Location: Russia

Can Central Banks Always Influence Financial Markets? Evidence from Russia

Posted on June 8, 2020 | Policy Brief

Tall buildings in Moscow city representing central banks and financial markets

In many financial markets, including the UK and US, central banks are able to influence asset prices through unexpected interest rate changes (so-called indirect channel of monetary policy). In our paper (Shibanov and Slyusar 2019) we study the Russian market in 2013-2019 and measure policy shocks by the difference between the key rate and analysts’ median forecast. We show that in the short-term, the Central Bank of Russia does not significantly influence the general stock market or the ruble exchange rate outside December 2014 and January 2015, while some sectoral stock indices react to the changes opposite to what theoretical models predict. Overall, the Russian case is more similar to the ECB and the case of the German economy than to results from the UK or the US. This may mean that the Bank of Russia has more influence through the direct channel on the interest rates of credits and deposits.

Asset Price Reaction to Policy Changes

What should we expect from a general stock market or a national currency reaction to the central bank interest rate policy? This indirect effect may lead to changes in the collateral available in the economy, or in imports and exports of a country. Theoretical models predict that an expected decrease in the key rate would have no impact on asset prices, while unexpected increases in the key rate may have a negative impact on asset prices (Kontonikas et al. 2013). If the interest rate increases more than the markets or analysts expect, we would see prices decrease as discount rates most probably increase; the opposite happens when the interest rate decreases more than expected.

The results of testing this presumption on different countries are not uniform. While in the US (Kontonikas et al. 2013) and in the UK (Bredin et al. 2009) the impacts of key rate policy surprises are significant, the ECB influences neither the UK nor the German stock markets (Breidin et al. 2009).

Regarding the exchange rate (Hausman and Wongswan, 2011), there is evidence that unexpected changes in the US interest rate have a strong impact on floating currencies.

The Case of Russia

Russian monetary policy has changed a lot since 2013. The introduction of the “key rate” as the main policy tool, switch to the floating ruble and inflation targeting in November 2014 all lead to a new framework used by the Bank of Russia. Therefore, it is of interest to check what happens with the indirect channel of policy transmission (through asset prices and financial markets).

There is at least one paper that precedes our research. Kuznetsova and Ulyanova (2016) study the impact of verbal interventions by the Bank of Russia (Central Bank of Russia) on both the returns and the volatility of the Russian stock market index (RTS) in 2014-2015. Their findings suggest that returns do react to the Bank of Russia communications, while volatility does not.

In our paper (Shibanov and Slyusar 2019) we study the period of 2013-2019, that is the time of Elvira Nabiullina as governor of the Bank of Russia. Our approach is based on the assumption that news are incorporated in the stock market reasonably fast, no later than 4 trading days after the day of announcement. For the exchange rate we take short-term movements 30 minutes before and after the time of publication (like in Hausman and Wongswan 2011). Monetary policy surprise is measured as the difference between the realized key rate and the median expectations of analysts in Thomson Reuters. Abnormal returns are computed using an index model.

Figure 1 shows that the surprises are close to zero except for two dates: December 2014 and January 2015. In the first period the key rate was increased to 17%, while in the second it was reduced to 15%. In the paper we show that these two days are clear outliers that bias the results, so we study the relationship without them.

Results for the Stock Market

The stock market reaction in the symmetric window of four days before the announcement and four days after is muted (see Table 1). While the main index (MICEX) does not react significantly, two sectors (MM – metals and mining, and chemistry) react positively to the unexpected increase in the key rate. This result seems to contradict what we would expect from the market. The bond index does not significantly react to the changes.

Table 1. Cumulative effect, sample with no shocks (days from -4 to +4).

Sector Estimate t-statistic P-value Significance
MICEX 1.6192 0.6803 0.4999 0.041
OG 0.2511 1.125 0.2668 0.005
Finance -1.2933 -1.080 0.2860 0.024
Energy -0.4513 -0.7145 0.4787 0.004
MM 2.2876 3.326 0.0018 *** 0.113
Telecom -0.2534 -0.2844 0.7774 0.001
Consum. 0.2178 0.4191 0.6772 0.001
Chemistry 2.9787 2.642 0.0114 ** 0.132
Transport 0.3200 0.1548 0.8777 0.001
Bonds 1.4080 1.048 0.3002 0.037

Source: Shibanov and Slyusar (2019), Thomson Reuters, Moscow Stock Exchange and Bank of Russia data.

Results for the Ruble Exchange Rate

The exchange rate should react with a depreciation to the unexpected key rate decrease. If there is an unexpected increase, the return on the ruble-denominated bonds rises and so the currency becomes more attractive to the international investors.

However, we do not observe any significant difference between the cases of expected and unexpected changes (see Table 2). All the movements are quite noisy and do not show any stable pattern.

Table 2. Exchange rate reaction to the key rate changes.

Key rate increase Key rate decrease
Unexpected -1.05% -0.04%
Expected 0.65% 0.003%

Source: Shibanov and Slyusar (2019), Thomson Reuters and Bank of Russia data.

Figure 1. Deviations of the actual key rate from median expectations (key rate surprises), percentage points.

Source: Shibanov and Slyusar (2019), Thomson Reuters and Bank of Russia data.

Conclusion

As we see from our analysis, the Bank of Russia’s impact on financial markets is similar to the one observed in Germany after ECB policy changes. There is almost no sizeable and stable effect neither on asset prices nor on the exchange rate.

The results do not mean, however, that monetary policy in Russia is irrelevant. The direct channel – i.e. the impact of the central bank’s decisions on the interest rates of credits and deposits works well. Moreover, we only consider short-term effects concentrated around the announcement date. Longer-term effects may be more pronounced.

References

  • Bredin, D. et al. (2009) ‘European monetary policy surprises: the aggregate and sectoral stock market response’, International Journal of Finance & Economics. Wiley Online Library, 14(2), pp. 156–171.
  • Hausman, J. and Wongswan, J. (2011) ‘Global asset prices and FOMC announcements’, Journal of International Money and Finance. Elsevier Ltd, 30(3), pp. 547–571. doi: 10.1016/j.jimonfin.2011.01.008.
  • Kontonikas, A., MacDonald, R. and Saggu, A. (2013) ‘Stock market reaction to fed funds rate surprises: State dependence and the financial crisis’, Journal of Banking and Finance, 37(11), pp. 4025–4037. doi: 10.1016/j.jbankfin.2013.06.010.
  • Kuznetsova, O. and Ulyanova, S. (2016) ‘The Impact of Central Bank’s Verbal Interventions on Stock Exchange Indices in a Resource Based Economy: The Evidence from Russia’, Working Paper, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2876617.
  • Shibanov, O. and Slyusar A. (2019) ‘Interest rate surprises, analyst expectations and stock market returns: case of Russia’, Working Paper.

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.

Covid-19 and Gender Inequality in Russia

Posted on May 14, 2020 | Policy Brief

20200514 Covid-19 and Gender Inequality in Russia FREE Network Policy Brief Image 01

Gender inequality is a complex phenomenon characterized by significant and persistent differences in social and economic indicators for women and men. In connection with the Covid-19 pandemic and unprecedented quarantine measures around the world, economists are thinking not only about the obvious global consequences for the global economy but also about the indirect effects, including those through gender-related changes in the labor market. What will the consequences of this crisis on the labor market be in the long run, especially on its gender and family-related components? In this brief, we look at the potential effects of the Covid-19 epidemic and the associated quarantine on gender inequality in Russia.

Introduction

Gender inequality is a complex phenomenon characterized by significant and persistent differences in social and economic indicators for women and men. These may be differences in access to education and medicine, labor market participation, wages, entrepreneurship, participation in politics and public administration, and the distribution of domestic unpaid labor within the family. Reducing gender inequality (like any other form of inequality) correlates with increases in GDP.

The prevalence and scale of gender inequality is, on average, lower in developed countries than in developing countries, and although there is a general tendency for gender gaps to narrow over time, this does not happen simultaneously and equally in all countries. According to the Global Gender Gap Index (2020), which ranks more than 150 countries, the five countries with the best indicators include Iceland, Norway, Finland, Sweden, and Nicaragua, while Congo, Syria, Pakistan, Iraq, and Yemen are in the very bottom. As of 2020, Russia is located approximately in the middle, being the 81st, right between El Salvador and Ethiopia.

In connection with the Covid-19 pandemic and unprecedented quarantine measures around the world, economists are thinking not only about the obvious global consequences for the global economy but also about the indirect effects, including those through gender-related changes in the labor market. A study of World War II, for example, shows that even short-term gender differences in the labor market can have long-term consequences (Goldin and Olivetti, 2013). What will the consequences of this crisis on the labor market be in the long run, especially on its gender and family-related components? In this brief, we look at the potential effects of the Covid-19 epidemic and the associated quarantine on gender inequality in Russia.

Heterogeneous Cross-Sectoral Effects

Economists are now discussing two main channels that can influence gender inequality (Alon et al., 2020). The first one works through differential risk of losing jobs and salaries for women and men due to the disproportionate impact of the epidemic and quarantine on sectors which predominantly employ each gender. The direction of this effect is not easy to predict. On the one hand, the current crisis differs from ordinary recessions in that the service sector, where more women are traditionally employed, is now suffering more than usual. However, it is very important to emphasize what kind of services we are talking about: restaurants and salons are not the whole of the Russian economy. According to the Russian Statistical Agency (Rosstat) 49% of all employed women in 2019 worked in three sectors – trade, healthcare, and education. At the same time, hotels, restaurants, and other services (which include hair and beauty salons) provided less than 8% of women’s employment.

Therefore, from the point of view of assessing the risk of job loss, it makes sense to consider state-financed sectors, where employees are likely to be retained, separately. Among the private businesses, two (non-mutually exclusive) types of sectors are likely to suffer the least. First, the critical ones that do not stop their activity during quarantine (for example, food retail, private medical centers). And second, those that are characterized both by a high ability to work “remotely” and continue to have sufficient demand for their goods and services – either directly or through value chains (see e.g. Volchkova, 2020). For example, agriculture, manufacturing and hotels are worse off in this combination than the financial sector, science, administration, and some types of online education. At the level of the individual characteristics of the employee, even when comparing the same occupations, the possibility of remote work positively correlates with the level of education, wealth, working for a company (rather than self-employment), and being female (according to Saltiel, 2020, for developing countries).

According to the same data from Rosstat, it turns out that about 49% of all women and 40% of all men worked in the “state-financed” and “remote-work” sectors (or 69% against 52%, if we add the trade sector). This is of course an overestimate, since not every job within a sector is characterized by state-financing or remoteness, but it likely represents the relative propensity across genders, which is of our interest. This relative propensity is mostly due to the much higher employment of women compared to men in health and education (approximately 4 to 1 in both sectors). In general, this may mean that the risk of job loss is now higher for men, and not for women as was predicted using US data by Alon et al. (2020), given the gender structure of employment by industry in the US. This rough assessment does not account for different opportunities for women and men to quickly find a new job, especially in the areas of high demand. For example, if the need for delivery workers has increased, and men are more likely to take this job, then it may be easier for them to quickly find a new job. This adaptive effect would unlikely overturn the original difference, because the number of such jobs is also limited.

