Location: Russia

What does the Gas Crisis Reveal About European Energy Security?

20220124 Gas Crisis European Energy Image 01

The recent record-high gas prices have triggered legitimate concerns regarding the EU’s energy security, especially with dependence on natural gas from Russia. This brief discusses the historical and current risks associated with Russian gas imports. We argue that decreasing the reliance on Russian gas may not be feasible in the short-to-mid-run, especially with the EU’s goals of green transition and the electrification of the economy. To ensure the security of natural gas supply from Russia, the EU has to adopt the (long-proclaimed) coordinated energy policy strategy.

In the last six months, Europe has been hit by a natural gas crisis with a severe surge in prices. Politicians, industry representatives, and end-energy users voiced their discontent after a more than seven-fold price increase between May and December 2021 (see Figure 1). Even if gas prices somewhat stabilized this month (partly due to unusually warm weather), today, gas is four times as expensive as it was a year ago. This has already translated into an increase in electricity prices, and as a result, is also likely to have dramatic consequences for the cost and price of manufacturing goods.

Figure 1. Evolution of EU gas prices since Oct 2020.

Source:  https://tradingeconomics.com/commodity/eu-natural-gas.

These ever-high gas prices have triggered legitimate concerns regarding the security of gas supply to Europe, specifically, driven by the dependency on Russian gas imports. Around 90% of EU natural gas is imported from outside the EU, and Russia is the largest supplier. In 2020, Russia provided nearly 44% of all EU gas imports, more than twice the second-largest supplier, Norway (19.9%, see Eurostat). The concern about Russian gas dependency was exacerbated by the new underwater gas route project connecting Russia and the EU – Nord Stream 2. The opponents to this new route argued that it will not only increase the EU’s gas dependency but also Russia’s political influence in the EU and its bargaining power against Ukraine (see, e.g., FT). Former President of the European Council Donald Tusk stated that “from the perspective of EU interests, Nord Stream 2 is a bad project.”.

However, neither dependency nor controversial gas route projects are a new phenomenon, and the EU has implemented some measures to tackle these issues in the past. This brief looks at the current security of Russian gas supply through the lens of these historical developments. We provide a snapshot of the risks associated with Russian gas imports faced by the EU a decade ago. We then discuss whether different factors affecting the EU gas supply security have changed since (and to which extent it may have contributed to the current situation) and if decreasing dependence on Russian gas is feasible and cost-effective. We conclude by addressing the policy implications.

Security of Russian Gas Supply to the EU, an Old Problem Difficult to Tackle

Russia has been the main gas provider to the EU for a few decades, and for a while, this dependency has triggered concerns about gas supply security (see, e.g., Stern, 2002 or Lewis, New York Times, 1982). However, the problem with the security of Russian gas supplies was extending beyond the dependency on Russian gas per se. It was driven by a range of risk factors such as insufficient diversification of gas suppliers, low fungibility of natural gas supplies with a prevalence of pipeline gas delivery, or use of gas exports/transit as means to solve geopolitical problems.

This last point became especially prominent in the mid-to-late-2000s, during the “gas wars” between Russia and the gas transit countries Ukraine and Belarus. These wars led to shortages and even a complete halt of Russian gas delivery to some EU countries, showing how weak the security of the Russian gas supply to the EU was at that time.

Reacting to these “gas wars”, the EU attempted to tackle the issue with a revival of the “common energy policy” based on the “solidarity” and “speaking in one voice” principles. The EU wanted to adopt a “coherent approach in the energy relations with third countries and an internal coordination so that the EU and its Member States act together” (see, e.g., EC, 2011). However, this idea turned out to be challenging to implement, primarily because of one crucial contributor to the problem with the security of Russian gas supply – the sizable disbalance in Russian gas supply risk among the individual EU Member States.

Indeed, EU Member States had a different share of natural gas in their total energy consumption, highly uneven diversification of gas suppliers, and varying exposure to Russian gas. Several Eastern-European EU states (such as Bulgaria, Estonia, or Czech Republic) were importing their gas almost entirely from Russia; other EU Member States (such as Germany, Italy, or Belgium) had a diversified gas import portfolio; and a few EU states (e.g., Spain or Portugal) were not consuming any Russian gas at all. Russian natural gas was delivered via several routes (see Figure 2), and member states were using different transit routes and facing different transit-associated risks. These differences naturally led to misalignment of energy policy preferences across EU states, creating policy tensions and making it difficult to implement a common energy policy with “speaking in one voice” (see more on this issue in Le Coq and Paltseva, 2009 and 2012).

Figure 2. Gas pipeline in Europe.

Source: S&G Platt. https://www.spglobal.com/platts/en/market-insights/blogs/natural-gas/010720-so-close-nord-stream-2-gas-link-completion-trips-at-last-hurdle

The introduction of Nord Stream 1 in 2011 is an excellent example of the problem’s complexity. This new gas transit route from Russia increased the reliability of Russian gas supply for EU countries connected to this route (like Germany or France), as they were able to better diversify the transit of their imports from Russia and be less exposed to transit risks. The “Nord Stream” countries (i.e., countries connected to this route) were then willing to push politically and economically for this new project. Le Coq and Paltseva (2012) show, however, that countries unconnected to this new route while simultaneously sharing existing, “older” routes with “Nord Stream” countries would experience a decrease in their gas supply security. The reason for this is that the “directly connected” countries would now be less interested in exerting “common” political pressure to secure gas supplies along the “old” routes.

This is not to say that the EU did not learn from the above lessons. While the “speaking in one voice” energy policy initiative was not entirely successful, the EU has implemented a range of actions to cope with the risks of the security of gas supply from Russia. The next section explains how the situation is has changed since, outlining both the progress made by the EU and the newly arising risk factors.

Security of Russian Gas Supply to the EU, a Current Problem Partially Addressed

Since the end of the 2000s, the EU implemented a few changes that have positively affected the security of gas supply from Russia.

First, the EU put a significant effort into developing the internal gas market, altering both the physical infrastructure and the gas market organization. The EU updated and extended the internal gas network and introduced the wide-scale possibility of utilizing reverse flow, effectively allowing gas pipelines to be bi- rather than uni-directional. These actions improved the gas interconnections between the EU states (and other countries), thereby making potential disruptions along a particular gas transit route less damaging and diminishing the asymmetry of exposure to route-specific gas transit risks among the EU members. Ukraine’s gas import situation is a good illustration of the effect of reverse flow. Ukraine does not directly import Russian gas since 2016, mainly from Slovakia (64%), Hungary (26%), and Poland (10%) (see https://www.enerdata.net/publications/daily-energy-news/ukraine-launches-virtual-gas-reverse-flow-slovakia.html). The transformation of the gas market organization brought about the implementation of a natural gas hub in Europe and change in the mechanism of gas price formation. It is now possible to buy and sell natural gas via long-term contracts and on the spot market. With the gas market becoming more liquid, it became easier to prevent the gas supply disruption threat.

Second, Europe has made certain progress in diversifying its gas exports. According to Komlev (2021), the concentration of EU gas imports from outside of the EU (excluding Norway), as measured by the Herfindahl-Hirschman index, has decreased by around 25% between 2016 and 2020. While the imports are still highly concentrated, with the HHI equal to 3120 in 2020, this is a significant achievement. A large part of this diversification effort is the dramatic increase in the share of liquified natural gas (i.e., LNG) in its gas imports – in 2020, a fair quarter of the EU gas imports came in the form of LNG. An expanded capacity for LNG liquefaction and better fungibility of LNG would facilitate backup opportunities in the case of Russian gas supply risks and improve the diversification of the EU gas imports, thereby increasing the security of natural gas supply.

However, the above developments also have certain disadvantages, which became especially prominent during the ongoing gas crisis. For example, the fungibility of LNG has a reverse side: LNG supplies respond to variations in gas market prices across the world. This change has intensified the competition on the demand side – Europe and Asia might now compete for the same LNG. This is likely to make a secure supply of LNG – e.g., as a backup in the case of a gas supply default or as a diversification device – a costly option.

In turn, new mechanisms of gas price formation in Europe included decoupling the oil and gas prices and changing the format of long-term gas contracts. The percentage of oil-linked contracts in gas imports to the EU dropped from 47% in 2016 to 26% in 2020. In particular, 87% of Gazprom’s long-term contracts in 2020 were linked to spot and forward gas prices and only around 13% to oil prices (Komlev, 2021). This gas-on-gas linking may have contributed to the current gas crisis: Indeed, it undermined the economic incentives of Gazprom to supply more gas to the EU spot market in the current high-price market. Shipping more gas would lower spot prices and prices of hub-linked longer-term contracts for Gazprom. In that sense, the ongoing decline in Russian gas supplies to the EU may reflect not (only) geopolitical considerations but economic optimization.

Similarly, this new mechanism also finds reflection in the ongoing situation with the EU gas storage. The current EU storage capacity is 117 bcm, or almost 20% of its yearly consumption, and thus, can in principle be effective in managing the short-term volume and price shocks. However, the current gas crisis has shown that this option might be far from sufficient in the case of a gas shortage (see, e.g., Zachmann et al., 2021).  One of the reasons for this insufficiency can be Gazprom controlling a sizable share of this storage capacity (see https://www.europarl.europa.eu/doceo/document/E-9-2021-004781_EN.html). For example, Gazprom owns (directly and indirectly) almost one-third of all gas storage in Germany, Austria, and the Netherlands.  Combining this storage market position with a long-term gas contract structure may also lead to strategic behavior for economic (on top of potential political) purposes.

Last but not least, the EU gas market is likely to be characterized by increased demand due to the green transition agenda (see Olofsgård and Strömberg, 2022). Being the least carbon-intensive fossil fuel, natural gas has an important role in facilitating green transition and increasing the electrification of the economy. For example, Le Coq et al. (2018) argues that gas capacity should be around 3 to 4 times the current capacity by 2050 for full electrification of transport and heating in France, Germany, or the Netherlands. In such circumstances, the EU is not likely to have the luxury to diminish reliance on Russian gas.

Conclusions and Policy Implications

Keeping the above discussion in mind, should the EU try to diminish its dependence on Russian gas to improve its energy security? This may be true in theory, but in practice, this might be too costly, at least in the short-to-medium run.

The current situation on the EU gas market suggests that simply cutting gas imports from Russia is likely to lead to high prices both in the energy sector and, later, in other sectors of the economy due to spillovers. Substituting gas imports from Russia with gas from other sources, such as LNG, is likely to be very costly and not necessarily very reliable. Alternative measures, e.g., improving interconnections between the EU Member States or controlling transit issues via the use of reverse flow technology, are effective but have limited impact. Simply cutting down gas demand is not a viable strategy. Indeed, with the EU pushing for a green transition and the electrification of the economy, the EU’s gas imports may have to increase. Russian gas may play an important role in this process.

As a result, we believe that the solution to keep the security issue of Russian gas supply at bay lies in the area of common energy policy. It is essential that the EU implements and effectively manages a coordinated approach in dealing with Russian gas supplies. The EU is the largest buyer of Russian gas, and given Russian dependency on hydrocarbon exports, such a synchronized approach would give the EU the possibility to exploit its “large buyer” power. While the asymmetry in exposure to Russian gas supply risks among the EU Member States is still sizable, the improvements in the functioning of the internal gas market and gas transportation within the EU make their preferences more aligned, and a common policy vector more feasible. Furthermore, recent EU initiatives on creating “strategic gas reserves” by making the Member States share their gas storage with one another would further facilitate such coordination. Implementing the “speaking in one voice” gas import policy will allow the EU to fully utilize its bargaining power vis-à-vis Gazprom and spread the benefits of new gas routes from Russia – such as Nord Stream 2 – across its Member States.

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.

From Russia with Love?

Russia Moscow City representing money laundering

Some recently discovered money laundering schemes have funnelled large amounts of illegal money from former soviet states through European banks. This note briefly describes the evolution of the Anti-Money Laundering (AML) regime for financial institutions, the introduction of which was concurrent with the post-soviet transition and the connected illegal flows of funds. It discusses the effectiveness of the current AML regime – and its ability to detect and seize illegal funds. The brief also highlights some of its deficiencies as well as lack of compliance with its prescriptions. It proceeds to stress that after judging the current framework insufficient, the US recently introduced whistleblower rewards for AML-infringements. Europe might want to follow their lead if it really aims at limiting money laundering.

