Project: FREE policy brief
The Gender Wage Gap in Belarus: State vs. Private Sector
This brief is based on research that studies gender difference in wages in Belarus using survey data from 2017. According to the results, the unconditional gender wage differential equals 22.6%. The size of the wage gap is higher in the state sector than in the private sector. Additionally, it increases in the state sector throughout the wage distribution and accelerates at the top percentiles, indicating the presence of a strong glass ceiling effect.
Introduction
The causes and consequences of the gender wage gap in the labor market, that is the difference between the wages earned by women and men, continue to attract increasing attention in empirical studies worldwide.
Belarus’ labor market is not an exception and faces the problem of wage inequality like other neighboring and transition countries. According to the National Statistical Committee of the Republic of Belarus (Belstat), the average gender wage gap in terms of monthly wages was 19% in 2000, it increased up to 23.8% in 2015, and reached 25.4% in 2017.
In this regard, this brief updates the estimates of the gender wage gap in Belarus. And it summarizes the results of the study on what the role of the state and private sectors are in the distribution of gender wage differences in Belarus (Akulava and Mazol, 2018).
Data and methodology
The data used in the research is from the Generations and Gender Survey (GGS) conducted in Belarus in 2017. This survey is a nationally representative dataset that is based on interviews of about 10,000 permanent residents of Belarus, aged 18–79, covering the whole country disaggregated by regions. The GGS contains information on a range of individual (age, gender, marital status, educational attainment, employment status, hours worked, wages earned etc.) and household-level characteristics (household size and composition, land holding, location, asset ownership etc.).
The analysis is based on the typical Mincer model of earnings that estimates individual wage income as a function of various influencing factors using the OLS approach (Mincer, 1974). Specifically, the Mincerian wage equation is defined where the log of the hourly wage rate is regressed on a set of male and female workers’ personal and job characteristics (educational level, working experience, occupational type, organization type, family characteristics, and region).
Next, we use the Oaxaca-Blinder (OB) methodology (Oaxaca, 1973; Blinder, 1973) to identify and quantify the contribution of personal characteristics and the unexplained component (which is referred to as differences in returns) to the wage difference between males and females.
Finally, we apply the Machado-Mata (MM) technique (Machado and Mata, 2005) to look into the nature of the wage gap at various points of the income distribution and also to test the difference for individuals employed in the state or private sectors. For the Machado-Mata procedure, we estimate our specifications at the 10th, 25th, median, 75th and 90th percentiles of the wage distribution.
Results
The analysis shows that women’s wages are lower than men’s wages all over the wage distribution. The average raw gender wage gap equals 22.6% and it increased substantially compared with 9.0% in 1996 and 17.8% in 2006, the numbers obtained in the study conducted by Pastore and Verashchagina (2011).
Figure 1. Gender differential by quantile of the wage distribution
Source: Authors’ estimates based on GGS.
The level of female earnings is lower than the male regardless of the occupational type, educational background, work experience and organizational type. Moreover, the underpayment of women is lower for low earning workers, but increases up to the end of the wage distribution (see Figure 1).
The OB decomposition shows that female educational attainment and job-related experience help to decrease the level of the wage gap slightly (see Table 1).
Table 1. Oaxaca-Blinder decomposition results
Source: Authors’ estimates based on GGS.
However, the occupational choice is leading to an expansion of the difference in earnings. However, its effect is also small, indicating that occupational segregation plays a minor role in explaining the gender wage gap. The major share of the gender wage gap is formed by the unexplained part, which is likely to be attributed to discrimination.
Next, the level of remuneration is higher among private companies. However, contrary to other countries in transition, the average gender wage gap in Belarus in the private sector is lower than in the public sector.
Moreover, the MM decomposition estimates presented in Table 2 demonstrate that the gender wage gap in the state sector shows evidence of the glass ceiling effect (the size of the total wage gap expands at the top of the wage distribution), while no evidence of either glass ceiling or sticky floor (the size of the total wage gap increases at the bottom of the wage distribution) in the private sector.