The Effect of Childcare Facilities Closure

The second channel, likely having a multiplicative effect on the first, operates through the unexpected closure of children’s educational institutions (kindergartens and schools). These effects may be different depending on family composition. While before the pandemic, working parents could send their children to kindergarten and school, this opportunity is now completely unavailable. In the case of online education, not all children are independent enough to learn at home, especially primary school students. At the same time, other childcare support (e.g. from nannies, grandparents and other relatives, etc.) can also be significantly limited due to social distancing and self-isolation, although Russia is in a better position in this regard compared to many developed countries because grandparents traditionally help more in raising children. (It is interesting that in developed countries, the possibility of outsourcing household chores – childcare, cleaning, etc. – is one of the important explanatory factors for higher fertility among more educated women, compared with less educated ones, (see Hazan and Zoabi, 2015)).

Naturally, the situation with closed childcare and educational institutions will not affect the productivity of people without young children. According to the latest census in 2010, about 88 million people, which is as much as 75% of the total adult population of the country, do not live together with children under 18 years old. Also, most likely there will not be a big negative effect on families with children where one of the parents (most often the mother) or another individual in the household (a grandparent) took care of the child at home before the quarantine.

For all other families, the critical problem is juggling childcare with work. The most vulnerable categories of the population here are single mothers and single fathers (and there are about 5 and 0.6 million in Russia, respectively), especially those who do not have any outside help.

Among families with small children where both parents work, several important factors can be identified. On the one hand, according to developed countries, even in families where both parents work, women spend more time on household chores and childcare than men (Doepke and Kindermann, 2019). If one believes that the initial factors that affected this distribution of domestic work (such as traditional norms and role models or the relative income of spouses) have not disappeared, then the sharply increased burden of household chores will disproportionately fall on women. This can lead to a decrease in the relative productivity of women compared to men in the labor market and a greater risk of dismissal. In the long run, this can also negatively affect gender inequality, as even a temporary exit from the labor market may be accompanied by human capital losses and a worse career path in the future.

The Interaction of Both Effects

On the other hand, the opposite situation is also possible. If, due to the disproportionate effect of quarantine on various sectors of the economy, which has been discussed above, women have a lower risk of losing their jobs, then it is possible that at least temporarily, a significant part of the childcare will fall on men. This situation can also happen in families where the woman works in critical sectors of the economy (especially in healthcare) and the man works remotely from home.

Economists have suggested several mechanisms for the effect of short-term additional interaction between fathers and children on long-term participation in their upbringing: there is more information about children’s needs, learning-by-doing, and greater attachment to children. For example, the data from Canada shows that the introduction of 5 weeks of parental leave for fathers led to a more even distribution of domestic labor in households and a greater likelihood of the mother’s participation in the labor market, even 1-3 years after the fact (Patnaik, 2019). Moreover, even if there are not many families like this in the country, the new social norms can gradually spread in society through so-called “peer effects”. Dahl et al. (2014), for example, show using Norwegian data that the brothers and colleagues of men who took parental leave were 11-15% more likely to take it in the future, relative to brothers and colleagues of men who did not take such leave.

Other Hypotheses

Another major consequence of the epidemic and quarantine is the potential upsurge in domestic violence. Several European countries have already noticed an increase in such crimes (European Parliament, 2020), and some crisis centers in Russia have also reported an increase in calls to helplines. Economists identify different triggers for this behavior (Peterman et al., 2020). This may be a direct consequence of quarantine, which increases the time spent by the potential victim and abuser in a closed space, and the inability to seek immediate help, both psychological and medical. Indirect effects can also work through an increased risk of depression and post-traumatic stress syndrome, which were well documented for previous epidemics such as SARS and swine flu. and that may happen due to job loss, reduced income, general economic uncertainty, or a direct fear of getting sick.

These effects disproportionately affect women (and children); therefore, additional resources should be dedicated to identifying such crimes, strengthening support structures for women, and increasing the availability of reporting options without attracting the attention of an abuser (for example, such a warning system may be installed in pharmacies – a place where a woman can go to alone).

Economists have yet to accurately measure and test all these mechanisms, which interact with each other in complex combinations, but it is now clear that very different scenarios are possible, including the positive ones – of a long-run decrease in gender inequality.

References

  • Alon T.,  Doepke M., Olmstead-Rumsey J., and Tertilt M. “The impact of Covid-19 on gender equality”, Covid Economics, Issue 4, 14 April 2020.
  • Dahl G.B., Løken K.V., Mogstad M. “Peer Effects in Program Participation”, American Economic Review 104(7): 2049–2074 (2014).
  • Doepke M. and Kindermann F. “Bargaining over Babies: Theory, Evidence, and Policy Implications”, American Economic Review, 109(9): 3264–3306 (2019).
  • Goldin C. and Olivetti C. “Shocking Labor Supply: A Reassessment of the Role of World War II on Women’s Labor Supply”, American Economic Review, 103(3): 257-262 (2013).
  • Hazan M. and Zoabi H. “Do highly educated women choose smaller families?” Economic Journal, 125(587): 1191-1226 (2015).
  • Patnaik A. “Reserving Time for Daddy: The Consequences of Fathers’ Quotas”, Journal of Labor Economics, 37(4): 1009-1059 (2019).
  • Peterman A., Potts A., O’Donnell M., Thompson K., Shah N., Oertelt-Prigione S., and van Gelder N. “Pandemics and Violence Against Women and Children”, Center for Global Development working paper, 1 April 2020.
  • Saltiel F. “Who can work from home in developing countries?” Covid Economics, Issue 6, 17 April 2020.
  • Volchkova N. “Who should receive government support during Covid-19 crisis”, in “Economic Policy during Covid-19”, April 2020.
  • European Parliament. “COVID-19: Stopping the rise in domestic violence during lockdown”, Press Release  7 April 2020.
  • Rosstat, “Russian census 2010”.
  • Rosstat, “Russian labor force survey 2019”.

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.

Covid-19: News for Europe’s Energy Security

Posted on May 7, 2020 | Policy Brief

Black and white image of natural gas processing plant representing Energy security Europe

While there has been a lot of attention on the effect of Covid-19-related developments in the oil market, the effect on the natural gas market has almost evaded media attention. For the EU, however, the gas market and especially the impact of the pandemic on the gas relationship with its largest gas supplier, Russia, is of high relevance. This brief discusses the potential implications of Covid-19 on this relationship both under the pandemic and during the expected slow economic recovery. We argue that, while in the short run the security of Russian gas supply is likely to improve, this is unlikely to be the case in the aftermath of the pandemic. To ensure gas supply security in post-pandemic markets, the EU may need to finally implement the long-awaited “speaking with one-voice” energy policy.

Introduction

The ongoing coronavirus pandemic will not only affect human lives, but also bring new economic and political challenges. The energy sector, and in particular the dramatic decrease of oil prices, has been in the news since the beginning of the Covid-19 crisis. But discussions have so far rarely touched the natural gas market, despite the pandemic taking its toll also on this market. As for oil, the demand and price have been negatively affected by the economic slowdown. While not as drastic as for oil, the price of natural gas in the EU has declined by approximately 40% since the beginning of 2020 (World Bank, 2020). However, the impact of the pandemic is likely to be quite different in oil and gas markets. There are multiple reasons for that; for example, oil and oil products are predominantly consumed by the transport sector while natural gas is mostly used in the power sector, the industry and households, and these sectors were differently affected by the Covid-19 pandemic.

Understanding the impact of the pandemic on the gas market is especially interesting from the European point of view, given that natural gas accounts for 25% of total energy consumption and two thirds of this gas is imported. The imports are also very concentrated, with the main supplier Russia providing around 40% of the gas, compared to 25% of the crude oil. This dependency, as well as a long history of tensions with third parties (Ukraine and Belarus) on the Russian gas transit routes, has made the EU’s concerns about the security of Russian gas supply much more pronounced than for oil (see Le Coq and Paltseva, 2012). The combination of these factors – i.e. the importance of natural gas for the EU and the long-standing concern about gas supply security warrant an analysis of the short and mid-term effect of the Covid-19 pandemic on the gas market, and, specifically, on the EU-Russia gas relationship. This brief discusses how the pandemic-driven decline in gas demand, and the potential shift in the balance of power between the parties may affect both the dependency on, and the transit of, Russian gas.

EU Dependency on Russian Gas Under the Covid-19 Pandemic

As is well known, Covid-19 and the associated lockdowns imposed by many EU Member States, have caused a slowdown in most economies and a decline in energy demand. However, for natural gas, the effect is likely to be significantly smaller than for oil. While we do not yet have statistics for the EU’s gas demand in recent months, the Norwegian energy consultancy Rystad Energy has predicted the decline of gas demand to be around 4% for March and April 2020. This forecast was given quite early in the course of the pandemic, and is very likely an underestimation; still, it is very different from the one for oil, with the demand drop estimated to be a whopping 34% in April.

One reason why we do not observe a sizable decrease in gas demand is that the natural gas is used in electricity generation, especially as a base-load fuel to compensate for the intermittency of green energy sources, such as sun and wind. With the reduced electricity demand, renewable power generation has become relatively more important in the electricity supply in many countries. Since mid-March 2020, the share of renewable power generation across the EU is 46%, nine percent higher than during the same period last year (Energy Transition Lab, 2020). Interestingly, in France, Germany, Belgium, the Netherlands, the Czech Republic, Poland and Hungary, the absolute volume of electricity generation by renewable sources even increased relative to the same period in 2019, despite declining energy demand. One potential channel, anecdotally recorded for Germany could be higher solar generation due to cleaner skies resulting from the decline in emissions because of lower fossil energy consumption. A higher volume of a renewable generation often requires more back-up power to maintain grid stability. While natural gas is not the only back-up source, this need might still limit the decline in gas demand (or even increase it like e.g. in the Czech Republic). Of course, cheaper gas prices may also play a role: for example, Slovakia and Romania experienced an increase in gas-based generation, but a drop in the renewable generation since mid-March 2020 relative to the same period in 2019. Finally, another reason for the moderate gas demand decline is its residential use – which is likely to be sustained due to the lockdown regime introduced by many countries.

When it comes to Russian gas imports, the official statistics since mid-March – roughly the beginning of lockdown policies across the EU – are not available yet. However, we can with some reservation look at the evolution of the volume of gas sales to the EU disclosed by Gazprom (2020). There was a very sizable decrease in Russian gas imports by the EU – of more than 21% – as compared to the same period last year but it started before the lockdown: January 2020 recorded a drop of 34% and February of 20%). This suggests that the current decrease in Russian gas imports is only marginally related to the pandemic, and more related to the overall gas market situation (such as relatively full gas storage in the EU in 2020, a warm winter, an increase in LNG imports, etc.).

It is, however, likely that the negative effect of the pandemic on Russian gas imports by the EU will be noticeably higher than it currently appears in the Gazprom data, thereby further decreasing the EU’s dependency on Russian gas. Moreover, since demand and prices decrease, substituting for Russian gas, were there a supply interruption, should be relatively easy and cheap with the current excess capacity of the natural gas market and the substantial storage in the EU.

