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Media Freedom in Eastern Europe

Posted on February 22, 2021 | Policy Brief

Photography of Magazine representing Media Freedom Eastern Europe

In recent years, press freedom in many Eastern European countries has increasingly come under threat. This policy brief provides an overview of the importance of a free press for democracy and the challenges to media freedom in these European transition economies.

Introduction

Freedom of expression – which encompasses media freedom – is a fundamental human right enshrined in most countries’ constitutions. Yet for many of their citizens, it is more of an aspiration than a reality. Following the dissolution of the Soviet Union, a number of countries in Eastern Europe embarked on a process of democratisation and accession to the European Union – for which one of the prerequisites is a free press.

Figure 1 shows a measure of press freedom for the eight Eastern European countries that joined the EU in 2004. These countries saw a general improvement in press freedom from the early 1990s to the early 2000s. But since then, experiences have diverged and in 2017 only Estonia and the Czech Republic showed better scores on press freedom than when they first joined the EU. This pattern of backsliding is not confined to the media, but is also evident in other measures of democracy.

Figure 1. Media Freedom in Eastern Europe

Media and Democracy

A free press and a strong democracy are mutually reinforcing. Research, from mainly Western democracies, shows that the media plays an important role in informing the electorate and holding politicians accountable. For example, Snyder and Strömberg (2010) find that U.S. voters are less informed about their Congressmen when they are covered less in the local press. This is ultimately damaging for voters, as these politicians work less for their constituency and these constituencies also receive less federal funding.

Investigative journalism can play an important role in uncovering corruption and other forms of wrongdoing by politicians. For instance, using the Panama Papers and other leaked documents, journalists uncovered 11,562 offshore entities linked to Russia, 2943 linked to Latvia, and 103 linked to Sweden (see: Offshore Leaks Database). While there are legitimate uses for these offshore entities, the lack of transparency surrounding offshore finance also facilitates tax evasion and money laundering. The revelations of offshore holdings became an embarrassment to many politicians, with some forced to resign. In Russian media, the allegations that the leaks document suspected money laundering by President Putin were characterised as US propaganda (Hoskins and Shchelin, 2018).

Figure 2 shows the relationship between the length of time a country’s leader has been in office and its press freedom score in 2020. While there is no systematic relationship between leader tenure length and press freedom in Western Europe (in blue), across Eastern Europe (in red), countries whose leader has been in power for longer tend to have less media freedom. This correlation is likely to reflect three factors: 1) media coverage can affect a government’s chances of staying in power; 2) a longer-lived government might be more able to control the media and 3) a host of other factors, such as the public’s political engagement and the strength of democratic institutions, could influence both freedom of the press and the longevity of governments.

Figure 2. Media Freedom and Leader Tenure

Source: Freedom of the Press, Freedom House. This figure shows the Freedom of the Press total score for the 8 central and eastern European countries that joined the EU in 2004 from 1993 to 2017. A country with a score between 0 and 30 (31 and 60) is designated as having a free (partly free) press.

Electoral Effects of the Media

A number of papers show the causal effects of (biased) media coverage in shaping support for political parties. For instance, watching Fox News increases voting for the Republican party in the US (DellaVigna and Kaplan, 2007; Martin and Yurukoglu, 2017).

Enikolopov, Petrova, and Zhuravskaya (2011) investigate the influence of NTV (the only national TV channel that was at the time independent of the government) on voting in the 1999 parliamentary election in Russia. They find that areas with greater access to NTV were significantly less likely to vote for the government party and more likely to vote for opposition parties.

Biased media can also be used as a foreign policy tool. Peisakhin and Rozenas (2018) find that Ukrainian areas that received Russian TV had on average greater support for pro-Russian parties and candidates in the 2014 elections.

The media landscape in many CEE countries is highly polarised and politicised. Kostadinova (2015) cites research showing that in some former communist countries many journalists still rely on government officials as news sources. In other countries, media in opposition to the communist regimes emerged at the end of the 1980s, such as in Poland where the Gazeta Wyborcza became one of the leading daily newspapers.

Government Control of the Media

Governments have many ways of controlling the media in their country. At the extreme, governments can own and run media outlets, dictate their contents, and censor any dissenting voices. While political and media systems across CEE are diverse, they share some common experiences that might explain their current fragility.

Transitions in Media Ownership

In the Eastern Bloc, the mass media was owned and tightly controlled by the state and used as a tool for propaganda. After the fall of communism, many state-owned media were privatised – along with other state-owned enterprises.  Foreign (mostly western European) media conglomerates purchased a significant fraction of media outlets in a number of countries.

While private and foreign ownership of the media can reduce the government’s ability to influence media content, the experience of CEE was not entirely positive.  Stetka (2012) argues that while foreign owners brought capital and technology, they were less concerned with transplanting Western journalistic and professional standards.  Dobek-Ostrowska (2015) claims that this focus on profit led to the tabloidisation of news across the CEE.

Following the global financial crisis in 2007/2008, foreign investors started to pull out of the CEE media markets and are being replaced by local owners who often have strong links with the government. This is evident in Hungary, where businessmen close to the government have been buying up independent media outlets, including its largest news website, one of two national commercial TV channels, and all regional newspapers (Bede, 2018). The Polish government also aims to “re-nationalise” its media. Plans by a state-run oil company to buy one of the country’s largest media publishers from its German owners were recently approved.

Elsewhere, domestically owned and previously independent media outlets are also being bought by new pro-government owners. In Russia, the formerly independent NTV from the above example was taken over by a state-owned company in 2001 and started to cover the ruling party in the run-up to the following elections in a similarly favourable way to state-controlled TV channels. Gehlbach (2010) argues that Putin’s media strategy is to exert tight control over the news coverage of these three main national television networks, while allowing media outlets with less reach to operate more independently.

In some countries of the region, there is limited information about the ultimate owner of media outlets. Within the EU, Latvia, Hungary, the Czech Republic, Slovakia and Cyprus, are assessed as high risk in terms of transparency of media ownership (Brogi et al. 2020). In 2009, the Swedish company Bonnier sold Diena – one of Latvia’s largest newspapers – to an initially undisclosed investor. A year later, a Latvian businessman acquired a controlling stake in the paper.

Government Advertising

Around the world, traditional news media is facing increased competition from digital platforms and becoming highly dependent on advertising revenue, including advertising from the government and pro-government businesses According to the Centre for Media Pluralism and Media Freedom, there are no clear and fair criteria for the distribution of state advertising to the media in the majority of EU countries – especially those in Eastern Europe (with the exception of Estonia).

Szeidl and Szucs (2021) document how the Hungarian government targeted advertising to friendly media outlets and how these media in turn covered the government more positively.  They also present suggestive evidence that a similar favour exchange between government and the media occurs in nine other Eastern European countries, including Poland.

Two weeks ago, many private Polish media outlets coordinated a media blackout to protest government plans to tax advertising revenues. The media companies complained that the tax would cost them $270m a year, while public media received twice as much from taxpayers.

Public Service Media

The establishment of public service media forms an integral part of the EU’s agenda for promoting press freedom. While public service media are an important and trusted source of unbiased information in many western European countries, they generally play a smaller role in the  Eastern European media markets. Furthermore, no laws are guaranteeing the independence of public service media from the government in eastern EU countries, with the exception of the Baltic states and Slovenia  (see Centre for Media Pluralism and Media Freedom).

Intimidation of Journalists

Governments can also ensure positive coverage by intimidating editors and journalists. Since 1992, 91 journalists were killed, imprisoned, or went missing in Russia, 18 in Ukraine, 15 in Belarus, and 8 in Georgia (data by the Committee to Protect Journalists). While not all of these cases reflect government action, several recent examples illustrate how the judicial system may be used against journalists. For instance, according to the CPJ, ten journalists were imprisoned in November 2020 for covering protests against President Lukashenko in Belarus and one journalist was charged with high treason and espionage in Russia in July 2020.

There are also fears that governments can use defamation laws to deter and punish unwelcome media reports. For instance, the head of Poland’s ruling party filed a libel charge against two journalists from the Gazeta Wyborcza for reporting about his alleged involvement in a real estate project (see, e.g. Council of Europe media freedom alert).

Conclusion

The media plays a vital role in shaping the public debate and holding those in power accountable to the wider population. This power of the media also increases the risk that governments attempt to influence media content.

