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Russia’s Real Cost of Crimean Uncertainty

Posted on June 10, 2019 | Policy Brief

The annexation of Crimea has real costs to the Russian economy beyond what is measured by some items in the armed forces’ budget; social spending in the occupied territories; or the cost of building a rather extreme bridge to solve logistics issues. Russia’s real cost of the annexation of Crimea is also associated with the permanent loss of income that the entire Russian population is experiencing due to increased uncertainty, reduced capital flows and investment, and thus a growth rate that is significantly lower than it would have been otherwise. Since the years of lost growth are extremely hard to make up for in later years, there will be a permanent loss of income in Russia that is a significant part of the real cost of annexing Crimea and continuing the fighting in Eastern Ukraine. It is time to stop not only the human bleeding associated with Ukraine, but also the economic.

Estimating the real cost of Russia’s annexation of Crimea and the continued involvement in Eastern Ukraine is complicated since there are many other things going on in the Russian economy at the same time. In particular, oil prices fell from over $100/barrel in late 2013 to $30/barrel in 2016 (Figure 1). Becker (2016) has shown that 60-80 percent of the variation in GDP growth can be explained by changes in oil prices, so this makes it hard to just look at actual data on growth to assess the impact of Crimea and subsequent sanctions and counter sanctions.

Figure 1. Russian GDP and oil price

Source: Becker (2019)

The approach here is instead to focus on one channel that is likely to be important for growth in these circumstances, which is uncertainty and its impact on capital flows and investment.

From uncertainty to growth

The analysis presented here is based on several steps that link uncertainty to GDP growth. All the details of the steps in this analysis are explained at some length in Becker (2019). Although this brief will focus on the main assumptions and estimates that are needed to arrive at the real cost of Crimea, a short description of the steps is as follows.

First of all, in line with basic models of capital flows, investors that can move their money across different markets (here countries) will look at relative returns and volatility between different markets. When relative uncertainty goes up in one market, capital will leave that market.

The next step is that international capital flows affect investment in the domestic market. If capital leaves a country, less money will be available for fixed capital investments.

The final step is that domestic investments is important for growth. Mechanically, in a static, national accounts setting, if investments go down, so does GDP. More long term and dynamically, investments have a supply side effect on growth, and if investments are low, this will affect potential as well as actual growth negatively.

These steps are rather straightforward and saying that uncertainty created by the annexation of Crimea leads to lower growth is trivial. What is not trivial is to provide an actual number on how much growth may have been affected. This requires estimates of a number of coefficients that is the empirical counterparts to the theoretical steps outlined here.

Estimates to link uncertainty to growth

In short, we need three coefficients that link: domestic investments to growth; capital flows to domestic investments; and uncertainty to capital flows.

There are many studies that look at the determinants of growth, so there are plenty of estimates on the first of these coefficients. Here we will use the estimate of Levine and Renelt (1992), that focus on finding robust determinants of growth from a large set of potential explanatory variables. In their preferred specification, growth is explained well by four variables, initial income, population growth, secondary education and the investments to GDP ratio. The coefficient on the latter is 17.5, which means that when the investment to GDP ratio increases by 10 percentage points, GDP grows an extra 1.75 percentage points per year. Becker and Olofsgård (2018) have shown that this model explains the growth experience of 25 transition countries including Russia since 2000 very well, which makes this estimate relevant for the current calculation.

The next coefficient links capital flows to domestic investments. This is also a subject that has been studied in many empirical papers. Recent estimates for transition countries and Russia in Mileva (2008) and Becker (2019) find an effect of FDI on domestic investments that is larger than one, i.e., there are positive spillovers from FDI inflows to domestic investments. Here we will use the estimate from Becker (2019) that finds that 10 extra dollars of FDI inflows are associated with an increase of domestic investments of 15 dollars.

Finally, we need an estimate linking uncertainty with capital flows. There are many studies looking at risk, return and investment in general, and also several studies focusing on international capital flows and uncertainty. Julio and Yook (2016) look at how political uncertainty around elections affect FDI of US firms and find that FDI to countries with high institutional quality is less affected by electoral uncertainty than others. Becker (2019) estimates how volatility in the Russian stock market index RTS relative to the volatility in the US market’s S&P 500 is associated with net private capital outflows. The estimate suggests that when volatility in the RTS goes up by one standard deviation, this is associated with net private capital outflows of $30 billion.

These estimates now only need one more thing to allow us to estimate how much Crimean uncertainty has impacted growth and this is a measure of the volatility that was created by the annexation of Crimea.

Measuring Crimean uncertainty

In Becker (2019), the measure of volatility that is used in the regression with net capital outflows is the 60-day volatility of the RTS index. Since we now want to isolate the uncertainty created by Crimea related events, we need to take out the volatility that can be explained by other factors in order to arrive at a volatility measure that captures Crimean induced uncertainty. In Becker (2019) this is done by running a regression of RTS volatility on the volatility of international oil prices and the US stock market as represented by the S&P 500. The residual that remains after this regression is the excess volatility of the RTS that cannot be explained by these two external factors. The excess volatility of the RTS index is shown in figure 2.

It is clear that the major peaks in excess volatility are linked to Crimea related events, and in particular to the sanctions introduced at various points in time. From March 2014 to March 2015, there is an average excess volatility of 0.73 standard deviations with a peak of almost 4 when the EU and the USA ban trade with Crimea. This excess volatility is our measure of the uncertainty created by the annexation of Crimea.

Figure 2. RTS excess volatility

Source: Becker (2019)

From Crimean uncertainty to growth

The final step is simply to use our measure of Crimean induced uncertainty together with the estimates that link uncertainty in general to growth.

The estimated excess volatility associated with Crimea is conservatively estimated at 0.7 standard deviations. Using this with the estimate that increasing volatility by one standard deviation is associated with $30 billion in capital outflows, we get that the Crimean uncertainty would lead to $21 billions of capital outflows in one quarter or $84 billions in one year. If this is in the form of reduced FDI flows, we have estimated that this means that domestic investments would fall by a factor of 1.5 or $126 billions.

In this period, Russia had a GDP of $1849bn and fixed capital investments of $392bn. This means that $126 billions in reduced investments correspond to a reduction in the investments to GDP ratio of 7 percentage points (or that the investments to GDP ratio goes from around 21 percent to 14 percent).

Finally, using the estimate of 17.5 from Levine and Renelt, this implies that GDP growth would have been 1.2 percentage points higher without the estimated decline in investments to GDP.

In other words, the Crimean induced uncertainty is estimated to have led to a significant loss of growth that has to be added to all the other costs of the annexation of Crimea and continued fighting in Eastern Ukraine. Note that recent growth in Russia has been just barely above 1 percent per year, so this means that growth has been cut in half by this self-generated uncertainty.

Of course, the 1.2 percentage point estimate of lost growth is based on many model assumptions, but it provides a more sensible estimate of the cost of Crimea than we can get by looking at actual data that is a mix of many other factors that have impacted capital flows, investments and growth over this period.

Policy conclusions

The annexation of Crimea and continued fighting in Eastern Ukraine carry great costs in terms of human suffering. In addition, they also carry real costs to the Russian economy. Not least to people in Russia that see that their incomes are not growing in line with other countries in the world while the value of their rubles has been cut in half. Some of this is due to falling oil prices and other global factors that require reforms that will reorient the economy from natural resource extraction to a more diversified base of income generation. This process will take time even in the best of worlds.

However, one “reform” that can be implemented over night is to stop the fighting in Eastern Ukraine and work with Ukraine and other parties to get out of the current situation of sanctions and counter-sanctions. This would provide a much-needed boost to foreign and domestic investments required to generate high, sustainable growth to the benefit of many Russians as well as neighboring countries looking for a strong economy to do trade and business with.

References

Becker, T, (2019), “Russia’s macroeconomy—a closer look at growth, investment, and uncertainty”, forthcoming SITE Working paper.
Becker, T. and A. Olofsgård, (2018), “From abnormal to normal—Two tales of growth from 25 years of transition”, Economics of Transition, vol. 26, issue 4.
Becker, T. (2016), “Russia and Oil – Out of Control”, FREE policy brief, October.
Julio, B. and Yook, Y. (2016), ‘Policy uncertainty, irreversibility, and cross-border flows of capital’, Journal of International Economics, Vol. 103, pp. 13-26.
Levine, R. and Renelt, D. (1992). ‘A Sensitivity Analysis of Cross-Country Growth Regressions’, American Economic Review, 82(4), pp. 942–963.
Mileva, E. (2008), ‘The Impact of Capital Flows on Domestic Investment in Transition Economies, ECB Working Paper No. 871, February.

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.

Institutions and Comparative Advantage in Services Trade

Posted on June 3, 2019 | Policy Brief

High office buildings facing sky representing Institutions and Services Trade

Recent studies have highlighted the role of human capital and good economic institutions in establishing a comparative advantage in trade in complex institutions-intensive goods. We show that the effect of institutions on comparative advantage in services trade is quite different: in fact, countries with bad institutions rely significantly more on services exports. More specifically, as the quality of institutions deteriorates, information technology sector (ICT) services exports as a share of total ICT exports increase significantly and countries with worse institutions get a substantial comparative advantage in the provision of ICT services. This is especially applicable to transitional economies characterized by high, arguably exogenous, human capital at the level of most advanced countries.

Introduction

Recent research in international trade has demonstrated that institutions influence the determination of comparative advantage in the trade of goods. Countries with strong domestic institutions have a significant comparative advantage in producing complex, institutions-intensive goods while countries with weak institutions tend to specialize in less complex goods. Through this channel, weak institutions can hinder growth and development (Nunn and Trefler, 2014).

We argue that the role of institutions in services trade can differ significantly from the one in trade in goods. The intuition behind it is that services provision often relies less on institution-driven factors, such as public infrastructure, availability of large number of inputs, property rights and capital investments than the production of complex goods.

We show, in the case of the information technology sector (ICT), that countries with bad institutions rely significantly more on services exports even after controlling for human capital input requirements and availability. We focus on the ICT sector to isolate the differences in the role of institutions in determining comparative advantage in goods and services. Both ICT goods and services provision are equally intensive in human capital and thus present a good opportunity to study differences between goods and services provision.

Our study is motivated by high ICT services exports (e.g. software development) and low ICT goods exports (e.g. computers, phones, etc.) of transition countries which are known to have high human capital and low institutional indicators.

Institutions and ICT Services Exports

Figure illustrates the high human capital availability of transitions economies and weak domestic institutions relative to other countries. Specifically, we categorize countries into four groups: 23 most developed economies (e.g. USA, Canada, Japan and Western European economies); new members of the European Union (a group of 13 countries including Poland, Slovakia, and Baltic countries); transition economies group consists of 17 mostly post-Soviet countries including Russia, Ukraine, Belarus; the most numerous fourth group includes more than hundred other developing countries.

Figure 1. Institutions quality and schooling by country groups

Source: Authors’ calculations, schooling data from Barro and Lee (2013)

Source: Authors’ calculations, institutional indicators data from the World Bank World Governance Indicators

Figure 1a presents an average number of years of schooling, our measure of human capital, for each country group in 2000 and 2010 (the years are chosen based on data availability). The human capital is at a similar level in the most developed economies, EU-13 and transition economies, but significantly lower in other developing countries. Figure 1b illustrates the average institutional quality for each group in 2000 and 2010. Institutional quality for each country is calculated as an average of six indicators, distributed approximately from -2.5 to 2.5: control of corruption, government effectiveness, political stability, rule of law, regulatory quality, voice and accountability, with a lower value corresponding to worse institutional quality. In contrast to education, the average institutional quality of transition economies, although improving from 2000, remains on average lower than the institutional quality of other developing countries.

Consistent with the literature on institutions and comparative advantage in relationship and investment-intensive goods production, ICT goods export from transition economies is significantly lower than in other countries. In contrast, ICT services exports is at a higher level and faster growth in transition economies than in other countries.

Belarus presents a good motivating example. On the one hand, fundamental education in Belarus is at a level of the most advanced countries, which allows 21 universities in the country to educate about 7,000 graduates in IT industry in a year. On the other hand, ICT services exports in Belarus is thriving: over the last 10 years, the growth of ICT services is an eightfold increase (it was 150M USD in 2008 and 1.2B USD in 2017). Nowadays, Belarus is one of the world leaders in ICT services exports per capita. At the same time, ICT goods export is not growing even close to the level of ICT services exports. Over the same time period, it has grown only by about 30 percent: in 2008 ICT goods export was 105M USD, in 2016 – 140M USD (BELARUS.BY, 2019).

The importance of ICT services exports in transition economies is seen in Figure 2. The figure presents ICT services exports as a share of total exports of ICT goods and services. To obtain values for each country group, we average ICT services shares across countries within each group.

Figure 2. ICT services exports as share of total ICT exports

Source: Authors’ calculations, ICT services export data from Trademap, ICT goods export data from WDI

As Figure 2 shows, the average share of ICT services exports in transition economies is higher than the share of ICT services exports in all other groups of countries. Transition economies, characterized by high human capital and weak institutional quality, specialize in exports of services over goods in their ICT exports. This descriptive evidence suggests that abundant human capital, inherited from the USSR and arguably exogenous, shifts to services within the human capital intensive ICT sector when facing weak institutions.

