spending from 2006 until 2017. Georgia was the only transition country with a significant increase in healthcare spending proportional to total government expenditures, nearly doubling it from 5.2% to 9.5%. Belarus, Estonia, Lithuania, Poland have implemented a more moderate redirection of the budget towards healthcare, increasing proportional expenditures by a factor of 1.26, 1.15, 1.21, and 1.21 respectively. In spite of public preferences, Armenia decreased the proportional share of the budget dedicated to healthcare by as much as 2.6 pp, Moldova, Russia, and Ukraine by 1.3 pp, and Latvia by 0.8 pp. Regardless of the direction of the trend, notwithstanding some slight convergence, no transition country spent as much of its budget on healthcare as Italy and Germany. The latter spent nearly two to four times as much on healthcare as a proportion of total expenditures compared to the studied transition countries, and this gap has been widening relative to all of those included in the analysis, apart from Georgia.

Figure 2: Public healthcare expenditures (% of GDP)

Source: WHO, 2020

While expenditures per capita are less indicative of government priorities in the budget, they are a better comparative measure for assessing the changes in healthcare provision, barring differences in efficiency. This comes with a huge caveat, namely that it is well established in the literature that additional healthcare expenditures often translate into “small to moderate” direct improvements in healthcare quality and outcomes due to inefficient spending or underlying factors (e.g. lifestyle choices, poverty) that are not addressed by investment in the healthcare system itself (Hussey et al, 2013; Self and Grabowski, 2003).  Nevertheless, this measure is more likely to translate to an improvement in the quality of care each person receives, and the data paints a more positive picture considering the clear preference of both men and women for higher spending. In Figure 3 we present healthcare expenditures per capita in USD, and apart from Italy and Ukraine, all of the countries have significantly increased spending between 2006 and 2017. While expenditures per capita in transition countries are dwarfed by Germany and Italy, Estonia, Georgia, and Lithuania have more than doubled their expenditures, and Armenia has more than tripled. Belarus, Latvia, Poland, Moldova, and Russia have also significantly increased their per capita spending on healthcare, by factors in the range of 1.54 and 1.91. However, while expenditures per capita is one indicator of improving healthcare quality, it does not identify government priorities and is largely dependent on overall economic growth (Fuchs, 2013; Bedir, 2016).

Figure 3: Health care expenditure per capita, USD

Source: WHO, 2020

In every country we include, increasing healthcare expenditure per capita is accompanied by advancements in many measures of healthcare outcomes for men and women. Between 2006-2017, life expectancy at birth increased across the board, with men in Russia experiencing the greatest improvement of 7.1 years (Figure 4a). These are promising trends – for women, life expectancy at birth improved by a larger margin in each transition country than in Germany or Italy, and the same can be said for men in every country apart from Armenia. Furthermore, the Healthcare Access and Quality (HAQ) index, which is composed of 32 indicators related to preventable causes of mortality, has improved across all 12 countries between 2005-2016. The change was most notable in Armenia, Belarus, Estonia, and Russia, constituting as much as 8.7, 10.2, 8.9, and 8.9 points out of a hundred, respectively (Figure 4b). These trends indicate convergence in the quality of healthcare as they significantly outpaced improvements in the HAQ index in Italy (3.1 points) and Germany (3.9 points). As of 2016, among the countries of interest, Georgia (67.1 points) and Moldova (67.4) had the lowest scores, while Germany (92.0) and Italy (94.9) scored highest, as could be expected based on healthcare spending measures presented in Figures 2 and 3.

Figure 4: 4a (left): Change in life expectancy, 2006-2017 / 4b (right): HAQ index

Source 4a: The World Bank (2020). Source 4b: Institute for Health Metrics and Evaluation (2018). Notes: The HAQ index is composed of 32 indicators, each related to a cause of death that is preventable with the proper healthcare. The scale ranges from 0 (worst) to 100 (best).

However, as presented in Figure 5, there is no clear relationship between the strength of the preference for additional healthcare spending and the scale of expansion in spending. Taking three of the four countries (Armenia, Belarus, and Russia) with the greatest improvement in the HAQ index as an example, there was virtually no change in healthcare spending as a percentage of GDP over the same period. These countries were also different in terms of how strong the preferences were for additional spending on healthcare as the first priority in 2006.

Figure 5: Public preferences and government healthcare spending (% of GDP)

Source: LiTS Wave I data (2006), The World Bank (2020). Notes: Germany and Italy were not included in the 2006 wave of the LiTS survey; thus, they are not shown here.

Conclusion

As we have demonstrated in this brief, in the ten post-communist countries for which we have analyzed LiTS data, there was a consistent and common preference for healthcare as the first priority for extra government spending between 2006 and 2016. We also find that in each country except Georgia, on average, women had a stronger preference for additional public healthcare spending, supporting a wealth of literature that suggests that women utilize healthcare services more frequently and spend more out of pocket on healthcare than men (Owens, 2008; Cylus et al, 2011; Williams et al, 2017). However, over the period we study, these preferences have not translated directly into a reallocation of budgetary resources. The countries with the strongest preferences for additional healthcare spending in 2006 did not experience the highest increases in any of the discussed measures of public healthcare expenditures since then.