In recent years, many countries in CEE have seen press freedom come increasingly under threat, undermining some of the progress made since the dissolution of the Soviet Union. Part of the present fragility of media freedom in Eastern Europe may be due to their historical experience. During the transition from communism, many formerly state-owned media companies were sold to private and often foreign owners. In the past decade, local business interests with strong ties to the government started to buy up large shares of the media market in a number of Eastern European countries. Meanwhile, public service media have been less successful at establishing themselves as important and unbiased sources of information across Eastern Europe compared to Western Europe.  To ensure positive media coverage, many governments adopt a carrot and stick approach: state advertising revenues and intimidation of individual journalists.

Article 19 of the Universal Declaration of Human Rights states that “everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers”. To ensure these fundamental rights, there need to be transparent and fair rules governing the ownership, management, and financing of media outlets and safeguards for individual journalists.

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.

Where We Are in the Covid-19 Vaccine Race: Eastern Europe and Beyond

Posted on February, 2021 | Videos

20210301 Addressing the COVID-19 Pandemic FREE Network Policy Brief Image 03

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. How are countries in Eastern Europe, around the Baltic Sea, and in the Caucasus managing vaccination efforts?

The FREE Network organized 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.

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 Myck, Director 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)

Ukraine’s Integration into the EU’s Digital Single Market

Posted on February 15, 2021 | Policy Brief

Blue EU flags in front of European Commission representing Ukraine’s integration into the single market

This brief is based on a study that investigates how Ukraine’s integration into the EU Digital Single Market (DSM) could affect EU-Ukraine bilateral trade as well as Ukraine’s GDP growth.  The major benefits of integration are expected to come from 1) reduction of cross-border regulatory barriers and restrictions to EU-Ukraine digital trade 2) acceleration of the development of Ukraine’s digital economy in line with EU standards. According to the results, enhanced regulatory and digital connectivity between Ukraine and the EU is expected to increase Ukraine’s exports of goods and services to the EU by 11.8-17% and 7.6-12.2% respectively. At the same time, the acceleration of the digital transformation of the Ukrainian economy and society will produce a positive effect on its productivity and economic growth – a 1%-increase in the digitalization of the Ukrainian economy and society may lead to an increase in its GDP by 0.42%.

Background

Integration into the EU has been one of the key topics on Ukraine’s political agenda for a number of years. Recently, more emphasis has been put on an essential component of issue – integration into the EU’s Digital Single Market (DSM). The DSM is a strategy aimed at uniting and enhancing digital markets and applying common approaches and standards in the digital sphere across the EU. The Ukraine-EU Summit, held on October 6, 2020, stressed the paramount importance of the digital sector in boosting its economic integration and regulatory approximation under the EU-Ukraine Association Agreement. Implementation of the provisions of this agreement, in particular the updated Annex XVII-3, would introduce the latest EU standards in the field of electronic communications in Ukraine. The country is also gradually approximating its regulations with regard to other components of the EU DSM – electronic identification, electronic payments and e-payment systems, e-commerce, protection of intellectual property rights on the Internet, cybersecurity, protection of personal data, e-government, postal services, etc. These steps will, in turn, ensure Ukraine’s gradual integration into the EU’s Digital Single Market, which will facilitate digital transformations within the country and open a new window of opportunity for individuals and businesses.

This brief summarizes the results of our recent work (Iavorskyi, P., et al., 2020), in which we estimate the effect that Ukraine’s integration into DSM could have on EU-Ukraine bilateral trade as well as Ukraine’s GDP growth.

Benefits of Integration into the EU DSM

The EU DSM strategy comprises three pillars: (1) better access for consumers and businesses to digital goods and services across Europe; (2) creating the right conditions and a level playing field for digital networks and innovative services to flourish; (3) maximizing the growth potential of the digital economy (EC, 2021).

These goals suggest that the major benefits of Ukraine’s integration into the DSM are likely to come from 1) reduction of cross-border regulatory barriers and restrictions to EU-Ukraine trade, 2) acceleration of the development of Ukraine’s digital economy in line with EU standards.

Indeed, the trade of goods and services is increasingly becoming “digital” – i.e., involving “digitally enabled transactions in goods and services that can be either digitally or physically delivered” (OECD, 2019). Trade digitalization (e.g., electronic contracts, electronic payments, e-customs, etc.) simplifies export and import procedures, reduces trade costs for exporters, and creates new opportunities for trade with the EU, in particular for SMEs. Therefore, the reduction of regulatory restrictions on cross-border digital trade reduces the overall level of restrictiveness of trade in goods and services.

Thus, digitalization is expected to facilitate and intensify the total EU-Ukraine trade in goods and services. It is also anticipated to increase the productivity of Ukraine’s economy which will have a positive impact on the country’s economic growth.

Major benefits include lower prices and greater access to EU online markets for Ukrainian consumers and business, digital innovative products and services, greater online consumer protection, lower transaction costs for businesses, improved quality and transparency of public digital services and e-government as well as an intensification of innovation development in Ukraine.

At the same time, Ukraine’s integration into the DSM entails several obligations: to align national legislation and standards with EU legislation and standards; to ensure institutional and technical capacity as well as interoperability of digital systems. For businesses in Ukraine, this means facing new EU requirements aimed at improving consumer and personal data protection, as well as increased competition from European companies in digital markets. However, these changes are necessary if the country wants to build a common economic space with the EU, especially given the growing impact of digital technologies on international trade and economy.

Ukraine in International Digital Rankings

Many international digital development rankings show that Ukraine lags behind EU countries, including its neighbors that recently joined the EU.

According to the UN e-Government Development Index (EGDI) for 2020, Ukraine ranks 69th among 193 countries and is included in the group of countries with high levels of e-government development. It received the lowest scores for Telecommunications Infrastructure and Online Services, and the highest for Human Capital. Nevertheless, Ukraine is lagging behind its neighboring EU members, – Poland, Hungary, Slovakia, Romania, Bulgaria, Lithuania, etc., – which belong to the group of countries with very high levels of e-government development (UN, 2020).

In the Network Readiness Index (NRI) ranking for 2019, Ukraine ranked 67th among 121 countries. As for the components of the index, Ukraine ranks worst in the following indicators: Future technologies (82nd out of 121), ICT Use by Government and Online Government Services (87th), and Regulatory Environment (72nd). Neighboring EU countries have higher rankings (Poland – 37, Latvia – 39, Czech Republic – 30, Croatia – 44). Other neighboring countries do somewhat better than Ukraine (Turkey is ranked 51st, Russia – 48th) or occupy positions close to Ukraine (Belarus – 61, Moldova – 66, Georgia – 68) (Portulans Institute, 2019).

In 2019, the country ranked 60th among 63 countries included in the World Digital Competitiveness Ranking (WDCR) rating. Just as in the other rankings, Ukraine scored well in the Knowledge component (40th among 63 countries), while in terms of Technology and Future Readiness it was at the bottom (61st and 62nd position respectively) (IMD, 2019).

Hence, it is primarily the technological and regulatory issues, that need to be addressed in order to improve Ukraine’s digital position in the region and the world.

Methodology

Measuring Ukraine’s Digitalization level

In order to estimate the impact of digitalization, a Composite Digitalization Index is calculated for Ukraine, the EU, and other countries included in the model. This index is based on 11 digital indicators, combined into five components that characterize different areas of the digital economy and society – Connectivity, Use of the Internet by citizens, Human capital, Integration of digital technology by businesses, and Digital public services.

Our results confirm that the level of digital development in Ukraine is far below the EU average. It also lags behind the new EU Member States, which have a lower level of digital development compared to the other EU countries. As of 2018, the widest gaps between Ukraine and the EU average are found in Digital Public Services, Connectivity and Use of Internet by citizens. At the same time, Ukraine performed better in Human Capital and Integration of digital technology by businesses.

Measuring Digital Services Trade Restrictiveness in Ukraine

To assess the impact of digital regulatory barriers on trade, we use the Digital Services Trade Restrictiveness Index (Digital STRI) (OECD, 2020). It quantifies the regulatory barriers in five different policy areas (communication infrastructure, electronic transactions, electronic payments, intellectual property, other restrictions) that affect trade in digital services (Ferencz, J., 2019). OECD calculates Digital STRI for OECD countries and some non-OECD countries. As Ukraine is not included in this index, we estimate it for 2016-2018 using the OECD methodology.