Empirical panel analysis confirms the descriptive evidence. To test our hypothesis, we use the share of ICT services in total ICT exports as a dependent variable and we show that quality of institutions is a significant determinant. Our regressions show that the higher the quality of institutions is, the lower will the share of ICT services in total ICT exports be. Moreover, regression analysis allows us to quantify this dependence: as the quality of institutions increases by 1, which is approximately the difference between Belarus and Georgia (as can be seen in figure 3 below), the share of ICT goods in total ICT services increases by about 20%.

Institutions as a source of comparative advantage in services

To explore the role of institutions in the relative services provision within a sector further, we look at comparative advantage in exporting ICT services. We incorporate a measure similar to Relative Share measure used in Levchenko (2007) for the analysis of comparative advantage in goods export. The measure effectively compares the share of ICT services export for a given country with the world average. The index of revealed comparative advantage in ICT services over ICT goods is computed for country in the following way:

where is share of ICT services exports in total ICT exports for country, is the export of ICT services for all countries, and is the total ICT export (goods plus services) for all countries.

We look at the revealed comparative advantage index across our group of transition economies in figure 3 and see that even within this group, there is a negative correlation between institutions quality and revealed comparative advantage in ICT services.

Figure 3. Revealed Comparative Advantage and Institutions Quality

Source: Authors’ calculations

Countries with high institutional quality, like Georgia, export relatively more goods compared to services. Countries with low institutional quality, like Ukraine and Belarus, have a comparative advantage in ICT services exports.

We hypothesize that the main mechanism responsible for this is as follows. Poor institutional quality, resulting in, for example, corruption and the impossibility to create binding contracts does not allow the countries to produce complex goods in the ICT industry, while the presence of high human capital in these countries allows them to produce ICT services that much less depend on corruption and contracting inefficiencies but are as intensive in human capital as ICT goods.

For a better understanding of the relationship between institutions and comparative advantage determination, we run panel regressions analysing the probability of having a comparative advantage in ICT services in exports of ICT goods and services as a function of institutional quality. Following Balassa (1965), a country has a comparative advantage in ICT services if the share of services in overall ICT exports is higher than the world average, in other words, revealed comparative advantage index is greater than 1. We find that one unit increase in institutional quality reduces the probability of having a comparative advantage in services by about 25%, which means that a country with institutional quality similar to Georgia is about 25% less likely to have comparative advantage than a country with institutional quality similar to Belarus.

Conclusion

In this brief we have discussed the role of institutions in determining comparative advantage in services. Our study argues that, given high human capital, low quality institutions create comparative advantage in services provision. Since low quality institutions act as an implicit tax on the production of complex goods, rational agents reallocate most resources to the production of services that are less sensitive to the institutional quality, while still requiring high level of human capital. We showed that transition economies are characterized by low institutions quality and high human capital. At the same time, transition economies have the highest share of ICT services export in total ICT export. We also showed that institutions negatively affect comparative advantage in ICT services export. Our results suggest that services exports can be a novel development channel for countries with weak institutional, capital investments and infrastructure. Specialization in high-value added services exports provides opportunity for fostering high human capital.

References

Arshavskiy, Victor, Arevik Gnutzmann-Mkrtchyan and Aleh Mazol, 2019. “Institutions and Comparative Advantage in Service Trade”, Working paper
Balassa, B. (1965). Trade liberalisation and “revealed” comparative advantage 1. The Manchester School of Economics and Social Studies, 33(2), 99-123.
Barro, Robert J. and Jong Wha Lee, 2013. “A new data set of educational attainment in the world, 1950–2010”, Journal of Development Economics, vol. 104, pp 184-198
Levchenko, Andrei A., 2007. “Institutional Quality and International Trade”, Review of Economic Studies, vol. 74, pp 791-819.
Nunn, Nathan and Daniel Trefler, 2014. “Domestic Institutions as a Source of Comparative Advantage”, Handbook of International Economics, Volume 4, Chapter 5, pp 263-315.
BELARUS.BY, 2019. “ИТ в Беларуси”, it-belarus, accessed on May 19, 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.

The Learning Crisis: Combining Incentives and Inputs to Raise Student Achievement

Posted on May 27, 2019 | Policy Brief

As school enrolment in low- and middle-income countries has increased substantially in the last couple of decades, attention has instead turned to the poor quality of education. This ”learning crisis” (UNESCO 2013) manifests itself in primary school students without basic skills in language and mathematics, and high school students being vastly outperformed by their peers in high-income countries (World Bank 2018). In this policy brief, I give a very brief background to the learning crisis and report on a research project we have implemented and evaluated in the Democratic Republic of Congo (DRC) with the aim of improving student learning in primary education. The intervention consisted of an incentivized program to stimulate more usage of existing textbooks for self-study, and the impact was evaluated through a randomized experiment (Falisse, Huysentruyt and Olofsgård 2019).

Education systems in many low- and middle-income countries fail to deliver actual learning at the level necessary for people and societies to thrive. According to leading international assessments of literacy and numeracy, the average student in low-income countries performs worse than 95 percent of the students in high-income countries. According to an assessment of second-grade students in India, more than 80 % could not read a single word from a short text or conduct two-digit subtraction. Students perform poorly also in some European middle-income countries; more than 75 % of students in Kosovo and the Republic of North Macedonia perform worse than the 25^th percentile in the average OECD country (World Bank 2018). The reasons behind the learning crisis are of course many, ranging from poorly trained and absent teachers, lack of financial resources for infrastructure and learning material, malnutrition and lacking early childhood development, and sometimes weak demand.

Textbooks for Self-Study in the DRC

The learning crisis is particularly evident in fragile, low income countries. This is also where the major challenge to achieve the 2030 Sustainable Development Goal 4 of quality education to all lies (World Bank, 2018). Yet, very few interventions targeting student achievement have been evaluated in the most fragile countries of the world (Glewwe and Muralidharan 2016). This is a concern, since interventions that work in poor but stable environments may not be feasible or effective in even more resource constrained and violent environments (Burde and Linden 2013). In particular, there is an extra value in identifying interventions that are not only cost efficient, but also low cost in absolute terms and simple and transparent.

Projects focusing on school inputs have often yielded surprisingly disappointing results (Glewwe and Muralidharan 2016). One example is interventions focusing on textbook distribution despite belief in their effectiveness and investments from donors and governments (Glewwe, Kremer and Moulin 2009; Sabarwal et al. 2014). One major challenge with textbooks is that they for different reasons are often not used by teachers or pupils, and certainly not to their potential (e.g. Sabarwal et al. 2014). This raises the question of whether the potential of textbooks can be leveraged through incentives on their usage. A couple of recent papers have found that it is indeed the combination of inputs (including textbooks) and incentives that is critical to yield a significant impact on student test scores (Mbiti et al. 2019; Gilligan et al. 2018).

Following up on this idea we collaborated with the Dutch NGO Cordaid that is running a program in primary education in South Kivu, in eastern DRC, in 90 schools. We designed an intervention that encouraged 5th and 6th grade students from 45 randomly selected schools to regularly take home textbooks and use them for self-study. We used a mix of financial and non-financial incentives focused on the students, such as a public display of stars assigned to each student that brought math and French textbooks home and back in good condition, and an in-kind gift of pens and pencils for all students in classes regularly participating in the routine. We also offered participating schools a small flat compensation to compensate for lost and damaged books. The main goals of the intervention were to increase student achievement and to affect their aspirations for further study and more qualified careers.

To measure student achievement, we rely on self-conducted tests in the French language and math, but also high stakes national exam scores that determine eligibility to secondary education. Following the literature, we analyze test results using a model that assumes that baseline test scores capture student learning up to that point, so once this is controlled for end line results capture cleanly the added value of the intervention introduced. We also carefully address potential statistical problems due to slight unbalance between treatment and control groups, students from baseline not present at end line and poor compliance with the intervention in a small set of schools. The results are generally robust across different specifications of the details of the model.

We emphasize three main sets of results. First, we find that the students in the treatment schools (those selected to receive the books) scored significantly better than those in control schools on the French language tests. The estimated improvement was 1/3 of a standard deviation, which compares favourably with other interventions in developing countries targeting student test scores (Kremer et al. 2013). On the other hand, we found no significant impact on math scores. We cannot tell for sure why we observe this difference between French and math, but it should be noted that both textbooks were in French, suggesting that language could be learned from both books. It has also been suggested that math requires more supervision than language and that math is more ”vertical” in terms of skills progression while language is more ”horizontal”. That is, if students are far behind the curriculum in the textbook, they don’t have the necessary basic building blocks to understand the math problems. But for language, this matters less, as progress can be made in different areas more independently.

Secondly, students in treatment schools were more likely to sit and pass the national exam. This is important as this is a requirement for the continuation of schooling at a higher level. More qualified jobs, and jobs that require more French language skills, typically require at least secondary schooling. This is also consistent with the finding that students exposed to the intervention were more likely to aspire to non-manual jobs. Finally, the intervention was low cost and cost-efficient. In particular in fragile environments with very limited resources, this is essential. The intervention is also easy to implement and transparent and does not give raise to incentives to cheat as has been the case in some interventions linking incentives directly to student test performance.

Conclusions

The current key challenge in education policy in low- and middle-income countries is to improve student achievement while continuing the successful increase in enrolment despite often serious constraints in complementary inputs in the education production function. Financial resources for school infrastructure and material are limited, competent and motivated teachers are in short supply, and weak parental support and little early childhood development leaves children unprepared for sometimes too ambitious curricula. In such circumstances simple and low-cost interventions that make better use of existing resources are particularly valuable. In this project we designed and evaluated such an intervention, using incentives to stimulate more usage of existing textbooks, in a particularly challenging environment, Eastern DRC. We find a positive impact on French language skills and higher student aspirations as shown through greater participation in national exams required for continued education. On the other hand, we find no impact on math test scores. Serious sustainable improvement in student learning in a country like the DRC requires wholesale reforms to the education sector and substantially increased financial resources. Realistically, this is a long-run ambition. In the meanwhile, small low-cost interventions that match incentives with existing resources can significantly increase student achievement also in the short run.

References

Burde, Dana and Leigh L. Linden, 2013. “Bringing Education to Afghan Girls: A Randomized Controlled Trial of Village-Based Schools.” American Economic Journal: Applied Economics, 5(3), 27-40.
Falisse, Jean-Benoit, Marieke Huysentruyt and Anders Olofsgård, 2019. “Incentivizing Textbooks for Self-Study: Experimental Evidence on Student Learning from the Democratic Republic of Congo”, Working Paper.
Gilligan, Daniel O., Naureen Karachiwalla, Ibrahim Kasirye, Adrienne M. Lucas, Derek Neal, 2018. “Educator Incentives and Educational Triage in Rural Primary Schools.” NBER WP 24911.
Glewwe, Paul, Michael Kremer, and Sylvie Moulin, 2009. “Many Children Left Behind? Textbooks and Test Scores in Kenya.” American Economic Journal: Applied Economics, 1(1): 112-35.
Glewwe, Paul and Karthik Muralidharan, 2016. “Improving Education Outcomes in Developing Countries: Evidence, Knowledge Gaps, and Policy Implications”, in Handbook of the Economics of Education, pp. 653-743. Elsevier.
Kremer, Michael, Conner Brannen, and Rachel Glennerster, 2013. “The Challenge of Education and
Learning in the Developing World.” Science 340, 297-300.
Mbiti, Isaac, Karthik Muralidharan, Mauricio Romero, Youdi Schipper, Constantine Manda, Rakesh Rajani, 2019. “Inputs, Incentives, and Complementarities in Education: Experimental Evidence from Tanzania.” NBER WP 24876.
Sabarwal, Shwetlena, David K. Evans, and Anastasia Marshak, 2014. “The permanent input hypothesis: the case of textbooks and (no) student learning in Sierra Leone”, Policy Research working paper, no. WPS 7021. Washington, DC: World Bank Group.
UNESCO, 2013. “The Global Learning Crisis: Why every child deserves a quality education”, UNESCO, Paris.
World Bank, 2018. “World Development Report 2018: Learning to Realize Education’s Promise”, Washington DC: World Bank.

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.

Gender and the Agency Problem

Posted on May 20, 2019 | Policy Brief

Is it good for a firm to have a female CEO? Are countries with more female politicians less corrupt? An increasing attention to female representation in key roles in society has called for research exploring the outcomes and implications of such representation. A useful approach to investigate the impact of gender in such contexts is the so-called principal-agent framework which studies situations in which one party acts on behalf of another party. The idea is that the gender of participating parties is likely to affect motives, behavior and outcomes, predicted by the principal-agent framework. This brief reviews the use of the principal-agent framework for analyzing the effect of gender in two important areas of research: corporate finance and corruption. It outlines postulated theoretical channels for gender to matter, summarizes empirical findings and points to some of the policy challenges.

Increasingly, arguments in favor of more women in key positions are being put forth in society. Many European countries have by now introduced gender quotas for corporate board participation, with Norway being the first one to mandate a quota of 40% female board membership in late 2003. The United States joined the trend in 2018, with California being the first state to require women on corporate boards. The 2019 share of female CEOs in Fortune 500 companies is 5 %; while this number sounds very low, it is twice as high as a decade ago. Women’s presence in politics and bureaucracy is also increasing in many countries worldwide.

This tendency is clearly positive news in the fight for more gender equality, and it is likely to improve the position of women in the society. However, its implications for other economic and societal outcomes are not immediately clear. For example, is a more gender-balanced board or a female CEO good news for company performance? How would female politicians affect policy and societal outcomes?

