Author: Admin
On Economics of Innovation Subsidies in Russia
Following the general agreement that innovation is a source of economic growth, the Russian government has provided various stimuli to foster domestic innovation. One of the mechanisms of innovation policy is research subsidies. This policy brief starts off with a discussion of the theoretical predictions and empirical evidence, which relates the economic incentives of research subsides to innovation and growth. We then address the potential adverse effects of focusing innovation subsidies mainly on large public companies in Russia. Finally, we attempt to establish a link between the innovation rate and market competition within Russian industries.
Overview
According to data from the Russian Statistical Agency, the R&D intensity – measured by R&D expenditure as percent of sales – increases with company size. Companies with 50 to 500 employees spend 1% of their sales on R&D, while the R&D intensity varies from 2 to 5% of sales for larger businesses (see Figure 1). The size non-neutrality of R&D in Russia contradicts the findings in the theoretical and empirical literature, which hold for companies in the developed countries (Cohen, 2010). An explanation may be the excessive government support to public companies in Russia, and in particular, to larger public corporations. A positive consequence of such policies is that public corporations come ahead of private companies, not only in R&D intensity, but also in innovation rates (see Figures 2–3).
However, government support towards innovation does not necessarily have a positive impact on overall economic activity. The purpose of this brief is to discuss the unwanted effects of the government policy in the form of research subsidies, both in theory and in an application to public companies and corporations in Russia. We base our analysis on the outcomes of the 2014–2017 micro surveys by the Analytical Center under the Government of the Russian Federation.
The role of government
Fighting under-provision of innovation
According to the seminal paradigm of the endogenous growth models with technological change, companies are engaged in quality competition, and their innovations are explained by a rational decision to raise profits through expanding the markets for existing products or entering markets for new products (Schumpeter, 1942; Romer, 1990; Grossman and Helpman, 1991; Kletter and Kortum, 2004). The innovation becomes one of the causes of economic growth, which is proved in empirical applications for developed countries, such as the U.S., Japan and the Netherlands (Akcigit and Kerr, 2010; Lentz and Mortensen, 2008; Grossman, 1990).
Figure 1. Innovation rate and R&D intensity by company size (number of employees)
Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.4, 2.16, Data for 2015. Innovative rate is % of companies involved in innovative activity.
However, the technological change is closely linked to knowledge disclosure, which means that new products become vulnerable to imitation, and that the non-rival character of knowledge causes an under-provision of innovation on the market (Arrow, 1962). The argument supports the cause for government policies through the system of intellectual property rights on the legal side, and research subsidies as an economic mechanism (Rockett, 2010; Hall and Lerner, 2010). Research subsidies are expected to have a positive effect on innovation rate, as is empirically shown for the U.S. in Acemoglu et al. (2016) and Wilson (2009). However, the impact on economic growth is ambiguous (Acemoglu et al., 2013; Grossman, 1990).
Figure 2. Innovation rate and R&D intensity by ownership
Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.6, 2.17, Data for 2015, public corporations are different from organizations by regional/federal government.
Figure 3. Share of public funds in R&D financing, % of company budget
Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.13; Innovation Development Programmes of Russian State-Owned Companies, Fig.4.
Unwanted effects of subsidies
Two concerns are associated with subsidization of innovation. First, while research subsidies may stimulate innovation among the targeted companies, the growth effect is likely to be heterogeneous across companies in the industry or economy, leading to a neutral or even negative overall effect. For instance, the increased innovation rate in subsidized large incumbents may curb entry of new (and more productive) firms, so the net outcome is deceleration of growth in the economy (Acemoglu et al., 2013). Research subsidies may even cause a shrinking of the high-tech sectors: if skilled labor moves from manufacturing to research labs, manufacturing may experience a shortage of labor, resulting in the net effect being a decrease in production (Grossman, 1990).
Another extreme of subsidizing entrants, in view of antitrust policies, occurs when former entrants change their market status to incumbents: now they face lower profits relative to newer entrants and hence, become less incentivized in their economic activity (Segal and Whinston, 2007).