Our estimations show that the level of digital services trade restrictiveness in Ukraine is much higher than the EU average. The regulatory differences in the digital sphere between Ukraine and the EU increase the cost of cross-border digital transactions between countries.

For Ukraine, most barriers are related to cross-border electronic payments and settlements, protection of intellectual property rights on the internet, cross-border electronic transactions (for example, the divergence of the national requirements for foreign trade agreements, including electronic ones, from international practices and standards, lack of practical mechanisms for the application of the electronic digital signature in foreign trade contracts, lack of mutual recognition of electronic identification and electronic trust services between Ukraine and major trading partners, etc.), other barriers (requirements for the use of local software and cryptography, etc.). These regulatory restrictions significantly hinder the development of cross-border cooperation and Ukraine’s integration into the European and global digital space.

Ukraine’s integration scenarios

In the event of Ukraine’s integration into the EU DSM, the country’s regulatory environment and digital development are expected to gradually approach the EU averages. We model it through assuming that the regulatory differences between Ukraine and the EU (captured by the Digital STRI Heterogeneity Indices – see OECD, 2020) will be decreasing, and level of digitalization in the country (captured by the Digitalization Index – OECD, 2020) will converge towards that of EU-DSM members.

We considered three integration scenarios that imply high, medium, and low levels of Ukraine’s approximation to the regulatory environment and digital development of the EU. For instance, the high scenario implies the highest level of Ukraine’s digital development and the lowest level of regulatory differences between Ukraine and the EU.

Models

We study the effect of reduced regulatory differences in the digital sphere on Ukraine-EU trade using a gravity model – one of the traditional approaches in the international trade literature. A gravity model predicts bilateral trade flows based on the size of the economy and trade costs between countries (affected by distance, cultural differences, FTAs, tariffs, etc.)

The study uses the following specification of the model for exports of goods and services in 2016-2018:

• Dependent variable – the total export flow of goods and services from country into country j (all possible pairs of countries).

• Independent variables – distance between countries and common characteristics (borders, language, law), existence of a free trade agreement, level of tariff protection (for goods), level of regulatory heterogeneity in the digital sphere between the two countries, and a set of fixed effects for each country.

We also estimate how digital development affects technical modernization, productivity, and economic growth. Technically, we use a Cobb-Douglas production function to describe each country’s output and model its total factor productivity component as a function of digital development (captured by the Digitalization index).

Results

The results suggest that Ukraine’s integration into the EU DSM will be beneficial for both Ukraine and the EU. Under all integration scenarios, bilateral trade between Ukraine and the EU is expected to intensify considerably due to enhanced regulatory and digital connectivity between the two.

Ukraine’s total exports of goods and services to the EU are estimated to grow by 11.8-17% ($2.4-3.4 billion) and 7.6-12.2% ($302.5-485.5 million), respectively – a cumulative increase throughout the period of implementation of reforms aimed at regulatory and digital approximation of Ukraine to the EU.

 Figure 1. The impact of Ukraine’s integration into the EU’s DSM on the exports of services from Ukraine to the EU*: three integration scenarios

Source: Authors’ own calculations. The current level of Ukraine’s exports of services to the EU – as of 2018

Figure 2. The impact of Ukraine’s integration into the EU’s DSM on exports of goods from Ukraine to the EU*: three integration scenarios

Source: Authors’ own calculations. The current level of exports of Ukrainian goods to the EU as of 2018

The EU would increase its exports of goods and services to Ukraine by 17.7-21.7% ($4.1-5 billion) and 5.7-9.1% ($191-305 million), respectively.

The acceleration of Ukraine’s digital development will bring productivity gains that would transform into higher GDP growth. It is estimated that a 1% increase in Ukraine’s digitalization level is expected to raise its GDP by 0.42%. As a result, the country’s gradual approximation to EU levels of digitalization would result in additional Ukraines GDP growth of 2.4-12.1% ($3.1-15.8 billion), depending on the scenario.  

Figure 3. Impact of digitalization on Ukraine’s GDP growth: three digitalization increase scenarios

Source: own calculations. The left axis – GDP growth (%), the right axis – the level of digitalization. The current level of digitalization of Ukraine as of 2018.

Conclusion

According to our estimations, improved digitalization and reduction of regulatory barriers in the digital sphere between Ukraine and the EU will have a positive effect on trade for both Ukraine and the EU. There is also a significant potential for economic growth to be attained in Ukraine by increasing digitalization and productivity of various spheres of the economy and society.

Realization of this potential would, however, require a substantial regulatory approximation on the Ukrainian side to achieve alignment with the EU DSM. The main emphasis needs to be put on electronic identification and transactions, payment systems and electronic payments, protection of intellectual property rights on the internet, cybersecurity, and personal data protection.

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.

Political Implications of the Rise of Mobile Broadband Internet

Posted on February 8, 2021 | Policy Brief

Image of 5g broadband tower representing implications mobile internet

In the last ten years, the world has experienced the dramatic rise of mobile broadband internet brought by third-generation (3G) and fourth-generation (4G) mobile networks. This has resulted in major political changes – reduced confidence in governments around the world, lower voting shares of incumbent political parties, and the rise of populists. The empirical evidence is consistent with both the optimistic view of 3G internet (the “Liberation Technology”) and the pessimistic one (the “Disinformation Technology”). 3G internet helps to expose actual corruption; however, it also contributes to electoral successes of populist opposition.

The Spectacular Rise of 3G

Communication technologies have undergone a dramatic change in the last 10-15 years. According to the International Telecommunications Union (ITU), there were only 4 active mobile broadband subscriptions per hundred people in the world in 2007, while this number reached 75 per hundred in 2020. The growth of mobile broadband internet – provided by the third and fourth generation of mobile networks (3G and 4G, respectively) – was the main driver of growth in broadband access. The number of fixed broadband subscriptions per hundred people has only increased from 5 to 15 percent in the same period of time.

Relative to the previous generations of mobile technology, 3G provides a qualitatively different way of using the internet. First, it is broadband access on the go, available wherever the user is rather than at a fixed point at home or in the office. Second, it allows for downloading and uploading photos and videos. Before 3G, mobile technology only allowed exchanging text messages along with limited and slow access to the web. Third, it is the technology that is best suited for social media. While social networks started before 3G and were initially accessed on fixed broadband, today most Facebook, Twitter and YouTube users are mobile.

Liberation Technology or Disinformation Technology?

What are the political implications of the spread of this new technology around the world? Initially, political scientists were excited about the internet as a “Liberation Technology”, especially after it played an important role in the Arab Spring. Internet – and in particular mobile internet –helped pro-democracy activists in autocratic states to disseminate critical information about the government, expose corruption, and coordinate protests.

Later on, however, it became clear that social media also provided a platform for the dissemination of false news and hate speech – thus supporting the rise of populists. This led to a rethinking of the role of mobile internet – and rechristening it into a “Disinformation Technology.”

Which view, the optimistic or the pessimistic one, is correct? In Guriev et al. (2021), we study the impact of the expansion of 3G around the world on attitudes to government and electoral outcomes.

Exposing Actual Corruption

In order to explore the effects on confidence in government, we use data from Gallup World Poll surveys of 840,537 individuals from 2,232 subnational regions in 116 countries from 2008 to 2017. In each region and year we calculate the population-weighted average access to mobile broadband relying on the network coverage data from Collins Bartholomew’s Mobile Coverage Explorer.

First, we find that increased access to 3G internet causes lower confidence in government, judiciary, honesty of elections, and a lower belief that the government is not corrupt. As shown in Figure 1, the magnitudes are substantial. In our paper, we show that a decade-long 3G expansion has the same effect on government approval as a 2.2 percentage-point rise in the national unemployment rate.

Figure 1. Mobile Broadband Access and Government Approval.

Source: Guriev et al. (2021), Table 1, authors’ calculations.

This effect is only present when there is no online censorship and stronger when traditional media are not free. Furthermore, the spread of 3G makes people think that the government is corrupt when the actual corruption is high. In the cleanest countries of the world, the effect is actually positive – better access to information may help citizens to understand that other countries are much more corrupt relative to their own. 