One useful approach for answering such questions is based on the so-called principal-agent framework (developed to study what is known as “agency problems”). This framework, widely used in economics, political science and other related disciplines in the last half century, addresses the problem of incentivizing one person (referred to as an “agent”) to act on behalf of another person or entity (referred to as a “principal”). Many situations in real life are well described by this basic framework and it has been used in a wide range of different contexts, from relationships within a firm, or between a lawyer and her client, to insurance, real estate, policy choices by elected officials or appointed bureaucrats, and even situations involving corruption.

The relevant question is then whether, and if so, how, the gender of the agents can affect motives, behavior and outcomes, predicted by the principal-agent framework. This brief will focus on two main areas of studies within gender economics that use agency theory to motivate their findings: the role of gender in corporate governance, and in corruption. The brief will outline the theoretical channels through which the gender of the actors may act in these contexts, summarize the empirical findings of this literature, and shortly comment on policy implications. While the focus on two areas only may seem to be relatively narrow, it will allow identifying a number of common gender effects across the contexts, which may suggest implications for the other potential applications of the approach.

The basic principal-agent framework

Effectively any situation in which one party acts on behalf of another party for monetary or non-monetary compensation can be analyzed within an agency framework. A typical feature of such situations is that the parties have different objectives: for example, the board of the firm (the principal in this case) would be interested in maximizing the firm value, while the CEO (the agent) would probably be more concerned about her personal compensation. This difference is not necessarily problematic per se as long as the principal can get the agent to act as the principal wants. However, if parties do not have the same information – which is typically the case in the reality – the misalignment of their objectives becomes an issue.

Two main problems may arise in such situations. The first one is referred to as the problem of hidden action (moral hazard) – that the agent is likely to act in line with her own objectives, rather than in the principal’s ones. This is likely to occur as long as her effort cannot be perfectly monitored by the principal. For example, shareholders typically cannot directly attribute the evolution of the firm’s value to the actions of the CEO, which may result in the CEO making decisions that are, for instance, too risky from the firm’s value maximization perspective. The second one is the problem of hidden information – when the agent is better informed about the issues at stake than the principal, which again may result in the agent not acting in the best interest of the principal. For example, shareholders may have a poorer knowledge of the market than CEO, which may result in the CEO making decisions maximizing her own compensation rather than the firm’s value.

To lessen the extent of these problems, one needs to think of the spectrum of tools/decisions under the agent’s control, as well as of the design of her compensation schemes so as to align her private objectives with those of the principal. For example, to motivate a CEO to behave in the interests of shareholders, his/her compensation package typically includes company stock options. In some cases, the way to provide better incentives for the agent is to delegate more decisions, allow her more discretion and link her compensation closely to the outcome of her actions. One possible example of such a mechanism is franchising: on average franchisees retain about 94% of franchise profits, which would make them very motivated to achieve good franchise performance. However, the cost of high incentivization is the potential misuse of decision power, especially if the set of the decisions for an agent to have control over is not chosen wisely and if sufficient alignment (or intrinsic motivation) is not achieved. Another obstacle when implementing the principal’s preferred outcome is the trade-off between agent’s incentivization and risk aversion. The agent is typically seen as more risk-averse than the principal (for example, firms’ shareholders would typically diversify their risks by investing in a number of companies, while the CEO’s main source of income would be associated with the company she manages). As a result, the agent may avoid undertaking the principal’s value-maximizing actions because of the risks associated with them.

The bottom line of this discussion is that the task of incentivizing the agent may be difficult, and the principal’s best-preferred outcome may not be achievable.

Gender and the agency problem

There are many twists and modifications of the basic framework described above aimed at better modelling the specific problem at hand. One particular feature of the principal-agent relationship that has received increasing attention in the literature is the gender of the participating parties. The main strands of this literature have studied the relevance of gender for corporate governance and corruption.

Gender and corporate governance

The corporate governance part of the literature focuses on the impact of the gender composition of the board of directors or of the gender of the CEO on firms’ (or banks’) performance, risk-taking, capital allocation decisions, firm reputation etc. One standard approach to this set of questions is to consider the principal-agent relationship between the agent – the CEO – and the principal(s) – the board of directors (and sometimes other firm stakeholders) – and ask how, and why, the gender of either party may affect the relationship between them and the outcomes of this relationship.

There are several channels suggested by the literature. First, women and men may have different personal characteristics – such as risk aversion, level of confidence or ethical values (though there is not necessarily agreement on the direction of the difference: while most studies argue that, on average, men are typically more overconfident than women (e.g., Barber and Odean, 2001; Lundeberg et al., 1994), there is no consensus about risk attitudes – e.g., Jianakoplos and Bernasek (1998) or Croson and Gneezy (2009) show that women are more risk-averse than men, while Adams and Funk (2012) document the opposite). These differences in personal traits may affect the decision-making of a board/CEO in an incomplete-information environment and ultimately the firm’s performance.

Second, women and men may face different employment opportunities in case they lose their job, which, again, is likely to affect their decision-making and risk-taking (e.g., Faccio, Marchica and Mura, 2016).

Third, more gender-diverse boards may better reflect the preferences of (gender-mixed) firm stakeholders; in terms of the agency theory this would imply more aligned interests between the principal and the agent. It may matter because mixed-gender groups (and, by implication, boards) may exhibit different decision-making processes than same-gender groups, which, again, may introduce frictions into the agency relationship (e.g., Amini et al., 2017 or Van Knippenberg and Schippers, 2007).

Finally, the gender composition of the board may matter because female board members may improve monitoring over the actions of the CEO, since they are more independent not being part of the same “old boys’” social networks as the male members of the board and the (male) CEOs (Adams and Ferreira, 2009).

Empirically, this literature is largely inconclusive: while the majority of studies does find that the gender of the firm’s decision-maker(s) matters, the sign of the effect differs between studies, datasets and specifications. For example, based on a US sample of firms, Bernile, Bhagwat and Yonker (2018) find that more gender-diverse boards lead to lower firm risk, and better performance. In turn, Adams and Ferreira (2009) document negative effects of more diverse boards on performance. Sila et al. (2016) find no relation between board gender diversity and risk. Similarly ambiguous are the findings on the effect of CEO’s gender on firms’ performance, as measured by risk exposure, capital allocation, propensity to acquire, business strategies etc.

One possible reason for this variability of findings is the endogeneity of the presence of female CEOs/board members and firms’ outcomes, which is difficult to account for empirically (Hermalin and Weisbach, 1998; Adams et al., 2010). For example, female CEOs may self-select into firms with lower risks due to their own risk-aversion. Alternatively, corporate culture may affect the relationship between the gender of the CEO/board members and firm performance, etc. (see Adams, 2016 for an overview of this problem). There has been a number of attempts to address the causality/endogeneity issues in this context. For example, Bernile, Bhagwat and Yonker (2018) and Alam et al. (2018) exploit variation in the gender composition of boards created by the diversity of potential directors residing a non-stop flight away from the firm headquarters. Their motivation is that the personal travel costs of directors decrease with the availability of non-stop flights. Faccio et al. (2016) attempt to resolve the endogeneity issue by proxying the likelihood of hiring a female CEO by a measure of how many other firms that share board members with the firm in question have female CEOs. The idea there is that working with female CEOs in other firms may make board members more familiar with working with female executives, and more willing to hire a female CEO in the firm in question. A subset of the literature exploits reforms introducing gender quotas in corporate boards. These studies argue that the reforms are introducing an exogenous variation in the proportion of mandated changes in board gender composition – firms with more women in the board prior to the reform would need less adjustments to comply with the reform (see, e.g., Bertrand et al., 2018 for a state-of-the-art example of such an approach). Still, the endogeneity concern remains very valid for this literature. A recent literature overview by Kirsch (2018) or somewhat more dated, but still be relevant one by Terjesen et al. (2009) can be a good starting point for more detailed information on this field.

Gender and corruption

Similarly, there is a sizeable literature of gender aspects of corruption. This literature addresses a variety of topics, including the impact of corruption on women and gender inequality, gender-associated forms of corruption, and most importantly for us in the current context, gender attitudes and behavior towards corruption. One of the predominant theoretical mechanisms in this literature, again, uses agency theory. The main difference to the version of agency theory applied in the corporate governance case above is, perhaps, that in the case of corruption there is not always a clear pattern of subordination between the principal and the agent. More specifically, the principal for a (potentially corrupt) agent official may be either a higher-level official, or the direct recipient of her services or the electorate in general (of the agent official is elected). However, just as in the corporate governance literature, the gender vs. corruption literature asks the question how the outcome of an interaction between the principal and the agent would be altered by the gender of either party. It argues that women may behave differently from men in a corrupt environment through a number of channels, most of which resemble the ones in the corporate governance literature outlined above.

For example, gender differences in behavior and attitudes to corruption may be due to of personal traits, such as risk aversion or gender-specific conformity with social norms (e.g., Esarey and Chirillo, 2013 suggest that women are more likely to conform to the local social norms, so they are less likely to engage in corruption in an institutional environment where corruption is condemned, than in the societies when it is more accepted).

These differences may be due to differences in outside options of the corrupt official in case corruption gets detected (such as alternative employment opportunities). They may also be due to women not being part of business/political network(s), or having less experience in how things are done in decision-making positions. This could make them better monitors when they are in a principal role, or less able (or willing) to engage in corruption when in the role of agent. Thereby, it may result in a negative link between women in government and corruption, but only a short-term one (e.g., Pande and Ford, 2011). However, Afridi et al. (2017) argues for an opposite view, that a newly appointed female bureaucrat’s lack of experience may increase corruption due to inability to handle matters efficiently. Their empirical results indeed support it: in India newly appointed female council heads are less efficient than male ones due to lack of experience; this efficiency gap also includes higher corruption levels in female-led villages. With time, as the female council heads gain experience, the difference disappears.

As can be expected, empirically this field is again not entirely conclusive. The early empirical research suggested a negative link between gender and corruption, or, more specifically, found that a higher presence of women in government is associated with lower levels of corruption (e.g., Dollar, Fisman, and Gatti, 2001 or Swamy et al., 2001). However, there has since been a wide discussion about the causal mechanisms of this relationship. One of the arguments has been that this correlation is due to institutional mechanisms: greater representation of women in power is observed in a more developed institutional environment, which is also providing more effective checks on corruption (e.g., Sung, 2003). Still, the discussion is ongoing, as other scholars argue that the relationship is still in place even after controlling for the institutional factors, though not in all power positions (e.g., Jha and Sarangi (2018) show that female presence in parliament decreases corruption while other measures of female participation in economic activities have no effect). There is certain evidence of female bureaucrats being less aggressive in extracting bribes (Dabalen and Wane, 2008) or female business owners paying less bribes (Breen et al., 2017), but the determinants and the causal relationship of these findings are again, unclear.

There has been a number of attempts to resolve the causality issue of the gender-corruption link. Similarly to the corporate governance literature, researchers have used an instrumental variable approach (e.g., Jha and Sarangi (2018) use number of genders in a country’s language to instrument for female labor force participation, as it has been shown that gender discrimination is higher in countries where the dominant language has two genders as opposed to countries where it has no gender or three or more genders. The same authors use the year of universal suffrage to instrument the female participation in parliament). Unlike in corporate governance literature, a large part of this literature uses experimental approach, relying both on lab experiments to study gender attitudes to corruption (e.g., Rivas, 2013), and natural experiments (Afridi et al., 2017 study the reform in India that randomly allocated a third of council headship positions to women) and quasi-experiments (Brollo and Troiano (2016) look into close elections in Brazil and use a regression discontinuity design to show that female mayors are less likely to be corrupt). A useful overview of the literature is offered in Rheinbay and Chêne (2016).

Summing up and policy implications

There is an active public and academic debate about the greater involvement of women in key positions in society, its implications and outcomes, and potential policies to achieve it. A natural way of analyzing the implications of having more women in strategic positions utilizes the principal-agent modelling approach, with the presumption that the gender of the parties is likely to affect the model’s predictions and outcomes. A substantial attention in this literature has been devoted to the impact of gender in corporate governance and corruption. Importantly, these two strands of literature outline several common channels through which gender is likely to have an impact, such as risk aversion, outside opportunities in case of losing employment, etc. This similarity suggests that the same channels are likely to play a role in other gender-relevant agency contexts.

Another similarity between these two areas of research is the ambiguity of the results in terms of both theoretical predictions and empirical findings. One possible source of this ambiguity is, likely, suboptimality of the empirical methods used, which might not allow to adequately establish the causal relationship between the characteristics and outcomes of the agency relation and gender of its participants. Differences of the contexts of the empirical studies are another probable contributor to the variation in predictions and results.

However, this ambiguity obviously does not mean that policies to empower women should not be undertaken at all. First, even if the results of a particular narrowly-targeted policy are so far found to be ambiguous, it may still be highly useful in changing social norms, with all the benefits attached to it. For example, there is no sufficient evidence that establishing gender quotes in corporate boards would improve firms’ performance. For example, Ahern and Dittmar (2012) find that introduction of quota in Norway had a negative effect on Tobin’s Q. However, a quota reform in Norway resulted in the appointment of better qualified female board members and raised the career expectations of younger women post-reform (Bertrand et al., 2018). Second, this ambiguity stresses that there is no universal “silver bullet” policy applicable to all countries and contexts: the design of policies that address gender inequalities, as any other policy, needs to carefully account for the local institutional and cultural context. Further, recent contributions to this literature has become much more informative for the policy makers. An active development of this field and its methods suggests that we are about to learn much about the role of gender and other compounding factors in the above contexts. In other words, modern informed gender policy is just around the corner.