The negative coefficient near the characteristics part in the private sector shows that female endowments outweighs their male counterparts. Thus, controlling for personal characteristics, if the labor market rewards males and females equally, the wages of females in the private sector should be substantially higher (see Table 2).
Table 2. Machado-Mata decomposition of the observed gender wage gap by organization type
Source: Authors’ estimates based on GGS.
Finally, the results also suggest that female workers are better off being in the private sector at the lowest and the highest percentiles (i.e. the size of the gender wage gap is lower there compared to the 25th and 50th percentile).
A possible explanation for all the above is that institutional differences seem to play a crucial role here. First, Belarusian private firms work under stronger regulation than in other transition economies which makes it harder for them to set low wages. Second, they also operate under stronger competition (compared to state companies), which force them to identify individual productivity more correctly, narrowing the gender difference in pay. In contrast, the paternalistic attitude to women left as a legacy from the Soviet Union further increases the gender wage gap in the public sector.
Conclusion
In this brief, we present new evidence on the existence of a gender wage gap in the Belarusian labor market and analyze the differences in its distribution between the state and private sectors.
Our results show that the unconditional gender wage gap in terms of hourly wages equals 22.6%. Thus, jointly with a previous study (see Pastore and Verashchagina, 2011) and recent official indicators, all these indicate that the pace towards gender equality in Belarus seems to be sluggish. For the moment, all institutional changes accomplished by the Belarusian government to reduce gender discrimination are not enough and require additional efforts to cope with that problem.
However, the gender wage gap is shown to be much wider in the public sector than in the private sector. At the same time the private sector appears to be more attractive than the public sector in the country in terms of the level of remuneration. Therefore, additional structural shifts of the economy accompanied by the growth of competition are needed to induce a further reduction of the gender wage gap.
References
- Akulava, M. and A. Mazol. (2018). What Forms Gender Wage Gap in Belarus? BEROC Working Paper Series, WP no. 55.
- Blinder, A. (1973). Wage Discrimination: Reduced Form and Structural Estimates. Journal of Human Resources, 8, 436-455.
- Machado, J., and J. Mata. (2005). Counterfactual Decomposition of Changes in Wage Distributions Using Quantile Regression. Journal of Applied Econometrics, 20(4), 445‑465.
- Mincer, J. (1974). Schooling, Experience, and Earnings. New York: Columbia University.
- Oaxaca, R. (1973). Male-Female Wage Differentials in Urban Labor Markets. International Economic Review, 14(3), 693-709.
- Pastore, F., and A. Verashchagina. (2011). When Does Transition Increase the Gender Wage Gap? An application to Belarus. The Economics of Transition, 19(2), 333-369.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Social Media and Xenophobia
We study the causal effect of social media on hate crimes and xenophobic attitudes in Russia, using variation in social media penetration across cities. We find that higher penetration of social media leads to more ethnic hate crimes, but only in cities with a high baseline level of nationalist sentiment prior to the introduction of social media. Consistent with a mechanism for the coordination of crimes, the effects are stronger for crimes with multiple perpetrators. We show that social media penetration also had a persuasive effect on young and uneducated individuals, who became more likely to have xenophobic attitudes.
In recent years, the world has witnessed a large increase in expressions of hate, particularly of xenophobia. Candidates and platforms endorsing nationalism and views associated with intolerance toward specific groups have also gathered increased popular support both in the U.S. and across Europe. There is a lot of speculation about the potential drivers of this increase in the expression of hate. In our recent paper (Enikolopov et al, 2019) we study the role of social media in this process. This brief introduces the topic and offers a short outline of our findings.