This positive impact is, however, limited to about 10% of the world’s countries. On average, the effect of 3G on the perception that government is clean is negative (see Figure 1). There are two potential explanations. First, as suggested by Gurriv (2018), before the arrival of the fast internet, the elites controlled the media and, as a result, the public was not fully aware of the elites’ corruption. 3G helped to expose this corruption and corrected the pre-3G positive bias. The second explanation is related to the negative bias of social media where critical messages spread faster and deeper (see the references in Guriev et al. 2021).

Another potential explanation is that social media promote overall negative and pessimistic attitudes. We show that this conjecture is not consistent with the evidence: the spread of 3G does not reduce life satisfaction or expected future life satisfaction.

Helping European Populists

The evidence above is consistent with the view that mobile broadband internet and social media help to expose misgovernance and corruption. These findings are in line with the optimistic view of mobile broadband internet as a “Liberation Technology.” However, it turns out that the pessimistic view of “Disinformation Technology” may also be correct.

We examine the impact of 3G expansion on the outcomes of 102 parliamentary elections in 33 European democracies between 2007 and 2018. Using subnational data, we show that the spread of 3G, not surprisingly, decreases the vote share of incumbents substantially (see Figure 2).

 Figure 2. The impact of 3G expansion on incumbent vote share in Europe.

Source: Guriev et al. (2021), Figure VIII.

Figure 3. The impact of 3G expansion on opposition vote share in Europe.

Source: Guriev et al. (2021), Figure IX.

If incumbents lose votes, who picks them up? We show that the main beneficiaries of 3G expansion are the populist opposition parties, both on the left and right (Figure 3). The non-populist opposition does not gain.

Why do populists benefit from the spread of mobile broadband and social media? One explanation is that social media is decentralized and has no entry barriers. It is not the first time in history that populist politicians have relied on new communication technology to circumvent mainstream media controlled by the elites (e.g. the US late 19thcentury populists used telegraph and railroads, the Nazis in Germany used radio). It may also be the case that populist messages may be simpler, and thus, better suited for a short and catchy communication on social media. For example, another pan-European family of anti-system parties, the Greens, do not benefit from the spread of the 3G internet at all (see Figure 3): their narrative is more complex, asking voters to take responsibility for the planet.

Fact-Checking Alternative Facts

Many populist politicians point to actual corruption of the incumbent elites, but some also spread false narratives or “alternative facts.” (It was Donald Trump’s Counselor Kellyanne who, in January 2017, when asked to comment on false statements by Trump’s Press-Secretary about his inauguration, famously said that these were not falsehoods but “alternative facts.”) What can be done to stop the dissemination of these falsehoods on social media? Can fact-checking by mainstream media and independent organizations help?

In two studies, Barrera et al. (2020) and Henry et al. (2021), we carry out two randomized online experiments to identify the causal effects of alternative facts spread by populist politicians and their fact-checking. The findings are as follows: (i) alternative facts are highly persuasive; (ii) fact-checking helps to correct factual beliefs – but do not change voting intentions; even though the voters understand that the populists misrepresent the facts, they still support their agenda; (iii) fact-checking, however, substantially reduces sharing of alternative facts on social media; (iv) the impact of fact-checking on sharing is equally strong regardless of whether the users are forced to view the fact-checking information or are simply given an option to click on a fact-checking link; (v) asking users to re-confirm their intention to share alternative facts with an additional click greatly reduces sharing.

Our results suggest that fact-checking may not be as effective as fact-checkers themselves hope, but can help slow down the dissemination of falsehoods on social media. Furthermore, our analysis delivers clear policy implications – both providing fact-checking (even in the form of accompanying alternative facts with fact-checking links) and requiring additional clicks before sharing can be very effective.

Conclusion

The findings from our analysis of the worldwide spread of mobile broadband internet in the last decade are consistent with both optimistic and pessimistic views. On the one hand, 3G internet does help expose actual corruption. On the other hand, it helps populist opposition to gain votes. Likely, the latter result is eventually due to the populists’ abuse of online platforms for spreading disinformation. We show that the propagation of falsehoods on social media can be at least partially slowed down by fact-checking.

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.

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

Posted on February 1, 2021 | Policy Brief

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. Reuters, The Economic Times, EUIdeas). These articles described measurable improvements in air quality in cities with government-mandated lockdowns. Recent academic publications have confirmed these reports in a variety of settings including the US (Berman and Ebisu 2020), China (Chen et al. 2020), and Korea (Ju et al. 2020).

While Eastern Europe was less affected by the initial wave of COVID-19 than Western Europe, most countries imposed lockdowns and social distancing measures that can be expected to have affected air quality. Figure 2 uses daily data from the World Air Quality Index for 221 European cities to compare average air pollution in 2020 to 2019. Overall, these plots suggest that air quality did improve in Eastern European cities relative to the previous year. However, not all types of pollutants declined and the declines are slightly smaller on average than in Western European cities. Panels A, B, and C plot air quality indices for fine particulate matter (PM 2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) respectively. Dots below the line represent cities where the average air quality index was lower (indicating less pollution) in 2020 than in 2019. The declines are largest for NO2 – a gas that is formed when fuel is burned. The reduction in traffic and transportation in all European cities is likely to have contributed to this drop. By contrast, there were no statistically significant declines in SO2. This may be due to the fact that power generation, which is the source of most SO2 emissions, was less affected by lockdowns than transportation.

Figure 2

Panel A

Panel B

Panel C

Source: Author’s calculations based on the World Air Quality Index COVID-19 dataset. Each marker represents a city. Markers below the 45-degree line represent cities where emissions for the respective category of pollutant were lower in 2020 than in 2019. For reasons of presentation, outliers were excluded from panels B and C.

The variation in COVID-19 prevalence over the course of 2020 is visible when tracking pollution over time. Figure 3 shows that average daily NO2 emissions in Western European cities dropped most from March to June of 2020, during the first wave of the pandemic. NO2 levels were comparable to the previous year in July and August when case numbers fell and restrictions were lifted. In the last months of the year, as the second wave hit, NO2 emissions once more dropped below the previous year’s average. This pattern is similar for Eastern European cities but the decline in NO2 in the first half of the year is less pronounced.

Figure 3

Source: Author’s calculations based on the World Air Quality Index COVID-19 dataset. Lines show the seven day moving average of the ratio between average NO2 emissions in 2020 and 2019.

Conclusion

The COVID-19 epidemic has highlighted the health costs of air pollution. The preliminary evidence suggests that long-term exposure to pollution increased COVID-19 mortality rates (Cole et al. 2020, Wu et al. 2020). This is a particular concern for countries across Eastern Europe which – at the time of writing – are still grappling with the second wave of the pandemic in Europe. Many people in this region have been exposed to polluted air for decades.

The pandemic has also demonstrated that air quality can improve relatively quickly when human behaviour changes. The data described in this brief suggest that Eastern Europe was no exception in this regard, although the declines were confined to some categories of pollutants. Achieving a more general, and sustained improvement in air quality will require a shift from coal power towards cleaner forms of energy.

Stimulus packages aimed at a post-pandemic economic recovery can provide an opportunity for policy to reorient the economy and accelerate such a shift. The consultancy Vivid Economics, which rated G20 member countries’ proposed stimulus packages in terms of their environmental impact, found that the ‘greenest’ stimulus proposals are those of the European Commission, France, UK, and Germany. Russia is one of the worst performers on this index (Vivid Economics 2020). Whether governments in Eastern Europe are able to take advantage of this opportunity will depend on their respective fiscal space and whether they make improving air quality a priority.