References

Adams, R. B., (2016). Women on boards: The superheroes of tomorrow? Leadership Quarterly, 27 (3). pp. 371-386.
Adams, R. B., Hermalin, B. E., & Weisbach, M. S. (2010). The role of boards of directors in corporate governance: A conceptual framework and survey. Journal of economic literature, 48(1), 58-107.
Adams, R. B., & Ferreira, D. (2009). Women in the boardroom and their impact on governance and performance. Journal of financial economics, 94(2), 291-309.
Adams, R. B., & Funk, P. (2012). Beyond the glass ceiling: Does gender matter?. Management science, 58(2), 219-235.
Afridi, F., Iversen, V. & Sharan, M.R. (2017), Women political leaders, corruption, and learning: evidence from a large public program in India. Econ. Dev. Cult. Change, 66 (1) pp. 1-30.
Ahern, K. R., & Dittmar, A. K. (2012). The changing of the boards: The impact on firm valuation of mandated female board representation. The Quarterly Journal of Economics, 127(1), 137-197.
Alam, Z. S., Chen, M. A., Ciccotello, C. S. & Ryan, H. E., (2018). Gender and Geography in the Boardroom: What Really Matters for Board Decisions? Mimeo. Available at SSRN: https://ssrn.com/abstract=3336445
Amini, M., Ekström, M., Ellingsen, T., Johannesson, M., & Strömsten, F. (2016). Does gender diversity promote nonconformity?. Management Science, 63(4), 1085-1096.
Barber, B. M., and Odean T. (2001). “Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment.” The Quarterly Journal of Economics 116, no. 1: 261-92.
Bernile, G., Bhagwat, V., & Yonker, S. (2018). Board diversity, firm risk, and corporate policies. Journal of Financial Economics, 127(3), 588-612.
Breen, M., Gillanders, R., McNulty, G., & Suzuki, A. (2017). Gender and corruption in business. The Journal of Development Studies, 53(9), 1486-1501.
Brollo, F., & Troiano, U. (2016). What happens when a woman wins an election? Evidence from close races in Brazil. Journal of Development Economics, 122, 28-45.
Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic literature, 47(2), 448-74.
Dabalen, A., & Wane, W. (2008). Informal payments and moonlighting in Tajikistan’s health sector. The World Bank Policy Research working paper 4555, https://elibrary.worldbank.org/doi/pdf/10.1596/1813-9450-4555
Dollar, D., Fisman, R., & Gatti, R. (2001). Are women really the “fairer” sex? Corruption and women in government. Journal of Economic Behavior & Organization, 46(4), 423-429.
Esarey, J., & Chirillo, G. (2013). “Fairer sex” or purity myth? Corruption, gender, and institutional context. Politics & Gender, 9(4), 361-389.
Faccio, M., Marchica, M. T., & Mura, R. (2016). CEO gender, corporate risk-taking, and the efficiency of capital allocation. Journal of Corporate Finance, 39, 193-209.
Hermalin, B. E., & Weisbach, M. S. (1998). Endogenously chosen boards of directors and their monitoring of the CEO. American Economic Review, 96-118.
Jha, C. K., & Sarangi, S. (2018). Women and corruption: What positions must they hold to make a difference?. Journal of Economic Behavior & Organization, 151, 219-233.
Jianakoplos, N. A., & Bernasek, A. (1998). Are women more risk averse?. Economic inquiry, 36(4), 620-630.
Kirsch, A. (2018). The gender composition of corporate boards: A review and research agenda. The Leadership Quarterly, 29(2), 346-364.
Lundeberg, M. A., Fox, P. W., and Punccohar, J. (1994). Highly confident but wrong: Gender differences and similarities in confidence judgments. Journal of Educational Psychology, 86( 1), 114
Pande, R., & Ford, D. (2011). Gender Quotas and Female Leadership. Background Paper for World Development Report, World Bank.
Rheinbay J. & Chêne, M. (2016). Gender and corruption topic guide, Transparency International, https://www.transparency.org/files/content/corruptionqas/Topic_guide_gender_corruption_Final_2016.pdf
Rivas, M. F. (2013). An experiment on corruption and gender. Bulletin of Economic Research, 65(1), 10-42.
Sila, V., Gonzalez, A., & Hagendorff, J. (2016). Women on board: Does boardroom gender diversity affect firm risk?. Journal of Corporate Finance, 36, 26-53.
Sung, H. E. (2003). Fairer sex or fairer system? Gender and corruption revisited. Social Forces, 82(2), 703-723.
Swamy, A., Knack, S., Lee, Y., & Azfar, O. (2001). Gender and corruption. Journal of development economics, 64(1), 25-55.
Terjesen, S., Sealy, R. & Singh, V. (2009). Women Directors on Corporate Boards: A Review and Research Agenda. Corporate Governance: An International Review, 17(3), pp.320–337.
Van Knippenberg, D., & Schippers, M. C. (2007). Work group diversity. Annu. Rev. Psychol., 58, 515-541.

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.

Effects of Civil Confrontation in Social Media

Posted on May 13, 2019 | Policy Brief

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This paper describes the practices of civil confrontation which can be found in social media (analyzing the cases of the Ukrainian segment of Facebook). The research shows that such practices can be used by interest groups to deliberately affect target audiences in certain ways and thus exacerbate civil confrontation or to expand its scope. Psychological effects of such practices for the society include monotony, ambivalence, desensitization and alertness. These effects can be used either to distract the attention from a certain issue or to enhance social mobilization, to reduce protest potential or to push large groups into impulsive actions, to impose contradictory ideas or to stimulate society to rethink values.

Civil Confrontation in Ukraine

Considering the warfare going on in Ukraine and the consequent state of society, it is important to clearly define what is going on between large social groups.

Figure 1. Continuum of Conflicting Sociopolitical Processes

A useful way to structure our thinking about these processes may be to use an approach to sociopolitical conflict presented in Iarovyi (2019), which suggests that the continuum of conflicting sociopolitical processes has 4 stages, as illustrated by Figure 1. In what follows we concentrate on the second stage, which is civil confrontation. Civil confrontation is defined as a form of intra-group confrontation in the society marked by a crystallization of value conflicts between opposing sides. It has the potential to escalate into other forms of conflict interaction as indicated by Figure 1. Unlike social tension, which is the earliest stage, the confrontation has an articulated ‘enemy’ image and identity. However, it is not as deep as a social conflict which has systematic and deep roots and exists in the framework of problems connected with values. It is also far from being a civil war since it does not include a military component and does not assume a dehumanization of the opponent.

Nevertheless, differences between the stages are rather vague. Within Ukraine one can observe social tensions between certain groups (such as civil servants of the “old generation” and new employees), social confrontation (e.g., between supporters of certain presidential nominees) and social conflict (e.g., between the believers of Russian and Ukrainian Orthodox Churches). The aggravation within this continuum occurs as a gradual buildup of the counteraction and change of the conflict gradient to a deeper one. For the society it might be beneficial to minimize the aggravation and identify the conflicts in their early stages. A simple way to identify conflicts is by studying communications in social media. In my dissertation, which is the basis for this policy brief, I perform this exercise.

Communication of Civil Confrontation

Sociopolitical conflicts are developing via communication, which is the linguistic representation of a conflict. The latter thrives via group polarization – transforming heterogeneous opinions of people into mutually exclusive opposing positions. To define the conflict of discourses in the Ukrainian segment of social media, it is necessary to consider both features of the modern Ukrainian political discourse in general and specific features of communication in social media.

Markers of Civil Confrontation in Ukraine

The overview of political conflicts in Ukraine allows me to define the general characteristics of Ukrainian political discourse which influence the growth of confrontation. They include (1) the exploitation of ethnic and civic identities; (2) the impact of the external (overseas) interest groups; (3) difficulties with defining the stage and type of the ongoing conflicts and (4) a lack of proactive work of the government on reducing the risks of conflict. These markers were taken into account during the research as the defining framework of the practices of civil confrontation, and they are attributed to a smaller or larger extent to the cases which were studied.

Characteristics of the Discourse in Social Media

In the context of competing discourses, communication in social media needs to be pragmatic and focused on broadcasting the own agenda of writers, otherwise a user who is overwhelmed with information from different sources will be distracted. Moreover, this communication should be interactive and cooperate with the audience in real-time to improve its impact (Westcott, 2008).

Communication in social media is often much more intense than in the real life. While people do not normally enter discussions in social media to “wage wars” (Whiting and Williams, 2013), the environment of the Internet itself is characterized by a weaker level of censorship and self-censorship, the absence of limits that restrict participants, quick responsiveness, scattering attention, a lack of real contact, interruption of public communication of two people by third parties, anonymity etc. Thus, communication in social media is less restricted for negative reactions of participants, less productive and at the same time more aggressive.

Psychological Practices of Civil Confrontation on Facebook

The psychological practices of civil confrontation are defined as a set of established methods and techniques within the community which allow an individual to engage in interactions of social institutions and change one’s own psychological states and processes. In the process of reproducing such practices in communication, the emotions, settings, stereotypes, and value orientations of the communicator are changed.

The research of such practices in Ukrainian social media used the critical discourse analysis (CDA) model by Norman Fairclough (1992), with the selection of 6 cases that differ in the intensity of verbal confrontation, the intensity of the discourses’ struggle in the virtual environment and the spread of discourses outside the virtual environment.

The source of empirical material are Facebook accounts of users who take active role in political life and communication in Ukraine. We select Facebook firstly since this platform in Ukraine is highly politicized and represents various views of political communicators who are often absent on YouTube, Twitter etc., and secondly, it publishes large texts, sometimes with a strong visual component, which allows to utilize the CDA comprehensively.

Effects of the Civil Confrontation

Monotony

The effect of monotony, or the reduction of motivation to control the activities and participate in social life, is reproduced due to excessive exploitation of some discourses in society.

The first case in which this effect is present is the story of Ukrainian boxer Oleksandr Usik who took part in a fight in Moscow, the capital of the aggressor state according to Ukrainian legislation. Some parts of the Ukrainian community met this event with strong condemnation. Sports and culture are traditionally considered the elements of “soft power”. Thus they are often used (or believed to be used) for political purposes. However, citizens who are less politically motivated often tend to doubt the political ideologies and put their personal sympathies to a certain person in the first place. The social media communication regarding this case was characterized by a segregation of community members depending on their belief in the statement “sport/art is outside of politics”, and caused numerous arguments between communicators. At the time, this very situation made more and more people voice their tiredness of the war (which is subconsciously perceived as the reason for the argument). It leads to the gradual implantation of the idea that “the war is the case of the politicians, and the peoples of Ukraine and Russia are friendly”, and could strengthen the position of pro-Russian politicians in Ukraine. The implantation of this idea is beneficial for Russia, as it lowers the loyalty of Ukrainians to their own state and discredits the authorities.

The second case relates to public protests of the Ukrainian opposition in 2017-2018 which never caused a really strong reaction of the ordinary citizens. Discursive instruments used to involve more people into protests (the famous phrase “Kyiv, get up!” which was used during Euromaidan in 2014) did not work since the society was tired of regular protests in 2016-2017 on every slightest occasion, each of them labelled “a Third Maidan” by the organizers. The monotony “filled” the public discourse with unnecessary information, people became tired of protests and manipulations, and the protests became marginalized. Thus, the monotony effect could be used for the diversion of attention, the reduction of the protest potential or the formation of the social “fatigue” (sharp decline of the ability and motivation to perform the social roles and functions or stand for the position). Getting out of this state is possible if the rhythm of the information supply changes and its foci are shifted, which will lead to new reactions and roll the discourse out, making it topical once again.

Ambivalence

The ambivalence, or the duality of the attitude of the same person to the same object/phenomenon, instead of monotony, leads to the production of public anxiety and nervousness. It was identified on the case of “derusification”, when one prominent Ukrainian official labelled Soviet and pre-Soviet poets and writers (V. Vysotskiy, V. Tsoi, M. Bulgakov) as the “tentacles of the Russian World” (i.e. Pax Russia).

The discussions over this case not only intensified contradictions among participants, they also led to the expansion of civil confrontation. While in the previous case with the boxer, the incitement of the hostility on the everyday level failed as the issues are rather unimportant, in case of famous poets and singers the incitement affects deeply rooted notions and nostalgia of the communicators and is much more efficient. With the growing hostility between communicators of opposing sides, it leads to disorganization of thoughts of hesitant people (e.g. those who have warm feelings about the Soviet culture and sub-culture despite supporting Ukraine in its war with Russia). As a result, communicators tend to be more nervous when making decisions and taking actions (physical actions or discursive). Thus the ambivalence effect could be used to push people to commit impulsive actions and diminish their rational thinking. Reducing its negative effects is possible via engaging the society into a dialogue, promoting compromise proposals and sticking to the principles of mutual respect in the process of communication.