Another reason for the improvement in the security of Russian gas supply to the EU is the observation that Russia’s dependency on oil and gas exports in combination with pandemic-associated factors may lead to a substantial economic downturn in Russia (Becker, 2020). In these dire circumstances, Russia is unlikely to further risk its gas export revenues by pursuing geopolitical goals through the means of gas supply and gas transit. For all these reasons, one may expect the security of Russian gas supply to the EU to improve during the pandemic.

However, the EU dependency on Russian gas may still be a concern due to medium-run effects of Covid-19. First of all, while the gas prices have been in decline for roughly a year now, the recent decrease in natural gas prices has accelerated the negative impact on the unconventional natural gas industry. For example, the US natural gas rig count has declined by 20% since mid-March 2020, which accounts for more than a third of the 54% year-to-year decline (Ycharts.com, 2020). Similarly, nearly 42% of Australian gas resources could be uneconomic under the current gas prices, according to Rystad Energy. While gas prices are unlikely to stay low forever, the industry will need time to recover even if/when the natural gas demand rises again. Moreover, the East-Asian markets are likely to be served first, as they are expected to recover from the pandemic shock before Europe. This dynamic, coupled with historically higher LNG prices in Asia may delay the LNG flows to Europe. A shortage of LNG in Europe, in turn, is likely to hinder any diversification strategy from Russian gas, weakening the EU’s bargaining power. The new Russia-China gas pipeline, “Power of Siberia”, operational since the end of 2019, will also be used to satisfy the post-Covid-19 Chinese gas demand which is likely to recover before demand picks up in the EU. Its use will then allow Russia to be less reliant on exporting gas to the EU, further contributing to the EU’s gas security concerns.

Transit of Russian Gas to the EU: Covid-19 Effect

The EU’s energy security also depends on the reliability of Russian gas transit to the EU. There are currently 5 transit routes connecting Russia to the EU (plus the routes that are serving the Baltic states and Finland without further transit), see Figure 1. Three onshore routes connect Russia to the EU via Ukraine and Belarus. There has been a history of gas transit disputes associated with these routes, at times threatening the Russian gas supply to the EU. Two newer offshore pipelines, Nord Stream 1 (in operation since 2011) and TurkStream (in operation since 2020) connect Russia directly to Germany, and to the South-East of Europe via Turkey. Further, one more offshore route to Germany, Nord Stream 2, is currently underway, with the operations announced to start in the first quarter of 2021. All three offshore projects are expected to not suffer from geopolitical transit issues.

In relation to the Covid-19 pandemic, there are likely to be two major effects on Russian gas transit. First, the inauguration of Nord Stream 2 is likely to be further delayed. Nord Stream 2 is 50% financed by Gazprom, and this financing scheme may be difficult to sustain after the fall in oil and gas prices and a significant decrease of Gazprom’s export revenues. Indeed, while the statistics for March and April 2020 are not yet available, the Russian customs statistics suggests that the USD value of gas exports from Russia in January-February 2020 has decreased by 45% relative to the same period last year. Because Nord Stream 2 could facilitate gas delivery to the EU in case of a transit conflicts, its expected delay may negatively impact the EU’s gas security.

Additionally, the Covid-19 related demand drop may impact the utilization of Russia-EU gas routes, driven by the current agreements between Russia and the transit countries. Russia and Ukraine have just signed a transit agreement for the next 5 years. This agreement was widely perceived as a diplomatic success of the EU (that facilitated the deal), given the historically difficult geopolitical relation between Ukraine and Russia. One of the new features of this agreement is of particular interest within the Covid-19 context. Unlike for previous deals, Russia agreed to prepay a fixed volume of gas transit, 178.1 mcm/day for 2020, and 110 mcm/day units for 2021-24 (Pirani et al., 2020). So, underutilization of this route is costly for Russia.

Figure 1. Gas supply Routes to the EU.

Source: Ukrainian Liaison Office in Brussels

With decreased demand due to Covid-19, warmer weather in the coming months and almost full gas storages in the EU, this contractual feature may affect how Russia allocates its gas exports across the routes. At least, in the short term, it may undermine Russian gas transit via the Belarus-Poland route. The concern about the utilization of this route in relation to the new Russia-Ukraine transit agreement has already been raised by Pirani et al. (2020). The Covid-19-associated decrease in gas demand is likely to make this concern much more real. Russia may use the Belarus-Poland pipeline sporadically, e.g. to adjust for the seasonal spikes in demand, without long-term capacity booking. Recent gas tensions between Russia and Poland (e.g. Poland winning in the arbitration court against Gazprom (RFE/RL, 2020), and Poland repeatedly expressing opinions and exercising legislative effort restricting the usage of Nord Stream 1 and construction of Nord Stream 2) may further exacerbate the issue.

In the medium term, however, when the EU gas demand has recovered but Nord Stream 2 is not yet in place, the Belarus-Poland route is likely to prove useful for Russia, at least starting from 2021 (when prepaid volumes of Russian gas transit via Ukraine will decline according to their agreement).

The transit contract between Russia and Poland is to be renewed in mid-May 2020, and as of now, it is unclear if, and how it will be written and whether the Belarus-Poland transit route will be used to a substantial degree or only marginally. If transit through the Belarus-Poland route is limited, it will imply poorer route diversification for a major part of European consumers of Russian gas, thereby lowering their security of Russian gas supply.   This may also put another strain on the bargaining power allocation within the EU and the EU’s intended common energy policy of “speaking with one voice” with external energy suppliers like Russia.

Conclusion

Summing up, the decrease in demand of natural gas, as well as other factors associated with the ongoing Covid-19 pandemic, such as economic recession and turbulence in stock markets, are likely to have noticeable implications for the security of Russian gas supplies to the EU in the short term. On the one hand, even if the current pandemic-associated decrease in demand of gas from Russia seems rather moderate, the ultimate negative effect on Russian gas imports by the EU is likely to be larger. Lower imports from Russia are likely to improve the security of supply, both through lower import dependency of the EU, and through improved market opportunities due to the current market’s overcapacity. On the other hand, in the medium run, lower demand also negatively affects the non-conventional gas industry, undermining the diversification opportunities to LNG, and, consequently, natural gas energy security. Further, a fall in the gas demand by the EU coupled with the newly signed transit agreement between Russia and Ukraine may potentially cause underusage of the Belarus-Poland transit route, thereby putting a strain on the diversification of Russian gas import routes to the EU and on the power balance within the EU.

Energy security might be even more of a concern in the post coronavirus period when the economy is slowly recovering, and cheap and guaranteed energy supply is crucial. To ensure this supply, national efforts combined with an EU-wide policy coordination would be required. The long-discussed “speaking with one voice” common energy policy may finally need to materialize in order to facilitate reliable access to natural gas.

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.

Russia Economic Update — Brace for the Covid-19 Impact!

Posted on April 15, 2020 | Policy Brief

A view of central Moscow City at dawn representing the sudden stop of Russian economy

Russia’s oil dependence will once again contribute to an economic downturn that most certainly will follow the Covid-19 outbreak in Russia as in other countries. The decline in oil prices alone could lead to a drop in GDP of more than 8 percent. On the positive side, Russia manages its macro economy well. However, its fiscal reserves are not unlimited and the recent massive fall in oil prices has not been matched by a similar decline in the ruble exchange rate which means potential extra problems for the budget. Furthermore, monetary policy will have less of a role to play in dealing with this type of crisis. This means that Russia like other countries will face difficult trade-offs in dealing with the crisis at a time when some of the previously announced economic policy changes have not been well received by the public.

Introduction

The corona virus crisis will destroy both lives and economies as it spreads across the globe. Fortunately, the corona virus death toll in Russia so far is relatively modest compared to many other countries, but the economy is most certainly heading for very difficult times. This is (again) due to the fact that the Russian economy is too dependent on the developments of international oil prices (see e.g. Becker, 2016a,b). In recent years, Russia had to deal with two severe declines in oil prices that hit its economy, first in connection with the global financial crises 2008/09, and second, in 2014/15, when there was a fall in oil prices simultaneously with Russia being hit by international sanctions after the illegal annexation of Crimea. Although these episodes were very costly for the Russian economy, they also provided important lessons for policy makers on fiscal, monetary and exchange rate policies that come in handy today. They also contributed with data on the relationship between large movements in oil prices and the effects they had on GDP growth in Russia. This is useful at this stage to assess what can happen with the economy after the significant decline in oil prices that has followed in the course of the corona outbreak.

Dramatic Decline in Oil Prices

We still do not know when this crisis will be over, but when it comes to the fall in international oil prices the start has been far more severe than the two crises referred to above. Since the beginning of 2020, oil prices have fallen from around $60/barrel to around $15/barrel or as Figure 1 shows, a barrel is now worth around 25 percent of what it was worth three months ago. Furthermore, prices are rather volatile and will continue to be so and there will most certainly also be periods of sharp increases in oil prices going forward – but the overall result for the year compared to the previous year is most likely a very sharp fall in prices. This decline in oil prices has so far been much more dramatic than the two previous crisis episodes the Russian economy has experienced under Putin as president or prime minister.

Figure 1. Oil price developments in recent crises

Note: This graph is based on the European Brent spot price FOB published by the U.S. Energy Information Administration and the axis shows trading days, so that the graph covers the period from January 1 to March 30. Different qualities of oil of course have different prices, but the patterns shown here are similar for other oil prices as well.

Exchange Rate and Stock Market

As in previous crises, the Russian stock market and exchange rate are following the evolution of oil prices. However, neither the stock market, nor the exchange rate has fallen as rapidly as oil prices. This can be due to many factors, but one likely explanation is that investors think that the decline in oil prices will not last for as long as it has in past crises. Whether this assumption is correct remains to be seen of course, but if oil prices stay low for an extended period, we can expect to see further declines in both the exchange rate and stock market.

Figure 2. Oil prices, exchange rate and stock market

Sources: Oil prices as in Figure 1, the exchange rate from Central Bank of Russia, RTS index from Moscow Stock Exchange.

The fact that the exchange rate this time has “only” depreciated by 20 percent when oil prices have fallen by 70-80 percent means that the oil price measured in rubles has fallen much more dramatically in this crisis compared to the previous ones. In the 2008/09 global financial crisis, the oil price in ruble terms was, in the end, unchanged compared to the start of the crisis. In 2014/15 this was not the case, but the decline in the ruble oil price was a more modest 25 percent compared to the 60 percent drop right now. This has serious implications for the government’s budget which is ruble-based and highly dependent on oil revenues.

Economic Policy

The Russian government now has plenty of experience in dealing with crises. The first lesson after the crisis at the end of the 90s was to have enough fiscal resources to deal with a crisis without having to go to the IMF again. The second lesson came in the global financial crisis when the fixed exchange rate had to be abandoned to avoid depleting the central bank’s international reserves. A prudent fiscal policy backed by the National Wealth Fund and a flexible exchange rate is still the backbone of the macroeconomic policies that can help mitigate the impact of lower oil prices.