Introduction

In recent years significant deficiencies in Anti-Money Laundering (AML) compliance have been discovered in some European banks (Spagnolo and Nyreröd, 2021). A notable example is the Danske Bank case that emerged in 2018.   Some have called it the largest money-laundering scandal in history: it is estimated that about $230 billion in suspicious funds went through its Estonian branch between 2007 and 2015.

In several of these cases, the sources of a large fraction of the illicit assets were Russia or other former Soviet states (Shaffer and Cassella, 2020).

Prior to the Danske revelations, several schemes have been uncovered that were aimed at laundering illicit money from former soviet states into the western financial system.

In a classic example going back to 2006, about $230 million were stolen in fraudulent tax refunds perpetrated by officials in Russia and then laundered through Moldova, Latvia and then UK shell companies and banks (Browder, 2009). Famously, the tax lawyer Sergei Magnitsky investigated the theft and testified against the fraudsters and was later put in detention for the same tax theft he was investigating. About a year after he was arrested, Magnitsky passed away after allegedly being tortured and denied medical care. This tragic episode gave rise to the Magnitsky Act, which prohibits persons believed to be involved in the theft to enter the US and access its financial system.

Another famous (and partly related) case is the so-called Russian Laundromat (then Global Laundromat), a scheme estimated to have funneled over $70 billion of illegal money out of Russia, through Latvia, Moldova, and then the UK (Tofilat and Negruta, 2019).

Indeed, Russia is widely considered the country with the largest estimated amount of ‘dark’ money hidden abroad, both as a percentage of GDP and in absolute terms (estimated around $1 trillion by Novokmet et al., 2017).

However, the origin of money laundered in the transition region is not limited to Russia. For example, it is estimated that between 2012 and 2014, about $2.9 billion from Azerbaijan were illegally laundered through UK shell companies and then European banks.

Funds from all these schemes appear to have been transacted through Danske bank (Bruun and Hjejle 2018: 33), Swedbank (Clifford Chance 2020: 123), and other European banks.

This evidence warrants some reflection on the effectiveness of the AML framework, particularly in Europe.

The Current AML Regime

The development of the global AML framework has been largely concurrent with the transition from communism and the connected illegal flows of funds.

The Financial Action Taskforce (FATF) was formed in 1989, after an initiative by the G7. FATF’s mission is to develop policies to combat money laundering and blacklist countries that do not comply. The FATF issued its first recommendations in 1999 and continually updates them, most recently in FATF (2021).

These recommendations set out essential measures that countries should have in place to identify money laundering risks, including regulation on preventive measures for the financial and other sectors, powers and responsibilities for competent authorities, coordination of their actions, and the facilitation of international cooperation (FATF 2021: 7).

AML regulation requires financial institutions to know their customers and engage in due diligence to reduce the risk that they onboard criminals seeking to launder money. Information about suspicious transactions and activities should be forwarded to a national financial intelligence unit, usually the financial police. National Financial Services Authorities (FSAs) are usually responsible for enforcing compliance with AML rules – the “preventive” side of money laundering regulation. The “repressive” criminal law or “enforcement” side of the fight against money laundering is usually enforced by the national financial police (Reuter and Truman 2004, Svedberg Helgesson and Mörth 2018).

There are certainly valid questions to be raised regarding the effectiveness of the current AML framework. While the World Bank estimates that between 2 and 5% of global GDP is laundered annually, it is also estimated that less than 1% of the proceeds of crime laundered via the financial system are currently seized by regulators and law enforcement agencies (UNODC 2011: 7).

At the same time, the framework is quite costly to comply with. There have been six EU Directives related to AML. All require legal implementation and impose new demands on banks and other covered institutions. FATF also requires that its members frequently carry out National Risk Assessments, and countries are also subject to Membership Evaluation Reports which imposes additional costs. Compliance costs for banks are estimated in the billions of dollars (Spagnolo and Nyreröd, 2021), and a whole industry surrounding “AML Compliance” has emerged. Part of these costs, not only monetary ones, end up transferred to bank customers.

From a more rigorous policy evaluation point of view, the AML regime is also problematic. There is a remarkable lack of data for assessing the effectiveness of the framework relative to its objectives (see e.g., Halliday et al. 2014, Levi 2018, Levi et al. 2018, Pol 2018, 2020).

Bank’s Failures

A lack of compliance with this preventative framework has been widespread.  In Sweden, for example, most large banks have been fined for various degrees of AML deficiencies. Similarly, many banks in other European countries received fines from local and US regulators (in the order of billions of dollars) for failing to comply with this framework, including HSBC, Credit Suisse, Deutsche Bank (multiple times), BNP Paribas, MagNet Bank, and Barclays Bank. Since 2016, the US has issued AML-related fines on eight occasions to banks with headquarters in European countries for an aggregate amount of $1.7 billion (mean $217 million fine; data from violationtracker.org).

In the case studies we discuss in Spagnolo and Nyreröd (2021), most forms of internal controls failed to some extent. Whereas external whistleblowing was rare or non-existent, internal whistleblowers did not manage to rectify the problems either.

Simultaneously, there were often clear red flags that should have alerted board members and executives. At Danske Bank group, for example, returns on allocated capital in the non-resident portfolio at their Estonian branch, where a substantial part of the money laundering occurred, hit 402% in 2013, compared with the 6.9% average for the whole group, a clear red flag (Schwartzkopff, 2018).

Supervisor’s Failures

The extensiveness of AML non-compliance cannot only be traced to negligent banks – it also has to do with the ineffectiveness of the enforcement of AML rules by supervising authorities.

In the cases reviewed in Spagnolo and Nyreröd (2021), supervisors appeared by and large aware of at least part of the AML deficiencies. Oftentimes, banks were given warnings by regulators, yet continued to violate the same rules.

For example, both the Danish FSA and the Estonian FSA seem to have had some knowledge of the AML deficiencies at Danske Bank’s subsidiary already in 2007, with little consequences.

Coordination between regulators has also been poor. The Danish FSA argues that the primary AML oversight responsibility for the Estonian branch should be the local FSA (Finanstilsynet, 2019), while the Estonian FSA retorts that European rules are not as clear and that the Danish FSA at least has some responsibility to oversee the branches of Danske Group (Finantsinspektsioon, 2019).

On September 24, 2018, the European Banking Authority (EBA) opened an investigation to assess whether the Danish and Estonian FSAs have violated any European laws. On April 16, 2019, it voted to reject an internal draft into supervisory failings that allegedly identified several shortcomings in how Danish and Estonian authorities supervised Danske bank. (Brunsden 2019). The EBA supervisory board’s decision to close the investigation without adopting any findings drew criticism from a range of senior policymakers and spurred calls for its reform. The EBA has also been criticized for its reluctance to pass judgment on its members (Bjerregaard and Kirchmaier 2019: 38).

Conclusion

The limited regulatory enforcement and compliance with the current AML system are likely to only marginally increase the cost of money laundering for criminals. Policymakers should thus wonder whether the current system is delivering value for money. There could be different ways to improve it. Increased fines for non-compliance may for example induce covered entities to comply with the AML framework to a greater extent.

Moving forward, the inconsistent enforcement of AML rules has led experts and policymakers to suggest centralizing some supervision and enforcement of AML regulation at the EU level (Kirschenbaum and Véron 2018, 2020; Unger 2020; JPP 2019; EC 2020, p.8), and improving information sharing between supervisors.

We believe these measures may not be sufficient for facilitating compliance with AML, while imposing substantial enforcing costs.

One way to increase AML compliance at a relatively low cost could be introducing whistleblower reward programs, as done in the US early this year (Nyreröd and Spagnolo, 2021). These programs offer substantial monetary rewards, often in the order millions of dollars, for information on non-compliance, and have proven extremely effective in combating fraud against the government, tax evasion, and securities fraud. While national EU supervisors may not have sufficient resources or competence to manage such programs, centralized actors such as the European Commission appear able to do so. If we see more centralized supervision, together with increased resources and competence, a well-designed and properly implemented whistleblower reward program may become a highly effective way to fight money laundering in the EU.

References

  • Bjerregaard, E., and T. Kirchmaier (2019). “The Danske Bank Money Laundering Scandal: A Case Study.” Copenhagen Business School.
  • Browder, W (2009). “Hermitage Capital, the Russian State and the Case of Sergei Magnitsky.” REP Edited Transcript, Chatham House.
  • Bruun and Hjejle (2018). “Report on the Non-Resident Portfolio at Danske Bank’s Estonian Branch.” Danske Bank.
  • Brunsden, J. (2019). “EBA faces calls to reform after dropping Danske Bank probe.” Financial Times, April.
  • Clifford Chance (2020). “Report of Investigation on Swedbank AB (publ).” Swedbank.
  • EC (2020). “Communication from the Commission on an Action Plan for a Comprehensive Union Policy on Preventing Money Laundering and Terrorist Financing.” 7.5.2020 C(2020) 2800 final.
  • FATF (2021). “International Standards on Combating Money Laundering and the Financing of Terrorism & Proliferation: The FATF Recommendations.”
  • Finanstilsynet (2019). “Report on the Danish FSA’s Supervision of Danske Bank as Regards the Estonia Case.” Danish Financial Services Authority.
  • Finantsinspektsioon (2019). “Response to the Report on the Danish FSA’s Supervision of Danske Bank.” Estonian Financial Services Authority.
  • Halliday, T. C., M. Levi, and P. Reuter (2014). “Global Surveillance of Dirty Money: Assessing Assessments of Regimes to Control Money-Laundering and Combat the Financing of Terrorism.” Center on Law & Globalization. University of Illinois College of Law and American Bar Foundation.
  • JPP (2019). “Joint Position Paper by the Ministers of Finance of France, Germany, Italy, Latvia, the Netherlands, and Spain.”
  • Kirschenbaum, J., and N. Véron (2018). “A Better European Architecture to Fight Money Laundering.” Peterson Institute for International Economics. Policy Brief 18-25.
  • Kirschenbaum, J., and N. Véron (2020). “A European Anti-Money Laundering Supervisor: From Vision to Legislation.” Peterson Institute for International Economics, January.
  • Levi, M. (2018). “Punishing Banks, Their Clients, and Their Clients’ Clients.” In King, C., C. Walker, and J. Gurulé (eds.) The Palgrave Handbook of Criminal and Terrorism Financing Law. Palgrave Macmillan.
  • Levi, M., P. Reuter, and T. Halliday (2018). “Can the AML System Be Evaluated Without Better Data?” Crime, Law and Social Change, 69(2): 307–328.
  • Novokmet, F., Piketty, T., and Zucman, G. (2017). “From Soviets to Oligarchs: Inequality and Property in Russia, 1905-2016”, NBER Working Paper Series, nr23712.
  • Nyreröd, T., and G. Spagnolo (2021). “Myths and Numbers on Whistleblower Rewards.” Regulation and Governance, 15(1): 82–97.
  • Pol, R. (2018). “Uncomfortable Truths? ML=BS and AML=BS².” Journal of Financial Crime, 25(2): 294–308.
  • Pol, R. (2020). “Response to Money Laundering Scandal: Evidence-Informed or Perception Driven?” Journal of Money Laundering Control, 23(1): 103–121.
  • Reuter, P., and E. M. Truman (2004). Chasing Dirty Money: The Fight Against Money Laundering. Peterson Institute for International Economics.
  • Schwartzkopff, F (2018). “Danske’s 402% Return Should Have Raised Red Flag, FSA Says.” Bloomberg, May.
  • Shaffer, Y. and Cassella, S (2020). ” The Causes, Effects, and Manifestations of the Money Laundering Problem in the Former Soviet Union.”, Georgetown Journal of International Affairs, February 21.
  • Spagnolo, G., and T. Nyreröd (2021). “Money Laundering and Whistleblowers.” SNS Report.
  • Svedberg Helgesson, K., and U. Mörth (2018). “Client Privilege, Compliance and the Rule of Law: Swedish Lawyers and Money Laundering Prevention.” Crime, Law and Social Change, 69(2): 227–248.
  • Tofilat, S., and V. Negruta (2019). “The Russian Laundromat – a $70 billion money-laundering scheme facilitated by Moldovan political elites.” Transparency International Moldova.
  • Unger, B. (2020). “Improving Anti-Money Laundering Policy.” Study requested by the ECON Committee, European Parliament.
  • UNODC (2011). “Estimating Illicit Financial Flows Resulting from Drug Trafficking and Other Transnational Organized Crimes.” Research Report, United Nations Office on Drugs and Crime.