Second, innovation policy (for instance, in the form of subsidies) may sometimes not even increase the innovation rate. Indeed, incumbents have no incentives to innovate in order to keep their market power or to prevent entry of higher quality firms in industries with non-perfect competition (Rockett, 2010; Qian, 2007).
Both mechanisms are likely to hold for Russian industries, where the protection of large public corporations has led to low competition, various forms of distortions on the market and hence, weak incentives to innovate.
Potential adverse effects in Russia
Large companies are likely to attract public attention owing to their obvious advantages in spreading fixed costs of innovations (Cohen,
2010). Russia is no exception to the phenomenon, so public corporations, which are commonly of a large size, received government subsidies. However, the subsidy is primarily used for acquiring new technologies and perfecting design, rather than conducting R&D (See Figure 4 with comparison available for communications and IT industry). The fact points to a possibility of a small effect of innovations on growth of public companies. Only if the research subsidy is spent on delegating the R&D research to specialized firms, with a subsequent acquiring of the resulting technology, the existing policy of supporting public corporations may induce their growth and/or growth of the corresponding industry.
Figure 4. Structure of spending the research subsidy in communications and IT in 2013, %
Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.134 Innovation Development Programmes of Russian State-Owned Companies, Fig.3.
In an attempt to formally assess the effect of innovation subsidies on company growth, we focus on the time profiles of the common proxies for company size: sales, profits and employment (Akcigit et al., 2017; Akcigit and Kerr, 2010; Acemoglu et al., 2013). The macroeconomic literature predicts that innovation becomes one of the channels for an increase of each of the three variables through a rise in quality. Motivated by this literature, the micro-data analysis “On the Interaction of the Elements of the Innovation Infrastructure”, conducted by the Analytical Center under the Government of the Russian Federation (2014), asked companies to assess their changes in sales, profits and employment in response to the innovation subsidy. As a result, the outcomes of the above analysis allow for a comparative assessment of the impact of the government’s innovation subsidy for public and private companies.
In particular, the results point to higher growth across private companies owing to research subsidies: the percent of private companies with new employees is higher than that of public companies. Similarly, the percentage of private companies that increased market share or raised profits/export due to subsidies exceed those of the public companies (see Figure 5). Here, we interpret new hires as employment growth and increase of market share as a potential indicator of sales growth.
Figure 5. Economic activity owing to research subsidies, % of companies
Source: Analytical Center under the Government of the Russian Federation, 2014. Fig.22
The innovation activity in private Russian companies lead to a higher prevalence of new products in comparison with public companies. The fact goes in line with a more important role of research and development in the innovative activity of private Russian companies (see Figure 4).
Finally, we attempt to establish a link between the innovation rate and market competition at the level of Russian industries. For this purpose, we use the results of the annual surveys “An assessment of the competitiveness in Russia”, conducted in 2015–2017 by the Analytical Center across 650–1500 companies from 84 Russian regions. The respondents were asked if they implemented R&D as a strategy for raising their competitiveness. We use the percentage of firms doing R&D as a proxy for the innovation rate. Competition in the industry was evaluated by respondents on a five-point scale (no competition, weak, median, high and very high), and we combine the prevalence of the two top categories as a proxy for competition in the industry.
Figure 6. Competition and R&D in Russian industries, % of firms
Source: Analytical Center under the Government of the Russian Federation, 2017, pp.8, 18.
The results show that innovative activity in the form of R&D or product modification is observed in industries with relatively high competition in Russia – for instance, in machinery and electric/electronic equipment (Figure 6). At the same time, industries where competition is not as high (e.g. woodworking, construction) show absence of either type of innovation. The findings go in line with the economic theory about market competition being a prerequisite for the rational choice of companies about innovation. Moreover, if the purpose of government subsidies is to foster innovation, the effective allocation of subsidies would imply the focus on Russian industries with high competition – here various forms of innovation do play a role in the company strategy on the market.