The central bank is pursuing inflation targeting and uses a 4 percent inflation rate as the target that guides its policy decisions. The main tool is setting the key interest rate at a rate that will achieve the inflation target. The key interest rate is currently 6 percent, significantly down from the high of 17 percent in January 2015. The central bank states clearly in its monetary policy documents that “Monetary policy lays the groundwork for economic development; however, it cannot be a source of a sustainable rise in economic potential” (see page 6 in Central Bank of Russia, 2020). This implies that the central bank will only lower the key interest rate if inflation falls, not to support growth or try to achieve other, potentially conflicting goals. This is good news for macroeconomic stability but may become an issue of political tension if there is a serious downturn in the economy while inflation remains higher than the target rate.

In mid-2019, the National Wealth Fund was doubled and went from $60 billion to just over $120 billion (Ministry of Finance, 2020). This was done as a one-off transfer of surplus funds from the government’s budget. However, at its peak in the global financial crisis, the combined reserve fund and wealth fund that existed then had assets of over $220 billion but by the start of 2011, the assets were down to $111 billion. In other words, a year and a half into that crisis episode, the government had used an amount from the funds that roughly corresponds to the total amount available in the National Wealth Fund today. The fiscal space is, therefore, less impressive than it may look at a first glace and just burning through the cash in the National Wealth Fund is not a sustainable fiscal policy if this crisis continues a few more months.

Instead, the government will have to plan other measures as soon as the most immediate spending to deal with the crisis is done. This will entail difficult trade-offs since the health system will need increased resources at the same time as households and companies will need support to mitigate the impact from lost jobs and closed businesses in the wake of corona-induced shut-downs rather than the decline in oil prices, so adding to the pressure coming from declining oil prices. Increasing taxes in a time of already depressed purchasing power and profits is also not an appealing option and although there are still tax increases in the pipeline, the government has announced that these will not come in effect this year. Like in many other countries, the Russian government is proposing several measures to support the economy that will be discussed in more detail in a forthcoming FREE policy brief. However, these measures will add to the costs of the government at a time of falling revenues. From an economic perspective, reallocating resources from the military and security sectors to other parts of the economy seems like an obvious choice under these circumstances, but most likely not the outcome of this process given the government’s geopolitical and domestic power ambitions. Again, the fiscal reserves will allow postponing these harder decisions, but if the crisis goes on for some time, alternative measures such as borrowing domestically or internationally will most certainly be discussed also in Russia. However, many governments will be in need of borrowing on international markets going forward and the rates required to access this type of funding may not be very attractive and still force domestic budget reallocations.

Growth Impact of the Oil Price Fall

It is of course too early in the crisis to make very precise forecasts on how the economy will fare in 2020. This will in the end crucially depend on how the Covid-19 pandemic develops and on government responses to the crisis not only in Russia but also in the rest of the world. A partial analysis of the impact of falling oil prices can however be done with the models presented in Becker (2016a) which link changes in oil prices to growth. This paper shows a few alternative specifications that differ in the GDP measure being in dollars or real rubles, and in some other dimensions. All specifications are highly statistically significant and able to explain between 60 and 90 percent of variations in GDP growth in the period 2000-2015. Focusing on the relationship between the percentage change in oil prices and growth in real ruble GDP, the estimated coefficient is 0.14. This implies that for every 10-percentage point drop of oil prices, GDP growth goes down by 1.4 percent. Currently, oil prices have declined by 75 percent since the beginning of the year. However, the model estimates are based on comparing how average oil prices change between years so this is the numbers we need to compute and compare. The average price of Brent oil (which is used in this model) was $64/barrel in 2019 but we obviously do not know what the average oil price will be this year. We therefore need to first “forecast” oil prices for the rest of the year before we can compute the impact on growth. If we make the simple assumption that oil prices stay at the current level and take into account that they were significantly higher the first couple of months this year, the average price would end up being $25/barrel. That would amount to a 60 percent decline in average oil prices between 2019 and 2020. The partial effect of this oil price decline would therefore make Russian real GDP drop by 8.5 percent in 2020. Again, this is the partial effect based on the estimated coefficient in a linear relationship between oil price changes and real GDP growth. In plainer English, we are not looking at the first order effect of closing stores etc. to avoid the virus from spreading but only the additional effect that we think will come from falling oil prices. In addition, the effect this massive decline in oil prices is assumed to have on GDP is derived by a coefficient that is estimated on smaller changes in oil prices and real GDP. Nevertheless, this exercise provides a first, and rather daunting, assessment of what can happen to GDP given the decline in oil prices alone.

Concluding Remarks with OPEC and IEA update

This brief has provided a first assessment of how the Russian economy may be impacted by the massive decline in oil prices that has followed in the course of the corona pandemic. It has shown that the economic downturn this time can be significantly worse than both the 2008/09 and the 2014/15 crises. A base line estimate suggests that GDP may fall by more than 8 percent only because of the fall in oil prices. The above calculation obviously includes neither the impact the health situation will have on companies or households, nor the government’s ability to mitigate the negative consequences. If the other problems the economy is facing as a direct result of the health crisis also lead to a significant decline in supply and demand, Russia could easily see real GDP declining by more than 10 percent in 2020.

Our estimate is an important reminder that Russia’s continued oil dependency is a risk to the economy and its citizens. Now is not the time for ambitious structural and institutional changes to generate growth, but hopefully the urgent crisis period passes without policy makers forgetting the risks the country’s oil dependence entails. They learnt the fiscal and monetary lessons well from past crises, now is the time to learn something new. The most appealing road to sustainable economic growth is still building credible property rights institutions and rule of law in a framework that would make Russia the innovative business-oriented superpower it could be.

A few days after the first version of this brief was published, oil prices started to rise as the OPEC together with Russia started discussions to cut production to support oil prices. A tentative agreement was reached which is supposed to cut production by 10 million barrels per day in May and June, the largest cut in OPEC’s history. Had this movements in prices continued, the forecast for the Russian economy would have been affected. However, this recovery in prices was soon reversed and oil prices started to fall again. The decline continued on April 15 as the International Energy Agency presented a dire forecast of oil demand and stated that this year may be the worst year ever in terms of declining demand. All in all, the price movements that have followed the OPEC meeting and the statements of the IEA do not change the baseline prediction this brief has provided.

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. This brief was first published on April 6, 2020 and then revised on April 15, 2020.

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

Posted on March 16, 2020 | Policy Brief

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

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

Introduction and Approach to Measuring the Shadow Economy

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

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

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

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

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

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

Size of the Shadow Economy in Russia and Nearby Countries

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

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

Components and Determinants of the Shadow Economy in Russia

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

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

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

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

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

Acknowledgments

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

References

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

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

A Decade of Russian Cross-Domain Coercion Towards Ukraine: Letting the Data Speak

Posted on February 17, 2020 | Policy Brief

20200217 A Decade of Russian Cross-Domain Coercion FREE Network Policy Brief Image 01

Russia’s coercion towards Ukraine has been a topic of major international events, meetings and conferences. It regularly makes the headlines of influential news outlets. But the question remains open – do we really understand it? We diligently collect and analyze data to make informed decisions in practically all domestic issues but is the same done for international relations? This research paper introduces a number of tools and methods that could be used to study Russia’s coercion towards Ukraine beyond its most visible manifestation, looking into latent trends and relations that could reveal more.

Introduction

For the past decade, Ukraine has been in the headlines of the major world news outlets more frequently than ever before. Ukrainian-Russian relations have been and still remain the topic of international summits and other events. The occupation of a part of Ukraine’s territory has been denounced and Russia’s coercion towards Ukraine is now generally accepted as a fact. But what do we really know about the underlying empirics and dynamics and how can this multi-domain assertiveness be measured and tracked? This paper presents a number of data-driven approaches that allow looking beyond the headline stories to identify and track various dimensions of Russia’s coercion towards Ukraine and the dynamics of its development.

Academic Interest

Mapping the landscape of scholarly literature reveals a number of interesting results. First, the body of works studying Russia’s coercion towards Ukraine remains relatively modest. It quintupled in 2014 but afterwards the interest started tapering off. A search for papers on this topic in Scopus and Web of Science with a very precise query (to increase the accuracy of search) and publication time of 2009-2019 returned 155 papers most of which were published in or after 2014.

Figure 1. Scholarly publications on Russian-Ukrainian relations.

Source: WoS and Scopus, 2009-2019

A closer look at the content of these works with the use of a bibliometric software called CiteSpace shows that the majority of papers focus on Putin, once again emphasizing the significant role of his personality in Russia’s coercion towards Ukraine. The second largest cluster has the “great power identity” as its main theme and presumably looks beyond actions of Russia to identify its ideological grounds. Another group of publications is devoted to sanctions, pointing to their important role in studying Russian-Ukrainian relations.

Figure 2. The landscape of topics in scholarly publications on Russian-Ukrainian Relations.

Expressions of Coercion

The “practical” side of Russia’s coercion towards Ukraine is also frequently associated with the personality of Vladimir Putin and his attitudes towards Ukraine. To analyze this perception further, we created a corpus of speeches of Russian presidents published on the Kremlin website, filtered them to keep only those that mention Ukraine, divided them into pre-2014 and 2014 and after, and then analyzed them using an LDA topic modeling algorithm. This algorithm is based on the assumption that documents on similar topics use similar words. So, the latent topics that a certain document covers can be identified on the basis of probability distributions over words. Each document covers a number of topics that are derived by analyzing the words that are used in it. In simple terms, the model assigns each word from the document a probabilistic score of the most probable topic that this word could belong to and then groups the documents accordingly.

Figure 3. Speeches of Russian presidents before 2014, LDA topic modeling.

Figure 4. Speeches of Russian presidents in 2014 and after, LDA topic modeling.

Quite surprisingly, we discovered that the overall rhetoric of speeches is very similar for the two periods. Although some speeches do differ and the later corpus includes new vocabulary to reflect some changes (i.e “Crimea”, “war”) the most common words remain practically the same. Thus, regardless of the apparent shift in relations between the two countries, Russian leadership still relies on the same notions of collaboration, interaction, joint activities, etc. The narrative of “brotherhood” between the nations persists despite and beyond the obvious narrative of conflict.

To include a broader circle of Russia’s leadership we also looked at the surveys of the Russian elite conducted regularly by a group of researchers led by William Zimmerman and supported by various funders over the years (in 2016 – the National Science Foundation and the Arthur Levitt Public Affairs Center at Hamilton College). Seven waves of the survey already took place; the most recent one in 2016. The respondents were the representatives of several elite groups (government, including executive and legislative branches, security institutions, such as federal security service, army, militia, private business and state-owned enterprises, media, science and education; for practical reasons from Moscow only).

The survey revealed a number of interesting observations. For instance, while the prevailing Russian opinion on Russia’s occupation of Crimea had been that it was not a violation of international law, a closer look at the demographic characteristics of respondents shows that they were not as coherent as it might seem from the outside. While the “green” answers from respondents with backgrounds such as media or private business may have been anticipated, the number of members of the legislative and especially executive branch and the military that had at least some doubt on the legality was surprisingly quite sizable, and they even demonstrated some support of the “violation of law” interpretation.

Figure 5. Elite and public opinion on Russia’s annexation of Crimea.

Comparing these elite opinions to the public opinion poll by Levada Center conducted in the same year shows that even the general public is slightly more likely to choose the most extreme “full legality” option than the respondents from the executive branch.