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.

Social Distancing and Ethnic Diversity

20211214 Social Distancing and Ethnic Diversity Image 01

Voluntary social distancing plays a vital role in containing the spread of the disease during a pandemic. As a public good, it should be more commonplace in more homogeneous and altruistic societies. For healthy people, social distancing offers private benefits, too. If sick people are more likely to stay home, healthy ones have fewer incentives to do so, especially if asymptomatic transmission is perceived to be unlikely. This interplay may lead to a stricter observance of social distancing guidelines in more diverse, less altruistic societies. Consistent with this prediction, we find that mobility reduction following the first local case of COVID-19 was stronger in Russian cities with higher ethnic fractionalization and cities with higher levels of xenophobia and we confirm that mobility reduction in the United States was also higher in counties with higher ethnic fractionalization. Our findings highlight the importance of creating strategic incentives for different population groups in crafting effective public policy.

During the COVID-19 pandemic, governments in almost all affected countries have imposed restrictions aimed at promoting social distancing. However, enforcing these restrictions is logistically and politically costly. The effectiveness of these measures depends heavily on people voluntarily observing social distancing guidelines. The conventional wisdom is that informal social norms are more difficult to sustain in ethnically diverse societies (Alesina and La Ferrara, 2000; Algan et al., 2016). In Egorov et al. (2021), we challenge this notion by showing that during the COVID-19 pandemic ethnic diversity has increased prosocial behavior in Russia and the United States.

At least at the beginning of the pandemic, most people considered themselves healthy. For them, the decision to stay home has been driven more by the fear of getting infected than by the desire to avoid infecting others. The likelihood of getting infected is higher if sick people cannot be expected to self-isolate, which, in turn, depends on their prosocial considerations. If people are subject to out-group biases and care less about people from other groups, then the sick are less likely to engage in social distancing in more diverse places. This makes people who consider themselves healthy more likely to self-isolate. Since healthy people constitute a majority, at least in the early stages of a pandemic, we expect to see more social distancing in more diverse societies. Generally, in these circumstances, the private benefits of those who consider themselves healthy align with social objectives.

In Egorov et al. (2021) we formalize this argument and provide causal evidence of the differential decline in social distancing based on ethnic diversity in Russia and the United States.

Method

Our theory predicts that people engage in social distancing more in places with higher ethnic fractionalization when the probability of getting infected becomes nontrivial. To test this prediction empirically, we use two approaches. First, we report difference-in-differences estimates, where we compare cities with higher and lower levels of ethnic fractionalization before and after the first reported case of COVID-19 infection in their region. Second, we combine the difference-in-differences approach with a two-stage least-squares approach, in which the timing of the first reported case is instrumented using measures of preexisting migration.

One potential concern with the first approach is that the timing of the first case is not fully random. For example, regions could report late COVID-19 cases because their medical capacity precluded them from correctly identifying the virus in time, or because their testing policies could be ineffective, or because their administration was prone to conceal the first cases for a longer time. To deal with these potential confounds in the first approach we use predicted timing of the first case. Specifically, we use the fact that travel connections between various cities and Moscow (where the first major outbreak occurred) could affect the timing of the first case in those cities’ respective regions. We rely on internal migration as a proxy for these types of connections (Mikhailova and Valsecchi, 2020; Valsecchi and Durante, forthcoming) and use a shift-share instrument for internal cross-regional migration to deal with the endogeneity of migration.

Data and Results

To measure social distancing, we use data on people’s movements provided by Russia’s largest technology company, Yandex, which tracks individuals’ cell phones with its mobile apps. In particular, we use daily averages of the Yandex Isolation Index, which aggregates data on people’s movements at the city level and is analogous to the Google Mobility Index. The index is calibrated for each city to be 0 for the busiest hour of the working day, and 5 for the quietest hour of the night before the coronavirus outbreak. We use daily data for 302 cities with a population over 50,000 from February 23, 2020, through April 21, 2020.

Information on the first reported case of COVID-19 in each region is taken from the government-agency website that contains official information about the pandemic. Data on ethnic fractionalization is based on the 2010 Census. Information on interregional migration and control variables comes from the Russian Federal State Statistics Service.

Figure 1. Isolation Over Time for Places with High and Low Ethnic Fractionalization

Source: Egorov et al. (2021)

Figure 1 shows no visible difference in the behavior of people in cities with low and high levels of ethnic fractionalization before the first coronavirus case. In both groups of cities, people have engaged in more social distancing since the discovery of the first case. However, after one week, people in more fractionalized cities have been more likely to stay home than people in less fractionalized cities. The effect does not manifest itself immediately after the discovery of the first case, which likely reflects the fact that a certain time is needed to disseminate information about the discovery of the coronavirus in the region. Moreover, the growth in self-isolation in more fractionalized cities is somewhat lower in the first days after the discovery of the first case, which may be driven by people catching up on unfinished tasks that require mobility, such as last-minute purchases, in anticipation of more stringent self-isolation in the future.

The results of the difference-in-differences and IV estimation confirm the results of the visual analysis. The magnitudes of the IV estimation imply that a one-standard-deviation increase in ethnic fractionalization leads to 3.7% higher social distancing following the report of the first local COVID-19 case. In other words, a one-standard-deviation increase in ethnic fractionalization can explain 5.7% of the average mobility reduction after the report of the first case or, alternatively, 4.7% of the weekday-weekend gap for an average locality.

To make sure that the results are not Russia- specific, we also show that ethnic fractionalization led to a bigger reduction in mobility following the first local COVID-19 case using the United States county-level data.

Conclusion

Overall, the results in Egorov et al. (2021) highlight the role of ethnic diversity in voluntary adherence to socially beneficial norms, such as self-isolation and social distancing during a pandemic. We show that people in more diverse places were more likely to restrict their mobility following the reports of the first local COVID-19 cases.

Our study has important implications for government policy. It highlights not only that the propensity of different groups of people to engage in prosocial behavior may differ but also that there may be important strategic effects. In the context of the pandemic, decisions by healthy and sick individuals to self-isolate are strategic substitutes. This means, for example, that in a homogeneous society with high levels of tolerance, extensive testing would allow people to learn that they are sick and self-isolate, enabling the rest to go out with little fear. In a heterogeneous society with low levels of tolerance, the same policy may spur people who learn that they are contagious to go out more because they have little to lose, with the exact opposite implications for the healthy population.

References

  • Alesina, A., La Ferrara, E., 2000. Participation in heterogeneous communities. Quarterly Journal of Economics. 115, 847–904.
  • Algan, Y., Hémet, C., Laitin, D.D., 2016. The social effects of ethnic diversity at the local level: a natural experiment with exogenous residential allocation. Journal of Political Economics. 124, 696–733.
  • Egorov, G., Enikolopov, R., A., Makarin, and M. Petrova. 2021. Divided We Stay Home: Social Distancing and Ethnic Diversity” Journal of Public Economics. 194: 104328.
  • Mikhailova, T., Valsecchi, M., 2020. Internal migration and Covid-19 (in Russian). In: Economic Policy in Times of Covid-19, New Economic School, pp. 26–33.
  • Valsecchi, M., Durante, R., forthcoming. Internal Migration Networks And Mortality In Home Communities: Evidence From Italy During The Covid-19 Pandemic. European Economic Review.

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.

Russian Exporters in the Face of the COVID-19 Pandemic Crisis

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This brief summarizes the results of recent work on the effects of the COVID-19 pandemic on Russian exporting companies (Volchkova, 2021).  We use data from the CEFIR NES survey of exporters conducted in 2020. 72% of respondents reported that they were affected by the crisis. We scrutinize this impact. Contrary to popular wisdom, we observe little difference in delays of inputs by domestic and foreign suppliers. On the other hand, exporters experienced more disruptions in their sales in foreign destinations than in the domestic market. Possible reasons for this may be due to restrictions on international travel.

Introduction

According to experts at the Gaidar Institute (Knobel, Firanchuk, 2021), in 2020, Russia’s non-resource non-energy exports, decreased by 4.3%, while export prices fell by 4.1 % on average. The export of high-tech goods decreased by 14% due to a reduction in the physical volume of export. These changes in export intensity are mainly associated with the COVID-19 pandemic crisis. But are exporting firms more affected by the crisis than firms only active in the domestic market? What are the main channels through which the crisis influenced exporters?  And how do exporters adjust to the COVID-19 related shocks?

The analysis in this brief is based on forthcoming publication in the Journal of New Economic Association (Volchkova, 2021). We use data from a survey of Russian non-resource exporters conducted in 2020. We show that involvement in international trade did not affect the company’s vulnerability to the crisis on the production side: supply delays were equally likely to occur from domestic and foreign suppliers. These findings are consistent with Bonadio et al. (2021) who consider a numerical multi-sectoral model for 64 countries around the world linked by supply chains. They show that, in the face of the employment shocks associated with quarantine measures and switching to a remote work format, the contribution of global chains to the decline of real GDP is about one quarter. Importantly, the authors show that the “re-nationalization” of supply chains does not make countries more resilient to shocks associated with quarantine measures on the labor market because these shocks are also bad for domestic industries.

At the same time, our results indicate that exporting companies are exposed to additional risks associated with the need to adjust to shocks in the sales markets. According to the data, exporters find it more difficult to adjust their sales in foreign markets than in the domestic one. This is consistent with the fact that, during the pandemic, all countries introduced a strict ban on international travel, reducing the possibility of establishing new business ties through personal contacts. Similarly, Benzi et al. (2020) show a significant negative effect of international travel restrictions on the export of services.

Survey of Non-resource Exporters

The survey of exporters was carried out in June – November 2020 by CEFIR NES. The primary purpose of the survey was to identify and estimate barriers to the export of non-primary non-energy products. In the context of the developing economic crisis caused by the COVID-19 pandemic, we have added several questions to identify how the crisis influenced companies’ operations and how the respondent firms adjusted to the new conditions.

The survey was conducted using a representative sample of Russian exporting firms. As a control group, we interviewed non-exporting firms with (observable) characteristics (region, industry, labor productivity) similar to those of the surveyed exporters. Altogether, 928 exporting companies and 344 non-exporting companies were interviewed during the field stage of the study.

Most exporting companies that took part in the survey produce food products, chemicals, machinery and equipment, electrical equipment, metal products, and timber. On average, a surveyed exporter had 827 full-time employees; 25% of the firms had fewer than 26 employees. More than half of the surveyed exporting firms (53%) are also importers: 81% import raw materials and other inputs, 66% import equipment, and 22% import technology. Most interviewed exporters sell their products both abroad and on the domestic market. On average, an enterprise supplies 67% of its output to the domestic market and 32% abroad.

Impact of the COVID-19 Crisis on Firms’ Performance

Among exporters that participated in the survey, 25% reported that their business was not affected by the COVID-19 crisis, while 72% of respondents stated that the crisis did have an impact. Like any crisis, the COVID-19 pandemic created problems for some enterprises and provided new beneficial opportunities for others. According to the data, exporting businesses were significantly more likely to be negatively affected by the crisis than their non-exporting counterparts, and the impact of the crisis was not correlated with the size of the enterprise. Figure 1 presents the exporters’ answers to the question of how their sales in the domestic and foreign markets have changed with the COVID-19 pandemic.

The distribution of changes in sales volume in domestic and foreign markets significantly differ from each other. Estimates of the mean values of changes in sales volumes also differ significantly: the average drop in sales in the domestic market was 5%, while for the external market, it reached 17%. Hence, in times of the COVID-19 crisis, opportunities for growth were less prominent in foreign markets than in the domestic one, while significant market losses were more frequent.

Figure 1. Change in sales of export companies associated with the COVID-19 pandemic

Source: Survey of non-resource exporters, CEFIR NES, 2020.

Adjustment to the Crisis

The most frequently used crisis adjustment measure was employees transition to remote work – it was reported by 70% of the surveyed companies. 25% of exporters were forced to suspend their work during the crisis, while 72% were not. 14% of respondents stated they had to cut their payroll expenditures and other non-monetary benefits for employees (food, insurance, etc.), 12% of companies sent workers on unpaid leave. Only 6.5% of export firms had to lay off workers, while 91% handled the crisis without layoffs.