Conclusion
Our analysis outlines the theoretical foundations for the potential adverse effects of innovation policies in the form of research subsidies. The unwanted outcomes may relate to heterogeneity of companies and absence of the association between innovation activity and growth on non-competitive markets.
We offer the empirical evidence, which points to the undesired effects of subsidizing public companies in Russia. For instance, compared to the overall Russian sector of communications and IT, the innovative activity in public corporations has a weaker association with research and development. Additionally, compared to private companies, the innovations may result in smaller prevalence of increased exports, profits or new hires, as well as in a less frequent development of new products by public companies in Russia.
References
- Acemoglu, D., Akcigit, U., Bloom, N., Kerr, W. R., 2013. “Innovation, reallocation and growth”, National Bureau of Economic Research Working paper, No. 18993.
- Acemoglu, D., Akcigit, U., Hanley, D., Kerr, W. (2016). Transition to clean technology. Journal of Political Economy, Volume 124(1), pages 52-104.
- Akcigit, U., Kerr, W. R., 2010. “Growth through heterogeneous innovations” National Bureau of Economic Research Working Paper, No. 16443.
- Analytical Center under the Government of the Russian Federation, 2014. “On the Interaction of the Elements of the Innovation Infrastructure”, Analytical report, in Russian.
- Analytical Center under the Government of the Russian Federation, 2015-2017. “An Assessment of the Competitiveness in Russia”, Analytical reports, in Russian.
- Arrow, K., 1962. “Economic welfare and the allocation of resources for invention”, In The Rate and Direction of Inventive Activity: Economic and Ssocial Factors, Princeton University Press, pages 609-626.
- Cohen, W. M., 2010. “Fifty years of empirical studies of innovative activity and performance”, Handbook of the Economics of Innovation, Volume 1, pages 129-213.
- Grossman, G. M., Helpman, E., 1991. “Quality ladders in the theory of growth”, The Review of Economic Studies, Volume 58(1), pages 43-61.
- Grossman, G.M., 1990. ”Explaining Japan’s innovation and trade”, BOJ Monetary and Economic Studies, Volume 8(2), pages 75-100.
- Hall, B. H., Lerner, J., 2010. “The financing of R&D and innovation”, Handbook of the Economics of Innovation, Volume 1, pages 609-639.
- Indicators of Innovation in the Russian Federation: 2017. N. Gorodnikova, L. Gokhberg, K. Ditkovskiy et al.; National Research University Higher School of Economics, in Russian.
- Innovation Development Programmes of Russian State-Owned Companies: Interim Results and Priorities, 2015. M. Gershman, T. Zinina, M. Romanov et al.; L. Gokhberg, A. Klepach, P. Rudnik et al. (eds.), National Research University Higher School of Economics, in Russian.
- Klette, T. J., Kortum, S., 2004. “Innovating firms and aggregate innovation”, Journal of Political Economy, Volume 112(5), pages 986-1018.
- Lentz, R., Mortensen, D.T., 2008. “An empirical model of growth through product innovation”, Econometrica, Volume 76(6), pages 1317–1373.
- Qian, Y., 2007. “Do national patent laws stimulate domestic innovation in a global patenting environment? A cross-country analysis of pharmaceutical patent protection, 1978–2002”, The Review of Economics and Statistics, Volume 89(3), pages 436-453.
- Rockett, K., 2010. “Property rights and invention”, Handbook of the Economics of Innovation, Volume 1, pages 315-380.
- Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.
- Segal, I., Whinston, M.D., 2007. “Antitrust in innovative industries”, American Economic Review, Volume 97(5), pages 1703-1730.
- Schumpeter, J., 1942. “Creative destruction”, Capitalism, Socialism and Democracy, pages 82-83.
- Wilson, D. J., 2009. Beggar thy neighbor? The in-state, out-of-state, and aggregate effects of R&D tax credits. The Review of Economics and Statistics, Volume 91(2), pages 431-436.