People living in Italy and Germany chose an increase in public spending on healthcare as their first priority less frequently than residents of post-transition countries. Better understanding these differences requires further research, but there is likely a combination of factors that play into this effect. For one, wealthier Western countries performed better when looking at simple measures of healthcare outcomes such as life expectancy and deaths from non-communicable diseases (WHO, 2020), and hence other priorities may have gained in salience. Furthermore, they allocated a greater proportion of the public budget towards healthcare. This in part stems from the significant challenges associated with the transition following 1989. Healthcare systems in post-communist countries experienced a fiscal shock when joining the global economy, with the loss of centrally controlled price mechanisms causing an increase in the relative prices of healthcare inputs such as medicines and equipment (Obrizan, 2017). This was exacerbated by a shrinking capability of governments to spend more on healthcare related to the general economic shocks at that time and led to the passing over of costs to patients in the form of out-of-pocket expenses (Balabanova, et al. 2012).  Although access to healthcare and the quality of that care have improved after the transition (Romaniuk and Szromek, 2016), these have failed to converge towards Western European countries on a number of substantial measures up to this point. Before the commencement of the COVID-19 pandemic, government healthcare spending did not reflect the preferences of the public in any of the ten studied transition countries. The outbreak of the pandemic has not only intensified the pressure on the healthcare system but also brought about a number of negative economic consequences. This combination can be expected to simultaneously increase the strain on the public budget and necessitate difficult decisions of reallocation at a time when fiscal sustainability during a global recession is already being brought under question (Creel, 2020).

References

Note: Annex included in the attached PDF.

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 Covid-19 Pandemic and Its Implications for Gender Equality

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The Forum for Research on Gender Economics (FROGEE) organizes an online workshop focused on the COVID-19 implications for gender equality, with the focus on the labor market and entrepreneurship. It is the next in the series of online events focused on the economic perspectives on gender equality.

Gender Inequality During a Pandemic

The COVID-19 pandemic affects gender equality in multiple ways, ranging from the implications of the lockdowns on household work distribution to the deeper economic damage to the sectors which disproportionately employ women. These effects might be especially damaging for the countries with limited resources to support their locked economies.

Keynote Speaker and Representatives of the FREE Network

The webinar will start with the keynote presentation of “COVID-19 Inequality Project” from Dr. Teodora Boneva (University of Zurich). To continue the discussion, the representatives of the FREE Network from Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine will present the brief overviews of the situation in their respective countries.

The workshop will be organized as part of the Forum for Research on Gender Economics (FROGEE) supported by the Swedish International Development Cooperation Agency (Sida). It is the next in the series of online events focused on the economic perspective on gender inequality. The event is aimed at providing a platform for discussion among academics and policy makers on issues related to broad consequences of socio-economic inequalities.

Program

Register here

About Forum for Research on Gender Economics (FROGEE)

FROGEE initiative is part of the Stockholm Institute of Transition Economics (SITE) umbrella. The aim of the FROGEE initiative is to contribute to the discussion on gender inequality, with a specific focus on the region of Central and Eastern Europe. By highlighting different dimensions of gender inequality and its consequences for socio-economic development, FROGEE aims at bringing the issue of gender equality to the focus of both the general public and policy makers. The project is supported by the Swedish International Development Cooperation Agency (Sida).

Addressing the Covid-19 Pandemic: Policy Responses Across Eastern Europe

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The world holds its breath as Covid-19 continues to spread and challenge local health care systems as well as local economies. The focus of international media has mostly been on China and then Western Europe and the US. However, countries around the Baltic Sea, Eastern Europe and the Caucasus differ from the West with respect to their socio-economic development, trade integration, and political systems. The webinar “Addressing the Covid-19 Pandemic in Eastern Europe: Policy Responses Across Eastern Europe” hosted by the the Forum for Research on Eastern Europe and Emerging Economies (FREE) Network on May 28, 2020 aimed to fill this gap in the current discourse and give voice to experts from Latvia, Russia, Georgia, Belarus, Poland, Ukraine as well as Sweden, in order to contextualize their countries’ policy choices and experiences in the crisis. Policy recommendations can only be of preliminary nature at this point of time. Yet, it becomes clear that even though transition countries have fared relatively well during the health crisis, they will not be spared from the ensuing economic crisis and will require policy tools which are adapted to the local context.

Introduction

Less than six months after the outbreak of the Covid-19 crisis in China, the pandemic has spread across the globe. The epicenter has moved from Asia to Europe and the US, and in late May 2020 some voices are warning that it is now shifting towards Latin America. While the world´s eyes have been on Milan and Paris, little has been said about how the new EU member states and countries to the East of the European Union cope with the pandemic. Some observers have claimed the emergence of a new “iron curtain” in the corona crisis; Eastern Europe, the Baltic States and the Caucasus having been relatively unscathed compared to the West. Persisting differences in trade and travel patterns, demographic and socio-economic differences, as well as differences in trust levels could account for such an observation.

Yet, the most recent statistics suggest that this may be a premature interpretation and the overall picture is much more heterogeneous. Infections in Russia seem to be rising quickly, Georgia by contrast has turned out to be one of the top students.

Figure 1: Total confirmed Covid-19 cases vs. deaths per million.

Source: Our World in Data, 2020. • CC BYa.
Note: Data includes the most recent numbers as of May 25, 2020. Both measures are expressed per million people of the country’s population. The confirmed counts are lower than the totals. The main reason for this is limited testing.

On May 28, 2020, the Forum for Research on Eastern Europe and Emerging Economies (FREE) Network hosted a webinar with its member institutes: BEROC in Belarus, BICEPS in Latvia, CEFIR@NES in Russia, CenEA in Poland, ISET-PI in Georgia, KSE in Ukraine, and SITE in Sweden to discuss how their countries have fared in the corona crisis so far. The webinar provided an opportunity to share experiences and to add some interpretations and insights to the crude statistics, which often become unintelligible in the current overflow of information.

Figure 2: FREE Network Countries.

Source: SITE 2020.

The webinar started with Torbjörn Becker, director of SITE, introducing recent developments in terms of health statistics in the region and the research being done within the framework of the FREE Network.