References

  • Bagayev, Igor, and Julie Lochard, 2017. “EU air pollution regulation: A breath of fresh air for Eastern European polluting industries?.” Journal of Environmental Economics and Management 83: 145-163.
  • Berman, Jesse D., and Keita Ebisu. 2020 “Changes in US air pollution during the COVID-19 pandemic.” Science of the Total Environment 739: 139864.
  • BP 2020 “Statistical Review of World Energy – all data, 1965-2019“
  • Bobak, Martin, and Richard GA Feachem. 1995. “Air pollution and mortality in central and eastern Europe: an estimate of the impact.” The European Journal of Public Health , no. 2: 82-86.
  • Cole, Matthew, Ceren Ozgen, and Eric Strobl, 2020. “Air pollution exposure and COVID-19.”.
  • Chen, Kai, Meng Wang, Conghong Huang, Patrick L. Kinney, and Paul T. Anastas, 2020. “Air pollution reduction and mortality benefit during the COVID-19 outbreak in China.” The Lancet Planetary Health 4, no. 6: e210-e212.
  • European Environment Agency 2020. “Air Quality in Europe – 2020 report“, EEA Report No 9/2020
  • Matkovic Puljic, V., D. Jones, C. Moore, L. Myllyvirta, R. Gierens, I. Kalaba, I. Ciuta, P. Gallop, and S. Risteska. 2019. “Chronic coal pollution–EU action on the Western Balkans will improve health and economies across Europe.” HEAL, CAN Europe, Sandbag, CEE Bankwatch Network and Europe Beyond Coal, Brussels.
  • Ju, Min Jae, Jaehyun Oh, and Yoon-Hyeong Choi. 2020. “Changes in air pollution levels after COVID-19 outbreak in Korea.” Science of The Total Environment 750: 141521.
  • Transport & Environment, 2018. “Briefing: Dirty diesels heading east”
  • Vivid Economics, 2020. “Greenness of Stimulus Index” December 2020 update
  • World Air Quality Index, 2021. “Worldwide COVID-19 dataset“
  • World Health Organization, 2018. “WHO Global Ambient Air Quality Database (update May 2018)”
  • Wu, Xiao, Rachel C. Nethery, Benjamin M. Sabath, Danielle Braun, and Francesca Dominici, 2020. “Exposure to air pollution and COVID-19 mortality in the United States.” medRxiv

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Optimal Recommendation System with Competing Sellers

Posted on January 25, 2021 | Policy Brief

Person Holding Pineapple Fruit Near Red Wall Representing Optimal Recommendation System

Many e-commerce platforms that connect buyers and sellers employ recommendation systems to help customers find products and services. Such platforms seek to maximize their profits which mainly comes from a commission on sales made via the platform. This may create incentives for platforms to use a recommendation strategy that suppresses competition among sellers and keeps prices and the resulting commission high. At the same time, the huge success of platforms such as Amazon suggests that they also care about customer satisfaction. Thus, the platform has an incentive to recommend goods that are cheaper and a better match for customer’s tastes. This requires not only sufficient competition between sellers but also that sellers act to improve the fit of their product to customer needs. Since these actions are typically costly, a high commission may disincentivize sellers to undertake them, thereby negatively affecting customers. Therefore, in designing the recommendation system and deciding on commissions, the platform should carefully balance the pro-competitive customer care and anti-competitive incentives to keep high prices and profits.

Introduction

When we search for a product on an e-commerce platform, such as Amazon or AliExpress, the default search outcome often contains a list of recommended products sold by vendors that are selected by the platform. The order of these sellers is, of course, not random – the platform’s decision on which sellers to recommend is strategic and there could be different forces driving such a strategy. For example, since the platform charges commission on sales, it may have an incentive to recommend the most expensive seller among those who sell similar products. At the same time, such a recommendation strategy, and high(er) prices in general, may negatively affect customer satisfaction from the marketplace and lead to a loss of its customer base. This is not in the best interest of the platform, especially if it wants to achieve long-term sustainability and growth.

The behavior of sellers adds a further layer to these considerations. Indeed, sellers are likely to adjust their pricing behavior and competitive strategies in response to a platform recommendation system.

These considerations give rise to two questions: First, how should an e-commerce platform design its recommendation system, or in other words, how does it optimally choose which sellers to recommend, which commission rate to set, etc.? Second, how does the presence of this system affect the competition and prices?

Further, a seller’s strategy may depend not only on the presence of recommendations but also on the commission rate set by the platform. Sellers usually have an option to perform costly actions in order to improve the match of their product to customers’ needs. For example, sellers may disclose more information on the characteristics of a good they are selling: spend time and money on detailed descriptions of their goods, or provide high-resolution photos. Though these actions are usually left at sellers’ discretion, they may substantially increase a customer’s satisfaction by improving the match between the purchased product and customer’s preferences.

In turn, a better fit may create a more loyal customer base for the seller, giving her more market power and increased profits. However, if the platform sets a high commission rate, sellers will have less incentive to undertake such costly actions (since the platform eats up a large share of the return to this action). This raises the questions – what is the optimal commission rate chosen by the platform, and how does the optimal commission rate affect sellers’ incentives to disclose information about their goods?

Another issue that arises here concerns the optimal precision of the recommendation system, that is, its ability to pin down customers’ tastes correctly. When the e-commerce platform deals with heterogeneous buyers, it should assess buyer’s preferences prior to making a recommendation. Although almost all research in Computer Science regarding recommendation systems focuses on how to make the precision as high as possible, I show that the highest level of precision may not be optimal from the platform’s perspective. Intuitively, this is because highly precise recommendation systems differentiate customers effectively, which in turn could give sellers local monopoly power and translate into higher prices. At the same time, an inaccurate recommendation system cannot distinguish customers with different preferences and views, which intensifies the competition by allowing sellers to compete for all customers.

In Fedchenko (2020), I address the abovementioned and other related issues on recommendation systems of e-commerce platforms. This brief summarizes the main findings of the study.

Model Description and Findings

In my model, I consider a platform that is designing a recommendation system. That is, for each seller, the platform chooses what share of customers end up receiving a recommendation to buy from this seller. This choice depends on the seller’s price, the quality of the good (if disclosed by the seller), and the buyers’ tastes. The platform also sets the commission rate it charges the sellers. I focus only on direct recommendations (i.e., the platform gives each buyer a unique recommendation). Although, in reality, platforms usually provide users with a ranking of alternatives, I assume that buyers always choose the top-ranked alternative which is equivalent to a single recommendation.

The model also assumes that a platform seeks to maximize the weighted sum of its profit (driven by commissions) and aggregate consumer surplus (motivated by the platform’s willingness to build a steady customer base). The (exogenous) weight assigned to the aggregate consumer surplus is referred to as the platform’s degree of consumer orientation (DCO). DCO is a measure of how much the platform cares about customer satisfaction and it plays an important role in determining the platform’s optimal recommendation strategy. In turn, customers have higher satisfaction if they buy a good that better fits their tastes, has higher quality, and is sold at a lower price.

Recommendation System Affects Competition

My model demonstrates that the presence of a recommendation system that charges sellers commission on sales (i.e. makes the platform have a stake in sellers’ profits) “softens” competition, and, in turn, increases prices. This effect is stronger the more a platform cares about its profits relative to customer satisfaction. The force that drives this result has already been touched upon in the introduction: if the platform has a stake in sellers’ profits, it will occasionally recommend sellers with higher prices. However, since the platform also cares about consumer surplus (which decreases if the price goes up) these high-priced recommendations will not go to all buyers, and therefore, the overall price level will not become too high. Still, the sellers are encouraged to set higher prices in this scenario, as compared to the hypothetical case in which customers know about the sellers without the platform.

Optimal Commission vs. Information Disclosure

The relationship between the commission rate and the seller’s decision on how much information to disclose is nontrivially affected by the DCO. If the DCO is high, then a higher commission rate causes sellers to disclose less information about their goods in equilibrium. If the DCO is low, the relationship is reversed: a higher commission rate increases the amount of disclosed information. This result stems from the interplay between two counteracting forces. On one hand, an increase in the commission rate decreases a seller’s return to providing disclosure, and hence, discourages sellers from making the effort to disclose. On the other hand, a higher commission rate increases the platform’s stake in the sellers’ profits and, as a result, softens competition, increases sellers’ prices and profits, and thus makes it more worthwhile for sellers to provide disclosure of their goods.

An interesting implication of this result is that for a high DCO, the optimal commission rate for a platform should be as small as possible (just enough for the platform to cover the operational cost).

Optimal Precision

Next, I show that a lower precision (i.e., ability of the recommendation system to pin down buyers’ tastes) weakens the effect of the presence of a recommendation system on competition. This happens since more imprecise recommendations effectively increase the share of “undecisive” customers and, thereby, the appeal to capture that market share. As a result, the competition for those customers will intensify.