Comparing exporters’ answers with those of non-exporters while controlling for enterprise size, we conclude that exporting firms were more rigid in their adjustment  to the crisis. They were significantly more likely to suspend enterprise activities, dismiss of employees, send workers on unpaid leave, and reduce of wages. Also, these events were more likely to occur for smaller companies than for larger ones.

At the same time, flexible adjustment measures such as remote work were equally likely to be used by exporters and non-exporters, as well as by firms of different sizes. In general, Russian exporters of non-primary goods maintained their efficiency mainly by adjusting the labor relations to the new epidemiological conditions rather than by reducing employee-related expenses.

Dealing with Counterparties

Delays in the supply of components and raw materials were reported by 36% of the surveyed companies, and such delays were equally likely for shipments from abroad and domestic shipments. There is a perception that international supply chains in the context of the pandemic crisis are an additional risk factor. Our results indicate that domestic and international supply chains were equally challenged in 2020. Nevertheless, non-exporting companies faced the problem of delayed deliveries significantly less often than exporters did, and about 60% of companies experienced no problems at all on the input supply side.

27% of surveyed exporters stated that they delayed payments to counterparties. Non-exporting companies reported these reactions much less frequently regardless of firm size.

On the sales side, half of the surveyed exporters experienced delays in payments from their customers during the pandemic crisis. Non-exporting enterprises encountered the problems with the same frequency, and companies of all sizes were affected by this obstacle equally.

The cases of planned purchases cancellation on behalf of buyers were reported by 34% of exporting companies. Exporters experienced these problems significantly more often than non-exporters, and smaller companies experienced them much more often than larger ones.

Crossing international borders presented a certain problem for Russian exporters when it concerns product delivery. Just over half of the respondents indicated that they had to delay deliveries due to difficulties with border crossing. However, about the same share of companies (48%) reported that they delayed products delivery due to the introduction of lockdowns. Thus, during the COVID-19 pandemic, exporters’ operations were complicated to the same extent by problems related to border crossings as by those associated with lockdown regimes.

Conclusion

It is widely believed that international exposure of companies in the context of the COVID-19 pandemic crisis creates additional risks. Our study shows that, regarding existing inputs supply, international relations pose problems for Russian companies just as often as relations with domestic partners. As far as sales are concerned, adjustment to the crisis was better on the domestic market than on foreign markets. A possible explanation of this phenomenon is that, in addition to the shocks associated with quarantine measures in the labor market, access to foreign markets was hampered by restrictions on international travel, which is essential for readjusting contractual relations to explore new opportunities brought by crises (Cristea, 2011). Without personal interaction, new contracts were more difficult to launch. Thus firms’ opportunities to adjust foreign sales were more restricted than the ones in the domestic market.

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.

Media mentions: Key takeaways from this policy brief have been published by one of the most influential media outlets in Russia Kommersant – Коммерсант: «Ковид сильнее ударил по экспортерам». Исследование ЦЭФИР РЭШ. 

Vaccination Progress and the Opening Up of Economies

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In this brief, we report on the FREE network webinar on the state of vaccinations and the challenges ahead for opening up economies while containing the pandemic, held on June 22, 2021. The current state of the pandemic in each respective country was presented, suggesting that infection rates have gone down quite substantially recently in all countries of the network, except in Russia which is currently facing a surge in infections driven by the delta-version of the virus. Vaccination progress is very uneven, limited by lacking access to vaccines (primarily Ukraine and Georgia) and vaccine scepticism among the population (primarily in Russia and Belarus but for certain groups also in Latvia, Poland and to some extent Sweden). This also creates challenges for governments eager to open their societies to benefit their economies and ease the social consequences of the restrictions on mobility and social gatherings. Finally, the medium to long term consequences for labour markets reveal challenges but also potential opportunities through wider availability of workfrom-home policies. 

Background

In many countries in Europe, citizens and governments are starting to see an end to the most intense impact of the Covid-19 pandemic on their societies. Infection and death rates are coming down and governments are starting to put in place policies for a gradual opening up of societies, as reflected in the Covid-19 stringency index developed by Oxford University. These developments are partially seasonal, but also largely a function of the progress of vaccination programs reaching an increasing share of the adult population. These developments, though, are taking place to different degrees and at different pace across countries.  This is very evident at a global level, but also within Europe and among the countries represented in the FREE network. This has implications for the development within Europe as a whole, but also for the persistent inequalities we see across countries.   

Short overview of the current situation

The current epidemiological situation in Latvia, Sweden, Ukraine, and Georgia looks pretty similar in terms of Covid-19 cases and deaths but when it comes to the vaccination status there is substantial variation.

Latvia experienced a somewhat weaker third wave in the spring of 2021 after being hit badly in the second wave during the fall and winter of 2020 (see Figure 1). The Latvian government started vaccinating at the beginning of 2021, and by early June, 26% of the Latvian population had been fully vaccinated.

Sweden, that chose a somewhat controversial strategy to the pandemic built on individual responsibility, had reached almost 15 thousand Covid-19 deaths by the end of June of 2021, the second highest among the FREE network member countries relative to population size. The spread of the pandemic has slowed down substantially, though, during the early summer, and the percentage of fully vaccinated is about to reach 30% of the population.

Figure 1. Cumulative Covid-19 deaths 

Source: Aggregated data sources from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, compiled by Our World in Data.

Following a severe second wave, the number of infected in Ukraine started to go down in the winter of 2020, with the total deaths settling at about 27 thousand in the month of February. Then the third wave hit in the spring, but the number of new daily cases has decreased again and is currently three times lower than at the beginning of the lastwave. However, a large part of the reduction is likely not thanks to successful epidemiological policies but rather due to low detection rates and seasonal variation

In June 2021, Georgia faces a similar situation as Ukraine and Latvia, with the number of cumulative Covid-19 deaths per million inhabitants reaching around 1300 (in total 2500 people) following a rather detrimental spring 2021 wave. At the moment, both Georgia and Ukraine have very low vaccination coverage relative to other countries in the region(see Figure 5).

In contrast to the above countries, Russia started vaccinating early. Unfortunately, the country is now experiencing an increase in the number of cases (as can be seen in Figure 2), contrary to most other countries in the region. This negative development is likely due to the fact that the new Covid-19 delta variant is spreading in the country, particularly in Moscow and St. Petersburg. Despite the early start to vaccinations, though, the total number of vaccinated people remains low, only reaching 10.5% of the population.

Figure 2. New Covid-19 cases

Source: Aggregated data sources from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, compiled by Our World in Data.

In some ways similar to Sweden, the government of Belarus did not impose any formal restrictions on individuals’ mobility. According to the official statistics, in the month of June, the rise in the cumulative number of covid-19 deaths and new daily infections has declined rapidly and reached about 400 deceased and 800 infections per one million inhabitants, respectively. Vaccination goes slowly, and by now, around 8% of the population has gotten the first dose and 5% have received the second.

There were two major waves in Poland during the autumn 2020 and spring 2021. In the latter period, the country experienced a vast number of deaths.  As can be seen in Figure 3, the excess mortality P-score – the percentage difference between the weekly number of deaths in 2020-2021 and the average number of deaths over the years 2015-2019 – peaked in November 2020, reaching approximately 115%. The excess deaths numbers in Poland were also the highest among the FREE Network countries in the Spring of 2021, culminating at about 70% higher compared to the baseline. By mid-June, the number of deaths and cases have steeply declined and 36% of the country’s population is fully vaccinated.

Figure 3. Excess deaths

Turning to the economy, after a devastating year, almost all countries are expected to bounce back by the end of 2021 according to the IMF (see Figure 4). Much of these predictions build on the expectations that governments across the region will lift Covid-19 restrictions. These forecasts may not be unrealistic for the countries where vaccinations have come relatively far and restrictions have started to ease. However, for countries where vaccination rates remain low and new variations of the virus is spreading, the downside risk is still very present, and forecasts contain much uncertainty.

 Figure 4. GDP-growth

Vaccination challenges

Since immunization plays such a central role in re-opening the economy and society going back to normal, issues related to vaccinations were an important and recurring topic at the event. The variation in progress and speed is substantial across the countries, though.

Ukraine and Georgia are still facing big challenges with vaccine availability and have fully vaccinated only 1.3% and 2.3% of the population by the end of June, respectively. Vaccination rates have in the recent month started to pick up, but both countries face an uphill battle before reaching levels close to the more successful countries.

Figure 5. Percent fully vaccinated

Other countries a bit further ahead in the vaccine race are still facing difficulties in increasing the vaccination coverage, though not so much due to lack of availability but instead because of vaccine skepticism. In Belarus, a country that initially had bottleneck issues similar to Ukraine and Georgia, all citizens have the opportunity to get vaccinated. However, Lev Lvovskiy, Senior Research Fellow at BEROC in Belarus, argued that vaccination rates are still low largely because many Belarusians feel reluctant towards the vaccine at offer (Sputnik V).

This vaccination scepticism turns out to be a common theme in many countries. According to different survey results presented by the participants at the webinar, the percentage of people willing or planning to get vaccinated is 30% in Belarus and 44% in Russia. In Latvia, this number also varies significantly across different groups as vaccination rates are significantly lower among older age cohorts and in regions with a higher share of Russian-speaking residents, according to Sergejs Gubins, Research Fellow at BICEPS in Latvia.

Webinar participants discussed potential solutions to these issues. First, there seemed to be consensus that offering people the opportunity to choose which vaccine they get will likely be effective in increasing the uptake rate. Second, governments need to improve their communication regarding the benefits of vaccinations to the public. Several countries in the region, such as Poland and Belarus, have had statements made by officials that deviate from one another, potentially harming the government’s credibility with regards to vaccine recommendations. In Belarus, there have even been government sponsored disinformation campaigns against particular vaccines. In Latvia, the main problem is rather the need to reach and convince groups who are generally more reluctant to get vaccinated. Iurii Ganychenko, Senior Researcher at KSE in Ukraine, exemplified how Ukraine has attempted to overcome this problem by launching campaigns specifically designed to persuade certain age cohorts to get vaccinated. Natalya Volchkova, Director of CEFIR at NES in Russia, argued that new, more modern channels of information, such as professional influencers, need to be explored and that the current model of information delivery is not working.

Giorgi Papava, Lead Economist at ISET PI in Georgia, suggested that researchers can contribute to solving vaccine uptake issues by studying incentive mechanisms such as monetary rewards for those taking the vaccine, for instance in the form of lottery tickets. 

Labour markets looking forward

Participants at the webinar also discussed how the pandemic has affected labour markets and whether its consequences will bring about any long-term changes.

Regarding unemployment statistics, Michal Myck, the Director of CenEA in Poland, made the important point that some of the relatively low unemployment numbers that we have seen in the region during this pandemic are misleading. This is because the traditional definition of being unemployed implies that an individual is actively searching for work, and lockdowns and other mobility restrictions have limited this possibility. Official data on unemployment thus underestimates the drop in employment that has happened, as those losing their jobs in many cases have left the labour market altogether. We thus need to see how labor markets will develop in the next couple of months as economies open up to give a more precise verdict.

Jesper Roine, Professor at SITE in Sweden, stressed that unemployment will be the biggest challenge for Sweden since its economy depends on high labor force participation and high employment rates. He explained that the pandemic and economic crisis has disproportionately affected the labor market status of certain groups. Foreign-born and young people, two groups with relatively high unemployment rates already prior to the pandemic, have become unemployed to an even greater extent. Many are worried that these groups will face issues with re-entering the labour market as in particular long-term unemployment has increased. At the same time, there have been more positive discussions about structural changes to the labour market following the pandemic. Particularly how more employers will allow for distance work, a step already confirmed by several large Swedish firms for instance.

In Russia, a country with a labour market that allowed for very little distance work before the pandemic, similar discussions are now taking place. Natalya Volchkova reported that, in Russia, the number of vacancies which assumed distance-work increased by 10% each month starting from last year, according to one of Russia’s leading job-search platforms HeadHunter. These developments could be particularly beneficial for the regional development in Russia, as firms in more remote regions can hire workers living in other parts of the country.