SITE on Sweden

Jesper Roine, Professor at the Stockholm School of Economics and SITE, then presented the case of Sweden, the country which – with regards to death rates – has surpassed all other FREE Network countries by far. The Swedish case has been very controversially discussed in international media throughout the pandemic. Yet, the common claim that in Sweden everything was “business as usual” is not true, according to Roine. Compared to its direct neighboring countries Finland, Denmark and Norway, Sweden has chosen a relatively lenient approach to Covid-19, but high schools and universities have moved to distance learning since March and working from home is highly encouraged. Mobility reports show that Swedes have reduced their movement a lot, but less so than their Scandinavian neighbors. Roine confirmed that the Swedish health policy has been dominated by the public health agency, Folkhälsomyndigheten. Even though this is the default option in Swedish law, Roine stressed that this does not mean that the government’s hands are tied.

He presented two preliminary conclusions regarding the impact of the Swedish strategy: first, Sweden’s mitigation strategy has worked relatively well; the public health system is seriously strained but not overwhelmed. Yet, Roine said that the “lack of testing [remained] a mystery”, even for advocates of the current mitigation strategy. Second, in Roine’s opinion the attempt to protect the elderly has failed. The virus has spread to numerous nursing homes and excess death rates indicate that mortality has increased sharply for citizens above 65 years of age, much less for other age groups. Geographically, Stockholm has been the center of the epidemic. Other parts of the country have been affected to a much lesser degree.

BICEPS on Latvia

Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS) presented the Latvian experience of the corona crisis. A small country of about 2 million inhabitants, Latvia currently presents the second lowest Covid-19 mortality rate within the EU. Gubins related this to the Latvian government’s quick and determined policy reaction. After the first cases were reported in early March, schools and universities were closed, public gatherings forbidden, international travel halted, and a two-meter social distance rule imposed. Given the success of this strategy, Latvia has started to loosen its restrictions. A “Baltic Schengen area” was announced very recently and travel among the Baltic states is now possible again. The economic support package announced by the government amounts to 45 percent of GDP and includes a large equity investment in the airline airBaltic as well as important investments in infrastructure. According to Gubins, the current policy discussion focuses on the accessibility and size of help funds, widely deemed insufficient. Furthermore, the economic outlook of the country in terms of unemployment rates and GDP growth is bleak despite its success in containing the virus.

CEFIR on Russia

According to Natalia Volchkova, Director of the Centre for Economic and Financial Research (CEFIR) at the New Economic School in Moscow, Russia has pursued a “standard European strategy” in its fight against Covid-19. Two new hospitals exclusively for Covid-19 patients were created in Moscow, the current epicenter of the pandemic, and nearby. Most money spent on health care went to these new facilities, less was transferred as bonuses to medical workers. Russia has emphasized testing: around 10 million tests were performed; close to 400,000 cases of Covid-19 were confirmed. On May 27, free antibody testing was started in Moscow and is to be extended to other parts of the country. State-financed testing will serve to measure the potential degree of immunization of the population. While cases have started to decline in Moscow, other regions of Russia lag behind and are still expected to peak.

Volchkova stressed the role of the Russian shadow economy, which has been severely hit by the crisis. The size of the informal sector makes it difficult for the Kremlin to pass efficient support packages for the economy. Another policy problem lies in the weakness of the social security net, particularly unemployment benefits are hard to obtain. Therefore, most policy measures have focused on companies. Family allowances are the government’s second heavily used tool, which to Volchkova’s mind is an efficient policy choice. She concluded that the current help measures may already amount to 3 percent of GDP.

ISET-PI on Georgia

As of May 28, 2020, Georgia had only reported 12 corona deaths. According to Yaroslava V. Babych, Lead Economist at ISET Policy Institute in Tbilisi, the key explanation for Georgia’s relative success in the corona crisis is that, as in Latvia, testing started very early. She explained that even before Georgia’s neighbor Iran confirmed an outbreak of Covid-19, passengers’ temperatures were taken at the border crossing. The government in Tbilisi then soon imposed harsh quarantine measures, local quarantines in regional hotspots, a shutdown of public transport, an evening curfew and very high fines. Compliance with the measures was very high. Orthodox Easter celebrations were allowed to take place under strict hygiene measures and did not result in a spike in infection rates.

The country, largely reliant on tourism and agriculture, is now focusing on the economic consequences of the crisis. According to Babych, Georgia holds the ambition to become the first European country to open up to international tourism again from July 1, 2020. The government is also determined to avoid another meltdown of the important construction sector, as happened in 2008 – 2009. However, similar to the Russian case, Babych identified two factors which crucially weaken the Georgian economy: the lack of automatic stabilizers in the form of unemployment benefits and the large informal sector. Policymakers have therefore resorted to monthly cash payments to those who stopped paying income tax around March and fixing prices for specific food products. While the effectiveness of these measures still has to be evaluated, the policy discourse in Georgia has moved on to the socio-economic consequences of the crisis.

BEROC on Belarus

Lev Lvovskiy, Senior Research Fellow at the Belarusian Economic Research and Outreach Center (BEROC), provided an overview of the Belarusian policy measures. According to Lvovskiy, Belarus has a high number of nurses and doctors and a relatively efficient “Soviet style of fighting pandemics”. There have been hardly any restrictions to public gatherings and events, both the Orthodox and the Catholic Easter festivities were maintained, as were soccer games and the national Victory parade. Initially, the official policy was to trace and isolate cases, but this did not prove to be very efficient, supposedly due to poor enforcement. Lvovskiy said that testing is rare which is why statistics on the spread of the virus and its effects remain of questionable quality.