Desensitization

The effect of desensitization, or diminishing the emotional responsiveness of the society to violent actions, arises from the practices of discourse discreditation and determining the boundaries of what is permitted, and is connected primarily with the loss of sensuality by the communicators. It was identified in the case of attacks on Roma people in Ukraine which were widely criticized on the official level but considered quite normal by a large amount of “ordinary people” in social media. The justification of the violence and lack of mass condemnation of the aggressive actions raise the threshold of sensuality in the society which leads to tolerating violence against certain groups (in this case – ethnic groups).

The toleration of violence could be further extended to other groups (such as political opponents). If this effect is implemented gradually, the negative consequences may not be visible until it is too late. Minimization of the negative impact is possible via disclosure of information about such practices, drawing attention to them and articulating the importance of preserving the universal human values.

Alertness

The effect of alertness, or the state of being highly aware and ready to face confrontation, arises as a result of communicators’ reaction to actions of their opponents. It was traced in the cases of “Euro-plates” (massive importation into Ukraine of not-cleared cars with European license plates) and “Night on Bankova” [the street where the Presidential Office is located] (demands of civic activists for investigation of the allegedly political murder). The first case demonstrates a self-organized non-political platform of owners of such cars, which without the support of any recognizable politician managed to effectively protect their economic interests through communication of their idea to the masses. The second case suggests that due to the use of moderate and non-violent methods of communication and action by civil activists, as well as the high authority and recognizability of communicators, their ideas are attractive: the public accepts them and the authorities demonstrate readiness for the dialogue. It works much better than pushing people to radical actions, as in the case of monotony of street protests. In both cases described above in the context of alertness, a minority conversion takes place, where the discursive impact of the self-organized group is being spread to a broader public. Due to reassessment of the values this effect can potentially be used by interest groups to achieve their political goals and mobilize groups of supporters.

Conclusion

The above described effects can be used to distract public attention, to change (increase or decrease) the level of protest potential, to push people towards impulsive actions, to impose contradictory ideas or to stimulate the society to rethink values – both in a positive or negative way. These effects can be utilized by interest groups to draft the agenda and establish domination of their own discourse in the public sphere.

Thus, the actions to be taken by governmental decision makers who want to deal with negative consequences of such effects are: (1) engaging in the dialogue with the society, (2) responding to the mobilization of large groups of people with policy actions, (3) drawing attention to the importance of human rights (and actually pursuing this policy on the state level instead of only declaring it). One of the major activities here is monitoring aimed at a timely detection of dangerous trends and handling communication in a proper way.

Further research in this direction could be focused on assessing the impact of psychological effects on various target groups in the society in the short- and long-term perspective.

References

Fairclough, Norman, 1992. “Discourse and social change”, Cambridge Polit Press, 272 p.
Iarovyi Dmytro, 2019. Psychological practices of civil confrontation in social media. Dissertation, Institute for Social and Political Psychology, National Academy of Educational Sciences of Ukraine, Kyiv.
Westcott, Nicholas, 2008. “Digital diplomacy: The impact of the Internet on International relations”, Research Report of Oxford Internet Institute, 16, 20 pages.
Whiting, Anita; and David Lindsey Williams, 2013. “Why people use social media: a uses and gratifications approach”, Qualitative Market Research: An International Journal, 14(4), 362-36

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.

Do Macroprudential Policy Instruments Reduce the Procyclical Impact of Capital Ratios on Lending? Cross-Country Evidence

Posted on May 6, 2019 | Policy Brief

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In this brief, we ask about the capacity of macroprudential policies to reduce the procyclical impact of capital ratios on bank lending. We focus on aggregated macroprudential policy measures and on individual instruments and test whether their effect on the association between lending and capital depends on bank size. We ﬁnd that macroprudential policy instruments reduce the procyclical impact of capital on bank lending during both crisis and non-crisis times. This result is stronger in large banks than in other banks. Of individual macroprudential instruments, only borrower-targeted LTV (loan-to-value) caps and DTI (debt-to-income) ratios weaken the association between lending and capital and thus act countercyclically. With our study, we are able to support the view that macroprudential policy has the potential to curb the procyclical impact of bank capital on lending and therefore, the introduction of more restrictive international capital standards included in Basel III and of macroprudential policies in general are fully justiﬁed.

Macroprudential policy after the GFC

The Global Financial Crisis (GFC) highlighted the need to go beyond a purely microprudential approach (i.e. focusing on the health of individual firms) to regulation and supervision of the banking sector. The empirical literature supports the view that macroprudential policies (i.e. those addressing the general condition of the whole financial system) are able to decrease the vulnerability of the banking sector (see Claessens et al., 2013 for a review, and Cerutti et al., 2015). The increased resilience of the banking sector means that banks are able to absorb losses of greater magnitude – due to higher capital buffers (or provisions) or better access to funding sources, thus reducing the likelihood of a costly disruption to the supply of credit (CGFS, 2012), in particular during crises or recessionary periods. Considering this, macroprudential policies are expected to reduce the procyclical impact of capital ratios on loan supply.

Lending activity of banks and capital ratio nexus

It is a well-known tenet in the banking literature that capital adequacy rules have an impact on the behaviour of banks (Borio & Zhu, 2012). They are expected to protect banks from economic death, i.e. from insolvency or going bankrupt. Previous literature stresses the importance of capital ratios for lending behaviour, during both good economic conditions and in crisis or recessionary periods, in particular in banks with thin capital ratios, and thus insufficient buffers needed to cover loan-losses, (see Beatty & Liao, 2011; Carlson, Shan, & Warusawitharana, 2013) or in large banks (Beatty & Liao, 2011). The problem of the effect of capital ratios on bank lending has been studied extensively since the 1990s, when the ﬁrst Basel Accord was introduced as an international capital standard (see Jackson et al., 1999). In the wake of the recent GFC, the topic has attracted renewed attention as concerns have arisen that large losses at banks would hinder their capital adequacy and restrain their lending. Capital is found to affect lending behaviour in large publicly-traded banks by Beatty and Liao (2011) and in US commercial banks by Carlson et al. (2013). Additionally, in a cross-country study, Gambacorta and Marqués-Ibáñez (2011) show that publicly traded banks tend to restrict their lending more during recessions or crisis periods due to insufficient capital ratios. Such an effect is referred to as a procyclical capital ratio on bank lending (Beatty & Liao, 2011; Peek & Rosengren, 1995a).

However, previous literature on the link between lending and capital can be roughly subdivided into two groups: The studies that considered macroprudential policy instruments have been limited to individual countries (United States by Beatty & Liao, 2011 and Carlson et al., 2013; France by Labonne & Lame, 2014; United Kingdom by Mora and Logan, 2011), so that all banks were equally affected by the country’s banking policy and regulations. In turn, the studies that focused on the link between lending and capital across countries, have not accounted for macroprudential policy and its instruments (Gambacorta & Marqués-Ibáñez, 2011).

In our recent paper (Olszak, Roszkowska, and Kowalska, 2019) we extend the existing research by exploring the countercyclical effects of macroprudential policy factors on the association between loan growth and capital ratios on a large cross-country panel.

Why can macroprudential policy affect the link between lending and capital ratios of banks?

While policy standard-setters argue that the new macroprudential approach to regulation and supervision should reduce procyclicality in banking, and in particular by increasing banks’ resilience, it should diminish the effect of capital ratio on loan supply, the empirical evidence on this subject is not available.

In our paper, we employ a cross-country data-set to examine whether the application of macroprudential policies affects the link between loan supply and capital ratios, before and during the 2007/2008 crisis period in a sample of over 4500 banks from 67 countries. The main purpose of the paper is to examine whether macroprudential policy instruments, which were in use before the GFC, had a signiﬁcantly negative impact on the positive association between lending and capital ratios, during the crisis and in the non-crisis period. If we identify such a negative effect, we will be able to empirically test the view that macroprudential policy is effective in increasing the resilience of banks and thus affects the procyclicality of bank capital regulation.

Based on the previous evidence, we ﬁrst hypothesize that the link between lending and capital is positive, and is reduced in countries which applied macroprudential policies in the pre-crisis period. Following the capital crunch theory (see Peek & Rosengren, 1995a; and Beatty & Liao, 2011), we expect that the link between lending and capital is strengthened in the crisis period, and is reduced in countries in which the use of macroprudential instruments was more extensive in the pre-crisis period and continued to be used during the crisis. As the association between loan growth and capital ratios, in particular during crisis periods, was found to be stronger in large banks (see Beatty & Liao, 2011), we also examine whether macroprudential policy effects on the association differ between large and other banks (i.e. medium and small).

We use the Bankscope database and data-set on macroprudential policies available in Cerutti et al. (2015) to test our hypotheses. We analyse the effects of macroprudential policies on the association between lending and capital ratio using individual commercial bank data from 67 countries over the period of 2000–2011.

Findings

We ﬁnd a consistent and strong effect of macroprudential policies on the association between loan growth and capital ratios.

Further, unlike previous studies on the link between bank vulnerability and macroprudential policy, we differentiate between large, medium and small banks, because previous evidence shows that capital ratios affect bank lending with a different magnitude, depending on the bank size (see Beatty & Liao, 2011). Indeed, we ﬁnd evidence in favour of the expectation that bank size matters for the impact of macroprudential policies for the link between lending and capital.

Analysis of the role of individual macroprudential policy instruments shows that only loan-to-value caps and debt-to-income ratios weaken the positive effect of capital ratios on lending. This means that in countries which apply such instruments, bank lending is not prone to shortages in capital buffers, in particular during financial crisis. Thus, the banking sector does not add to business cycle fluctuations.

We also identify which instruments are better at curbing the procyclicality of capital standards. In particular, we find that borrower targeted macroprudential instruments (such as loan-to-value caps) or restrictions on balance sheets of ﬁnancial institutions (such as dynamic provisions or leverage ratios), are more effective in reducing the procyclicality of capital standards.

Policy implications

Our ﬁnding that macroprudential policies are able to alleviate the impact of capital ratio on lending, in particular during the crisis, may have certain implications for policy makers in the area of implementation of commonly recognized standards targeted at the reduction of borrower risk-taking. Our results suggest that more frequent use of these instruments may create additional buffers in large banks and in emerging and closed-capital-account economies, thus making large banks’ lending and lending of banks in emerging markets and closed economies less affected by capital ratios during crisis periods. Therefore, in the current work aimed at creating macroprudential regulations, more attention should be focused on instruments which have the potential to reduce borrower risk.

References

Beatty, A., & Liao, S. (2011). Do delays in expected loss recognition affect banks’ willingness to lend? Journal of Accounting and Economics, 52, 1-20.
Borio, C., & Zhu, V.H. ( 2012). Capital regulation, risk-taking, and monetary policy: A missing link in the transmission mechanism? Journal of Financial Stability, 8, 236–251. doi:10.1016/j.jfs.2011.12.003
Carlson, M., Shan, H., & Warusawitharana, M.(2013). Capital ratios and bank lending: A matched bank approach. Journal of Financial Intermediation, 22, 663–687. doi:10.1016/j.jﬁ.2013.06.003
Cerutti, E., Claessens, S., & Laeven, L. (2015). The use and eﬀectiveness of macroprudential policies: New evidence. IMF Working paper WP/15/61.
Claessens, S., Ghosh, S., & Mihet, R. (2013). Macro-Prudential policies to mitigate ﬁnancial system Vulnerabilities. Journal of International Money and Finance, 39, 153–185.
Committee on the Global Financial System. (2012). Operationalising the selection and application of macroprudential instruments. CGFS Papers No 48. Bank for International Settlements. 2012.
Gambacorta, L., & Marqués-Ibáñez, D. (2011). ‘The bank lending channel. Lessons from the crisis.’ Working paper series No 1335/May 2011. European Central Bank.
Jackson, P., Furﬁne, C., Groeneveld, H., Hancock, D., Jones, D., Perraudin, W., Yoneyama, M. (1999). Capital requirements and bank behaviour: The impact of The Basle Accord. Basle: Bank for International Settlements.
Labonne, C., & Lame, G. (2014). Credit growth and bank capital requirements: Binding or not? Working Paper.
Mora, N., & Logan, A. (2012). Shocks to bank capital: Evidence from UK banks at Home and Away. Applied Economics, 44(9), 1103–1119.
Olszak, M., Roszkowska, S. & Kowalska, I. (2019). Do macroprudential policy instruments reduce the procyclical impact of capital ratio on bank lending? Cross-country evidence, Baltic Journal of Economics, 19:1, 1-38, DOI: 10.1080/1406099X.2018.1547565
Peek, J., & Rosengren, E. (1995a). The capital crunch: Neither a borrower nor a lender be. Journal of Money, Credit and Banking, 27, 625–638.

Acknowledgement: This Policy Brief is based on a recent article published in the Baltic Journal of Economics (Olszak, Roszkowska, and Kowalska, 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.

Trade Induced Technological Change: Did Chinese Competition Increase Innovation in Europe?

Posted on April 29, 2019 | Policy Brief

20190428 Trade Induced Technological Change Image 01

The last 30 years has witnessed a shift of the world’s manufacturing core from Europe and North America to China. A key question is what impact this has had on manufacturing workers in other developed economies, and also on innovation, patenting, IT adoption, and productivity growth. While a rigorous data analysis on these variables for developing economies, particularly in Eastern Europe, is not yet available, this brief examines the impact of the rise of China on innovation in Western Europe, and also reviews the evidence on the impact of the rise of China generally. Recent research by Bloom, Draca, and Van Reenen (2016) found that Chinese competition induced a rise in patenting, IT adoption, and TFP by 30% of the total increase in Europe in the early 2000s. Yet, we find numerous problems with the Bloom et al. analysis, and, overall, we do not find convincing evidence that Chinese competition increased innovation in Europe.