Imprecision also affects the amount of product information sellers choose to disclose in equilibrium. However, the direction of this effect depends on the cost of disclosure: if the cost is low, a more precise recommendation system may increase the amount of disclosed information, while the result is reversed if the cost is high. The reason for that is as follows: The platform has two sources of information to infer whether a particular seller fits a certain buyer – the buyer’s preferences and the seller’s information on the quality of the product (if disclosed). If the buyer’s taste is measured imprecisely, while the seller’s information is more precise, it is optimal for the platform to focus on the latter when designing a recommendation system. This, in turn, would motivate sellers to disclose more information about their products.  In the case of low disclosure costs, this positive effect on disclosure more than offsets the direct negative effect of imprecision brought about by harsher competition and lower profits. In the case of high costs, the direct effect dominates.

I also show that some imprecision, in fact, can be optimal for the platform. Perfect precision softens the competition and results in increased prices for consumers. This negative effect on consumer satisfaction outweighs the benefits of a perfect match between seller and buyer. So, consumers prefer a certain degree of imprecision over perfect precision, which in turn, makes the platform unwilling to implement perfect precision. In other words, it is optimal to “sacrifice” some customers (i.e., not recommending them the best fitting alternative) in order to intensify the competition among sellers and, eventually, benefit all customers through lower prices.

Conclusion

The presence of a recommendation system on an e-commerce platform that charges sellers commissions on sales may cause softer competition and lead to higher prices and profits of sellers, as well as increased earnings for the platform. At the same time, it can sometimes be optimal for a platform to set a low commission rate since it would guarantee that sellers disclose more information about their goods which would improve the match between customers’ tastes and the goods they buy. If customer satisfaction is important for a platform, the indirect positive effect on customer satisfaction of a low commission rate, via sellers’ decisions, may outweigh the direct negative effect on the platform’s and sellers’ profits. Similarly, a recommendation system with some degree of imprecision can be beneficial for customers since it does not allow sellers to get local monopoly power. So, increasing the precision in the measurement of customers’ tastes – which seems to be the focus of many ongoing computer science studies devoted to recommendation systems, – may not actually be in the best interest of a platform.

In the modern era of digitalization, the use of e-commerce platforms is on the rise. Moreover, the ongoing COVID-19 pandemic has increased the use of such platforms even further. Understanding the implications of the strategies used by these platforms, such as recommendation systems, on prices, competition, and societal welfare is, thus, a necessary component for developing efficient regulation principles.

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 Southern Urals as a Touchstone for Soviet Wartime Performance

Posted on January 18, 2021 | Policy Brief

Image of a Soviet tank representing soviet war performance

As time passes and archives open, ever more topics in Russian military-economic history can be studied with primary sources. One such theme is the colossal evacuation of industrial enterprises and equipment from July 1941 onwards. Thousands of railway cars and lorries carried equipment, raw materials, as well as personnel from Ukraine, the Baltics, and western regions of the Russian Federation to the Urals and beyond. A recent documentary collection Put’ k Pobede (The Road to Victory) opens new areas for research on the southern Urals. These regional sources illustrate and add details to documents from the federal archives on the history of the Soviet military-industrial complex. Successful evacuation of industrial capacity eastwards was a decisive factor for the Soviet endurance and finally its victory in 1945. However, many empirical questions remain to be answered and analytical calculations to be done, on how in fact the Soviet system managed simultaneously to successfully evacuate factories eastwards and thousands of troop transports westwards to the fronts.

New Frontiers for Research on the Soviet War effort, 1939–1945

The role of the new industrial centers in the Urals and Siberia for the Soviet defense potential has been recognized long ago (1). From the mid-1920s, Soviet military leaders included projections for full mobilization of industrial and human resources in contingency plans for the case of war. Evacuation projects outlined which important factories were to be re-located from close-to-border areas (within the range of enemy air bombings) to well-prepared interior locations (2). Industrial plans in the late 1930s put significant emphasis on the enhancing of defense-related production, as well as on modernization of the armed forces (3).

Checking the blueprints for IS heavy tank at the Kirov Tank Factory in Cheliabinsk.

In the early 2000s, a grand research project started on the history of the Russian and Soviet military-industrial complex by exploring the main federal archives (GARF, RGAE, RGVA, and others). The project has so far resulted in five volumes that cover the period from 1914 till 1942. The first volumes show the evolution of the Russian defense industries until the mid-1930s, with special emphasis on how military considerations influenced the five-year plans for 1928–32 and 1933–37. The fourth volume starts (p. 5–85) with a historical preface by Professor Andrei Sokolov (1941–2015), who was also the author of a most informative study of the military-industrial complex. It contains documents for the crucial period up to June 1941 (4). The fifth volume reproduces relevant documents from several archives concerning the first war-years 1941 and 1942. (5)

How did Soviet security concerns change in the first stage of World War Two? In August 1939, the Red Army won a momentous victory over the Japanese forces at Khalkhin-Gol in Mongolia. Japan thereafter gave up their invasion plans against the Soviet Far East, and shifted its aggression southwards to the Philippines and Indochina. Thus, the risk diminished considerably of the USSR facing a two-front war, with tough enemy coalitions in Europe as well as in the East. (6). This strategic significance of the Red Army’s victory was apparently missed in Berlin. In 1940, the German military leaders paid attention mostly to the poor performance of the Soviet army in the Winter War against Finland (7). Encouraged by an easy victory over France by June 1940, Hitler ordered Wehrmacht to plan for war against Russia.

When the Soviet leaders in 1939 concluded a non-aggression pact with Germany, they obviously calculated that France and Great Britain were to wage a long-drawn-out war against Germany for many years, yet with uncertainty as to who would be the winning one. The drastically changed outlook after the sudden defeat of France in 1940 challenged the Soviet leaders to speed up already expansive plans for military-industrial production.

The American engineer John Scott who had worked as a welder in Magnitogorsk in the 1930s, and thereafter as a correspondent in Moscow for a British newspaper, compiled a massive dossier for the Research and Analysis department of the American intelligence O.S.S. (Office of Strategic Studies). His 1943 exhaustive “Heavy industry in the Soviet Union east of the Volga; a report prepared for the Board of Economic Warfare” covered a unique amount of data on new industrial enterprises obtained from open sources. While stationed in Stockholm as O.S.S. agent later in World War II, under the cover of a Time-Life correspondent, John Scott lectured in many cities in Sweden over his best-selling book “Behind the Urals”, which in Swedish had the more pertinent subtitle “The secret of the endurance of the Russian defense” (8). Scott emphasized that Stalinist forced drive in the 1930s had created completely new industrial zones far beyond the borders, out of reach for even long-range German air raids. This had been a revelation for many Westerners. British and American military attachés in Moscow were profoundly mistaken in 1941 when they predicted a rapid German victory. As Hitler’s Operation Barbarossa came to a standstill in the winter of 1941-42, Western assessments of the real Soviet military-industrial capabilities had to be reconsidered (9).

Relocation of a Minor Industrial Nation – the 1941-42 Evacuations

A crucial factor – likewise often neglected in Western historiography – for the Soviet military-industrial endurance was the evacuation of industry. In an unprecedented way, another Soviet defense-industrial basis would rapidly emerge east of Volga, in the Urals and in Siberia.

A fundamental Russian 12-volume work on the Great Patriotic war describes main traits of the industrial evacuation (10). Already a few days after the German invasion, the situation on the fronts forced the Soviet leadership to consider completely unexpected scenarios. It was soon obvious that the German invasion could not be stopped, as the principal Red Army doctrine had expected, at the borders. All pre-war considerations of how to mobilize the Soviet military-industrial potential were up for revision. The unforeseen disasters on Soviet territory, not covered in pre-war plans for industrial mobilization, led to the formation of a council for evacuation of factories. Tens of thousands industrial workers and millions in the civilian population must be evacuated.

The massive evacuations of entire factories, or at least the most crucial equipment, started already in July 1941 from the Baltic republics, Ukraine, and Russia’s Western regions. The council on the evacuation sent directives concerning which factories to relocate eastwards and to which cities.

Evacuated equipment installed, under open skies, even before the factory walls were built!

Evacuation organs were responsible for rail, road, and river transports, as well as for the integration of evacuated resources to existing factories or to new building sites.