Beyond the elite or general opinion polls, we tried to develop a metric that might allow us to track Russian sensitivities towards Ukraine. For that, we examined two different ways of expressing “in Ukraine” in Russian language: ‘на Украине’ (the ‘official’ Russian expression) vs. ‘в Украине’ (the version preferred by Ukrainians). [In English, this can be compared so saying ‘Ukraine’ vs ‘the Ukraine’.]

Our first visual plots how many search queries were done on Google Search with both versions over the last decade.

Figure 6. Search queries for “в Украине” (green) versus “на Украине” (red), Google Trends, 2009-2019.

We can clearly observe that during less turbulent times the more politically sensitive version is much more common. This however drastically changes during the peaks of Russia’s coercion towards Ukraine when the number of searches with the less politically correct term increases significantly.

A different trend can be observed if we look at official media publications stored in the Factiva database. We estimated the ratio of search volumes for each term and observed that until the beginning of 2013, about a third of articles and news reports used “in Ukraine”. This changed around January 2013 when the ratio starts to decrease for “in Ukraine” searches and plummets to a mere 10% of outlets still preferring this term.

Figure 7. The ratio of “в Украине” to “на Украине” occurrences in large Russia media (2009 – 2019), Factiva.

Tracking Coercion Itself

What is the track record of Russia’s actual coercion over this decade? For this, we turn to a few recent datasets that try to systematically capture verbal and material actions (words and deeds): the automated event datasets. The largest one of those, called GDELT (Global Database of Events, Language, and Tone), covers the period from 1979 to the present, and contains over three quarters of a billion events. It is updated every fifteen minutes to include all “events” reported in the world’s various news outlets. To exclude multiple mentions of the same event by one newswire, the events are “internally” deduplicated. The events are not compared across newswires.

An event consists of a “triple” coded automatically to represent the actor (who?), the action (what?) and the target (to whom?) as well as a number of other parameters such as type (verbal or material; conflict or cooperation; diplomatic, informational, security, military, economic), degree of conflict vs cooperation etc. Other similar datasets include ICEWS (Integrated Crisis Early Warning System) and TERRIER (Temporally Extended, Regular, Reproducible International Events Records). For this analysis, we filtered out only those events in which Russia was the source actor and Ukraine was the target country. We present two metrics: (1) the percentage of all world events that this subset of events represents and (2) the monthly averages of the Goldstein score, which captures the degree of cooperation or conflict of an event and can take a value from -10 (most conflict) to +10 (most cooperation). Also, to add a broader temporal perspective, we looked beyond the last decade. It can be clearly seen that the number of events before 2013 was significantly lower, especially in “material” domains. Some verbal assertions from Russia towards Ukraine happened during the Orange Revolution and so-called “gas wars”.

The situation changes radically starting from 2013. The proportion of events increases with some especially evident peaks (i.e. during the occupation of Crimea). The verbal events remain quite neutral while the actions towards Ukraine move from some fluctuations to steadily conflictual.

Figure 8. Russia’s negative assertiveness towards Ukraine, 2000-2019.

Measuring Influence

We have seen that the past decade was exceptional in the scale of Russian assertiveness towards Ukraine. But what do we know about Russia’s influence on Ukraine and Ukraine’s dependence on Russia? Influence measures the capacity of one actor to change the behavior of the other actor in a desired direction. In an international context this often concerns the relations between countries. Influence can be achieved by various means, one of which is to increase the dependence of the target country upon the coercive one. This strategy is frequently employed by Russia willing to regain and/or increase control over the former post-Soviet countries. The Formal Bilateral Influence Capacity (FBIC) Index developed by Frederick S. Pardee (Center for International Future) looks at several diplomatic (i.e. intergovernmental membership), economic (trade, aid) and security (military alliances, arms import) indicators allowing to identify the level of dependence of one country upon another. This is especially interesting from a comparative perspective. Figure 9 shows that countries such as Armenia and Belarus remain highly dependent on Russia. For half of the decade, Ukraine was number three on this list. Today the situation has changed. Ukraine’s dependence on Russia has gradually decreased and has become even smaller than Moldova’s, moving closer to the steadily low level of dependence of Georgia. This may signify a positive trend and a break of a decade-long relationship of dependence.

Figure 9. Dependence of post-Soviet countries on Russia, FBIC.

Conclusion

Consequently, Russia and Ukraine have become much more visible in the international academic and policy research efforts. This can be measured through a number of instruments, including a comprehensive mapping of the academic landscape itself with regard to salience and topics that are being studied, analysis of the word choice (that could be represented by the use of the terms to describe events in Ukraine by the government media and Google search users (“на Украине” versus “в Украине”); speeches of Russian presidents that use the same rhetoric of collaboration when talking about Ukraine despite the obvious change in relationships) and material coercion (significant increase in number of assertive conflictual Russia’s actions towards Ukraine). Some findings do give hope for change: the opinions of the Russian elite on recent Russian actions towards Ukraine while remaining generally unfavourable are not as cohesive as it might appear and Ukraine’s dependence on Russia has decreased significantly.

Disclaimer

This research is a part of a larger research effort titled RuBase funded by the Carnegie Foundation of New York and implemented jointly by The Hague Centre for Strategic Studies and Georgia Tech with the help of the Kyiv School of Economics StratBase team in Ukraine. The ‘Ru’ part of the title stands for Russia; and ‘base’ has a double meaning – both the knowledge base built during the project, and the (aspirationally) foundational nature of this effort. The project intends to look beyond the often-shallow traditional understanding of coercion and apply innovative tools and instruments to study coercion in its multifaceted form. This is only a small selection of the tools that have been successfully tested in the course of this (ongoing) research project and applied to the study of Russia’s coercion in different domains. The prospects of any progress in resolving the Russian-Ukrainian conflict are currently slim, thus further work that would allow identifying patterns and trends that the human eye may oversee to understand Russia better and develop an informed foreign policy strategy both for Ukraine and the West is crucially important.

References

The Political Economics of Long Run Development in Eastern Europe: Insights from the 2019 SITE Academic Conference

Posted on January 20, 2020 | Policy Brief

Roller coaster photographed from below symbolising Eastern Europe transition

Thirty years after the fall of communism, many assume that the economic transition of Eastern Europe and the former Soviet States towards a system of market economy is complete. But the region faces new challenges, of both economic and political kind, which renders a thorough understanding the past even more important. This policy brief is based on the scientific contributions presented at the 7th SITE Academic Conference held at the Stockholm School of Economics from December 16th to December 17th, 2019. Organized by the Stockholm Institute of Transition Economics (SITE), the conference brought together academics from all over Europe and the United States to share and discuss their research on economic and political development in Eastern Europe.

The Imperial and Soviet Periods

In the first section of the conference, papers with a focus on the long-term history of Eastern Europe and its implications for more recent events were presented. Marvin Suesse presented his research on how the Russian State Bank financed Tsarist Russia´s belated industrialization, a question that had been discussed by historians, but never thoroughly analyzed quantitatively. By geo-coding historical manufacturing censuses around the turn of the century and using distance between bank branches and factory location, the causal impact of the expansion of the State Bank is estimated, revealing large effects on firm revenues and productivity. These effects are largest in areas where alternative means of financing were least available and where human capital was more abundant.

Natalya Naumenko presented her findings on the economic consequences of the 1933 Soviet famine, which in terms of casualties was extremely devastating. She uses the meteorological conditions a year earlier as an instrumental variable and finds that the famine, which was mostly a rural phenomenon, had a persistent negative effect on the urban population while the rural population recovered relatively quickly.

Gerhard Toews discussed the long-term consequences on regional development of the displacement of an estimated 3 million “enemies of the people”, political prisoners typically belonging to the elite of the society, into the gulags in the early years of the Soviet Union. Using archival data, he has constructed a large database describing the gulag population in terms of the shares of “enemies” relative to other prisoners and taking into account their socio-economic characteristics i.e. the much higher levels of education of the former group. Exploiting variation within gulags, the results suggest that a historically higher density of “enemies” means higher economic prosperity today as measured by nightlight intensity.

Taking another angle, Christian Ochsner investigated the effects of the Red Army´s occupation on post-war Europe, using the demarcation line crossing the Austrian state of Styria as a natural experiment. His conclusion is that even the temporary occupation affected the region’s long-term development, the main channel being age-specific migration.

Finally, Andreas Stegman offered an analysis of the effects of the 1972 East German Extended Visitors Program. The program reduced travel restrictions for West German visitors traveling to certain districts of East Germany. Using a geographic regression discontinuity design comparing similar districts with and without the program, he shows that included districts indeed received much more visits from West Germany and that their citizens were more likely to protest against the Communist government and less likely to vote for the ruling party. This suggests that face-to-face interaction can influence beliefs and attitudes in non-democratic regimes, in turn influencing individual behavior and societal outcomes during transition.

Corruption, Conflict and Public Institutions

Another topic of the conference was the current role of corruption, conflict, electoral fraud and public sector effectiveness for the region. Scott Gehlbach presented his most recent research on the ownership patterns and strategies of Ukrainian oligarchs before and after the Orange revolution. By mapping oligarchs to changing political leadership, he shows how firm owners in Ukraine take actions to protect their property depending on their connections with the current government. He finds that obfuscation of ownership behind holding companies and complicated structures is a potentially valuable strategy in this environment in general but becomes particularly important when an oligarch loses direct connections to the ruling regime.

Likewise, Timothy Frye analyzed election subversion by employers in Russia, Argentina, Venezuela, Turkey and Nigeria. He finds that in Russia, public sector employers and especially state-owned firms are more likely to influence their employees’ decision to vote than private companies. Furthermore, work place mobilization by employers in Russia is clearly negatively associated with the freedom of the press. Election subversion is more likely to be successful when the degree of dependence of the employee is high and the employer’s potential threats are credible. Among Russian firm officials, the most frequently named motivations for them to practice election subversion are the desire to improve their relationship with the authority and the intention to help their party.

Michal Myck studied the impact of the transition experience on economic development around the Polish-German border. Polish communities close to the border were economically backward at the beginning of the transition but could potentially benefit from trade opportunities with an opening towards the West. Using similar methods to those of Stegman above, and nightlight intensity as a measure of economic activity as for instance Toews, Myck finds significant evidence for economic convergence both between Germany and Poland, and between Polish border regions and the rest of Poland.

Vasily Korovkin presented his research on the impact of the conflict in Eastern Ukraine on trade in non-conflict areas in Ukraine, hypothesizing that the conflict may cause a trade diversion away from Russia, particularly so in areas with many ethnic Ukrainians. Using variation in the share of the Russian speaking population at the county level as well as detailed firm level export and import data, he finds that the decrease in trade with Russia is negatively correlated with the share of the Russian speaking population. Potential mechanisms include a decline in trust at the firm level and changes in local attitudes including consumer boycotts.

Finally, Tetyana Tyshchuk analyzed the effects of a Ukrainian public sector reform on civil servants’ capacity and autonomy. The reform created public policy directorates parallel to the regular bureaucracy in 10 ministries. Members of the directorates were hired based on a different procedure and different merits relative to regular public servants and received significantly higher salaries.  Tyshchuk finds that the better paid civil servants indeed score higher on many, though not all, indicators of capacity and autonomy.