While Belarus disposed of a solid health care system, it was not well prepared economically, which explains why the government has not been very proactive in Lvovskiy’s opinion. The Belarusian industrial production decreased by 7 percent in April 2020 compared to the same month the year before; unemployment has started to increase, yet, there are no significant unemployment benefits. Increasing the height of unemployment pay is the key policy issue under discussion in Minsk but in the absence of international loans, the government´s hands are tied. The issue is urgent: the most recent BEROC survey suggests that 46% of individuals living in urban areas have already seen their income decrease. Lvovskiy’s preliminary conclusion is that the Belarusian policy response to the Covid-19 crisis was not as bad as expected by many international observers: the health crisis has mostly been contained. But like in the Georgian case, the socio-economic implications of the crisis are becoming more pressing now.

CenEA on Poland

Michal Myck, Director of the Centre for Economic Analysis (CenEA) in Szczecin, explained that Poland also successfully avoided a spike in infection rates thanks to a quick policy response. Poland was one of the first countries to impose international travel restrictions and very harsh social distancing measures, yet, infection rates remain higher than in other FREE Network countries. Since the second half of April, most measures have been lifted and the spread of the virus seems under control and concentrated in the region of Silesia.

All limitations were implemented without invoking a state of emergency. Myck suggested that the government may have made this choice because the presidential elections would have been automatically postponed otherwise, an outcome the government wanted to avoid. The elections were eventually postponed, but doubts persist with regards to the constitutional validity of the way this decision was taken. Myck stressed the persisting political uncertainty. Economic policy in Poland has focused on protecting jobs and providing liquidity to enterprises. State loans have been primarily directed to SMEs and will be partly written off, conditional on continued activity and employment. In Myck’s opinion, the economic outcome for Poland will depend on whether investments from and exports to Western Europe quickly resume or not.

KSE on Ukraine

Tymofiy Mylovanov, President of the Kyiv School of Economics and former Minister of Economic Development, Trade and Agriculture, stressed that in the first few weeks of the pandemic, Ukraine enforced harsher policy measures than its neighbors. The lock down was almost complete, with only grocery stores and pharmacies allowed to open. Compliance was high during the first few weeks but then started to decline.

The government allocated 3 percent of GDP to a Covid-19 support fund, there has been a lot of deregulation on the labor market, but the central bank’s key interest rate remains at 8 percent. Pressure for a looser monetary policy increases according to Mylovanov, as GDP has fallen by 1.2 percent and unemployment is expected to reach up to 10 percent by the end of the year.

Mylovanov’s thoughts about Ukraine’s economic prospects are mixed: average salaries continue to grow during the crisis which may be explained by the fact that low-skilled employees get laid off first, suggesting a potentially long-lasting change of the composition of the workforce. At the same time, the political situation is volatile with local elections coming up in October 2020 and public pressure mounting. As Poland, Ukraine did not declare a state of emergency. While Mylovanov thinks that the policy response could have been better, he is optimistic that Ukraine was better prepared to Covid-19 than to previous crises and will not have to resort to international loans.

Preliminary Conclusions

It is too early to draw any definite conclusions, but undoubtedly, a lot can be learned from the very diverse experiences of the corona crisis in the region. The former Soviet countries have a different historical and political legacy than Western European countries and accordingly, have found different ways of handling the crisis. Some have been more successful than their Western neighbors. But even those countries which have not faced a large health crisis have been severely hit economically and are likely to suffer economic hardship in the future.

The lack of a strong tradition of unemployment benefits and automatic stabilizers renders countries like Georgia, Belarus and Russia particularly vulnerable to the economic crisis which will inevitably follow the Covid-19 outbreak. In some countries, the corona shock may also accelerate or trigger political changes. In the view of this, the FREE Network will organize a series of follow-up webinars and briefs on more specific corona-related topics, with the aim of contextualizing statistics and providing a wider picture of the socio-economic consequences and policy implications of the crisis.

Please find a full recording of the webinar below. Updates on further events will be posted on the FREE website and on social media channels (Facebook, Twitter).

List of Speakers

  • Jesper Roine, Professor at the Stockholm Institute of Transition Economics (SITE / Sweden)
  • Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS / Latvia)
  • Natalia Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR@NES / Russia)
  • Yaroslava V. Babych, Lead Economist at ISET Policy Institute (ISET / Georgia)
  • Tymofiy Mylovanov, President at the Kyiv School of Economics (KSE / Ukraine)
  • 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)
  • Torbjörn Becker, Director of the Stockholm Institute of Transition Economics (SITE)

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 in Eastern Europe

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The Covid-19 pandemic is affecting everyone around the globe and leaves none untouched. However, much of the focus in international media has been on the most affected countries and richer countries in East Asia, the European Union and the United States with less attention given to countries around the Baltic Sea, Eastern Europe and the Caucasus.

Since the FREE Network includes research and policy institutes in Belarus (BEROC), Latvia (BICEPS), Russia (CEFIR@NES), Poland (CenEA), Georgia (ISET), Ukraine (KSE) and Sweden (SITE), experts from the FREE Network institutes discuss the regional perspective on the pandemic with examples of very different strategies implemented in the countries concerned.

Speakers

  • Jesper Roine, Professor at the Stockholm Institute of Transition Economics (SITE / Sweden)
  • Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS / Latvia)
  • Natalia Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR@NES / Russia)
  • Yaroslava V. Babych, Lead Economist at ISET Policy Institute (ISET / Georgia)
  • Tymofiy Mylovanov, President at the Kyiv School of Economics (KSE / Ukraine)
  • 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)

Chair/Moderator

  • Torbjörn Becker, Director of the Stockholm Institute of Transition Economics (SITE / Sweden)

Addressing the Covid-19 Pandemic in Eastern Europe: Policy Responses Across FREE Network Countries

An image of a woman sitting in a public transport with a COVID-19 protection mask on the face representing the Covid-19 pandemic in Eastern Europe

The FREE Network is delighted to invite you to a webinar to share insights and knowledge about how countries around the Baltic Sea, in Eastern Europe and the Caucasus have fared in the Covid-19 pandemic.