Concluding Remarks

It has been over a year since the Covid-19 virus was declared a pandemic by the World Health Organization. This webinar highlighted that, though vaccination campaigns in principle have been rolled out across the region, their reach varies greatly, and countries are facing different challenges of re-opening and recovering from the pandemic recession. Ukraine and Georgia have gotten a very slow start to their vaccination effort due to a combination of lack of access to vaccines and vaccine skepticism. Countries like Belarus and Latvia have had better access to vaccines but are suffering from widespread vaccine skepticism, in particular in some segments of the population and to certain vaccines. Russia, which is also dealing with a broad reluctance towards vaccines, is on top of that dealing with a surge in infections caused by the delta-version of the virus.

IMF Economic Outlook suggests that most economies in the region are expected to bounce back in their GDP growth in 2021. While this positive prognosis is encouraging, the webinar reminded us that there is a great deal of uncertainty remaining not only from an epidemiological perspective but also in terms of the medium to long-term economic consequences of the pandemic.

Participants

  • Iurii Ganychenko, Senior Researcher at Kyiv School of Economics (KSE/Ukraine)
  • Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS/ Latvia)
  • Natalya Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR at NES/ Russia)
  • Giorgi Papava, Lead Economist at the ISET Policy Institute (ISET PI/ Georgia)
  • Lev Lvovskiy, Senior Research Fellow at the Belarusian Economic Research and Outreach Center (BEROC/ Belarus)
  • Jesper Roine, Professor at the Stockholm Institute of Transition Economics (SITE / Sweden)
  • Michal Myck, Director of the Centre for Economic Analysis (CenEA / Poland)
  • Anders Olofsgård, Deputy Director of SITE and Associate Professor at the Stockholm School of Economics (SITE / Sweden)

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.

Enemies of the People

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From the early days of the Soviet Union, the regime designated the educated elite as Enemies of the People. They were political opponents and considered a threat to the regime. Between the late 1920s and early 1950s, millions of enemies of the people were rounded up and forcedly resettled to remote locations within the GULAG, a system of labor camps spread across the Soviet Union. In recent research (Toews and Vezina, 2021), we show that these forced relocations have long-term consequences on local economies. Places close to camps that hosted more enemies of the people among prisoners are more prosperous today. We suggest that this result can be explained by the intergenerational transmission of education and a resulting positive effect on local development, which can still be observed to this day.

Historical Background

Targeting the educated elite, collectively referring to them as Enemies of the People and advocating their imprisonment, can be traced back to the beginning of the Russian Revolution in 1917. After consolidating power a decade later, Stalin launched the expansion of the GULAG system, which at its peak consisted of more than a hundred camps with over 1.5 million prisoners (see Figure 1). A large number of historians extensively described this dark episode in Russian history (Applebaum (2012), Khlevniuk (2004), and Solzhenitsyn (1974)). During the darkest hours of this episode, the Great Terror, 1.5 million enemies were arrested in just about two years. While half were executed immediately, the other half were forcedly allocated to GULAG camps spread across the Soviet Union and mixed with non-political prisoners (see Figure 2). Enemies accounted for about a third of GULAG prisoners after the Great Terror. As a result, education levels were higher in the GULAG than in society. In 1939, the share of GULAG prisoners with tertiary education was 1.8%, while, according to the Soviet Census of the same year, only 0.6% of the population had tertiary education.

After Stalin’s death, labor camps started closing rapidly, but many ex-prisoners settled close to the campsites. New cities were created and existing cities in the proximity of camps started growing fast (Mikhailova, 2012). Enemies remained once freed for a combination of political, economic, and psychological reasons. Politically, they were constrained in their choice of location by Stalin-era restrictions on mobility. Economically, they had few outside options and could keep on working for the camps’ industrial projects. On the psychological level, prisoners had become attached to the location of the camp, as Solzhenitsyn (1974) clearly puts it: “Exile relieved us of the need to choose a place of residence for ourselves, and so from troublesome uncertainties and errors. No place would have been right, except that to which they had sent us.”.

Figure 1. Location and size of camps in the Soviet Gulag system

Notes: The circles are proportional to the prisoner population of camps. The data is from the State Archive of the Russian Federation (GARF) and Memorial

Enemies of the People and Local Prosperity

At the heart of our analysis is a dataset on GULAG camps which we collected at the State Archive of the Russian Federation (GARF). It allows us to differentiate between prisoners who were imprisoned for political reasons (Enemies of the People) and those arrested for non-political crimes. The share of enemies varied greatly across camps, and we argue that this variation was quasi-random. We back this up by the historical narrative, according to which the resettlement process was driven by political rather than economic forces, suggesting that strategic placements played little role in the allocation of enemies (Khlevniuk (1995) and Ertz (2008)). Moreover, while the forced nature of allocation to camps allows us to rule out endogenous location decisions, we also show that neither economic activities nor geographic attributes, such as climatic conditions, soil quality, or the availability of resources, predict the share of enemies across camps.

To estimate the long-run effects of enemies on local prosperity, we link the location of camps in 1952, the year before Stalin’s death and at the peak of the GULAG system, to post-Soviet data covering the period 2000-2018.

Figure 2. The rise and fall of the Gulag

Notes: The solid line shows the number of Gulag camps while the dashed line shows the total number of prisoners in the Gulag. The two vertical dash lines indicate the years that can define the start and end of the Gulag, starting with Stalin’s 5-year plan in 1928 and ending with Stalin’s death in 1953. The shaded areas show specific periods of marked change for the Gulag, starting with dekulakization in 1929, when when Stalin announced the liquidation of the kulaks as a class and 1.8 million well-off peasants were relocated or executed. The Great Terror of 1936-1938, also referred to as the Great Purge, is the most brutal episode under Stalin’s rule, when 1.5 million enemies were arrested, and half of them executed. The Gulag’s prisoner population went down during WW2, as non-political prisoners were enlisted in the Red Army, and as the conditions in camps deteriorated and mortality increased. Source: Memorial.

In particular, the camp level information is linked to the location of firms from the Russian firm census (2018), data on night-lights (2000-2015), as well as data from household and firm-level surveys (2016 and 2011-2014, respectively). Our results suggest that one standard deviation (28 percentage point) increase in the share of enemies of the people increases night-lights intensity per capita by 58%, profits per employee by 65%, and average wages by 22%. A large number of specifications confirm the relationship depicted in Figure 3, which illustrates the positive association between the share of enemies across camps and night-lights intensity per capita.

Figure 3. Share of enemies vs. night lights per capita across Gulags

Notes: The scatters show the relationship between the share of enemies in camps in 1952 and night lights per capita within 30 km of camps in 2000 and 2015. Each circle is a 30km-radius area around a camp, and the size of the circles is proportional to the camps’ prisoner populations. The biggest circle is Khabarovsk. The solid lines show the linear fit, and the shaded areas show the 95% confidence interval. Areas near camps with a higher share of enemies have brighter night lights per capita both in 2000 and 2015. The data on Gulags is from the State Archive of the Russian Federation (GARF) and the data on night lights is from the DMSP-OLS satellite program and made available by the Earth Observation Group and the NOAA National Geophysical Data Center. The data on population is from the gridded population of the world from SEDAC.

Intergenerational Transmission

We suggest that the relationship between enemies and modern prosperity is due to the long-run persistence of high education levels, notably via intergenerational transmission, and their role in increasing firm productivity. For the identification of the intergenerational link, we rely on a household survey collected by the EBRD in which interviewees are explicitly asked whether their grandparents have been imprisoned for political reasons during Soviet times. Exploiting this information, we show that the grandchildren of enemies of the people are today relatively more educated. We also find that grandchildren of enemies are more likely to be residing near camps that had a higher share of enemies of the people among prisoners in 1952. An alternative explanation for our results could be that the leadership of the Soviet Union may have strategically chosen to invest more during the post-GULAG period in locations that had received more enemies to exploit complementarities between human and physical capital. We find no evidence for this mechanism. We document that Soviet investment in railroads, factories of the defence industry, or universities was, if anything, lower in places with a large share of enemies.

Conclusion

We show that the massive and forced re-allocation of human capital that took place under Stalin had long-run effects on local development. Sixty years after the death of Stalin and the demise of the GULAG, areas around camps that had a higher share of enemies are richer today, as captured by firms’ wages and profits, as well as by night-lights per capita. We argue that the education transferred from forcedly displaced enemies of the people to their children and grandchildren partly explains variation in prosperity across localities of Russia. This can be seen as a historical natural experiment that identifies the long-run persistence of higher education and its effect on long-run prosperity. Sadly, it also highlights how atrocious acts by powerful individuals can shape the development path of localities over many generations.

Bibliography

  • Applebaum, A., Gulag: A History of the Soviet Camps, Penguin Books Limited, 2012.
  • Ertz, Simon. Making Sense of the Gulag: Analyzing and Interpreting the Function of the Stalinist Camp System. No. 50. PERSA Working Paper, 2008.
  • Khlevnyuk, Oleg, “The objectives of the Great Terror, 1937–1938.” In Soviet History, 1917–53, pp. 158-176. Palgrave Macmillan, London, 1995.
  • Khlevnyuk, Oleg, The History of the Gulag: From Collectivization to the Great Terror Annals of Communism, Yale University Press, 2004.
  • Mikhailova, Tatiana, “Gulag, WWII and the long-run patterns of Soviet city growth,” 2012.
  • Solzhenitsyn, Aleksandr, The Gulag Archipelago, 1918-56: An Experiment in Literary Investigation, New York: Harper Row, 1973.
  • Toews, Gerhard, and Pierre-Louis Vézina. “Enemies of the people.” (2021).

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.

Energy Storage: Opportunities and Challenges

Wind turbines in a sunny desert representing energy storage

As the dramatic consequences of climate change are starting to unfold, addressing the intermittency of low-carbon energy sources, such as solar and wind, is crucial. The obvious solution to intermittency is energy storage. However, its constraints and implications are far from trivial. Developing and facilitating energy storage is associated with technological difficulties as well as economic and regulatory problems that need to be addressed to spur investments and foster competition. With these issues in mind, the annual Energy Talk, organized by the Stockholm Institute of Transition Economics, invited three experts to discuss the challenges and opportunities of energy storage.

Introduction

The intermittency of renewable energy sources poses one of the main challenges in the race against climate change. As the balance between electricity supply and demand must be maintained at all times, a critical step in decarbonizing the global energy sector is to enhance energy storage capacity to compensate for intermittent renewables.

Storage systems create opportunities for new entrants as well as established players in the wind and solar industry. But they also present challenges, particularly in terms of investment and economic impact.

Transitioning towards renewables, adopting green technologies, and developing energy storage can be particularly difficult for emerging economies. Some countries may be forced to clean a carbon-intensive power sector at the expense of economic progress.

The 2021 edition of Energy Talk – an annual seminar organized by the Stockholm Institute of Transition Economics – invited three international experts to discuss the challenges and opportunities of energy storage from a variety of academic and regulatory perspectives. This brief summarizes the main points of the discussion.

A TSO’s Perspective

Niclas Damsgaard, the Chief strategist at Svenska kraftnät, gave a brief overview of the situation from a transmission system operator’s (TSO’s) viewpoint. He highlighted several reasons for a faster, larger-scale, and more variable development of energy storage. For starters, the green transition implies that we are moving towards a power system that requires the supply of electricity to follow the demand to a much larger extent. The fact that the availability of renewable energy is not constant over time makes it crucial to save power when the need for electricity is low and discharge it when demand is high. However, the development and facilitation of energy storage will not happen overnight, and substantial measures on the demand side are also needed to ensure a more dynamic energy system. Indeed, Damsgaard emphasized that demand flexibility constitutes a necessary element in the current decarbonization process. However, with the long-run electrification of the economy (particularly driven by the transition of the transport industry), extensive energy storage will be a necessary complement to demand flexibility.

It is worth mentioning that such electrification is likely to create not only adaptation challenges but also opportunities for the energy systems. For example, the current dramatic decrease in battery costs (around 90% between 2010 and 2020) is, to a significant extent, associated with an increased adoption of electric vehicles.

However, even such a drastic decline in prices may still fall short of fully facilitating the new realities of the fast-changing energy sector. One of the new challenges is the possibility to store energy for extended periods of time, for example, to benefit from the differences in energy demand across months or seasons. Lithium-ion batteries, the dominant battery technology today, work well to store for a few hours or days, but not for longer storage, as such batteries self-discharge over time. Hence, to ensure sufficient long-term storage, more batteries would be needed and the associated cost would be too high, despite the above-mentioned price decrease. Alternative technological solutions may be necessary to resolve this problem.