Information, Populism and Authoritarianism Today

The final important theme of the conference was the role of information and media, old and new, in today’s politics. In the event´s first keynote speech, Ruben Enikolopov analyzed the political effects of the Internet and social media whose low entry barriers and reliance on user-generated content make them decisively different from traditional media channels. On the one hand, this represents a chance for opposition leaders and whistleblowers to make their voice heard and may improve government accountability. On the other, these media may also become a platform for extremists. Enikolopov presented some of his work analyzing to what extent social media has contributed to fighting corruption in Russia. Using the timings of blog posts by the famous Russian opposition leader Alexei Navalny on corporate governance violations in state-owned companies, he shows that revelations resulted in an immediate drop in the price of the traded shares of the respective companies. He also finds evidence suggesting that Navalny´s blog posts resulted in management changes in these companies. In related papers, he exploits the spread of VKontakte (VK), the Russian version of Facebook, to better understand the influence of social networks on political activism, voting and the occurrence of hate crime. He finds that the spread of VK is indeed causally related to political protests, though not because it nurtures opposition to the government, but rather because it facilitates protest co-ordination. With respect to hate crime, he finds that social media only has an effect in areas where it falls on fertile grounds and where there already are high levels of nationalism. The tentative conclusion is that in Russia – as in Western countries – social media seems to have increased political polarization.

On a similar topic but taking a more theoretical approach, Galina Zudenkova investigated the link between information and communication technologies (ICT), regime contestation and censorship. In a game theoretical framework, where citizens use ICT both to learn about the  competency of the government and to coordinate protests, governments can use different tools to censor information to increase their chances of survival. Zudenkova finds that less competent regimes are more likely to censor coordination, whereas intermediate regimes are more likely to focus on censoring content. These theoretical predictions are then tested using country level data.

The targeted use of information has also played a key role in Putin’s Russia according to Daniel Treisman. In his keynote speech, he argued that while the 20th century dictatorships were mainly based on violence and ideology, the 21st century has been characterized by a sizeable shift towards what he calls “informational autocracy”. Constructing a dataset on the methods used by authoritarian regimes to maintain power between 1946 and 2015, he shows that the use of torture and violence peaked among those dictators who took power in the 1980s and has declined since. Furthermore, he highlights a remarkable shift from topics of violence towards topics of economic competency in dictators’ speeches. However, Treisman finds that by instrumentalizing information, dictators fool the public “but not the elite”. In democratic regimes, those with tertiary education tend to rate their political leaders higher than people without tertiary education. In the new informational authoritarian regime, the opposite seems to be the case. According to Treisman, this is because the “informed elite” has a better understanding of the political reality in places where the media is censored, Putin’s Russia being a good example. Treisman concluded that this new model of authoritarianism has become the prevalent model outside of Europe and today also has its advocates inside the European Union.

The conference ended with a final keynote speech by Sergei Guriev on the political economy of populism. Using existing definitions, he first confirmed that Europe has seen a rise in right-wing populism in the last 20 years. Secular trends, such as globalization and new communication technology, but also the recent global financial crisis, are driving factors behind the rise of populist parties. For instance, analyzing regional variation in voting patterns suggests that the Brexit vote was primarily driven by economic motives rather than by anti-immigrant sentiments. Ironically, though, most evidence suggests that populist governments have a below-average economic performance once in office, the US and Poland being notable exceptions. A key point of Guriev’s presentation was that populism seems to be a good method to obtain power, but, once in power, populists tend to be less successful in promoting citizen welfare. These findings seem to be of high importance given the increasing public support for populist parties around the world and in parts of Eastern Europe

The conference was very well received and on behalf of SITE, the authors would like to express their appreciation to all speakers and participants for sharing their knowledge and to Riksbankens Jubileumsfond for financial support. For those interested to learn more about the papers summarized very briefly above, please visit the conference website and the presenters’ websites as indicated in the text and here below.

Speakers at the Conference

Andreas Stegman, briq – Institute on Behavior and Inequality

Christian Ochsner, CERGE-EI and University of Zurich

Daniel Treisman, University of California, Los Angeles

Galina Zudenkova, TU Dortmund University

Gerhard Toews, New Economic School Moscow

Marvin Suesse, Trinity College

Michal Myck, CenEA

Natalya Naumenko, George Mason University

Ruben Enikolopov, New Economic School Moscow

Scott Gehlbach, University of Chicago

Sergei Guriev, Sciences Po Paris

Tetyana Tyshchuk, Kyiv School of Economics

Timothy Frye, Columbia University

Vasily Korovkin, CERGE-EI

The Long Shadow of Transition: The State of Democracy in Eastern Europe

Posted on November 25, 2019 | Policy Brief

Dark hill on the right side of the image with a shadow of a man holding his bicycle on the right side

In many parts of Eastern Europe, the transition towards stronger political institutions and democratic deepening has been slow and uneven. Weak political checks and balances, corruption and authoritarianism have threatened democracy, economic and social development and adversely impacted peace and stability in Europe at large. This policy brief summarizes the insights from Development Day 2019, a full-day conference organized by SITE at the Stockholm School of Economics on November 12th. The presentations were centred around the current political and business climate in the Eastern European region, throwing light on new developments in the past few years, strides towards and away from democracy, and the challenges as well as possible policy solutions emanating from those.

The State of Democracy in the Region

From a regional perspective, Eastern Europe has seen mixed democratic success over the years with hybrid systems that combine some elements of democracy and autocracy. Based on the V-Dem liberal democracy index, ten transition countries that have joined the EU saw rapid early progress after transition. In comparison, the democratic development in twelve nations of the FSU still outside of the EU has been largely stagnant.

In recent years, however, democracy in some of those EU countries, such as Bulgaria, the Czech Republic, Hungary, Poland and Romania have been in decline. Poland, one of the region’s top performers in terms of GDP growth and life expectancy, has experienced a sharp decline in democracy since 2015. Backlashes have often occurred after elections in which corruption and economic mismanagement have led to the downfall of incumbent governments and a general distrust of the political system. Together with low voter turnout, this created fertile ground for more autocratic forces to gain power helped by demand for strong leadership.

An example from Ukraine illustrated the role of media, both traditional and social, for policy-making. In some countries of the region, traditional media is strictly state-controlled with obvious concerns for democracy. This is less the case in Ukraine, where also social media plays an important role in forming political opinions. The concern is that, as elsewhere, opinions that gain traction on social media may not be impartial or well informed, affecting public perception about policy-making. A recent case showing the popular reaction to an attack on the former governor of the Central Bank suggests that those implementing important reforms may not get due credit when biased and partial information dominates the political discourse on social media.

Another case is the South Caucasian region: Armenia, Georgia and Azerbaijan. The political situation there has been characterized as a “government by day, government by night” dichotomy, implying that the real political power largely lies outside the official political institutions. In Georgia, the situation can be described as a competition between autocracy and democracy, with a feudalistic system in which powerful groups replace one another across time. As a result, trust in political institutions is low, as well as citizens’ political participation.

In the case of Azerbaijan, there is an elected presidency, but in reality, power has been passed on hereditarily, becoming a de facto patrimonial system. Lastly, in Armenia, the new government possesses democratic credentials, but the tensions with neighbouring Azerbaijan and Turkey have given increasing power to the military and important economic powers. Overall, democratisation in these countries has been hindered by a trend for powerful politicians to form parties around themselves and to retain power after the end of their mandates. Also, the historical focus on nation-building in these countries has led to a marked exclusion of minorities and a conflict of national identities.

The last country case in this part of the conference focused on the current political situation in Russia and on the likely outcomes after 2024. The social framework in Russia appears constellated by fears – a fear of a world war, of regime tightening and mass repressions, and of lawlessness – all of them on the rise. Similarly, the economy is suffering, in particular from low business activity, somewhat offset by a boost in social payments. Nonetheless, it was argued that it is not economic concerns, but rather political frustration, that has recently led citizens to take to the street. Despite this, survey data shows that trust in Putin is still over 60%, and that most people would vote for him again. However, survey data also points out that the most likely determinant of this trust is the lack of another reference figure, and that citizens are not averse to the idea of political change in itself. Lastly, Putin will most likely retain some political power after 2024, transiting “from father to grandfather of the nation”.

Voices from the civil society in the region also emphasized the importance of a free media and an active civil society to prevent the backsliding of democracy. With examples from Georgia and Ukraine, it was argued that maintaining the independence of the judiciary, as well as the public prosecutor’s office, can go a long way in building credibility both among citizens and the international community. The European Union can leverage the high trust and hopeful attitudes it benefits from in the region to push crucial reforms more strongly. For example, more than 70% of Georgians would vote for joining the EU if a referendum was held on the topic and the European Union is widely regarded as Georgia’s most important foreign supporter.

Weak Institutions and Business Development

The quality of political and legal institutions strongly affects the business environment, in particular with regards to the protection of property rights, rule of law, regulation and corruption. Research from the European Bank for Reconstruction and Development (EBRD) highlights that the governance gap between Eastern Europe and Central Asia and most advanced economies is still large, even though progress in this area has actually been faster than for other emerging economies since the mid-‘90s. This is measured through enterprise surveys as well as individual surveys. In Albania, for instance, a perception of lower corruption was linked to a decrease in the intention to emigrate equivalent to earning 400$ more per month. Another point concerned the complexity of measuring the business environment and the benefits of firm-level surveys asking firms directly about their own actual experience of regular enforcement. For example, in countries such as Poland, Latvia and Romania the actual experience of business regulation measured via the EBRD’s Business Environment Enterprise Performance Survey, is far worse than one would expect from the World Bank’s well known Doing Business rating.

From the perspective of Swedish firms, trade between Sweden and the region has remained rather flat in the past years, as the complexity and risks of these markets especially discourage SMEs. Business Sweden explained that Swedish firms considering an expansion in these markets are concerned with issues of exchange rate stability, and the institutional-driven presence of unfair competition and of excessive bureaucracy. Moreover, inadequate infrastructure and the presence of bribery and corruption make everyday business operations risky and costly. It was generally emphasized that countries have to create a safe investment environment by reducing corruption, establishing a clear and well enacted regulatory environment, having dependable courts and strengthening domestic resource mobilization. Swedish aid can play a part, but there is a need to develop new ways of delivering aid to make it more effective.

An interesting example is Belarus, that has seen more economic and political stability than most neighbours, but at the same time a lack of both economic and political reforms towards market economy and democracy. Gradually the preference towards private ownership, as opposed to public, has increased in recent years and the country has seen a rising share of the private sector, even without specific privatization reforms. Nonetheless, international businesses are still reluctant to invest due to high taxes, a lack of access to finance as well as to a qualified workforce, but most importantly due to the weak legal system. An exception has been China, and Belarus has looked at the One Belt One Road Initiative as a promising bridge to the EU. Scandals connected with the two main Chinese-invested projects have damped the enthusiasm recently, though.