The Covid-19 pandemic is affecting everyone around the globe and leaves none of us untouched. However, much of the focus in international media has been on the most affected countries and richer countries in East Asia, the European Union and the United States with less attention given to countries around the Baltic Sea, in Eastern Europe and the Caucasus. Since the FREE Network includes research and policy institutes in Belarus (BEROC), Latvia (BICEPS), Russia (CEFIR@NES), Poland (CenEA), Georgia (ISET), Ukraine (KSE) and Sweden (SITE), we are uniquely placed to provide a comprehensive regional perspective on the pandemic with examples of very different strategies implemented in the countries concerned.

Many of the countries in Eastern Europe and the Baltic region differ from Western Europe in terms of successfully limiting infections and deaths resulting from the pandemic so far. At the same time, the situation in Russia has worsened rapidly over the last few weeks, despite a lockdown having been imposed. The fatality rate and the number of infections have also been high in Sweden, where, in contrast to other Baltic countries, only relatively lenient restrictions have been imposed on the population. In the same vein, the Belarusian government has taken few, mild measures in response to the pandemic, but the mortality rate seems to have remained rather low.

This webinar will provide a first overview of how countries in the region have fared in the pandemic and allow for a better understanding of what governments have done, how people have responded, how other countries are being portrayed in the national media, and what the current discussions focus on.

Speakers

  • 🇸🇪 Jesper Roine, Professor at the Stockholm Institute of Transition Economics (SITE / Sweden)
  • 🇱🇻 Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS / Latvia)
  • 🇷🇺 Natalia Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR@NES / Russia)
  • 🇬🇪 Yaroslava V. Babych, Lead Economist at ISET Policy Institute (ISET / Georgia)
  • 🇺🇦 Tymofiy Mylovanov, President at the Kyiv School of Economics (KSE / Ukraine)
  • 🇧🇾 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)

Chair/Moderator

  • Torbjörn Becker, Director of the Stockholm Institute of Transition Economics (SITE / Sweden)

The webinar opens a series of online discussions aiming to provide a regional overview, updates as well as in-depth analysis of specific topics related to the Covid-19 pandemic. Follow-up webinars will focus on such topics as regional differentiation within countries, effects on the environment, the gender dimension of the pandemic, and the analytical aspects of Covid-19 statistics.

Date: Thursday, May 28th, 15.00-16:30 CET

Location: Zoom webinar, link to be provided for registered participants

RSVP: The number of participants for the webinar is limited, therefore we invite to register as soon as possible, but no later than May 25, 23:59 CET.

Registration link: Please click here to register.

Quota or not Quota? On Increasing Women’s Representation in Politics

20200504 FREE Network Policy Brief image with dozen people standing at the seaside in sunset representing Women’s Representation in Politics Image 01

All over the world, politics remains one of the most male-dominated spheres in society, in spite of the substantial progress made in achieving more gender balance in the last decades. A large number of countries worldwide have adopted some form of electoral gender quotas to accelerate this progress, but the empirical evidence on the effectiveness of such policy tools is mixed.

In this policy brief, we first discuss the potential impacts of gender quotas. Quotas may (a) increase women’s representation in political positions, or decrease it, if there are backlash effects; (b) improve or worsen the quality of selected politicians; and (c) bring about important policy changes, given the wealth of empirical evidence of gender differences in policy preferences, with, for instance, women appearing more concerned about health and the health system than men. We then provide an overview of the empirical evidence on quota impacts in the economics literature, and contextualize these findings with a special focus on the countries of the FREE (Forum for Eastern Europe and Emerging Economies) network. We end with policy advice on the design of gender quotas in the domain of politics.

Quotas in the World and in the FREE Network Region

According to the International Institute for Democracy and Electoral Assistance (IDEA), 127 countries worldwide currently use quotas with the goal of increasing the presence of women in governmental institutions. Broadly speaking electoral gender quotas can be classified into seat reservation and candidate lists quotas. The former limit the competition for a governmental seat to women, whereas the latter prescribe a minimum representation of women in electoral lists. Candidate quotas can be legislated, i.e. they constitute a legal requirement, or voluntary, whereby parties adopt quotas in their internal statute.

Table 1: Share of women in national parliaments (in %) FREE Network countries

Source: World Bank Data (2020).

The popularity of gender quotas is, however, not uniformly distributed across the globe. For example, while political gender representation is far from equal in most countries of FREE network region (see e.g. table 1), out of these countries only Armenia, Poland and Sweden dispose of electoral gender quotas (see figure 1).

Figure 1: Gender quotas in the FREE Network region

Note: the FREE Network region is marked in light red, the countries in the region with quota are marked in dark red. Source: SITE, 2020.

Since 2011, Armenia has had a legislated candidate quota of 40% for its National Assembly. This quota replaced a previous quota of 15%, passed in 2005 – one of the requirements to enter the Council of Europe (Itano 2007). Poland has also had a legislated candidate quota of 35% for the Lower House (the Sejm) as well as for subnational elections since 2011 (IDEA 2020; World Bank 2019). Sweden, the fourth most gender equal country worldwide according to the 2020 ranking of the World Economic Forum, and ninth in the women’s political empowerment sub-index, does not have legislated quotas. However, political parties themselves have decided to adopt voluntary quotas: the ruling Social Democrats use a zipper system in which the two sexes alternate on party lists; the Left Party has a minimum 50% quota for women, while the Green Party has a 50% gender quota (IDEA 2020). The Swedish Moderates, Liberals, Center parties and the extreme-right Swedish Democrats currently do not have gender quotas. The Swedish Democrats entered the parliamentary elections in 2018 with the highest share of male candidates observed among the Swedish parties – 70% (SVT 2020; SVT 2018).