Fiscal Redistribution in Belarus: What Works and What Doesn’t?
Belarus proudly calls itself a social state. Indeed, Belarus boasts one of the lowest poverty and inequality levels in the region. Fiscal policy in Belarus is equalizing and pro-poor, effectively redistributing income from rich to poor. As in Russia and many other Post-Soviet states, the equalizing effect of the fiscal policy in Belarus is mostly attributable to the pension system. Some of the other social policies are highly inefficient, failing to redistribute income. The prominent examples are utility subsidies and student stipends, which mainly benefit the upper part of the income distribution. The lack of adequate unemployment benefits is an opportunity to improve the efficiency of the social support system in Belarus.
The Constitution of Belarus characterizes Belarus as a social state, and Belarus takes its social state status seriously. The economic growth in the beginning of the 2000’s was strongly pro-poor (Chubrik, 2007). Poverty according to the national definition (calorie-based poverty line, which in 2015 corresponded to $10.67 PPP per day) declined from 42% in 2000 to 5.7% in 2016, while the poverty according to the international threshold of $3.1 per day in PPP terms is fully eradicated. Belarus also has one of the lowest levels of income inequality in the region with a Gini coefficient of only 0.27 (UNDP, 2016).
How much of the pro-poor and equalizing effects could be attributed to the government policy? Probably it is impossible to give a complete answer to the question. Many non-formalized and not easily quantifiable government policies lead to the decrease in poverty and inequality. For example, the policy of support to state-owned enterprises might have redistributive effects through job creation. However, the absence of access to relevant data makes it impossible to estimate the effects of the policy.
Some of the government policies, on the other hand, are easily quantifiable with available data. Bornukova, Chubrik and Shymanovich (2017) analyze the redistributive effects of fiscal policies in Belarus using the Commitment to Equity methodology (Lustig, 2016). The authors find that the direct taxes and transfers in Belarus (taxes, transfers, and subsidies) are equalizing and pro-poor, lowering the national poverty headcount by 17 percentage points and the income Gini coefficient from 0.41 to 0.27. The high equalizing effect of the fiscal policies in Belarus surpasses those in other developing countries, including Russia where the direct taxes and subsidies reduced the income Gini coefficient by 0.13 (Lopez-Calva et al., 2017). The remaining discussion in this brief is based on the results from Bornukova, Chubrik and Shymanovich (2017), if not otherwise stated.
Fiscal policies and their redistributive effects
Taxation
The two types of direct personal taxes – the personal income tax and the social contributions tax – are both almost flat in Belarus. To fight tax evasion, the Belarusian authorities introduced flat tax rates in 2009, following a successful experiment in Russia. The personal income tax has some small exemptions for families with children, while the social contributions tax has a lower rate for agriculture employees. However, the effect of these deductions is relatively small: the direct taxes decrease the Gini coefficient by only 0.015.
The indirect taxes – the value-added tax, the import duties, and the excises – are weakly regressive, putting the burden of taxation on the poor. This is particularly true for the alcohol and tobacco excises. Again, the main purpose of these taxes is to penalize unwelcome behavior, and not to redistribute income, hence the result is not unexpected, and common for many countries. Overall the indirect taxes in Belarus increase the Gini coefficient by 0.05.
Direct transfers
Direct transfers are responsible for most of the equalizing effects of the fiscal policies. This is not surprising, given that the main purpose of the direct transfers is to fight poverty and provide support for those in need. However, most of the transfers are not need-based or targeted to the poor. Instead they are assigned to households based on their socio-economic characteristics aside income, such as age and maternity status.
Pensions are the main factor of reducing poverty and inequality. They reduced the Gini coefficient by 0.11 and decreased poverty (according to national definition) by 19 percentage points. The incredible effectiveness of the pensions is largely explained by the absence of other sources of income of the retirees. The majority of them does not work, and have no other pension savings or passive income. Pensions in Belarus are also redistributive in nature since they only weakly depend on one’s income during the working life.