Energy Storage and Market Structure

As emphasized above, energy storage facilitates the integration of renewables into the power market, reduces the overall cost of generating electricity, and limits carbon-based backup capacities required for the security of supply, creating massive gains for society. However, because the technological costs are still high, it is unclear whether the current economic environment will induce efficient storage. In particular, does the market provide optimal incentives for investment, or is there a need for regulations to ensure this?

Natalia Fabra, Professor of Economics and Head of EnergyEcoLab at Universidad Carlos III de Madrid, shared insights from her (and co-author’s) recent paper that addresses these questions. The paper studies how firms’ incentives to operate and invest in energy storage change when firms in storage and/or production have market power.

Fabra argued that storage pricing depends on how decisions about the storage investment and generation are allocated between the regulator and the firms operating in the storage and generation markets. Comparing different market structures, she showed as market power increases, the aggregate welfare and the consumer surplus decline. Still, even at the highest level of market concentration, an integrated storage-generation monopolist firm, society and consumers are better off than without energy storage.

Fabra’s model also predicts that market power is likely to result in inefficient storage investment.

If the storage market is competitive, firms maximize profits by storing energy when the prices are low and releasing when the prices are high. The free entry condition implies that there are investments in storage capacity as long as the marginal benefit of storage investment is higher than the marginal cost of adding an additional unit of storage. But this precisely reflects the societal gains from storage; so, the competitive market will replicate the regulator solution, and there are no investment distortions.

If there is market power in either generation or storage markets, or both, the investment is no longer efficient. Under market power in generation and perfectly competitive storage, power generating firms will have the incentive to supply less electricity when demand is high and thereby increase the price. As a result, the induced price volatility will inflate arbitrage profits for competitive storage firms, potentially leading to overinvestment.

If the model features a monopolist storage firm interacting with a perfectly competitive power generation market, the effect is reversed. The firm internalizes the price it either buys or sells energy, so profit maximization makes it buy and sell less energy than it would in a competitive market, in the exact same manner as the classical monopolist/monopsonist does. This underutilization of storage leads to underinvestment.

If the model considers a vertically integrated (VI) generation-storage firm with market power in both sectors, the incentives to invest are further weakened: the above-mentioned storage monopolist distortion is exacerbated as storage undermines profits from generation.

Using data on the Spanish electricity market, the study also demonstrated that investments in renewables and storage have a complementary relationship. While storage increases renewables’ profitability by reducing the energy wasted when the availability is excess, renewables increase arbitrage profits due to increased volatility in the price.

In summary, Fabra’s presentation highlighted that the benefits of storage depend significantly on the market power and the ownership structure of storage. Typically, market power in production leads to higher volatility in prices across demand levels; in turn, storage monopolist creates productive inefficiencies, two situations that ultimately translate into higher prices for consumers and a sub-optimal level of investment.

Governments aiming to facilitate the incentives to invest in the energy storage sector should therefore carefully consider the economic and regulatory context of their respective countries, while keeping in mind that an imperfect storage market is better than none at all.

The Russian Context

The last part of the event was devoted to the green transition and the energy storage issue in Eastern Europe, with a specific focus on Russia.

Alexey Khokhlov, Head of the Electric Power Sector at the Energy Center of Moscow School of Management, SKOLKOVO, gave context to Russia’s energy storage issues and prospects. While making up for 3% of global GDP, Russia stands for 10% of the worldwide energy production, which arguably makes it one of the major actors in the global power sector (Global and Russian Energy Outlook, 2016). The country has a unified power system (UPS) interconnected by seven regional facilities constituting 880 powerplants. The system is highly centralized and covers nearly the whole country except for more remote regions in the northeast of Russia, which rely on independent energy systems. The energy production of the UPS is strongly dominated by thermal (59.27%) followed by nuclear (20.60%), hydro (19.81%), wind (0.19%), and solar energy (0.13%). The corresponding ranking in capacity is similar to that of production, except the share of hydro-storage is almost twice as high as nuclear. The percentage of solar and wind of the total energy balance is insignificant

Despite the deterring factors mentioned above, Khokhlov described how the Russian energy sector is transitioning, though at a slow pace, from the traditional centralized carbon-based system towards renewables and distributed energy resources (DER). Specifically, the production of renewables has increased 12-fold over the last five years. The government is exploring the possibilities of expanding as well as integrating already existing (originally industrial) microgrids that generate, store, and load energy, independent from the main grid. These types of small-scaled facilities typically employ a mix of energy sources, although the ones currently installed in Russia are dominated by natural gas. A primary reason for utilizing such localized systems would be for Russia to improve the energy system efficiency. Conventional power systems require extra energy to transmit power across distances. Microgrids, along with other DER’s, do not only offer better opportunities to expand the production of renewables, but their ability to operate autonomously can also help mitigate the pressure on the main grid, reducing the risk for black-outs and raising the feasibility to meet large-scale electrification in the future.

Although decarbonization does not currently seem to be on the top of Russia’s priority list, their plans to decentralize the energy sector on top of the changes in global demand for fossil fuels opens up possibilities to establish a low-carbon energy sector with storage technologies. Russia is currently exploring different technological solutions to the latter. In particular, in 2021, Russia plans to unveil a state-of-the-art solid-mass gravity storage system in Novosibirisk. Other recently commissioned solutions include photovoltaic and hybrid powerplants with integrated energy storage.

Conclusion

There is no doubt that decarbonization of the global energy system, and the role of energy storage, are key in mitigating climate change. However, the webinar highlighted that the challenges of implementing and investing in storage are both vast and heterogenous. Adequate regulation and, potentially, further government involvement is needed to correctly shape incentives for the market participants and get the industry going.

On behalf of the Stockholm Institute of Transition Economics, we would like to thank Niclas Damsgaard, Natalia Fabra, and Alexey Khokhlov for participating in this year’s Energy TalkThe material presented at the webinar can be found here.

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.

Does the Russian Stock Market Care About Navalny?

Moscow citi in the sunset representing Russian stock market and Navalny

Alexei Navalny is the most prominent opposition leader in Russia today. During 2020, he entered not only the domestic Russian news flows, but was a major news story around the world following his horrific Novichok poisoning in August. This brief investigates the response in the Russian stock market to news about Navalny. For many significant Navalny news stories, the stock market experienced large negative returns that are not explained by the regular factors that move the market. Although the causality and permanency of these negative excess returns in the stock market are difficult to pin down completely, a first look at the numbers suggests that the short-run drops in the stock market on the days with most significant news regarding Navalny translates into several billion dollars in lost market value on the Russian stock market. In other words, for people that care about their stock market investments and the health of the Russian economy more generally, it makes a lot of sense to care about the health of Navalny.

Introduction

Alexei Navalny has become the leading political opponent to the current regime in Russia. His visibility (and possibly support) has been growing as he has endured poisoning, recovery in hospital, and court rulings that have imposed a harsh prison term. At the same time, Navalny and his team have posted new material online to make his case that both the president and other Russian leaders are seriously corrupt.

The question addressed in this brief is whether the news regarding Navalny affected the Russian stock market. The reasons for such a response may vary between different investors but could include a fear of international sanctions against Russia; an aversion to keeping investments in a country that put a nerve agent in the underwear of a leading opposition leader; or that news of a national security service poisoning one of its own citizens could trigger domestic protests that create instability.

This brief only investigates if Navalny-related news or events are taken into account at the macro level in the stock market and if so, how important the news seem to be relative to other news as drivers of the stock market index. However, there is a long list of related questions that are subjects for upcoming briefs that include differential effects across sectors and companies as well as identifying what dimensions of the news stories investors responded to.

Navalny in the News

Since August 2020, news regarding Alexei Navalny’s health and his role as the most important opposition leader in Russia have featured prominently in media around the world. There are different ways to analyze the significance of Navalny in the news and here the readily available measure provided by Google trends will be used. Figure 1 shows a global search on the keyword “Navalny” over the period July 1, 2020 to March 13, 2021 relative to total searches, where the maximum level in the period is normalized to 100 and other values are scaled to this. While the numbers on the graph are just relative measures, not telling much about the actual popularity, or market relevance of searches, the spikes in Figure 1 have very clear connections to major news stories as will be detailed below.

Figure 1. Google trends on Navalny

Source: Google trends, global search on Navalny on 2021-03-18

Four episodes stand out in Figure 1 and are marked by red numbers:

1 (August 20-25, 2020) is associated with Navalny falling ill on the flight from Tomsk to Moscow which led to an emergency landing in Omsk and then going to Germany for specialist treatment where it was stated that he had been poisoned.

2 (September 2-3, 2020) is when the German government said that the poison Navalny was exposed to was Novichok, which was also confirmed by laboratories in Sweden and France.

3 (January 17-25, 2021) is an extended period covering the arrest of Navalny as he returned to Russia on January 17; the publication of the YouTube video on “Putin’s palace”; and the street protests that followed.

4 (January 31-February 5) is a period covering a new weekend of public protests and then on February 2, Navalny being sentenced to prison for not complying with parole rules when he was in a coma in Germany. At the tail end of this period, Navalny’s chief of staff announced that street protests will be suspended due to thousands of arrests and police beatings.

Russian Stock Market Reactions

Using stock markets to investigate the value of political news is not new; for example, Fisman (2001) looks at how news regarding Suharto’s health differentially impacted firms that were connected to Suharto versus those that were not. On a topic more closely related to this brief, Enikolopov, Petrova, and Sonin (2018), show that Navalny’s blog posts on corruption negatively affect share prices for the exposed state-controlled companies. Looking at the overall stock market index rather than individual shares in Russia, Becker (2019) analyzes stock market reactions to Russia invading Crimea.

To get a stock market valuation effect of Navalny news that is as clean as possible, we need to filter out other factors that are known to be important drivers of the stock market. In the case of Russia’s dollar denominated stock market index RTS (short for Russia Trading System), we know from Becker (2019) that it is sensitive to movements in global stock markets and international oil prices. The former factor is in line with other stock markets around the world and the oil dependence of the Russian economy makes oil prices a natural second factor (see Becker, 2016).

Figure 2 shows how the RTS index moves with the global markets (proxied by S&P 500 index) and (Brent) oil prices in this period. The correlations of returns are around 0.4 between the RTS and both S&P500 and oil prices respectively. This figure is also the answer to the obvious argument that the stock market was doing very well in the time period of Navalny in the news, so he could not be a major concern to investors. As we will show below, this argument goes away when the effects of the exogenous factors are removed.

To filter out these exogenous factors, we follow the approach in Becker (2019) and regress daily returns on the RTS on daily returns of the exogenous variables. We then compute the residuals from the estimation to arrive at the excess returns that are utilized in the subsequent analysis. For more details on this, see Becker (2020). Since the estimated model provides the foundation for the subsequent analysis, it is important to note that all of the coefficients are statistically significant, and that results are robust to changes in the estimation period and exclusion of lagged values of the exogenous variables.

Figure 2. RTS and exogenous factors

Source: Data on RTS from the Moscow Exchange (MOEX), S&P500 from Nasdaq, and Brent oil prices from the US energy information administration.

With a time-series of excess returns for the Russian stock market, we can look at the stock market reactions to the four Navalny episodes identified in Figure 1. These periods cover some days for which we cannot compute excess returns since there are days when there is no trading, but all dates in the period are shown in Figure 3 to provide a full account of what stock market data we have for the events. In addition to excess returns during the events that are shown in blue, the day before and the day after the events are shown in light grey. In the first three episodes, the cumulative returns during the events windows were minus 6.2, minus 2.4, minus 6.0 percent, while in the fourth event window it was plus 0.8 (although in this period, the day after Navalny was sentenced to jail, the excess return was minus 1.7).

The correlations between news and excess returns in this brief are based on daily data. Since many things can happen during a day, the analysis is not as precise as in the paper by Enikolopov, Petrova, and Sonin (2018), where the authors claim that causality is proven by the minute by minute data. Although we have to be more modest in claiming that we have identified a causal relationship going from Navalny news to negative stock market returns, the daily data used here provides enough evidence to claim that there is a strong association pointing in this direction. If we take all four events and translate the cumulative excess returns in percent (which is 14) into dollars by using the market capitalization on the RTS at the time of the events (on average around 200 billion dollars), this amounts to a combined loss in market value of over 27 billion dollars.