Facilities and stock that could not be evacuated were destroyed so as not to fall into the hands of the enemy (“scorched earth policy”). Most complicated from a logistic point of view was the evacuation of the industrial, transport, and energy production facilities. These had to be constantly re-adapted as the military situation changed with the German armies’ further advance towards Moscow, Leningrad, and in Ukraine in particular. Troop transports towards the fronts had priority; thus, evacuation trains sometimes had to wait on sidetracks for many days.

Assembly of engines at the Urals Automotive Factory (UAZ) in the Miass city.

Hundreds of thousands of civilians were evacuated from Ukraine, southern and western parts of the Russian Federation, and sent to Uzbekistan and other interior regions. Western literature has described few aspects of the evacuation, with emphasis on problems by influx of thousands of refugees, e.g. in the cities of Kirov (now Viatka) and Tashkent (11).

Mentioned should be the successful evacuation of the country’s cultural treasures. One telling example is how the staff of the Hermitage museum and hundreds of volunteers in Leningrad managed to pack down much of the museum’s exhibits. Over a million works of art were sent in special trains to Sverdlovsk (now Ekaterinburg), where they were safely stored until 1945. Remaining paintings and sculptures were stored in the underground of the Hermitage. When evacuation could not be accomplished, German occupation forces plundered art collections, and thousands of war trophies sent home by Nazi generals.

An Innovative Source Collection Volume from Cheliabinsk

In regional studies more complex, detailed analyses of the evacuation, its successes and failures have been presented. A documentary collection Put’ k Pobede (The Road to Victory) from the Cheliabinsk State Archives (OGAChO), shows how formerly restricted topics can be studies as archive holdings are declassified. The Road to Victory contains over sixty photocopied documents. It gives short biographies of industrial managers and contains many pertinent photographs from enterprises. The interested reader of the photocopies will find a great amount of new information that calls for analysis (12). One of the primary findings in the archives is that the number of enterprises, whole or parts thereof, set up and restarted in Cheliabinsk and other cities in the southern Urals were 329 enterprises from 27 different ministries (commissariats). That is substantially larger a figure than the previously assumed number of enterprises. The leading historian on this topic, Marina Potiomkina, professor at the G.I. Nosov Magnitogorsk State Technical University, gives a thorough presentation of how evacuated enterprises in fact managed to integrate into the existing factories (13). The dimensions of this emergency relocation of entire industrial plants are enormous. Often German troops were approaching closely and the factories were under bombardment. One striking example is the report on evacuation from Zaporozhie to Magnitogorsk in 1941 as the front skirmishes already threatened several factories.

Historians like to unscramble interesting information from seemingly peripheral, marginal notes in such documents. There are lots of “food for thought” in the commentaries by the wartime managers. The reader furthermore gets a clear perspective on the massive change of the urban landscape in the region. The new administrative structure is reflected in biographies of leading managers and designers, in detailed information on every known evacuation site, as well as in the characterization of affiliate people’s commissariats (ministries) that were moved from Moscow to Cheliabinsk. Important wartime reports with photos, diagrams, and drawings are reproduced in a rich illustrative section of this book. The documentary clarifies how the relocation of equipment from the Kirov Works in Leningrad to the Tractor Factory in Cheliabinsk laid the foundations for the consolidated tank industry in the Urals. Contemporary correspondence reflects both complaints and achievements, in particular under the most severe conditions in winter 1941–42.

A meeting at the Cheliabinsk Kirov Factory: Tank industry minister Isaak Zaltsman (2d from left), Region party secretary Nikolai Patolichev (4thfrom left), chief tank designer Zjozef Kotin (9th from left).

At the end of the war in 1945 many cadres, engineers, and workers could return to their home cities in western parts of Russia. The Cheliabinsk region had undergone dramatic changes. It was then a mix of the original factories, established in the 1930s or even earlier. To this was added trainloads of evacuated equipment from Leningrad, Kharkov, and other cities. New branches, in particular of defense-related industries thus formed the basis for the postwar planning. Any of the documents in Put’ k Pobede can serve as a starting point for discussions concerning the undoubtedly strong aspects of the Soviet command economy, on the one hand, and also on which reforms might have been called for even at that time period, on the other hand.

In conclusion and forward-looking, it should be mentioned that Professor Potiomkina has recently surveyed the entire historiography of Soviet wartime industrial evacuation. Her article includes not only her own and others’ works on the Urals, but also an impressive number of contributions from other regions. Her evaluation of the character of the evacuation calls for a stricter methodology, for a common conceptualization, and for a better grasp of the primary sources, in order to estimate the relative weight of planning versus improvisation, of success stories as compared to failures in the evacuation process. (14)

Note: Illustrations reproduced with permission by Cheliabinsk Regional Archive (OGAChO).

References

  • (1) Compare my previous SITE Policy Briefs in 2015, https://www.hhs.se/sv/om-oss/news/site-publications/2015/research-of-formerly-secret-archives-sheds-new-light-on-the-soviet-wartime-economy/  and https://freepolicybriefs.org/2015/05/04/new-light-on-the-eastern-front-contributions-from-russia-to-the-70th-anniversary-of-the-victory-in-europe-in-world-war-two/; see also Samuelson, Tankograd (Swedish, English or Russian version, chapters 7, 8 and 9.
  • (2) Meliia, Aleksei, Mobilizatsionnaia podgotovka narodnogo khoziaistva SSSR, [Mobilization preparedness of the Soviet economy], Moscow: Alpina Biznes Buks, 2004.
  • (3) For a most recent work, see Robert W. Davies et altere, The Industrialisation of Soviet Russia 7: The Soviet economy and the Approach of war, 1937–1939, by, London 2018, referred to in previous Policy Brief: https://freepolicybriefs.org/wp-content/uploads/2020/07/freepolicybriefs20200702-1.pdf
  • (4) Sokolov, Andrei K. Ot Voenproma k VPK: Sovetskaia voennaia promyshlennost 1917–iiun 1941, [From Voenprom to VPK: Soviet military industry 1917–June 1941], Moscow: Novyi Khronograf, 2012, chapter IV. Compare Sokolov (ed.), Oboronno-promyshlennyi kompleks SSSR nakanune Velikoi Otechestvennoi voiny (1938 – iium 1941), [The Defence-industry complex of the USSR prior to the Great Patriotic war (1938 – June 1941], vol. IV, Moscow 2014.
  • (5) Artizov, Andrei (ed.) et altere, Oboronno-promyshlennui kompleks SSSR v gody Velikoi Otechestvennoi voiny, iiun 1941–1942, [The Defence-industry complex of the USSR during the Great Patriotic war, June 1941–1942], Moscow:  Compare lecture by RGAE Director Elena A. Tiurina on this documentary volume, Оборонно-промышленный комплекс СССР в годы Великой Отечественной войны – Российское историческоеобщество (historyrussia.org) .
  • (6) Goldman, Stuart D., Nomonhan, 1939; The Red Army’s Victory That Shaped World War II, Naval Institute Press, Annapolis 2012, for analysis of this decisive battle that was previously neglected in Western historiography.
  • (7) Compare Carl Van Dyke, The Soviet Invasion of Finland, 1939–1940, London: Routledge, 1997, for a pioneer study based on declassified Soviet archival sources, that shows lessons Stalin and his generals drew from the Winter War 1939–40.
  • (8) See John Scott, Behind the Urals: An American Worker in Russia’s City of Steel, London, 1989, new edition in with foreword by Stephen Kotkin). Idem, Vad gör Ryssland bortom Ural?: Hemligheten med det ryska försvarets kraft, Stockholm: Natur och Kultur 1943. Scott’s O.S.S. study of prewar industry in the Urals and Siberia is in the Library of Congress, Washington, DC (Manuscript Division).
  • (9) For the – mostly mistaken! – Western estimates of Soviet military capabilities before the fascist invasion as well as  many months later in 1941 – 42, compare Martin Kahn, The Western Allies and Soviet Potential in World War II: Economy, Society and Military Power, London: Routledge 2019.
  • (10) Velikaia Otechestvennaia voin 1941–1945 godov. Tom 7. Ekonomika i oruzhie voiny, [The Great Patriotic war, 1941–1945. Volume 7: The Economy and Armaments of the War], Moscow 2013, “Mobilizatsiia ekonomiki SSSR i perekhod k ekonomike voennogo vremeni”, p. 60 – 117; “Evakuatsiia kak sostavnaia chast perestroika ekonomiki v voennoe vremia”, p. 118 – 144; “Sozdanie ekonomicheskikh predposylok dlia korennogo pereloma v voine”, p. 145 – 196.
  • (11) Larry E. Holmes, Stalin’s World War II Evacuations: Triumph and Troubles in Kirov, University Press of Kansas 2017; Rebecca Manley, To the Tashkent Station: Evacuation and Survival in the Soviet Union at War, Cormell University Press 2009.
  • (12) Nikolai A. Antipin et altere (ed.), Put’ k Pobede: Evakuatsiia promysjlennosti predpriiatii v Cheliabinskuiu oblast v godu Velikoi Otechestvennoi voine 194 –1945 gg., [The Road to Victory: The Evacuation of industrial factories to the Cheliabinsk region during the Great Patriotic war 1941–1945], Cheliabinsk 2020.
  • (13) See Marina N. Potiomkina, in Put’ k Pobede, p. 7–21; idem, Evakuatsiia v gody Velikoi Otechestvennoi voiny na Urale: liudi i sudby, [Evacuation in the Urals during the Great Patriotic war: People and destinies], Magnitogorsk 2002; idem, Evakuatsiia naseleniia v gody Velikoi Otechestvennoi voiny na Ural: Gendernoe izmerenie, [The Evacuation of the populations to the Urals during the Great Patriotic war: The Gender dimension], Magnitogorsk 2019; idem, Demograficheskii aspect evakuatsii naseleniia v sovetskii tyl v gody Velikoi Otechestvennoi vony, [The Demographic aspect of the evacuation of the population to the Soviet interiors during the Great Patriotic war], Magnitogorsk 2019.
  • (14) Potiomkina, Marina N. & Aleksei Yu. Klimanov, ”Sovremennaia otechestvennaia istriografiia i perspektivy izuchenija promyshlennoi evakuatsii perioda Belikoi Otechestvennoi voiny”, [Contemporary Russian historiography and perspectives on the study of industrial evacuation in the Great Patriotic War], Noveishaia istoria Rossii, Tom 10, No 3, 2020.