In spite of their popularity among policy-makers worldwide, the merits of quotas are still largely debated. Opponents of gender quotas are often concerned about their effects on the meritocratic selection of politicians. Another common criticism is that nominating more female candidates may not automatically translate into more women in powerful positions. For instance, the shares of women in the Armenian and the Polish Parliament are 24 and 29% respectively (World Bank 2019), well below the national legislated candidate quota (it bears noting, however, that these shares have been growing over the last ten years, as shown in Figure 3). The respective shares of female ministers are 7% and 23% (Government of the Republic of Armenia 2020; OECD 2020,).

Figure 2: Share of women in national parliaments (in %)

Source: The authors’ own rendering of World Bank Data (2020).

Why is increasing women’s political participation considered a policy objective of utmost importance in many countries worldwide, and how can gender quotas help achieving it? In this brief we contribute to the ongoing debate on the merits of gender quotas, by offering an overview of their potential effects and by critically reviewing the empirical evidence from the most recent academic literature.

Which Effects Can We Expect From Quotas?

The primary objective of electoral quotas is to reduce gender gaps in representation in electoral lists and in the targeted representative institutions. Quotas can also activate trickle-up mechanisms, whereby gender gaps decrease in positions that are not directly targeted by the quota. The trickle up effect occurs, for instance, if women’s networks within parties or in governmental organizations help the promotion of female leaders. Furthermore, gender quotas may help to improve the quality of politicians. As noted by, among others, Bertrand (2018), a society likely improves the quality of its leaders when it enlarges the pool where those leaders are chosen from. A critical underlying assumption in this line of argument is that there are no major differences in the distribution of “political talent” between women and men. However, even with equal distribution of political talent, if the supply of women willing to enter politics is very limited and there are not enough qualified women to fill the quota positions, the average quality of a “quota” politician may end up being lower than that of her colleagues – and quotas may have the unintended consequence of reinforcing stereotypes against female politicians. This, in turn, may ultimately imply lower promotion rates of women to key positions and/or worse electoral support of female politicians, thereby undermining women’s political empowerment at various levels.

One of the most popular arguments in favor of the adoption of gender quotas is that women’s political preferences may not be adequately represented by male-dominated political bodies. Gender quotas, by increasing female representation among politicians (and possibly among voters), can thus help closing a potential gap in substantial representation. A large body of literature has documented gender differences in policy preferences, by considering, e.g. the size and composition of government spending after the expansion of suffrage to women (Kenny and Lott 1999), voting records in referenda (Funk and Gathmann 2015), survey data (see, e.g. Bagues and Campa 2020), or women’s contributions to legislative amendments (Lippmann 2020). In this historical moment when the world is plagued by a pandemic, the most important gender difference to emphasize seems to be in the area of health. Exploiting the federal referenda held between 1981 and 2001 in Switzerland, Funk and Gathmann (2015) show that Swiss women are more likely to be in favor of health, unemployment and social security spending than men, and less likely to be in favor of military spending. Similarly, based on survey data from a sample of nearly 60,000 Spanish residents, Bagues and Campa (2020) find that women are significantly more likely than men to report that the health system is one of the problems that affects them the most. Likewise, Lippmann (2020) analyzes the contribution of French legislators to amendments and finds that women are 25% more likely than men to initiate at least one amendment related to health issues. This gender difference regarding health policy is also visible in the European Social Survey (ESS), which covers a representative sample of the population of 19 European countries. When asked to give a general opinion on the current state of health services in their country, female respondents turn out to be significantly less satisfied than male respondents on average. The difference is statistically significant, albeit not particularly large (12% of a standard deviation) and holds in most of the countries included in the ESS. One potential reason behind this noticeable difference in satisfaction with health services is that women also report lower health status than men (10% of a standard deviation and statistically significant).

Figure 3: Self-reported satisfaction with the current state of national health services

Source: The authors’ own rendering of the ESS (2018).

A natural question to ask in spring 2020 is whether a world with more women among political leaders would have had health systems better equipped to face a pandemic. While we will never have a definite answer to this question, studies of the impacts of gender quotas can help assessing whether the gender of political leaders matters for policy decisions.

What is the Empirical Evidence on the Effects of Quotas?

Quotas increase women’s representation in electoral lists, but only when they are binding and appropriately enforced (i.e. the cost for parties of not complying with the quota must be high enough). Yet, when quotas are limited to the composition of electoral lists, the strategic positioning of female candidates in “not-winning” positions tends to undermine the quota effect on the election of women (see Esteve-Volart and Bagues, 2012, and Bagues and Campa, 2020). This seems to be the case of Poland: According to Gwiazda (2017), the lack of a placement mandate obliging parties to put women in the top positions of a party list, is indeed one reason why the Polish quota has not translated into a higher share of female representatives.

The evidence on the spill-over of quotas to higher positions is mixed. Two studies find that candidate quotas in Italy and Sweden increased the probability that women reach leadership positions, above and beyond the quota mandate (De Paola et al. 2010, O’Brien and Rickne, 2016). Bagues and Campa (2020), however, fail to establish similar evidence in Spain.

In studies of developing countries, Beaman et al. (2009) find that seat reservation in India improved male voters’ perception of female leaders, as well as women’s probability of being elected once the reservation was removed. Conversely, experimental evidence from Lesotho suggests that, if anything, a quota-mandated female representative reduces women’s self-reported engagement with local politics (see Clayton, 2015).