Few events have inspired the ire of economists as much as Brexit and the rise of Donald Trump, two events seen as related as both were a seeming reaction to both globalization and slowing economic growth, particularly as some (such as Trump himself) saw the former as a key cause of the latter. Both Brexit and the trade war spawned by Trump do seem to have had negative economic effects – US equities have suffered every time the trade war has escalated, while anecdotal reports and more sophisticated economic analyses seem to suggest that Brexit has cost the UK jobs.

And yet, there is a need for policy makers and economists to hold two ideas in our heads simultaneously: Trump’s trade war and Brexit may be policy disasters, and yet globalization can create both winners and losers, even if it is clear that, generally speaking, the overall gains are likely positive and large. This is likely also true of the rise of China – one of the most dramatic events in international economics in the past 50 years. Figure 1 shows the increase in trade with China from the early 1980s to 2017, a period in which US imports from China grew from 7 to 476 billion dollars.

Figure 1. Chinese Imports (in logs, deflated)

Source: World Bank WITS

The academic literature tends to show that this impact, the rise of China, may have cost the US as much as 2.2 million jobs directly (Autor et al.), and as much as 3 million jobs once all input-output and local labor market effects are included. While approximate, these numbers are large enough for the China shock to have played a role in the initial onset of “secular stagnation” – the growth slowdown which began around 2000 for many advanced nations, including the US and Europe. In addition, Autor et al. (forthcoming) found that Chinese competition also resulted in a decline in patent growth. In the European context, however, other authors have found that although China did do some damage to certain sectors, overall, it does not appear to have been quite as damaging, particularly in Germany, which also benefitted from exporting increased machine tools to the Chinese manufacturing sector. And, in a seminal paper, Bloom, Draca, and Van Reenen (2016) find that Chinese competition actually led to an increase in patents, IT adoption, and productivity in Europe from 1996 to 2005, along accounting for nearly 30% of the increase. This is important, as it implies that without the rise of competition with China, the slowdown in European growth would have been even more pronounced than it was. It also implies that, far from being a source of stagnation, Chinese competition has been a source of strength. It also makes it more likely that the slowdown in growth since 2000 was caused by supply-side factors, such as new inventions becoming more difficult over time, as is perhaps the leading explanation among economists, notably Northwestern University business professor, Robert Gordon (2017), and also supported by others (see this VoxEU Ebook featuring a “who’s who?” among economists). It would also be evidence that contradicts the “Bernanke Hypothesis” that the former US Fed Chair first laid out in a 2005 speech at Jackson Hole, in which he suggested that international factors – particularly the savings glut and US trade deficit – were behind falling interest rates in the US. Since then, Ben Bernanke has followed up with a series of blog posts suggesting that these international factors were the cause of the initial onset of secular stagnation.

Figure 2. European Growth Relative to Trend

Source: World Bank WDI

In this brief, I present new research in which my coauthor and I test the robustness of the research finding that China had a positive impact on innovation in Europe (Campbell and Mau, 2019). We find that these findings are very sensitive to controls for time trends and other slight changes in specification. We also find that the number of patents matched to firms in the sample shrinks over the sample period (from 1996 to 2005). Overall, we conclude that, unfortunately, it is unlikely that the rise led to a significant increase in innovation in Europe, although more research is needed. Our research also sheds light on the so-called “replication crisis” currently gripping the social sciences, as researchers begin to realize that many published findings are not robust.

Trade-Induced Technical Change?

Bloom, Draca, and Van Reenen (2016) – hereafter BDV – tried to isolate the impact of the rise of China on Europe using several methods, using firm-level data for Europe. They placed each firm in a 4-digit sector, where they measured imports from China over time. First, they just looked at changes in patents, IT, and total factor productivity (TFP) at the firm level for sectors in which Chinese imports increased a lot vs. other sectors. But, because economists are always weary of the difficulty of isolating a causal relationship from non-experimental data, the authors, worrying that the sectors which saw increases in Chinese imports might differ systematically from the others, the authors also used what is called an instrumental variable. That is, they used the fact that when China joined the WTO in 2001, they also negotiated a reduction in textile quotas. Thus, BDV reason that textile sectors which had tightly binding quotas prior to removal were likely to have had fast growth in Chinese imports after China’s accession to the WTO. Thus, they end up comparing textile sectors in which the quotas were binding to sectors in which they were not binding. We went back and compared the evolution of patents in these same groups (sectors with binding textile quotas vs. not binding) below in Figure 3.

Figure 3. Patent Growth in China-Competing Sectors (Quota Group) vs. Other Sectors

Notes: The vertical red lines are dates when textile quotas were removed. The blue line shows the evolution of patents in the sectors without binding quotas (non-competing sectors), and the red line is the evolution of patents in the China-competing sectors. The dotted lines are 2 standard deviation error bounds.

What is immediately obvious in Figure 3 is that patents are declining rapidly over the whole period in both groups. The overall level of patents was falling in both groups for the full period. There is a 95.8% decline in patenting for the China-competing group, vs. a 96.2% decline for firms in the non-competing (“No quota”) group. By 2005, average patents per firm are close to zero in both groups (.04 in the China-competing sectors vs. .11 in the others). However, in the “No quota” group, the initial level of patents – close to three per firm per year – was much larger than in the quota group. Since patents are falling rapidly in both groups but bounded by zero, the level of the fall in patents in the non-quota group is larger, but one can easily see that much of this decline happens before quotas are removed. If we control for simple time trends, the effect goes away. Also, given the tendency of patents to decline, we can also remove the correlation between Chinese competition and patent growth in some specifications by simply controlling for the lagged level of patents. The overall declining share of patents in the BDV data also raises questions about data selection issues, as patents granted in the BDV data in the later years were a smaller share of the total patents actually granted in reality.

BDV also look at the impact of the rise of China on IT adoption. However, here they proxied IT adoption by computers per worker, but they did not collect enough data to control for pre-trends properly in the data, so we cannot be sure whether this correlation is causal or not. (For what it is worth, on the data we do have, from 2000 to 2007, including trends in the data renders the apparent correlation between Chinese import growth and computers-per-worker insignificant.)

Lastly, BDV look at the impact of the rise of China on TFP growth. Here, unlike before, we find that their measure is robust across various estimation methodologies. However, when we look at changes in a commonly used alternative measure of productivity, value-added per worker, instead of TFP (as TFP needs to be calculated using strong assumptions about the functional form of technology), we find no impact (see Figure 4 below).

Figure 4. Value-Added per worker Growth: China-competing sectors vs. others

Figure 4 above compares the evolution of value-added per worker in the most China-competing sectors vs. the others. Trends look similar for firms in either group of sectors (China-competing or otherwise), and we do not find a correlation. We also do not find that Chinese competition led to an increase in profits, nor an increase in sales per worker (in fact, we found a significant decrease in most specifications).

Conclusion

All in all, we find that the BDV findings suggesting that the rise of China had a large impact on innovation in Europe is not robust. However, in most specifications, we also don’t find a negative impact as did Autor et al. (forthcoming) for the US. This might have to do with data quality, although it does seem to be closer to other work, such as Dauth et al. (2014), which suggests that the rise of China had a smaller impact in Germany than in the US.

We also felt it was a bit alarming that a simple plot of the trends in patents for China-competing and not-competing sectors was enough to seriously question the conclusions of BDV, as their paper was published in the Review of Economic Studies, a top 5 journal in academic economics. If influential articles published in the most fancy journals can exhibit such mistakes, this underscores the extent which the profession of economics may suffer from many published “false-positive” results. The reasons why this could be the case are obvious: researchers are under pressure to find significant results, as top journals don’t often publish null results, and replication is exceedingly rare in a field in which one needs to make friends to publish. However, there are signs that replication is becoming more mainstream, and as it does, we can certainly hope that voters around the world will turn back to science.

References

Autor, D., D. Dorn, G. H. Hanson, G. Pisano, and P. Shu. Forthcoming. Foreign Competition and Domestic Innovation: Evidence from US Patents. Forthcoming: AEJ:Insights.
Bloom, N., M. Draca, and J. Van Reenen. 2016. “Trade Induced Technical Change? The Impact of Chinese Imports on Innovation, IT and Productivity.” The Review of Economic Studies 83 (1): 87–117.
Campbell, Douglas and Mau, Karsten. 2019.. Trade Induced Technological Change: Did Chinese Competition Increase Innovation in Europe?”, mimeo
Dauth, W., S. Findeisen, and J. Suedekum. 2014. “The Rise of the East and the Far East: German Labor Markets and Trade Integration.” Journal of the European Economic Association 12 (6): 1643–1675.
Gordon, R.J., 2017. The rise and fall of American growth: The US standard of living since the civil war (Vol. 70). Princeton University Press.

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

The Nordic Model of Prostitution Legislation: Health, Violence and Spillover Effects

Posted on April 21, 2019 | Policy Brief

An emerging literature is studying, with the help of new types of data and clever identification strategies, the effects of different legislative measures regulating the market for sexual services. The primary target of such measures are arguably the participants in the market, prostitutes and their clients, and law and order concerns in their immediate vicinity. In a new research project, we mean to shift the spotlight on potential broader spillovers from these policies, both to other outcomes and other countries. In their presence, we cannot understand the full impact of a law change if we limit our analysis to the prostitution market in that country alone. We focus on a particular model of prostitution legislation, first adopted in Sweden in 1999 and known since as the Nordic model.

The Nordic model

The debate on prostitution legislation shares clear similarities with the standard arguments put forward for or against alcohol prohibition or drug liberalization. The criminalization of an activity is most likely shrinking the corresponding market, because it increases the cost of participation. It also functions as a signal of what a society deems acceptable or not, and coordinates behavior to potentially change social norms. At the same time, however, it pushes the remaining market into the darkness, where criminal activity potentially increases. In the specific case of the prostitution market, what is particularly feared is an increased risk of violence and general worsening of conditions for the potentially fewer sex workers.

When, in 1999, Sweden enacted the first asymmetric criminalization of prostitution, whereby buyers but not sellers of sexual services are punished, a third way between criminalization and legalization seemed to appear. This legislation would still give a clear signal on societal values, but at the same time protect the, in large part female and in large part exploited, sex workers. The model proved very successful in deterring street prostitution, and, under the catchy name of the “Nordic model”, has subsequently been adopted by Norway, Iceland, Canada, and France. It is currently under consideration in further countries as well.

This is where most reports and policy evaluations stop. In a new project at SITE, involving an international research cooperation, we propose to investigate the impacts of this legislation beyond the participants in the prostitution market. Specifically, we encompass other outcomes such as gender-based violence, health outcomes and online behavior, both within Sweden and other countries that implemented the reform, but also, most importantly, across their borders. The idea is that law changes in one country may also affect the demand and supply of prostitution in other countries, especially but not exclusively those bordering the country that enacts the law change. Two possible channels for such cross-border effects are sex tourism and human trafficking.

This brief summarizes the preliminary evidence we collected so far.

Violence

The focus on the role of policies is a recent but rapidly growing addition to the economic literature on prostitution. The risk of violence, both for the participants and within the neighboring geographic areas, is a natural area of concern for policy in relation to the sex market, and to criminal activities in general. To improve on cross-country comparisons and draw causal links from policies to outcomes, the most robust contributions in this area focus on natural experiments. Cunningham and Shah (2018) study an unintentional, and therefore unexpected and temporary, decriminalization of indoor prostitution in Rhode Island, and find that reported rape offences fall by 30%. Cunningham and coauthors (2019) also look at the geographic expansion of the erotic services section of Craigslist, a popular advertisements website, before online solicitation was banned in 2018. The possibility to use online platforms for their work, by allowing prostitutes to keep mostly indoors, and screen their potential clients to a larger extent, appears to have been very beneficial: the study finds lower female homicide rates by 10-17% when and where the service was available. Ciacci and Sviatschi (2018) find that the opening in a neighborhood of indoor prostitution establishments decreases sex crime by 7-13%, with no effect on other types of crime, arguing that the reduction is mostly driven by potential sex offenders resorting to the establishments, instead, to satisfy their needs. What is common to these studies is the finding that allowing the sex market to exist in some form is beneficial for outsiders, while indoor prostitution is safer for the sex workers themselves.

Preliminary findings from our project (Berlin et al., 2019 a) are consistent with this. We base our strategy on a comparison, within Sweden, between counties that are above or below average in terms of representation of women among police force and elected officials (we refer to them as treated and control counties, respectively). Both these indicators have been found in previous studies to drive greater reporting and lower incidence of crimes against women (Iyer et al., 2012; Miller and Segal, 2018). Looking at population-wide rates of violence against women in Sweden, we observe an increase in assaults committed by acquaintances indoors by about 10% and an increase in rapes indoors by more than 20% in treated as compared to control counties. Since the reform is argued to have eliminated street prostitution, and pushed the remaining sex trade indoors, violence against prostitutes will be counted in the indoor assaults statistic. However, in treated counties, where we observe the increase in violent crimes against women, we at the same time find fewer convictions for buying sex. We argue therefore that the increase in assaults we observe is not likely in the context of the sex market, but rather indicates increased violence against non-prostitutes from frustrated former customers, in other words a negative externality of deterring prostitution. In order to distinguish whether this increase is only in reported or actually committed crimes, we look at hospitalizations of women for injuries that are related to sexual interactions. If we think that seeking hospital care is less sensitive than reporting a violent man to the police, the series of hospitalizations should be closer to the true violence than the convictions. Although numbers are small and differences not significant, hospitalizations spike up in treated counties directly after the reform, as Figure 1 shows. All in all, our preliminary evidence from Sweden suggests that intimate partner violence and violence on women in general might have increased as a consequence of the “Nordic model”.