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

Posted on December 21, 2020 | Policy Brief

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.

Circular Economy in Belarus: What Hinders the Transformation?

Posted on December 14, 2020 | Policy Brief

20201214 Circular Economy in Belarus FREE Network Policy Brief Image 02

The transition towards a circular economy has accelerated in response to increasing environmental challenges and the need for more sustainable and cleaner production. Many countries are mainstreaming a circular economy into their policy agenda. In particular, the European Commission’s new Circular Economy Action Plan, adopted in March 2020, will be a key element of the EU Industrial strategy. In Belarus, similar policy agendas that promote circular economy have not been developed yet, however, this concept is now attracting increasingly more attention. Therefore, it is essential to identify barriers that hamper the implementation of circular economy business practices in the country. This policy brief presents the results of a survey that studied 452 Belarusian companies and their prospects and opportunities of circular transformation both within enterprises and at the national level. The findings show that high levels of capital and technology spending and lack of state-provided economic incentives are the most pressing barriers to circular economy development in Belarus. When it comes to enterprises’ own prospects for circular transformation, lack of funding is ranked as the main impediment.

Barriers to Circular Economy Development in Belarus

Despite the fact that there has been an increased interest in the circular economy, evidence suggests that its implementation has been hampered by a variety of barriers. Based on academic literature and business case studies, these barriers can be categorized into several groups (Rizos, et al., 2015; Rizos, et al., 2016; Kirchherr et al., 2018; Ritzén and Sandström, 2017):

  • Cultural barriers (e.g. social, behavioral, and managerial) – a lack of interest, environmental awareness, and/or existing differences in personal values, which hinder the development of a circular economy.
  • Information constraints – a lack of consumer and producer awareness about the key principles and best practices of circular economy implementation;
  • Inadequate regulatory environment – a lack of consistent legal framework, policy support, and incentives for circular economy transition (e.g., through tax relief, fiscal measures, or public procurement);
  • Technological barriers – an absence of a well-managed logistic infrastructure for the collection, extraction, and processing of secondary raw materials (SRM); the lack of standardization and, as a result, lower quality of goods produced from SRM; the absence of knowledge on how circularity can be implemented in a particular industry;
  • Economic impediments – barriers to circular economy transition that are due to low prices for primary raw materials and high investment costs for the implementation of circular business models, as well as lack of funding and restricted access to finance.

This categorization served as the basis for the development of our questionnaire. We surveyed enterprises on the prospects and opportunities relating to their own circular transformation as well as factors constraining the more general development of a circular economy in Belarus. The survey was conducted in 2020 by BEROC and IBB Dortmund and included 452 companies from the Belarusian regions of Brest and Mogilev. The results show that businesses view economic, regulatory, and informational barriers as the most hindering to a circular transformation of Belarus. In particular, the respondents stated that the main impediments are high levels of capital and technology spending (62.8% of respondents), as well as lack of state-provided economic incentives (50.4%). Information constraints are also important as enterprises are not aware of circular technologies and believe that they do not exist (50.4%). Furthermore, there is a lack of knowledge on how to implement circularity in their industry (33.8%) (see Figure 1).

Figure 1. Barriers to circular economy development in Belarus, % of respondents

Source: Figure compiled by the authors based on the survey results.

Respondents also identified barriers that hamper a shift of their own enterprise – rather than that of the entire Belarusian economy – from a linear to a circular business model. According to the survey, the lack of funding is considered as the main barrier to circular transformation among Belarusian companies, as 83.5% of respondents characterized its impact as high or medium. This impediment is followed by the absence of circular technologies that can be applied at the surveyed enterprise (64.9%) and the lack of information and best practice examples with regard to the implementation of circular business models (62.4%). Half of the respondents also indicated that the shift from a linear economy is hampered by the lack of consulting on how to implement circularity (see Figure 2).

Figure 2. Barriers to the circular transformation of the Belarusian enterprises, % respondents

Source: Figure compiled by the authors on the basis of the survey results.

Enterprises identified specific technical challenges associated with possible supply chain constraints. In particular, 40% of respondents raised concerns about the absence of an online database on waste and secondary raw materials, and 39.3% of them worried about possible interruptions in the supply of secondary raw materials.

Stimulus for Circular Transformation in Belarus

Respondents also expressed their views on potential stimulus measures that could be implemented to encourage a transition towards a circular economy in Belarus. Tailored support programs (83.9%), tax incentives (78.5%), and development of infrastructure for the processing of secondary raw materials (76.4%) were identified as the strongest motivators for enterprises’ decision to opt for a circular business model. Other important measures listed by the respondents were revisions of the legislative framework to prioritize the use of secondary raw materials, prevent waste generation, etc. (67.4%) as well as access to consulting on how to implement circularity in a business (62.8%) (Figure 3).

Figure 3. Stimulus for the circular economy development in Belarus, % of respondents

Source: Figure compiled by the authors on the basis of the survey results.

Surveyed enterprises stated that they had already incorporated some circular economy elements in their business model. More than 35% of respondents have used recycled materials in the production process, 19% have recycled products in the production of new materials or products, and around 19% have reused products or embedded raw materials. Moreover, more than 35% of enterprises would be ready to introduce reusage and recycling in their business within the next three years. However, they emphasized that existing regulations should be revised, and economic incentives provided in order to encourage these efforts.

Conclusion

The results confirm that Belarus has potential for circular economy development. Yet, its implementation might be hampered by economic, regulatory, informational, and technological barriers. In particular, the surveyed enterprises stated that high upfront costs, e.g., for technology and equipment, as well as the lack of state economic incentives, are the most pressing impediments to the circular transformation of Belarus. At the company level, lack of funding is seen as the main obstacle in shifting from a linear to a circular business model. Another important barrier is lack of information, as enterprises are not aware of circular technologies and best practice examples.

The results of our survey suggest that, in order to encourage a transition towards a circular economy in Belarus, a tailored support program should be developed, existing regulations revised, and economic incentives provided. The transition will not be possible without mainstreaming a circular economy into Belarus’ policy agenda.

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.

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

Posted on December 7, 2020 | Policy Brief, Policy Papers

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.

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