Conceptually, social media could foster hate being expressed through different channels. First, social media reduces the cost of coordination. For example, there is evidence that it facilitates political protest (Enikolopov, Makarin, Petrova, 2018). Coordination facilitated through social media might be particularly relevant for illegal and stigmatized activities, such as hate crime: social media might make it easier to find like-minded people (through targeted communities and groups); it might also reduce the cost of asking or exposing oneself by providing a more anonymous forum for social interactions. Social media might also influence people’s opinions: tolerant individuals might be more exposed to intolerant views, while intolerant individuals might end up in an “echo chamber” (Sunstein 2001, 2017, Settle 2018) that make their views even more extreme. In our paper, we study the causal effect of social media exposure on xenophobic crimes and xenophobic attitudes in Russia and provide evidence on the particular mechanisms behind these effects.
The challenge in identifying a causal effect of social media is that access and consumption of social media are not randomly assigned. To surmount this challenge, we follow the approach of Enikolopov et al. (2018) and exploit a feature of the introduction of the main Russian social media platform – VKontakte (VK). This social media, which is analogous to Facebook in functionality, was the first mover on the Russian market and secured its dominant position with a user share of over 90% by 2011. VK was launched in October 2006 by Pavel Durov, its founder, who at that time was an undergraduate student at St Petersburg State University (SPbSU). Initially, users could only join the platform by invitation, through a student forum of the University, which was also created by Durov.
As a result, the vast majority of the early users of VK were students of SPbSU. This, in turn, made their friends and relatives more likely to open an account. And since SPbSU attracted students from around the country, this sped up the development of VK in the cities, from which these students were coming from. Network externalities magnified these effects and, as a result, the idiosyncratic variation in the distribution of the home cities of Durov’s classmates had a long-lasting effect on VK penetration. Following this logic, we use fluctuations in the distribution of student of SPbSU across cities as an instrument for the city-level penetration of VK. We then evaluate the effect of higher VK penetration on hate crimes and hate attitudes, combining data on hate crimes for the period between 2007 and 2015 collected by a reputable Russian NGO SOVA with survey data on hate attitudes.
Previous findings indicate that whether information from media induces people to be involved in the active manifestation of xenophobic attitudes or not depends on predispositions of the population. For example, Adena et al (2015) demonstrate that radio propaganda by the Nazis in the 1930’s was effective only in areas with a historically high levels of anti-Semitism. The role of the underlying level of nationalism is likely to be even stronger for social media, in which the content of the media itself directly reflects the attitudes of the population. This is particularly relevant for hate crimes committed by multiple perpetrators, in which social media can facilitate the coordination of such crimes.
Thus, we test whether the effect of social media depends on the pre-existing level of nationalism. To get at this underlying sentiment, we break cities by their level of support for the Rodina (“Motherland”) party, which ran in the national 2003 elections (the last parliamentary elections before the creation of VK) on an explicit nationalistic, xenophobic platform.
We find that penetration of social media leads to more ethnic hate crimes, but only in cities with a high baseline level of nationalist sentiment prior to the introduction of social media. For example, in cities with a maximum level of support of Rodina an increase in the number of VK users by 10% lead to an increase in ethnic hate crimes by 20%, while it had no significant effect on hater crime in cities with minimal support of Rodina. There is also no evidence that future social media penetration is related to ethnic hate crimes before the creation of social media, regardless of the level of pre-existing nationalistic attitudes.
Further evidence is consistent with social media playing a coordination role in hate crimes. The effect of social media is stronger for crimes perpetrated by multiple individuals (as opposed to crimes committed by a single person), where coordination is more important. These heterogeneous effects are also not consistent with results being simply driven by a higher likelihood of hate crime in places with higher social media penetration, unless this effect were present precisely in cities with higher support for Rodina and for crimes with multiple perpetrators, for example – which we find unlikely.
Having found evidence of a causal effect of social media on ethnic hate crimes, consistent with a mechanism of coordination, we turn next to the impact of social media on xenophobic attitudes. We designed and organized an online survey, and launched it in the summer of 2018, reaching 4,327 respondents from 64 cities. To measure xenophobic attitudes, we examined answers to the question “Do you feel irritation of dislike for individuals from some other ethnicities?” Note that, unlike the coordination of hate crimes, the persuasive effects of social media are not necessarily expected to be strongest in cities with higher baseline nationalistic sentiment since individuals on social media can get as easily connected to people outside their city. In fact, it is conceptually possible that the persuasion would be stronger in cities with lower baseline nationalistic sentiment: individuals might have previously been less aware of and less exposed to these types of views before the introduction of social media.