Figure 3. Excess returns and Navalny news

Source: Excess returns from author’s calculations based on data from the Moscow Exchange (MOEX), Nasdaq, and the US energy information administration. The chart indicates days for which we cannot compute excess returns since not all days are trading days.

We may think that excess returns of this magnitude are common and that what we pick up for the four Navalny episodes are regular events in the market. To investigate this and other potential factors that have been important to explain excess returns in this time period, Table 1 provides a list of all the days when the excess return in the market was minus 2 percent or worse. Between August 2020 and mid-March 2021, there were eight such days. The table also shows what could be an associated Navalny event on or close to those dates as well as other competing factors or news that could explain the large negative returns on these days.

Out of 8 days with strong negative returns, the first three days are very clearly associated with major news regarding the poisoning of Navalny. The fourth day is close to Navalny’s release from the hospital but also when there are discussions about U.S. views on Iran and Ukraine. Two of the days are in the time period of the protests following Navalny’s video on “Putin’s palace” and two more days are related to important international institutions speaking out regarding first the poisoning with Novichok and then about the prison term of Navalny.

Although we would need a more fine-grained look at market data to make a final judgment on the most important drivers of the excess returns of a specific day, the fact that every single day with large negative excess returns is on or close to a Navalny news story is again pointing in the direction of a stock market that reacts to news about Navalny. Furthermore, the most significant drops with less competing news are associated with events that have a direct connection to Navalny’s health and how his life was put in danger. In the list of competing news are Nord Stream, Biden affecting the oil and gas industry, and a law regarding the taxation of digital currencies. They are likely to be of at least some relevance for stock market valuations and could account for certain days or shares of poor performance of the RTS, but it is hard to ignore the general impression of Navalny being important for the stock market in this period.

Table 1. Days with RTS excess returns of minus 2% or worse (August 1, 2020 to March 12, 2021)

Source: Excess returns from author’s calculations based on data from the Moscow Exchange (MOEX), Nasdaq, and the US energy information administration. News comes from internet searches on Navalny and relevant dates.

Conclusions

Although it is difficult to prove causality and rule out all competing explanations, this investigation has shown a strong association between major news regarding Navalny and very poor performance of the Russian stock market. Every day since August 2020 that had excess returns of minus 2 percent or worse is more or less closely associated with significant news on Navalny. More than that, almost all days with significant Navalny news during this period, – as captured by high search intensity of Navalny on Google, – are associated with a poorly performing stock market. In particular, this holds for the day of his poisoning and the following days with comments by international doctors, politicians, and institutions regarding the use of Novichok to this end.

It could be noted that a 1 percent decline in the RTS equates to a loss in monetary terms of around 2 billion USD in this time period since the market capitalization of the RTS index was on average around 200 billion USD. The combined decline in the events shown in Figure 3 is 14 percent and for the days listed in Table 1, it is 21 percent, i.e., corresponding to market losses of somewhere between 28 and 42 billion USD. Even if only a fraction of this would be directly associated with news on Navalny, it adds up to very significant sums that some investors have lost. One may argue that the losses are only temporary and recovered within a short time period (which would still need to be proven), but for the investors that sold assets on those particular days, this is of little comfort. At a minimum, events like these contribute to increased volatility in the market that in turn has a negative effect on capital flows, investments, and ultimately economic growth (Becker, 2019 and 2020). For anyone caring about the health of their own investments or the Russian economy, it makes sense to care about the health of Navalny.

References

  • Becker, Torbjörn, 2016. “Russia and Oil — Out of Control”, FREE policy brief.
  • Becker, Torbjörn, 2019. “Russia’s Real Cost of Crimean Uncertainty”, FREE policy brief, June 10.
  • Becker, Torbjörn, 2020. “Russia’s macroeconomy—a closer look at growth, investment, and uncertainty”, Ch 2 in Putin’s Russia: Economy, Defence And Foreign Policy, ed. Steven Rosefielde, Scientific Press: Singapore.
  • Enikolopov, Ruben, Maria Petrova, and Konstantin Sonin, 2018, “Social Media and Corruption”, American Economic Journals: Applied Economics, 10(1): 150-174.
  • Fisman, Raymond, 2001, “Estimating the Value of Political Connections.” American Economic Review, 91 (4): 1095-1102.
  • Google trends data.
  • Moscow Exchange (MOEX), RTS index data.
  • Nasdaq, S&P 500 data.
  • U.S. Energy Information Administration, 2021, data on Brent oil prices.

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.

Understanding Russia’s GDP Numbers in the COVID-19 Crisis

20210308 Understanding Russia GDP Numbers FREE Network Policy Brief Image 02

Russia’s real GDP fell by a modest 3 percent in 2020. The question addressed here is how a major oil-exporting country can go through the COVID-19 pandemic with a decline of this magnitude when oil prices fell by 35 percent at the same time as the domestic economy suffered from lock-downs. The short answer is that it is mainly a statistical mirage. The aggregate real GDP decline would have been almost three times greater than in the official statistics if changes in exports were computed in a way that better reflects their value. In particular, the real GDP calculation uses changes in volumes rather than values to omit inflation, but for exports, it thus ignores large changes in international oil prices. In the end, what the government, companies, and people in Russia can spend is much more closely related to how much money is earned on its exports than how many barrels of oil the country has sold to the rest of the world. More generally, this means that real GDP growth in Russia is not a very useful statistic in years with large changes in oil prices, as was the case in 2020, since it does not properly reflect changes in real income or spending power. When policymakers, journalists, and scholars now start to compare economic developments across countries in the covid-19 pandemic, this is something to bear in mind.

Introduction

The world is closing the books on 2020 and it is time to take stock of the damage done by the COVID-19 pandemic thus far. A year into the pandemic, over 100 million cases have been confirmed and almost 2.5 million people have died worldwide according to ECDC (2021) statistics. Russia has not been spared and Rosstat reported 4 million infected and over 160 000 dead in 2020.

Human suffering in terms of lost health and lives is certainly the main concern in the pandemic, but on top of that comes the damage done to economies around the world. Falling incomes, lost jobs, closed businesses, and sub-par schooling will create significant health and other problems even in a fully vaccinated world for years to come.

Understanding how real GDP has fared in the crisis does not capture all of these aspects, but some. With the IMF’s latest World Economic Outlook update on economic performance out in January 2021, it is easy to start comparing GDP growth across countries (IMF, 2021). GDP growth is a standard measure of past performances in general, but the numbers for 2020 may also enter various domestic and international policy discussions of what does and does not work in protecting economies in the pandemic. For countries that seem to have fared better than their peers, the growth numbers are likely going to be used by incumbent politicians to boost their ratings or by consumers and business leaders making plans for the future.

In short, real GDP numbers are important to most economic and political actors, domestically and globally, with or without a crisis unfolding. It is therefore important to understand how Russia, a major oil exporter with significant losses of lives and incomes in the pandemic, could report a real GDP decline of only 3 percent in 2020 (Rosstat, 2021). Although this is not far from the global average reported by the IMF (2021), it is far better than the 7.2 percent drop in the Euro area, 10 percent fall in the UK, or 7.5 to 8 percent declines of its BRICS peers, South Africa and India. This brief provides the details to understand that Russia’s performance is more of a statistical artifact than a fundamental reflection of the health of the Russian economy.

Oil prices, GDP growth, and the ruble

Russia’s dependence on exporting oil and other natural resources is well documented (see for example Becker, 2016a and 2016b) and often discussed by Russian policymakers and pundits. In particular, changing international oil prices is a key determinant of growth in the Russian economy. Even if the level of real GDP disconnected from oil prices somewhere between 2009 and 2014 (Figure 1), the link between real GDP growth and changes in oil prices persists (Figure 2).

Figure 1. Russia real GDP and oil prices

Source: Author’s calculations based on U.S. Energy Information Administration and Rosstat.

The empirical regularity that still holds is that, on average, a 10 percent increase (decline) in oil prices leads to around 1.4 percent real GDP growth (fall), see Becker (2016a). With a 35 percent decline in oil prices in 2020, this alone would lead to a drop in GDP of around 5 percent.

Figure 2. GDP growth and oil price changes

Source: Author’s calculations based on U.S. Energy Information Administration and Rosstat.

One factor that has a fundamental impact on how the relationship between oil prices and different measures of GDP changes over time is the ruble exchange rate. For a long period, Russia had a fixed exchange rate regime with only occasional adjustments of the rate. A stable exchange rate was the nominal anchor that should instill confidence among consumers and investors. However, when changes in the oil prices were too significant, the exchange rate had to be adjusted to avoid a complete loss of foreign exchange reserves. This was evident in the 90’s with the crisis in 1998 and later in the global financial crisis in 2008/09. Eventually, this led to a flexible exchange rate regime and in 2014, Russia introduced a flexible exchange rate regime together with inflation targeting as many other countries had done before it.

As can be seen in Figure 3, this has important implications for how changes in international oil prices in dollars are translated into rubles. Note that the figure shows index values of the series that are set to 100 in the year 2000 so that values indicate changes from this initial level. Starting in 2011, but more prominently since 2014, the oil price in rubles has been at a significantly higher level compared to the oil price measured in dollars, which is of course due to the ruble depreciating. This affects the government’s budget as well as different measures of income in rubles. However, if oil prices in dollars change, this affects the real spending power of Russian entities compared with economic actors in other countries regardless of the exchange rate regime. Moving to a flexible exchange rate regime was inevitable and the right policy to ensure macroeconomic stability in Russia when oil prices went into free fall. Nevertheless, it does not change the fundamental economic fact that falling oil prices affect the real income of an oil-exporting country. It also makes it even more important to understand how real GDP is calculated.

Figure 3. Oil prices and exchange rate indices

Source: Author’s calculations based on U.S. Energy Information Administration and Central Bank of Russia.

The components of real GPD

GDP is an aggregate number that can be calculated from the income or expenditure side. The focus in this brief is on the expenditure side of GDP. The accounting identity at play is then that GDP is equal to private consumption plus government consumption plus investments (that can be divided into fixed capital investments plus change in inventories) plus exports minus imports (where exports minus imports is also called net exports). Being an accounting identity, it should add up perfectly but in the real world, components on both the income and expenditure sides are estimated and things do not always add up as expected. This generates a statistical discrepancy in empirical data.

Another important note on real GDP (rather than nominal GDP measured in current rubles) is that the focus is on how quantities change rather than prices or ruble values. The idea is of course to get rid of inflation and focus on, for example, how many refrigerators are consumed this year compared to last year and not if the price of refrigerators went up or down. This may sound obvious, but it comes with its own problems concerning implementation and interpretations. For Russia, real GDP becomes problematic because its main export is oil (gas and its related products). The price of oil is just one of many drivers of Russia’s inflation but is an extremely important driver of its export revenues and growth as has been discussed above. On top of that, oil prices are volatile and basically impossible to control for Russia or even the OPEC.

So why does this matter for understanding Russia’s real GDP growth in 2020? The answer lies in how the different components of real GDP are computed. To make this clear, the evolution of the components between 2019 and 2020 is shown in Table 1.   

Table 1. Russia’s GDP components from the expenditure side

Source: Author’s calculations based on data from Rosstat

In short, private consumption fell by close to 9 percent in 2020 compared to 2019; government consumption increased by 4 percent; gross fixed capital formation declined by 6 percent while inventories increased by 26 percent; exports lost 5 percent, but imports went down by 14 so that net exports showed an increase of 65 percent! To calculate the impact these changes have on aggregate GDP growth, we need to multiply with the share of GDP for a component to arrive at the impact on GDP growth in the final column of Table 1.

Although there are some issues to resolve with both government consumption and inventory buildup, to understand real GDP growth in 2020, it is crucial to understand what happened to exports and imports in real GDP data. First of all, how does this data compare with the balance of payments data that measures exports and imports in dollar terms or the data that show the value of exports of oil, gas, and related products? Table 2 makes it clear that the numbers do not compare at all! Again, this is due to real GDP numbers being based on changes in volumes rather than values while the trade date reports values in dollars (that can be translated to rubles by using the market exchange rate).

In the real GDP statistics, net exports show growth of 66 percent in 2020, compared to declines of 37 to 44 percent if merchandise trade data is used. Going into more detail, real GDP data has exports declining by 5 percent, while other indicators fall by between 11 and 37 percent. It is similar with imports (that enter the GDP calculation with a negative sign); the import decline recorded in real GDP is 14 percent, while trade data suggest a 6 percent decline in dollar terms but an increase of 7 percent in nominal ruble terms.