Figure 1. Hospitalizations of women

Source: Hospitalizations of women for injuries related to sex, from Berlin et al. (2019 a).

Other outcomes

Besides violence, health outcomes are also a policy relevant objective with the regulation of prostitution. Indicators such as the spread of sexually transmitted infections serve the double purpose of giving a rough indication of the changes in the size of the sexual market while at the same time enabling inference on the work environment and general living conditions for prostitutes. In a companion paper, which is underway, we examine these statistics for Sweden and Norway, in terms of within country changes but also with a mind to capture potential cross-border spillovers between the two countries.

Cross-border spillovers

In another working paper (Berlin et al., 2019 b) we study the reform enacted in France on April 13th, 2016, which removed the punishment for solicitation of prostitution (previously set to two months imprisonment plus a fine) and introduced instead a range of fines for the purchasing of sexual services, thereby, pushing the punishment to the side of the buyer. In order to study the cross-border effect of this change, we focus on the German Bundesländer bordering France: Baden-Württemberg, Saarland and Rheinland-Pfalz. The national law in Germany generally allows prostitution, but gives federal states the right to regulate it on a more detailed level. This generates variation at the level of the Gemeinde, the administrative division corresponding roughly to a municipality. The idea behind our analysis is to compare municipalities where prostitution is at least in part allowed with municipalities where it is banned (we refer to them as treated and control municipalities, respectively). Our preliminary results show that foreign tourism to cities where prostitution is at least partly legal increased after the reform more than to those completely overlapping with a Sperrbezirk, i.e. an area in which prostitution is banned. However, so does domestic tourism. This might be seen as a threat to our interpretation, since we can’t connect this increase directly to the French reform, unless we can show that there is a dynamic adjustment of the supply of sexual services, which also attracts domestic flows. We can’t isolate tourism from France in this data, so we go a step further by looking at online behavior.

Google searches

A key contribution of this project is to gather new data that haven’t been analyzed to date in the existing literature. In particular, we collected detailed data on Google searches originating in France using as keywords different German cities. The idea is to capture potential deviations of search trends over time driven by prostitute customers who after the legislative change find it more attractive to look for sexual services across the German border. Preliminary findings show that after the policy change there is a larger increase in search activity for cities closer to the French border relative to cities further away. While searches are generally downward trending over time, the trend is slowed after the French reform, and this effect is stronger the closer a city is to the border, although intermittently significant. Figure 2 reports the differential increase in searches (with 95% confidence intervals) as related to the distance from the border. The negative relationship between size of the impact and distance to the border is consistent when controlling for city and time fixed effects. However, further analysis is needed in order to validate the results and control for confounding factors.

Figure 2. Google searches for German cities before and after the French reform

Source: Google Search data on searches originating in France for cities closer to VS farther from the German border than the indicated distance (in km).

We are currently repeating the same exercise at the French borders with Belgium and Spain, with searches originating in Norway around the time of the Norwegian reform (2009), and at the US-Canada border around the time of the Canadian reform (2014).

Conclusion

When adopting a version of the Nordic model in 2014, the Canadian Department of Justice stated that the “overall objectives [of the reform] are to:

Protect those who sell their own sexual services;
Protect communities, and especially children, from the harms caused by prostitution; and
Reduce the demand for prostitution and its incidence.”

Research seems to show that restrictions on the sexual services market, rather than the sex trade itself, have substantial negative impacts on communities and sex workers. Nevertheless, it is understandable that legislators in many countries, sharing similar concerns and expectations as expressed by the Canadian DoJ, find it unattractive to legalize prostitution. What our project points to, then, is that when considering various forms of criminalization, it is crucial to understand how best to pursue each of these objectives. Taking into account side-effects, or spillovers, such as the ones we highlight above, might reveal the need for complementary policies, in order to avoid unexpected and counterproductive consequences.

References

Berlin, Maria P.; Giovanni Immordino, Francesco F. Russo and Giancarlo Spagnolo, 2019 a. “Prostitution and Violence. Empirical Evidence from Sweden”, Unpublished manuscript.
Berlin, Maria P.; Ina Ganguli, and Giancarlo Spagnolo, 2019 b. “Spillover effects from prostitution legislation: evidence on the Nordic model”, In progress.
Ciacci, Riccardo; and Maria Micaela Sviatschi, 2016. ”The Effect of Indoor Prostitution on Sex Crime: Evidence from New York City”, Columbia University Working Paper.
Cunningham, Scott; Gregory DeAngelo, and John Tripp, 2019. “Craigslist Reduced Violence Against Women.” (forth.)
Cunningham, Scott; and Manisha Shah, 2017. “Decriminalizing indoor prostitution: Implications for sexual violence and public health.” The Review of Economic Studies, 85.3, 1683-1715.
Iyer, Lakshmi; A. Mani, P. Mishra, & P. Topalova, 2012.”The power of political voice: women’s political representation and crime in India.” American Economic Journal: Applied Economics 4.4, 165-93.
Miller, Amalia R.; and Carmit Segal, 2018. “Do Female Officers Improve Law Enforcement Quality? Effects on Crime Reporting and Domestic Violence.” The Review of Economic Studies.

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.

Resident Altruism and Local Public Goods

Posted on April 15, 2019 | Policy Brief

This policy brief discusses residents’ voluntary payments for local public goods in Russian municipalities in a historic and a comparative international context. We emphasize the behavioral aspects of such collective action and the political economy risks of implementing this financial mechanism. Finally, we use data from the Russian Federal Treasury to offer empirical evidence on the regional variation in the amounts of these payments.

Theoretical grounds

One of the drawbacks of a system of fiscal federalism is that it often results in an inadequate distribution of fiscal authority between regional and local governments. As a result, municipalities may be incapable of levying a due amount of taxes for the provision of the required quantity or quality of local public goods. A solution to the problem may be found in residents’ voluntary monetary and nonmonetary contributions to local projects. In Russia these are financial contributions to projects such as the renovation of roads, pedestrian bridges, parks, sports grounds and playgrounds, street lighting, the cleaning of ponds and rivers, etc. (Besstremyannaya, 2019). The experience of municipalities in the U.S. provides similar examples of residents’ financial contributions to municipal projects: here these resources are used, for example, as additional funds for financing secondary education (Winerip, 2003).

There are several potential theoretical explanations for the motivation of individuals to engage in such voluntary contributions. To start with, they can be motivated by purely altruistic concerns about local public welfare and the benefits of others (Ferris, 1984). Alternatively, the motives of individuals may be better (and, perhaps, more realistically) described by the approach of impure altruism (Andreoni, 1990), which trades off the amount of the public good against the size of contribution in motivating the behavior of the individual.

Further, the phenomenon of voluntary contributions is closely related to the desire of local authorities to substitute for insufficient budgetary revenues. As a result, residents may be coerced to submit monetary or in-kind labor payments for community development (Beard, 2007), for instance to put asphalt on rural roads (Olken and Singhal, 2011). Accordingly, instead of referring to residents’ contributions as donations, one may consider this mechanism of raising extra resources for local budgets as a type of informal tax. Arguably, altruism for the provision of public goods may be more prevalent among residents in developed countries, while contributions for local projects in developing countries reflect direct or indirect coercion by local authorities.

This policy brief analyses voluntary contributions to municipal budgets by residents in modern Russia. The presence of only fragmentary evidence from other countries limits our formal comparative analysis. However, we attempt to summarize common issues on the implementation of this financial mechanism.

Russian experience and legal framework

In contemporary Russia, residents’ contributions to local projects are called self-taxes (“samooblozheniye”) and constitute non-tax revenues of local governments (Article 131 of the Budget Code of 1998, Article 56 of the Local Government Law of 2003).

According to the Budget Code, self-taxes are fixed-size and one-time payments by residents for purposes of local projects, with the list of projects initiated directly by residents and voted at a local referendum. The projects commonly include activities on improving local infrastructure (Balynin, 2015). The December 2017 revision of the Local Government Law attempted to add additional incentives for self-financing by making it more targeted (in terms choosing urgent local projects) and easier to coordinate (in terms of organizing a referendum) by allowing referendums by residents of only selected parts of a municipality.

According to the Budget Code of the Russian Federation, self-taxes are earmarked items in non-tax revenues of local budgets, and may not be interrelated with other types of revenues or with the deficit of local government.

It should be noted that the use of self-taxes is not new in modern Russia: this funding mechanism was temporary exploited by Soviet authorities in the 1920s and 1930s, and was revitalized in the emerging Russian economy in the 1990s.

The early use of self-taxes in Soviet Russia illustrates the issue with the transformation of self-taxation into informal taxation. Self-taxation was introduced in 1924 as a formally voluntary decision of residents on financing local public goods. However, one may doubt whether the decision was indeed made by residents without pressure. Moreover, the lists of local public goods to be financed by self-taxes were determined by public authorities (Resolution by the Central Executive Committee and Soviet of National Commissars of the USSR of 3.08.1931). An illustration of the opposition to this informal tax may be found in the protocols of the council of residents of Roksanka, a village in Kaluzhskaya region from August 1928: citizens decided not to use self-taxes to finance a local school, since they believed there were sufficient budgetary funds – namely revenues from sold public property (Sergienko, 2015).

Calls to avoid similar retransformation of self-taxes into an informal tax were noted in modern Russia in 2006-2007, when the Bills on the amendments to the Local Government Law attempted to empower local authorities with the rights to deal with issues of self-taxation (Emetz and Makarov, 2016).

International experience

Private contributions in the form of monetary payments or labor participation are common in developing countries and are explained by the need to improve the insufficient quality of basic local public goods. For instance, the mechanism is used for road construction, water supply or primary education (Olken and Singhal, 2011). At the same time, residents of developed countries may choose to contribute to sustaining a high quality of local public goods: fire departments, medical centers, museums (Bice and Hoyt, 2000; Ferris, 1984). For example, the introduction of a redistributional mechanism of budgetary funds across rich and poor municipalities may lead to a decrease in the quality of public goods in the richest municipalities (owing to a fall in per capita funds after the redistribution). Accordingly, residents of rich municipalities may voluntarily decide to collect extra funds to recover the formerly high quality of public goods (e.g. secondary education in the U.S., see Brunner and Sonstelie, 2003; Winerip, 2003).

A common challenge to implementing a mechanism of voluntary payments is associated with the difficulties of reaching a decision within a large group of individuals. Indeed, residents may demonstrate selfish behavior or may follow selected local leaders (Jack and Recalde, 2015; Blackwell and McKee, 2003). Moreover, the common lack of enforcement instruments makes voluntary contributions unreliable (Slemrod, 1998).

Interestingly, the methods of dealing with non-compliance are similar across countries: the Perm krai of Russia, municipalities in the U.S. and villages in developing countries use techniques as such notification by mail, home visits, disclosing the lists of non-compliers and employing various ways of informal coercion by neighbors or public leaders (Olken and Sighal, 2011; Miguel and Gugerty, 2005; Winerip, 2003).

Data from Russian regions

We use the 2013-2016 annual data of the Russian Treasury, which allows disentangling self-taxes as an item in the list of non-tax revenues of local budgets. Owing to municipal-level data being unavailable, our analysis concerns the sum of local budgets in each region. Only 33 regions out of 83 analyzed regions had positive self-tax revenues in 2013, and the leading regions in 2015-2016 are the Tatarstan Republic, the Bashkortostan Republic, Kirovskaya oblast, Lipetskaya oblast, Kaluzhskaya oblast, and Perm Krai. The share of self-taxes in non-tax revenues is rather low: it amounts to 2-3% in Tatarstan, while it is less than 1% in the remaining regions (Table 1).

Table 1. Top regions according to levied self-taxes in 2015-2016

	Self-taxes in 2015		Self-taxes in 2016
	Thousand rubles	% of non-tax revenues of local budgets	Thousand rubles	% of non-tax revenues of local budgets
Tatarstan republic	122268.26	2.11	183413.26	3.44
Kirovskaya oblast	11431.02	0.50	7301.01	0.36
Bashkortostan republic	1943.96	0.02	2781.02	0.03
Lipetskaya oblast	3670.65	0.22	2701.14	0.16
Kaluzhskaya oblast	2073.97	0.11	2620.54	0.15
Permskii krai	3087.31	0.08	2335.02	0.06
Republic South Osetiya-Alaniya	1807.11	0.38	1451.16	0.30
Tyva republic	792.93	0.42	1342.60	0.78
Rostovskaya oblast	1307.36	0.02	1124.40	0.02
Zabaikalskiy krai	847.58	0.08	1092.68	0.11
Samarskaya oblast	1023.76	0.02	978.87	0.02

Arguably, the share of self-taxes in non-tax revenues is not associated with the desire to compensate for insufficient transfers from the federal or regional budgets: the absolute value of the correlation coefficient with the share of transfers to local budgets in non-tax revenues is below 0.25 (Besstremyannaya, 2019, Table 1). Similarly, we found no interrelation of the share of self-taxes with such socio-economic variables as (per capita) gross regional product and density of population.