Since there might be a stigma in reporting xenophobic attitudes even in anonymous surveys, we use a “list experiment” to approximate “truly-held” xenophobic attitudes. In particular, the list experiment works as follows: first, respondents are randomly assigned either into a control group or a treatment group. Respondents in all groups are asked to indicate the number of policy positions they support from a list of positions on several issues. Support for any particular policy position is never indicated, only the total number of positions articulated on the list that a respondent supports. In the control group, the list includes a set of contentious, but not stigmatized, opinions. In the treatment group, the list includes all the contentious opinions from the control list, but also adds the opinion of interest, which is potentially stigmatized. The degree of support for the stigmatized opinion can be assessed by comparing the average number of issues supported in the treatment and control groups. The question of interest, randomly added to half of the questionnaires, was “Do you feel irritation of dislike for individuals from some other ethnicities?”.
The results indicate that the average share of people who agree with the statement is 37%. While there is no significant effect of social media penetration on xenophobic attitudes for the whole sample, there is a significant effect for important subsamples, which are at a higher risk of being involved in hate crime, such as respondents with lower levels of education or young respondents. Of course, the individuals that became more likely to engage in hate crime are not necessarily the same that have been persuaded to have more xenophobic attitudes (especially given the question used to assess attitudes) – though it is possible that some individuals who would have been close to committing crimes in the absence of social media might have been persuaded enough to switch their behavior in the presence of social media.
At the same time, we do not find that social media leads to an increase in xenophobic attitudes when measured with a direct question. The results are confirmed if we use a much larger, nationally representative survey of more than 30,000 respondents conducted by one of the biggest Russian survey companies FOM in 2011. In principle, it is possible that social media not only changed real attitudes but also the perception of the social acceptability of expressing these attitudes. However, we do not find any evidence that social media reduces the stigma of admitting xenophobic attitudes. The fact that we find the effect of social media on actual attitudes, but not on the expressed ones suggests, that if anything the stigma increased, at least for the respondents who acquired xenophobic attitudes as a result of social media influence. This highlights the importance of using a survey method that reduces concerns with social acceptability, such as list experiments.
Overall, our results indicate that social media lead to an increase in both ethnic hate crimes and xenophobic attitudes in Russia. However, the effect on hate crime is observed only in cities in which there was already a high level of nationalism. Additional evidence indicates that this effect is driven both by facilitating the coordination of nationalists and by persuading people to become more xenophobic. These findings contribute to a growing body of evidence that social media is a complex phenomenon that has both positive and negative effects on the welfare of people (see also Allcott et al, 2019), which has to be taken into account in discussing policy implications of the recent changes in media technologies.
References
- Allcott, H., Braghieri, L., Eichmeyer, S., Gentzkow, M. (2019) “The Welfare Effects of Social Media”, Working paper.
- Burzstyn, L., Egorov, G., Enikolopov, R., Makarin, A. (2019) “Social Media and Xenophobia: Evidence from Russia”, Working paper.
- Enikolopov, R., Makarin, A., Petrova, M. (2018) “Social Media and Protest Participation: Evidence from Russia“, Working paper.
- Settle, J. E. (2018) Frenemies: How Social Media Polarizes America. Cambridge University Press.
- Sunstein, C. (2001) Republic.com. Princeton University Press.
- Sunstein, C. (2017) Republic: Divided Democracy in the Age of Social Media. 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.
Russia’s Real Cost of Crimean Uncertainty
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
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
1a
Source: Authors’ calculations, schooling data from Barro and Lee (2013)
1b
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
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 25th 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
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
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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
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
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?
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
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.