The economic and political risks of extensively relying on badly diversified energy sources, as is the case with natural gas imports from Russia in many transition states were also discussed. It was shown how some countries such as Ukraine, Poland and Lithuania have improved their energy security by either benefitting from reverse-flow technology and the EU’s bargaining power or building their own LNG terminals to diversify supply sources. However, either of these, as well as other energy security improving solutions are likely to come with an economic cost, though, that not all countries in the region can afford.

A Government Perspective

The main focus of this section was the Swedish government’s new inspiring foreign policy initiative, “Drive for Democracy”. Drawing from a definition of democracy by Kerstin Hesselgren, an early Swedish female parliamentarian, democracy enables countries to realize and utilize the forces of the individual and draw them into a life-giving, value-creating society. It was emphasized that the values of democracy are objectives by themselves (e.g. freedom of expression, respect for human rights) but also that democracy has important positive effects in other areas of human welfare. The Swedish government views democracy as the best foundation for a sustainable society, equality of opportunity and absence of gender or racial bias.

The “Drive for Democracy” specifically identifies Eastern Europe as one of the main frontiers between democracy and autocracy, and the Swedish government promotes human rights and stability through various bilateral programmes through the Swedish International Development Cooperation Agency, Sida, and multilateral initiatives within the EU, such as the Eastern Partnership. It was also emphasized that democracy is a continuous process that can always be improved, as indeed experienced by Sweden. Political rights were granted to women only in 1919 followed by convicts and prisoners in 1933 and to the Roma people only in 1950. Political and democratic rights are thus never once and for all given, and it is crucial that the dividends from democracy are carried forward to the younger generation.

Conclusion

In sum, the day illustrated clearly how democracy engages all segments of society, from the business sector to civil society, and the potential for but also challenges involved for democratic deepening in Eastern Europe. To get more information about the presentations during the day, please visit our website.

Participants at the Conference

  • PER OLSSON FRIDH, State Secretary, Ministry for Foreign Affairs.
  • ALEXANDER PLEKHANOV, Director for Transition Impact and Global Economics at EBRD.
  • TORBJÖRN BECKER, Director, SITE.
  • CHLOÉ LE COQ, Associate Professor, SITE and Professor of Economics, University of Paris II Panthéon-Assas.
  • THOMAS DE WAAL, Senior Fellow at Carnegie Endowment for International Peace.
  • NATALIIA SHAPOVAL, Vice President for Policy Research at Kyiv School of Economics.
  • ILONA SOLOGUB, Scientific Editor at VoxUkraine and Director for Policy Research at Kyiv School of Economics.
  • KETEVAN VASHAKIDZE, President at Europe Foundation, Georgia.
  • MARIA BISTER, Senior Policy Specialist, Sida.
  • HENRIK NORBERG, Deputy Director, Ministry for Foreign Affairs.
  • YLVA BERG, CEO and President, Business Sweden.
  • LARS ANELL, Ambassador and formerly Volvo’s Senior Vice President.
  • ERIK BERGLÖF, Professor in Practice and Director of the Institute of Global Affairs, London School of Economics and Political Science.
  • KATERYNA BORNUKOVA, Academic Director, BEROC, Minsk.
  • ANDREI KOLESNIKOV, Senior Fellow, Carnegie Moscow Center.

Liberal Democracy in Transition – The First 30 Years

Posted on October 28, 2019 | Policy Brief

20191027 Liberal Democracy in Transition FREE Network Policy Brief Image 07

This year marks 30 years since the first post-communist election in Poland and the fall of the Berlin Wall. Key events that started a dramatic transition process from totalitarian regimes towards liberal democracy in many countries. This brief presents stylized facts from this process together with some thoughts on how to get this process back on a positive track. In general, the transition countries that joined the EU are still far ahead of the other transition countries in terms of democratic development.

The recent decline in democratic indicators in some EU countries should be taken seriously as they involve reducing freedom of expression and removing constraints on the executive, but should also be discussed in light of the significant progress transition countries entering the EU have shown during the first 30 years of transition. The brief shows that changes in a democracy can happen fast and most often happen around elections, so getting voters engaged in the democratic process is crucially important. This requires politicians that engage the electorate and have an interest in preserving democratic institutions. An important question in the region is what the EU can do to promote this, given its overloaded political agenda. Perhaps it is time for a Greta for democracy to wake up the young and shake up the old.

This brief provides an overview of political developments in transition countries since the first post-communist elections in Poland and the fall of the Berlin Wall 30 years ago. It focuses on establishing stylized facts based on quantitative indices of democracy for a large set of transition countries rather than providing in-depth studies of a small number of countries. The aim of the brief is thus to find common patterns across countries that can inform today’s policy discussion on democracy in the region and inspire future studies of the forces driving democracy in individual transition countries.

The first issue to address is what data to use to establish stylized facts of democratic development in the region. By now, there are several interesting indicators that describe various aspects of democratic development, which are produced by different organizations, academic institutions and private data providers. In this brief, three commonly used and well-respected data providers will be compared in the initial section before we zoom in on more specific factors that make up one of these indices.

The big picture

The three indicators that we look at first are: political rights produced by Freedom House; polity 2 produced by the Polity IV project; and the liberal democracy index produced by the V-Dem project. Figures 1-3 show the unweighted average of these indicators for two groups of countries. The EU10 are the transition countries that became EU members in 2004 and 2007 and include Bulgaria, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovakia, and Slovenia. The second group, FSU12, are the 12 countries that came out of the Soviet Union minus the three Baltic countries in the EU10 group, so the FSU12 group consists of Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.

Figure 1. Freedom House

Source: Freedom House and author’s calculations
Note: Scale inverted, 1 is best and 7 worst score

Figure 2. Polity IV project

Source: Polity IV project and author’s calculations
Note: Scale from -10 (fully autocratic) to 10 (fully democratic)

Figure 3. V-Dem

Source: V-Dem project and author’s calculations
Note: Scale from 0 to 1 where higher is more democratic

All three indicators convey the message that the democratic transformation in the EU10 group was very rapid in the early years of transition and the indicators have remained at high levels since the mid-90s only to show some decline in the most recent years for two of the three indicators. The FSU12 set of countries have made much less progress in terms of democratic development and remain far behind the EU10 countries in this regard. Overall, there is little evidence at the aggregate level that the democratic gap between the EU10 and FSU12 groups is closing. While the average EU10 country is more or less a full-fledged democracy, the average FSU12 country is at the lower end of the spectrum for all three democracy measures.

The average indicators in Figures 1-3 obviously hide some interesting developments in individual countries and in the following analysis, we will take a closer look at the liberal democracy index at the country level. We will then investigate what sub-indices contribute to changes in the aggregate index in the countries that have experienced significant declines in their liberal democracy scores.

For the first part of the analysis, it is useful to break down the democratic development in two phases. The first phase is from the onset of transition (1989, 1991 or 1993 depending on the specific country) to the time of the global financial crisis in 2009 and the second phase is from 2009 to 2018 (the last data point).

Figure 4. Liberal democracy, the first phase

Source: V-Dem project and author’s calculations

Figures 4 and 5 compare how the liberal democracy indicator changes from the first year of the period (measured on the horizontal axis) to the last year of the period (on the vertical axis). The smaller blue dots are the individual countries that make up the EU10 group while the red dots are the FSU12 countries. The 45-degree line indicates when there is no change between start and end years, while observations that lie below (above) the line indicate a deterioration (improvement) of the liberal democracy index in a specific country.

In the first phase of transition (Figure 4), all of the EU10 countries increased their liberal democracy scores and the average increase for the group was almost 0.5, going from 0.26 to 0.74. This was a result of many of the countries in the group making significant improvements without any countries deteriorating. The FSU12 group had a very different development with the average not changing at all since the few countries that improved (Georgia and Ukraine) were counterbalanced by a significant decline in Belarus and a more modest decline in Armenia.

Figure 5. Liberal democracy, the second phase

Source: V-Dem project and author’s calculations

The very rapid improvement in the liberal democracy index in the EU10 countries in the first phase of transition came to a halt and also reversed in several countries in the second phase of transition. Of course, as they had improved so much in the first period, there was less room for further positive developments, but the rapid decline in some of the countries was still negative news. However, it does point towards that reform momentum was very strong in the EU accession process, but once a country had entered the union, the pressure for liberal democratic reforms has faded.

Overall, the EU10 average fell by 0.1 from 2009 to 2018. This was a result of declining scores in several countries. The particularly large declines in this period have been seen in Hungary (-0.28), Poland (-0.27), Bulgaria (-0.14), the Czech Republic (-0.14), and Romania (-0.12). Again, the average FSU12 score did not change much, although Ukraine (-0.2) put its early success in reverse and lost as much in this period as it had gained earlier.

Country developments

Since much of the current discussion centers on how democracy is being under attack, the figures name the countries that have seen significant declines in the liberal democracy score in the first or second phase of transition. Figures 6 and 7 show the time-series of the liberal democracy index in the countries with significant drops at some stage of the transition process.

Figure 6. FSU12 decliners

Source: V-Dem project and author’s calculations

In many countries, the drop comes suddenly and sharply, with the first and most prominent example being Belarus. There, it only took three years to go from one of the highest ranked FSU12 countries to fall to one of the lowest liberal democracy scores. In Poland, Romania, Bulgaria and Armenia, the process was also very rapid and significant changes happened in 2-3 years.

Figure 7. EU10 decliners

Source: V-Dem project and author’s calculations

In the Czech Republic and Hungary, the period of decline was much longer and in the case of Hungary, the drop was the most significant in the EU10 group. Ukraine stands out as more of an exception with a roller-coaster development in its liberal democracy score that first took it up the list and then back down to where it started. For those familiar with politics in these countries, it is easy to identify the elections and change in government that have occurred at the times the index has started to fall in all of these countries. In other words, the democratic declines have not started with coups but followed election outcomes where in most cases the incumbent leaders have been replaced by a new person or party.

How democracy came under attack

We will now take a closer look at what has been behind the instances of decline in the aggregate index by investigating how the sub-indices have developed in these countries. The sub-indices that build up the liberal democracy index are: freedom of expression and alternative sources of information; freedom of association; share of population with suffrage; clean elections; elected officials; equality before the law and individual liberty; judicial constraints on the executive; and legislative constraints on the executive (the structure is a bit more complex with mid-level indices, see V-Dem 2019a).

Table 1 shows how these indicators have changed in the time period the liberal democracy indicator has fallen significantly (with shorter versions of the longer names listed above but in the same order). The heat map of decline indicated by the different colours is constructed such that positive changes are marked with green, smaller declines are without colour, declines greater that 0.1 but smaller than 0.2 are in yellow and larger declines in red. Note that the liberal democracy index is not an average of the sub-indices but based on a more sophisticated aggregation technique (see V-Dem 2019b). Therefore, the Czech Republic and Bulgaria can have a greater fall in top-level liberal democracy index that what is indicated by the sub-indices.

Table 1. Changes in liberal democracy indicators at times of democratic decline

Source: V-Dem project and author’s calculations

For the countries with the largest changes in the liberal democracy index, it is clear that both freedom of expression and alternative sources of information have come under attack together with reduced judicial and legislative constraints on the executive. Among the EU10 countries, Hungary and Poland stand out in terms of reducing freedom of expression, while Romania has seen most of the decline coming from reducing constraints on the executive. Not surprisingly, Belarus stands out in terms of the overall decline in liberal democracy coming from reducing both freedom of expression and constraints on the executive in the most significant way.