Next, we focus on the policy of regional governments to provide budgetary funds on top of the money collected through self-taxes. As of 2016, such regional co-financing was present in the Tatarstan Republic, Kirovskaya oblast, Vladimirskaya oblast and Perm Krai (Emetz and Makarov, 2016; Balynin, 2015). The coefficient of regional co-financing of local projects (the amount of regional funds over the locally provided funds) equals 1 in Vladimirskaya oblast and varies from 1.5 to 5 in other above-mentioned regions. Examples of such co-provision of local public goods by region and municipalities include the renovation of water supply facilities in Perm Krai and the cleaning of lakes in Tatarstan (Nikitin, 2018, Platoshino budget, 2017).

Our estimates reveal that coefficients higher than 1 are associated with a higher prevalence of self-taxes. Indeed, the increase in the share of self-taxes in the revenues of local budgets in such regions is much higher than the corresponding growth in regions without co-financing or with unity co-financing (Besstremyannaya, 2019, Table 2).

Finally, we use the data for Perm Krai which experienced a recent reform with a rise of the coefficient from 3 to 5 in 2014. Our estimates of the treatment effect of such a reform and an extrapolation to other regions reveal that a unit increase of the coefficient causes a 55% growth in the share of self-taxes in non-tax revenues (Besstremyannaya 2019, Table 3).

To sum up, regional co-financing of local projects is associated with a growth in the collected self-taxes.

Conclusion

The phenomenon of voluntary contributions to local budgets is relatively common in real life. However, the literature addressing it is rather fragmented. In particular, little is known empirically on the motivation of individuals to engage in such contributions.

Our analysis with the 2013-2016 annual data for Russian regions reveals that residents’ contributions to local public goods are unrelated to insufficient revenues by local budgets. Moreover, the share of residents’ contributions in the budgetary non-tax revenues is positively associated with regional co-financing of these local projects. Hence, one may conjecture that in Russia, this phenomenon may be viewed as an altruistic attempt to raise quality of local public goods or as a means to signal about the most urgent local projects to regional governments.

References

Andreoni, J. (1990). Impure altruism and donations to public goods: A theory of warm-glow giving. The Economic Journal, Vol. 100(401), pp. 464-477.
Balynin I.V. (2015). The use of self–taxes of citizens in forming the revenues of the local budgets. Finansy i Upravleniye, No.2, pp. 53–62. (In Russian).
Beard, V. A. (2007). Household contributions to community development in Indonesia. World Development, Vol. 35(4), pp. 607-625.
Besstremyannaya G.E. (2019) Informal taxes for the provision of public goods in Russian regions. Voprosy Ekonomiki No.1, pp 124-134. (In Russian).
Bice D.C., Hoyt W.H. (2000). The impact of mandates and tax limits on voluntary contributions to local public services: An application to fire–protection services. National Tax Journal, Vol. 53(1), pp. 79–104.
Blackwell C., McKee M. (2003). Only for my own neighborhood?: Preferences and voluntary provision of local and global public goods. Journal of Economic Behavior and Organization, Vol. 52(1), pp. 115–131.
Brunner E., Sonstelie J. (2003). School finance reform and voluntary fiscal federalism. Journal of Public Economics, Vol. 87(9–10), pp. 2157–2185.
CEFIR project for the Ministry of Finance of the Russian Federation “The development of methodological recommendations for increasing the revenues of Russian regions and municipalities” (Final report of November 2017)
Emetz M.I., Makarov M.A. The self–taxation of citizens as a source of local budget revenues. Ekonomika i Menedgment Innovatsionnyh Tehnologii, No. 12, http://ekonomika.snauka.ru/2016/12/13433 (In Russian).
Ferris J.M. (1984). Coprovision: Citizen time and money donations in public service provision. Public Administration Review, pp. 324–333.
Jack B.K., Recalde M.P. (2015). Leadership and the voluntary provision of public goods: Field evidence from Bolivia. Journal of Public Economics, Vol. 122, pp. 80–93.
Miguel E., Gugerty M.K. (2005). Ethnic diversity, social sanctions, and public goods in Kenya. Journal of Public Economics, Vol. 89(11–12), pp. 2325–2368.
Nikitin, E. (2018) Self-taxation in Tatarstan republic provides for 4 to 1 budgetary cofinancing https://www.tatar-inform.ru/news/2018/02/16/593910/
Olken B.A., Singhal M. (2011). Informal taxation. American Economic Journal: Applied Economics, Vol. 3(4), pp. 1–28.
Platoshino budget for 2017 and forecast for 2018-2019. http://www.platoshino59.ru/index.php/2012-01-05-09-21-25/2016-08-28-09-18-38/item/403-publichnyj-byudzhet-platoshinskogo-selskogo-poseleniya-na-2017-god-i-planovyj-period-2018-i-2019-godov-byudzhet-dlya-grazhdan
Sergienko, N.S. (2015). Self-taxation as a form of voluntary participation of the population in socioeconomic development of settlements. Sovremennye Issledovaniya Sotsialnyh Problem, Vol. 1, No. 21, pp. 266–270. (In Russian).
Slemrod, J. (1998). On voluntary compliance, voluntary taxes, and social capital. National Tax Journal, Vol. 51(3), pp. 485–491.
Winerip, M. 2003. On Education: Giving green or turning red. The New York Times, Feb 26.

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.

Capital Flows from Russia — The Bigger Picture

Posted on April 8, 2019 | Policy Brief

A bunch of dollar bills covering table that represents capital flows in Russia

There is an increasing focus on how Russian capital flows are being channelled through Western banks to various destinations, including offshore havens. There are of course legitimate reasons and legal ways of moving capital across borders, but much of the international focus on capital flows in recent decades is linked to the financing of terrorism, tax evasion, and money laundering in connection with criminal activities. This brief provides the macro view of capital flows between Russia and the rest of the world to paint the bigger picture behind the more specific stories we read about in the news that involve individual businessmen, corrupt officials, criminals, and banks.

International capital movements have a clear role in allocating resources efficiently across countries. However, today’s media coverage instead typically focuses on the role of capital flows in financing terrorists and avoiding taxes. Recently, money laundering has been creating headlines around the world in the Panama papers and other similar stories, illuminating complicated schemes in the global financial system in connection with illegal activities such as tax evasion, corruption, drug dealing and human trafficking.

In the international policy making arena, since 1989, the Financial Action Task Force (FATF) has the objective “to set standards and promote effective implementation of legal, regulatory and operational measures for combating money laundering, terrorist financing and other related threats to the integrity of the international financial system”. After the terrorist attacks in 2001, the issues of anti-money laundering (AML) and combatting the financing of terrorism (CFT) also became a central area of the IMF’s work and has since become an increasingly important policy question.

In several of the news stories, money flowing from Russia features prominently. This brief provides the bigger picture of Russian capital flows based on publicly available data as a complement and background to the news stories that are based on inside information, or “leaks”, and that focus on particular individuals and banks.

Composition of capital flows

In the official balance of payments statistics, capital flows are divided into a number of different categories, for example, private vs public or banks vs non-banks. There is also a distinction made between foreign direct investments (FDI) on the one hand and portfolio flows, loans and other types of transactions (PLO) on the other. Since the balance of payments also has to balance (despite the fact that not all international transactions have been recorded) there is also a term called errors and omissions (E&O) that take care of various discrepancies. In environments with poor data collection and a large share of activities that take place “off the books”, this term tends to be large. For Russia, this term has become smaller over time as the economy and data collection has matured.

In terms of volatility and magnitude of flows, the distinction between FDI and PLO is often important and so also in Russia. Figure 1 shows the private sector flows to and from Russia over the last two plus decades.

Figure 1. Capital flows to and from Russia

Source: Central Bank of Russia and author’s calculations

After a rather slow start in the early years of transition, capital flows took off as Russia started to generate growth in 2001, and the flows kept growing until the global financial crisis. As expected, FDI flows have been less volatile than PLO flows but perhaps more surprising, in- and outflows in both categories seem to move closely together (see Becker (2019) on why this is the case). We can also note that there has been a marked downturn in flows at the time of the annexation of Crimea and subsequent sanctions and counter sanctions between the West and Russia.

Cumulative capital flows

By computing net flows from the data in Figure 1 and accumulating this over time, we get a clearer idea in Figure 2 of the massive amounts of capital that have left Russia over the last decades. In the early years, the outflows were in the form of errors and omissions (E&O) and PLO, but the PLO trend was reversed in the early 2000’s and turned total accumulated flows back to zero before the global financial crisis hit. The global financial crisis was a clear turning point for capital flows in general and PLO flows in particular.

Figure 2. Net private capital flows

Source: Central Bank of Russia and author’s calculations

In the year following the global financial crisis, almost USD 300 billion left Russia. Outflows then continued, albeit at a slower pace, only to accelerate again at the time of Russia’s annexation of Crimea. By mid-2018, USD 700 billion had left Russia since 2008, mainly in the form of PLO flows. This is equivalent to twice the amount of fixed capital investments in Russia in 2017.

For a country like Russia that is in need of increased investments both from domestic and foreign sources to generate long-term sustainable growth, these outflows are very costly at the macro level even if they are beneficial to individual entities that are behind the flows.

Destinations of capital flows

Where the money from Russia ultimately ends up should matter less to people in Russia than the fact that they are not invested and generating growth at home. However, it can matter a great deal to people, policy makers and businesses in the destination countries. Not only because it involves business opportunities and employment to some, but also because it generates concerns among regulators, law enforcement and tax authorities regarding the origins and purposes of the investments.

We do not have full coverage of where all the money Russian entities invest or park abroad end up, but official statistics are available for at least part of the investments. First of all, there is data on cross-border assets and liabilities of the banks that report to the Bank of International Settlement (BIS), which shows what foreign residents have deposited in the banks. Russian claims on BIS reporting banks are shown in Figure 3, where we can note that total claims by Russians amount to USD 131 billion. Half of this amount was deposited with French, Swiss, UK, and Belgian banks at the end of September 2018.

Figure 3. Russian claims on BIS reporting banks in different countries (USD bn, Sept. 2018)

Source: BIS and author’s calculations

Given the recent scandal in Danske Bank, we can also note that USD 8 billion was deposited by Russian entities in Danish banks, which may not sound much in this context but amounts to around 2 per cent of Danish GDP.

Again, macro level data does not tell us if the flows behind the numbers are illicit or legitimate, but it provides some sense of the order of magnitude and possible significance for the entities involved in the transactions and their regulators and supervisors.

The next piece of information is due to the IMF’s and others’ efforts to collect and harmonize data on the destination of portfolio and FDI assets, and the data for Russia is presented in Figures 4 and 5.

The prime locations for Russian owned portfolio assets are Ireland and Luxembourg, followed far behind by the Netherlands, UK and US. In total, official portfolio assets are rather modest at USD 69 billion, which is far off the cumulative net PLO flows in Figure 2 of over USD 500 billion even if we add the BIS reporting bank deposits in Figure 3.

Figure 4. Russian portfolio assets by the destination country (USD bn, Sept. 2018)

Source: Central Bank of Russia and author’s calculations

This could have many explanations, including that a significant share of Russian PLO assets is not in BIS reporting banks or in countries that provide transparent reporting of other types of PLO assets. The fact that cumulative flows and stocks reported in international statistics are so different, though, clearly asks the question where the remaining assets are invested.

The last component for which we have data is the location of Russian FDI assets. This turns out to be the most significant asset class available in the official statistics with a total of USD 364 billion invested abroad. Given that the magnitudes of FDI flows in Figures 1 and 2 are much smaller than PLO flows, this is somewhat surprising. Less surprising is the fact that more than half of this is invested in Cyprus, which is a well-known destination for Russian money.

However, it also begs the question on how assets are classified and where; Cyprus annual GDP was USD 24 billion in 2018, or 13 per cent of what is classified as Russian FDI assets in Cyprus. The only reasonable interpretation is that Cyprus is an offshore destination to park Russian money and not the ultimate location of direct investments from Russia. It is not unlikely that similar explanations are also valid for a significant share of the assets recorded as investments in the Netherlands, Austria and Switzerland, not to mention the British Virgin Islands (BVI) or the Bahamas. This problem is not unique for Russian data, but the magnitude of the problem regarding this data is still striking.

Figure 5. Russian FDI assets by the destination country (USD bn, Sept. 2018)

Source: Central Bank of Russia and author’s calculations

Policy conclusions

Capital leaving Russia is mainly a problem for investments and growth in Russia, but, as has become far too clear recently, some of the flows also create problems in other countries. In particular, flows that are associated with money laundering and channelled through financial institutions in the West can create massive problems for banks that do not have sufficient control mechanisms in place or are guided by short-term profit maximization that encourages staff to look the other way when illicit flows are coming in.

Given the massive scale of flows coming from Russia, it can obviously be tempting to be part of this business while at the same time very costly to implement procedures and routines that control all of the flows adequately. However, not understanding the bigger picture of Russian flows can be even costlier.

References

Becker, T, (2019), “Russia’s macroeconomy—a closer look at growth, investment, and uncertainty”, forthcoming SITE 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.