Table 2. Trade statistics

Source: Author’s calculations based on Rosstat, Central Bank of Russia and BOFIT

What would it mean if we use some of these alternative growth rates for exports and imports (while keeping other components in line with official statistics) to calculate aggregate GDP growth in 2020? The rationale for keeping other components unchanged is that this provides a first-round effect of changing trade numbers on real GDP growth.

To make this calculation, the GDP shares of exports and imports (or net exports) in 2019 are needed. Table 1 shows that these numbers are 27 and 24 percent (or a net 3 percent) of total GDP. Multiplying the share of a GDP component with its growth rate gives the contribution of the component to overall GDP growth. The calculations based on different trade data are shown in Table 3. The last line of the table is what GDP growth would have been with these alternative trade data. Note that the real GDP growth number is -2.9 percent when we use the individual components of GDP decomposition (rather than the official headline number -3.1 real GDP growth when using aggregate GDP) so this is shown here to make the table consistent with the alternative calculations. In the last column of Table 3, oil and gas exports are assumed to make up for half of exports and this number disregards changes in other exports or imports to isolate the effect of changes in the value of oil and gas exports from other changes.

The summary of this exercise is that with more meaningful trade data used in calculating GDP growth, Russia would have recorded a decline of around 9 percent rather than 3 percent. This is of course a partial analysis focusing on the trade part of real GDP since this effect is very striking. Other components of the calculation may also have issues that need to be adjusted to arrive at a more realistic growth number. Still, even the current estimate is not unrealistic. For example,  household consumption fell by around 9 percent, which would be consistent with a GDP decline of 9 percent that is not recovered in the future in a permanent income model.

Table 3. GDP growth contributions from alternative trade data

Source: Author’s calculations based on U.S. Energy Information Administration and Rosstat

Conclusions

Real GDP growth numbers are important to understand economic developments in a country and provide the foundation for many types of economic decisions. The numbers are also used to compare the economic performance of different countries and evaluate policy responses in the COVID-19 pandemic we are currently part of.

The problem with Russia’s reported growth of minus 3 percent is not that the real GDP calculation is wrong per se, but it is clearly the wrong metrics to use for understanding how incomes and purchasing powers of Russian households, companies, and the government changed in 2020. If we instead use trade data that better reflect plummeting oil prices in international markets, alternative estimates of Russia’s real growth show a GDP decline of (at least) 9 percent.  This is a three times larger drop than the official number of minus 3 percent. This is important to keep in mind when Russia’s economic performance in the pandemic is compared with other countries or while discussing the economic realities of people living in Russia.

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.

Addressing the COVID-19 Pandemic: Vaccination Efforts in FREE Network Countries

Preparing Covid Vaccine on Pink Surface representing COVID-19 vaccination

There are great expectations that vaccinations will enable a return to normality from Covid-19. However, there is massive variation in vaccination efforts, vaccine access, and attitudes to vaccination in the population across countries. This policy brief compares the situation in a number of countries in Eastern Europe, the Baltics, the Caucasus region, and Sweden. The brief is based on the insights shared at a recent webinar “Addressing the COVID-19 pandemic: Vaccination efforts in FREE Network countries” organized by the Stockholm Institute of Transition Economics.

Introduction

As of February 16, 2021, the total number of confirmed COVID-19 deaths across the globe has reached 2.45 million according to Our World in Data (2021).  Rapid implementation of vaccination programs that extend to major parts of the population is of paramount importance, not only from a global health perspective, but also in terms of economic, political, and social implications.

Eastern Europe is no exception. Although many countries in the region had a relatively low level of infections during the first wave of the COVID-19 pandemic in the spring of 2020, all have by now been severely affected. Vaccination plays a key role for these economies to bounce back, especially as many of them depend on tourism, trade, and other sectors that have been particularly hurt by social distancing restrictions.

 Figure 1. Cumulative confirmed COVID-19 cases (top panel) and deaths per million (bottom panel) in the FREE Network region

Source: John Hopkins University CSSE COVID-19 visualizations: Ourworldindata.org/coronavirus

Against this background, the Stockholm Institute of Transition Economics invited representatives of the FREE Network countries to discuss the current vaccination efforts happening in Eastern Europe, the Baltics, and the Caucasus (the represented countries were Belarus, Georgia, Latvia, Poland, Russia, Sweden, and Ukraine). This brief summarizes the main points raised in this event.

Vaccination Status

In Latvia, Poland, and Sweden, the second wave of infections started to pick up in November 2020 and peaked according to most COVID-19 impact measures in early 2021. As all three countries are members of the EU and take part in its coordinated efforts, they have all received vaccines from the same suppliers (i.e. Astra/Zeneca, Moderna, and Pfizer/BioNTech).

Latvia had problems early on with getting the vaccination process off the ground. The health minister was blamed for the slow start since he declined orders from Pfizer/BioNTech in the early stages, and was forced to resign. As of February 16, two doses per 100 people have been distributed primarily to medical staff, social care workers, and key-state officials.

Figure 2. Cumulative COVID-19 vaccination doses per 100 people

Source: Our world in data, last updated February 24th, 2021. This is counted as a single dose, and may not equal the total number of people vaccinated. Visualizations: Ourworldindata.org/coronavirus

With the first phase starting in late December, Sweden has by February 16th, 2021, fully vaccinated 1,05% of the population while experiencing serious problems with delivery and implementation. As planning and delivery of vaccines are centralized while the implementation is decided regionally, there have been some unclarities regarding who stands accountable for issues that emerge. Guidelines, issued by the Public Health Agency of Sweden, for how to prioritize different groups have been changed a couple of times. Currently, the (non-binding) recommendation is to prioritize vaccinating people living in elderly care homes, as well as personnel working with this group, followed by those above 65 years of age, health care workers, and other risk groups.

Looking at regional statistics there are significant differences in vaccinating people across regions with an average of 70% usage rate of delivered vaccines, and with lows at 40-60%, see figure 3. Reasons for this remain unclear.

Figure 3. Distributed relative to delivered vaccines across counties (län) in Sweden.

Source: Authors’ calculations based on data collected by the Public Health Agency of Sweden. Last updated February 14th, 2021.

Poland has so far been somewhat more efficient than Sweden in its vaccination efforts. Despite turbulent political events over the last couple of months, it has managed to distribute 5.7 doses per 100 people. The country has just finished the first phase of the national vaccination plan, which focused on vaccinating healthcare personnel, and has now entered the second phase with a shifted focus towards elderly care homes, people above 60 years of age, military, and teachers.

Among the countries that are not members of the EU, and thus, not taking part in its coordinated vaccination efforts, the vaccination statuses are more diverse.

Russia was fast in developing and approving the Sputnik V vaccine. The country started vaccinating in early December, although only people in the age of 18-60 in prioritized occupations such as health care workers, people living and working in nursing homes, teachers, and military. At the start of 2021, the program extended to people above 60 and, on January 16, all adults were given the possibility to register themselves and get vaccinated within one week. There are no precise data at the moment, but the fraction of the population vaccinated is likely to be higher than 1%.

Others in the region have faced greater challenges in signing contracts with vaccine suppliers. Georgia and Ukraine are still waiting to secure deliveries and have not yet started to vaccinate. Being outside the EU agreements and with public and political mistrust towards Sputnik V and Russia alternatives are being explored. Georgia has ordered vaccines through the COVAX platform (co-led by Gavi, the Coalition for Epidemic Preparedness Innovations (CEPI) and WHO) but there are concerns about potential delays in deliveries. In terms of prioritizing groups once vaccinations can start, both Ukraine and Georgia have set similar priorities as other countries, with extra focus on health-care and essential workers, age-related risk groups, and people with chronic illnesses.

While Belarus’ official figures on the death toll have been widely perceived as unrealistic from the beginning, the most accurate and recent data shows an excess deaths rate of about 20% in July. The country has no precise data on vaccinations, but some reports have emerged based on interviews with government officials in the Belarusian media. These suggest that around 20,000 imported doses of Sputnik V have been distributed mainly to medical professionals and an additional 120,000-140,000 doses have been promised by Russia.

Main Challenges

The discussion during the Q&A session at the webinar concerned the economic and political implications of vaccinations in the region.

Pavlo Kovtoniuk, the Head of Health Economics Center at KSE in Ukraine, stressed the importance of a coordinated vaccination effort in Europe with regards to geopolitics. There is a clear EU vs Non-EU divide in the vaccination status across European countries. The limited vaccine availability in Non-EU countries such as Ukraine, Georgia, and Belarus offers opportunities for more influential nations like Russia and China to pressure and affect domestic policy in these countries.

Also highlighting the fact that no one is safe until everybody is safe, Lev Lvovskiy, Senior Research Fellow at BEROC in Minsk, noted that vaccination efforts in Europe are important for recovery in small open economies like Belarus as many of its trade partners currently have imposed temporary import restrictions.

Similar to the political crisis happening alongside the pandemic in Belarus, the challenges we see in Poland – protests against the recent developments regarding abortion rights and attempts by the government to limit free media – have deflated the urgency to vaccinate in terms of its future economic and political implications, according to Michal Myck, director of CenEA in Szczecin.

Looking forward, another major challenge for the region is vaccine skepticism. Not only do many countries have to build proper infrastructure that can administer vaccines at the required scale and pace, but also make sure that people actually show up. In Latvia, Poland, Georgia, Russia, and Ukraine, polls show that less than 50% of the population are ready to vaccinate. Sergejs Gubin, Research Fellow at BICEPS in Riga, highlighted that there can be systematic variation in the willingness to vaccinate within countries as e.g. Russian-speaking natives in Latvia have been found to be less prone to vaccinate on average. Also, most of the skepticism in Georgia has been more directed towards the Chinese and Russian vaccine than towards those approved by the EU, according to Yaroslava Babych who is lead economist at ISET in Tbilisi.

Even though vaccine skepticism is an issue in Russia too, Natalya Volchkova, Director of CEFIR at New Economic School in Moscow, pointed to the positive impact of “bandwagon effects” in vaccination efforts. When one person gets vaccinated, that person can spread more accurate information about the vaccine to their social circle, resulting in fewer and fewer people being skeptical as the share of vaccinated grows. In such a scenario vaccine skepticism can fade away over time, even if initial estimates suggest it is high in the population.

Concluding Remarks

Almost exactly a year has passed since Covid-19 was declared a pandemic. The economic and social consequences have been enormous. Now vaccines – developed faster than expected – promise a way out of the crisis. But major challenges, of different types and magnitudes across the globe, still remain. As the seminar highlighted, there are important differences across transition countries. Some countries (such as Russia) have secured vaccines by developing them, but still face challenges in producing and distributing vaccines. Others have secured deliveries through the joint effort by the EU, but this has also had its costs in terms of a somewhat slower process (compared to some of the countries acting on their own) and sharing within the EU. For some other countries, like Belarus, Ukraine, and Georgia, the vaccination is yet to be started. All in all, the choice and availability of vaccines across the region illustrates how economic and geopolitical questions remain important. Finally, for many of the region countries vaccine skepticism and information as well as disinformation are important determinants in distributing vaccines. Summing up, the combination of these factors once again reminds us that how to best get back from the pandemic is truly a multidisciplinary question.

List of Participants

  • Iurii Ganychenko, Senior researcher at Kyiv School of Economics (KSE/Ukraine)
  • Jesper Roine, Professor at Stockholm School of Economics (SSE) and Deputy Director at the Stockholm Institute of Transition Economics (SITE/ Sweden)
  • Lev Lvovskiy, Senior Research Fellow at the Belarusian Economic Research and Outreach Center (BEROC/ Belarus)
  • Michal Myck, Director of the Centre for Economic Analysis (CenEA/ Poland)
  • Natalya Volchkova, Director of the Centre for Economic and Financial Research  ­New Economic School (CEFIR NES/ Russia)
  • Pavlo Kovtoniuk, Head of Health Economics Center at Kyiv School of Economics (KSE/Ukraine)
  • Sergej Gubin, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS/ Latvia)
  • Yaroslava V. Babych, Lead Economist at ISET Policy Institute (ISET PI/ Georgia)

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

Video of the FREE Network webinar “Addressing the Covid-19 Pandemic: Vaccination Efforts in Free Network Countries