On a more general level, the attack on democracy does differ between the countries, but in the cases where serious declines can be seen, the attack has been particularly focused on information aspects and constraints on the executive. At the same time, all countries let all people vote (suffrage always at 1) and let the one with the most votes get the job (elected officials).

Policy conclusions

This brief has provided some stylized facts on the first 30 years of liberal democracy in transition and some details on how democracy has come under attack in individual countries. It leaves open many questions that require further studies and some of these are indeed ongoing in this project and will be presented in future briefs and policy papers here.

Some observations have already been made here that can inform policy discussions on liberal democratic developments in the region. The first is that changes can happen very rapidly, both in terms of improvements but also in terms of dismantling important democratic institutions, including those that provide constraints on the executive or media that provides unbiased coverage before and after elections. What is also noteworthy is that these changes have almost always happened after an election where a new person or party has come to power, so the democratic system is used to introduce less democracy in this sense.

It is also interesting that in all of the countries, the most easily observed indicators of democracy such as suffrage and having the chief executive or legislature being appointed by elections are given the highest possible scores. In other words, even the most autocratic regime wants to look like a democracy; but as the old saying goes, “it is not who votes that is important, it is who counts”.

The regime changes at election times that have led to declining liberal democracy scores have also in many cases come as a result of the incumbents not doing a great job or voters not turning up to vote. It was enough for Lukashenko in Belarus to promise to deal with corruption and rampant inflation that was a result of the old guard’s mismanagement to turn Belarus into an autocracy. In Hungary, the change of regime came after the Socialist leader was caught on tape saying he had been lying to voters. While in Romania, only 39% voted in the 2016 election. And in Bulgaria, around half of the voters stayed at home in the presidential election the same year.

In sum, both incompetent and corrupt past leaders and disengaged or disillusioned voters are part of the decline in a liberal democracy that we have seen in recent years. It is clearly time for policy makers that are interested in preserving liberal democracy in the region and elsewhere to think hard about how democracy can be saved from illiberal democrats. Part of the answer clearly will have to do with how voters can be engaged in the democratic process and take part in elections. It also involves defending free independent media and the thinkers and doers that contribute to the liberal democracy that we cherish. The question is if the young generation will find a Greta for democracy that can kick-start a new transition to liberal democracy in the region and around the world.

For those readers that want to participate more actively in this discussion and have a chance to be in Stockholm on November 12, SITE is organizing a conference on this theme which is open to the public. For more information on the conference, please visit SITE’s website (see here).

References

  • Freedom house data downloaded on Oct 4, 2019, from https://freedomhouse.org/content/freedom-world-data-and-resources
  • Freedom house methodological note available at https://freedomhouse.org/report/methodology-freedom-world-2018
  • Polity IV project data downloaded on Oct 4, 2019, from http://www.systemicpeace.org/inscrdata.html
  • Polity IV project manual available at http://www.systemicpeace.org/inscr/p4manualv2018.pdf
  • V-Dem project data downloaded on Sept 24, 2019, from https://www.v-dem.net/en/data/data-version-9/
  • Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Anna Lührmann, Kyle L. Marquardt, Kelly McMann, Pamela Paxton, Daniel Pemstein, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Steven Wilson, Agnes Cornell, Lisa Gastaldi, Haakon Gjerløw, Nina Ilchenko, Joshua Krusell, Laura Maxwell, Valeriya Mechkova, Juraj Medzihorsky, Josefine Pernes, Johannes von Römer, Natalia Stepanova, Aksel Sundström, Eitan Tzelgov, Yi-ting Wang, Tore Wig, and Daniel Ziblatt. 2019a. “V-Dem [Country-Year/Country-Date] Dataset v9”, Varieties of Democracy (V-Dem)
  • Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2019b. “The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data”, V-Dem Working Paper No. 21. 4th edition. University of Gothenburg: Varieties of Democracy Institute.

The Russian Food Embargo: Five Years Later

Posted on October 14, 2019 | Policy Brief

20191014 The Russian Food Embargo FREE Network Policy Brief Image 01

In this brief, we report the results of a quantitative assessment of the consequences of counter-sanctions introduced by the Russian government in 2014 – Russian food embargo. We consider several affected commodity groups: meat, fish, dairy products, fruit and vegetables. Applying a partial equilibrium analysis to the data from several sources, including Rosstat, Euromonitor, UN Comtrade, industry reviews etc. as of 2018, we obtain that consumers’ total loss amounts to 445 bn Rub, or 3000 Rub per year for each Russian citizen. This is equivalent to a 4.8% increase in food expenditure for those who are close to the poverty line. Out of this amount, 84% is distributed towards producer gains, 3% to importers, while the deadweight loss amounts to 13%. Based on industry dynamics, we identify industries where import substitution policies led to positive developments, industries where these policies failed and group of industries where partial success of import substitution was very costly for consumers.

The full text of the underlying paper is forthcoming in the Journal of the New Economic Association in October 2019.

In August 2014, in response to sectoral sanctions against Russia, the national government issued resolution No. 778, which prohibited import of processed and raw agricultural products from the United States, the EU, Ukraine and a number of other countries (Norway, Canada, Australia, etc.).  The goal was to limit market access for countries, which supported sectoral sanctions. The other rhetoric of the counter-sanctions was to support domestic producers via trade restrictions, or by other words – import substitution.

This brief provides an update of welfare analysis of counter-sanctions based on partial equilibrium  model of domestic market. The initial estimations based on 2016 data can be found in another FREE Policy Brief here. This time we compare the consumption, outputs and prices of the counter sanctioned goods as of 2018 relative to 2013. The estimated consumer surplus changes, producer gains and prices are reported in Table 1.

Table 1. Welfare effects of counter-sanctions in 2018 relative to 2013.

Data sources: Rosstat, Euromonitor, UN COMTRADE
* Negative losses correspond to gains
** Negative gains correspond to losses
Green color was used to mark the commodity groups with a noticeable consumption growth in 2013-2018 and red color those with consumption decrease.

Effect on production

From the point of view of price dynamics, on the one hand, and consumption and output, on the other, the studied products can be divided into three groups.

The first group which we call “Success of import substitution”  includes goods for which real prices (in 2013 level) increased by 2016 but afterwards, the growing domestic production ensured that by 2018 prices fell below the level of 2013 with a corresponding increase in consumption. This group includes tomatoes, pork, poultry and, with some reservation, beef. For beef, growing domestic production pushed prices down after 2016, but the level of consumption and prices have not yet reached the pre-sanction level.

For the second group, import substitution has not resulted in a price decrease, we call this group “Failure of import substitution”. For products in this group, the initial increase in prices by 2016 was not reverted afterwards. Their consumption decreased significantly compared to 2013, and domestic production either continued to fall after 2016, or its growth turned out to be fragile. This group includes apples, cheese, fish, as well as condensed milk and processed meat.

We call the third group “Very expensive import substitution”. It includes fromage, sour milk, milk and (to a lesser extent) butter. This group is characterized by increase in consumption and output in the period 2016–2018, but real prices over this period still remain very high.

Effect on consumers

By comparing the losses and gains of consumers in different categories of goods due to changes in real prices and real consumption, our analysis provides the following monetary equivalents. For all considered counter-sanctioned product groups, with the exception of poultry, pork and tomatoes, consumer losses are around 520 billion rubles per year (in 2013 prices). In three product groups (poultry, pork, tomatoes), in which there was a decrease in prices and a significant increase in consumption, the consumer gains are equivalent to 75 billion rubles per year. Thus, the total negative effect from counter-sanctions for the consumers amounted to 445 billion rubles a year, or about 3000 rubles for a person per year.

Given the cost of the minimum food basket, defined in Russia as 50% of the subsistence level, the impact of counter-sanctions on the budgets of Russian consumers can be estimated as follows. 3000 rubles account for approximately 4.8% of the annual cost of the minimum food basket. The minimum food basket is a set of food products necessary to maintain human health and ensure its vital functions that is established by law. In other words, one can say that 3000 rubles a year are equivalent to a 4.8% increase in food expenditure for those who are close to the poverty line.

Consumer surplus losses were significantly redistributed in favor of domestic production, totaling 374 billion, or 2500 rubles per year per person. Another 56 billion rubles (or 390 rubles per person) correspond to the deadweight loss, i.e., reflect the inefficiency increase of the Russian economy, and 16 billion rubles (110 rubles per person) is the equivalent of redistribution in favor of foreign producers, who get access to Russian market with higher priced products than before counter-sanctions.

Effect on foreign partners

As a result of the selective embargo, the geography of Russian imports of the affected goods has changed. Traditional suppliers of these goods, primarily from Europe, were replaced by suppliers from other countries due to trade diversion. Given the changes in the composition of importers after the imposition of sanctions, we single out countries that have lost and countries that have gained access to the Russian market. We use the change in trade volumes from the respective countries as indicators of growth and decrease in share of these importers in the Russian market. Below we consider in detail the three groups of goods with the largest gains for importers in 2018 compared with 2013: cheese, apples, butter.

Cheese imports decreased significantly after the imposition of counter-sanctions, in 2018 accounting for only 42% of their dollar value in 2013. The total gain of importers due to the growth of domestic prices in 2013-2018 amounted to 17.3 billion rubles (Table 1) and was distributed among following importing countries: Belarus (78%), Argentina (6%), Switzerland (4%), Uruguay (3%), Chile (3%), other countries (6%). Countries that lost their shares of the Russian cheese market included Ukraine, Holland, Germany, Finland, Poland, Lithuania, France, Denmark, Italy and Estonia. As mentioned earlier, domestic production and Belarusian imports were not able to fully compensate for imports from countries on the counter-sanctions list, and in 2016-2018 cheese consumption in Russia decreased significantly.

Apple imports after the initial drop in 2016 partially recovered in 2018, amounting to 66% of their dollar volume in 2013. The total gain of importers in 2018 compared to 2013 amounted to 15.0 billion rubles (Table 1); it was distributed between Serbia (22%), Moldova (19%), China (13%), Turkey (10%), Iran (10%), Azerbaijan (7%), South Africa (4%), Chile (3%), Brazil (3%) and other countries (9%). Poland suffered the most from the ban on apple imports; it accounted for about 80% of all losses. Other losers from counter-sanctions include Italy, Belgium and France. The reorientation of trade flows did not completely replace Polish imports, so apple consumption in 2016-2018 was significantly lower than in 2013.

Imports of butter in 2018 was also below the level of 2013 (67% of dollar value). The gain of importers in 2018 compared to 2013 amounted to 11.2 billion rubles and was distributed among the following  trading partners: Belarus (90%), Kazakhstan (4%), Kyrgyzstan (3%) and other countries (3%). Among the countries bearing most of the negative burden of the diversion of trade, one should mention Finland and Australia.

Conclusions

Five year after counter-sanctions were put in place Russian consumers continue paying for them out of their pockets. While few industries have demonstrated a positive effect of import substitution policies, most are not effective enough to revert the price dynamics.

References