An increasing number of studies also examine the quota impact on the quality of the elected politicians, proxied by different measures. Baltrunaite et al. (2014) find that a gender quota improved the average education of elected politicians in Italy, and Besley et al. (2017) provide similar evidence looking at a measure of labor market performance in Sweden. Bagues and Campa (2020), studying candidate quotas in Spain, fail to find an improvement in the quality of politicians, measured by their education and electoral performance; however, their assessment is that the quota did not decrease quality either, contrary to the expectation of many quota opponents. However, Chattopadhyay and Duflo (2004) find that, in the context of seat reservations in rural India, quota candidates are less educated.

Finally, the evidence on whether gender quotas bring about policy change is scarce. Chattopadhyay and Duflo (2004) show that the reservation of the most important seat in Indian villages brought policy choices closer to women’s preferences. In Spanish municipalities, Bagues and Campa (2020) fail to find significant increases in the share of “female expenditures” (issues women have been found to care more about than men, based on surveys) over two legislatures when candidate quotas were used.

Conclusion

Gender quotas are a popular policy tool used to close existing gender gaps in political empowerment, which are large in many countries in the FREE Network. A growing economics literature on the impacts of gender quotas helps assessing what objectives policy-makers may be pursuing when they adopt them, and under which conditions these objectives can be achieved. There is a number of lessons to be learned from this literature.

First, the design of the quota is crucial for it to achieve its primary objective, which is to increase women’s presence in the targeted political positions. Placement mandates, for instance, are particularly important in the design of candidate quotas to avoid that women are strategically placed at the end of the ballot. Second, policy-makers need to take the local context into account. Whether a candidate quota can generate spill-overs to higher-level positions likely depends on the degree of centralization of political parties for instance; where party leaders are very powerful, we may be less likely to see an increase in the share of female leaders following the adoption of a candidate quota. Third, the question when gender quotas successfully bring about policy change needs additional investigation. Different factors likely play a role, such as: the type of position targeted by the quota (legislative or executive, local or national, etc.); the extent of the increase in representation achieved; the magnitude of the gender difference in preferences; the type of decision-making process prevailing (majority voting or unanimity); how the selection of politicians is affected by the quota; and how women’s influence on policy is measured. Studies that systematically vary some of these factors will improve our understanding of this area of research. Fourth, there is no overwhelming evidence of negative effects of gender quotas in a number of dimensions, at least over a medium-term horizon.

The case for adopting and testing different forms of gender quotas, perhaps in combination with additional measures, is therefore relatively strong. Overall, our assessment is that quotas will have to remain in policy-makers’ toolbox for some time if the worldwide effort to close the persisting gender gaps in political empowerment is to continue.

References

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 Shadow Economy in Russia: New Estimates and Comparisons with Nearby Countries

Image of a metro elevator going upwards representing shadow economy of Russia

We apply a new method to measure the shadow economy in Russia during the period 2017-2018 and provide evidence on the main factors that influence involvement in the shadow economy. Drawing on a methodology developed by Putnins and Sauka (2015), we estimate that the size of the shadow economy in Russia is 44.7% of GDP in 2018. This is similar to the size of the shadow economy in countries such as Kyrgyzstan, Kosovo, Ukraine, and Romania, but higher than the level of the Baltic countries. Our findings are largely consistent with other less direct approaches for estimating the shadow economy. An advantage of our approach is that it can provide more detailed information on the components of the shadow economy.

Introduction and Approach to Measuring the Shadow Economy

The aim of the Shadow Economy Index, which has now been estimated in a number of countries, is to measure the size of shadow economies and explore the main factors that influence participation in the shadow economy. We use the term “shadow economy” to refer to all legal production of goods and services produced by registered firms that is deliberately concealed from public authorities (OECD, 2002; Schneider, Buehn and Montenegro, 2010).

The Shadow Economy Index draws on a survey-based methodology developed by Putnins and Sauka (2015). It combines estimates of business income that has been concealed from authorities, unregistered employees, and ‘envelope’ wages. The approach exploits the fact that entrepreneurs and business leaders are in a unique position in that they have knowledge about the amount of business income that is concealed from authorities, the number of employees that work for them unofficially, and the extent to which they pay wages informally to avoid taxes.

The challenge for such methods is to elicit maximally truthful responses about these sensitive issues, otherwise, the size of the shadow economy will be underestimated. To address this challenge, we use a number of survey and data collection techniques shown in previous studies to be effective in eliciting more truthful responses (e.g. Gerxhani, 2007; Kazemier and van Eck, 1992; Hanousek and Palda, 2004). While the full details can be found in Putnins and Sauka (2015), they include confidentiality with respect to the identities of respondents, framing the survey as a study of satisfaction with government policy, phrasing misreporting questions indirectly about “similar firms in the industry” rather than the respondent’s actual firm, gradually introducing the most sensitive questions after less sensitive questions, excluding inconsistent responses, and controlling for factors that correlate with a potential untruthful response such as tolerance towards misreporting.

The Index measures the size of the shadow economy as a percentage of GDP. Computing the Index involves three steps:

  • (i) estimate the degree of underreporting of employee remuneration and underreporting of firms’ operating income using the survey responses;
  • (ii) estimate each firm’s shadow production as a weighted average of its underreported employee remuneration and underreported operating income, with weights reflecting the proportions of employee remuneration and firms’ operating income in the composition of GDP; and
  • (iii) calculate a production-weighted average of shadow production across firms.

The survey about shadow activity in Russia from 2017 to 2018 was conducted between February and March 2019. We use random stratified sampling to construct samples that are representative of the population of firms in Russia drawing on the official company register and covering all regions in Russia. In total, 500 phone interviews were conducted with owners, directors, and managers of companies in Russia. We use the same methodology to collect data in other countries, which we compare with Russia, conducting a minimum of 500 interviews in each country.

Size of the Shadow Economy in Russia and Nearby Countries

The estimated size of the shadow economy in Russia is 44.7% of GDP in 2018. Our estimates suggest that the year before, in 2017, the shadow economy was slightly larger with 45.8% of GDP, although the annual change is not statistically significant. For comparison with nearby countries, using the same approach, high levels of shadow economy are also found in Kyrgyzstan (44.5% of GDP in 2018), Kosovo (39.5% of GDP in 2018), Ukraine (38.2% of GDP in 2018), and Romania (33.35% of GDP in 2016), but considerably lower levels are found in the Baltic countries, especially Estonia (16.7% of GDP in 2018). See Table 1 for the full set of estimates.

The estimates using our direct micro-level approach to measuring the shadow economy are largely consistent with other less direct approaches for estimating the size of the shadow economies, such as Schneider (2019). An advantage of the direct micro-level approach is that it is able to provide more detailed information on the components of the shadow economy, which we turn to next.

Components and Determinants of the Shadow Economy in Russia

We find that envelope wages and underreporting of business profits stand out as the two largest components of the Russian shadow economy. Underreporting of salaries or so-called ‘envelope wages’ in Russia are approximately 38.7% of the true wage on average in 2018, whereas approximately 33.8% of business income (actual profits) are underreported. Unofficial employees in Russia as a percentage of the actual number of employees are estimated 28.2% in 2018.

Some companies in Russia, rather than simply concealing part of the income or employees, are completely unregistered and therefore also contribute to the shadow economy. We estimate that such companies make up 6.1% of all enterprises in Russia.

Our findings also suggest that there is a very high level of bribery in Russia: the magnitude of bribery (percentage of revenue spent on ‘getting things done’) is estimated to be 26.4%, whereas the percentage of the contract value that firms typically offer as a bribe to secure a contract with the government in Russia is 20.6% in 2018. We also find that more than one-third of companies in Russia pay more than 25% of the revenue or contract value in bribes.

We find that the size of the shadow economy in all sectors of the Russian economy is close to 40% with somewhat higher levels in the construction and wholesale sectors, controlling for other factors. Using regression analysis, we find that entrepreneurs that view tax evasion as a tolerated behaviour tend to engage in more informal activity, as do entrepreneurs that are more dissatisfied with the tax system and the government. This result offers some insights into why the size of the shadow economy in Russia is so large – it is at least in part due to relatively high dissatisfaction of entrepreneurs with the business legislation and the government’s tax policy. We also find some evidence that higher perceived detection probabilities and, in particular, more severe penalties for tax evasion reduce the level of tax evasion, suggesting increased penalties and better detection methods as possible policy tools for reducing the size of the shadow economy.

Finally, while firms of all sizes participate in the shadow economy, we find that younger firms tend to do so to a greater extent than older firms. The results support the notion that young firms use tax evasion as a means of being competitive against larger and more established competitors.

Acknowledgments

This research was supported by a Marie Curie Research and Innovation Staff Exchange scheme within the H2020 Programme (grant acronym: SHADOW, no: 778118).

References

  • Gerxhani, K. (2007). “Did you pay your taxes?” How (not) to conduct tax evasion surveys in transition countries. Social Indicators Research 80, pp. 555-581.
  • Hanousek, J. and Palda, F. (2004). Quality of government services and the civic duty to pay taxes in the Czech and Slovak Republics, and other transition countries. Kyklos 57, pp. 237-252.
  • Kazemier, B. & van Eck, R. (1992). Survey investigations of the hidden economy. Journal of Economic Psychology 13, pp. 569-587.
  • Lechmann, E. and D. Nikulin (2017). Shadow Economy Index in Poland. Gdansk University of Technology, Poland: Gdansk.
  • Lysa, O. et al. (2019) Shadow Economy Index in Ukraine. SHADOW: an exploration of the nature of informal economies and shadow practices in the former USSR region. Kyiv International Institute of Sociology, Ukraine: Kyiv.
  • Mustafa, I., Pula J.S., Krasniqi, B., Sauka, A., Berisha, G., Pula, L., Lajqui, S. and Jahja, S. (2019) Analysis of the Shadow Economy in Kosova. Kosova Academy of Sciences and Arts, Kosova: Pristina.
  • OECD, 2002. Measuring the Non-Observed Economy: A Handbook. OECD, Paris, France.
  • Putnins, T.J. and Sauka, A. (2019). Shadow Economy Index for the ‘Baltic Countries 2019-2018. SSE Riga: Riga, Latvia.
  • Putnins, T.J., A. Sauka and A. Davidescu (2020, forthcoming). Shadow Economy Index for Moldova and Romania, 2015-2018. SSE Riga, National Scientific Research Institute for Labour and Social Protection.
  • Putnins, T.J. and Sauka, A. (2015). Measuring the shadow economy using company managers. Journal of Comparative Economics 43, pp. 471-490.
  • SIAR (2019). Shadow Economy Index for Kyrgyzstan. SHADOW: an exploration of the nature of informal economies and shadow practices in the former USSR region. SIAR research and consulting, Kyrgyzstan: Bishkek.
  • Schneider, F. (2019) Calculation of the Size and Development of the Shadow Economy of 35 Mostly OECD Countries up to 2018. Unpublished manuscript.
  • Schneider, F., Buehn, A. and Montenegro, C. (2010). New estimates for the shadow economies all over the world. International Economic Journal 24, pp. 443-461.

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.