Different benefits and privileges also decrease poverty and inequality, but at a much smaller scale. The childcare benefits (for families with children aged 0-3 years) contribute most to the effects, decreasing the Gini coefficient by 0.013 and poverty by 3 percentage points. The variety of privileges does not contribute much due to their relatively small size.
Subsidies
Utilities and transport subsidies are also important elements of the social support system, and their existence is usually justified by the necessity to support those in need. Since the utilities subsidies are incorporated into tariffs and available for everyone independent of need, they are in fact benefitting the rich (i.e. people with big apartments and houses).
Figure 1. Incidence of utilities subsidies by income deciles
Source: Bornukova, Chubrik and Shymanovich, 2017
As seen on Figure 1, upper deciles receive more support through utilities subsidies, and this support is quite substantial, often surpassing $1 per day in PPP. However, as a share of income the utilities subsidies are still progressive, and they in fact decrease the Gini coefficient by the tiny amount of 0.006, and decrease poverty (as any handout). The same is true for transport subsidies.
What could be improved?
Due to the flat nature of direct taxation and an absence of well-targeted needs-based transfers, some of the people in need still fall through the cracks. 1.9% of the population actually becomes poor after we account for the direct taxes and transfers. This headcount increases to 3.3% if we account for indirect taxes.
Another important issue is the efficiency of government transfers and subsidies in fighting poverty and inequality. It is not surprising that pensions have the largest equalizing contribution, as the government spends almost 11% of GDP on pensions. If we account for this fact and look at the efficiency (effect on poverty and inequality per dollar spent), pensions are not the leading program. It is in fact surpassed by different kinds of child support. Given that mothers in Belarus are allowed to take 3 years of unpaid maternity leave, which decreases household income, childcare benefits are relatively efficient.
The unexpected leader in efficiency is unemployment benefits, despite (or maybe due to) their negligible size. Shymanovich (2017) shows that unemployed face high risks of poverty, suggesting that an increase in the size of unemployment benefits and an easier access may bring huge benefits. The current minuscule size of the benefits (around $10-15 per month) is still enough to lift some people out of poverty, and has important equalizing effects, generating the biggest “bang for the buck” out of all benefits.
The student grants (stipends), the utilities subsidy and the transport subsidy have very low efficiency. These programs relocate a lot of funds to the upper deciles of the income distribution. Our calculations show that if all benefits, privileges and subsidies were not available to those in the top two income deciles, the Belarusian budget could save 1.4% of GDP.
Conclusion
Fiscal policies in Belarus are quite effective in redistributing income. Bornukova, Chubrik and Shymanovich (2017) show that the direct taxes and transfers in Belarus result in a decrease of poverty by 17 percentage points, and decrease the Gini coefficient of inequality from 0.41 to 0.27. The pension system has the most important contribution, decreasing poverty by 19 percentage points, and the Gini coefficient by 0.11.
However, the absence of a needs-based, well-targeted social support system leads to many inefficiencies. Direct and indirect taxes lead to impoverishment of 3.3% of population, which is not compensated by direct transfers.
The absence of targeting also leads to 1.4% of GDP redistributed towards the two upper income deciles through benefits, privileges and subsidies. This is, of course, highly inefficient. Better targeting could allow saving these funds or redirecting them to unemployment benefits – the most efficient but a very small benefits program so far.
References
- Bornukova, Kateryna, Alexander Chubrik and Gleb Shymanovich, 2017. “Fiscal Incidence in Belarus: a Commitment to Equity Analysis”, BEROC Working Paper Series, WP no. 42
- Chubrik, Alexander, 2007. “GDP Growth and Income Dynamics: Who Reaps the Benefits of Economic Growth in Belarus?” In Haiduk, K., Pelipas, I., Chubrik, A. (Eds.) Growth for All? Economy of Belarus: The Challenges Ahead; IPM research Center
- Lopez-Calva, L. F., Lustig, N., Matytsin, M., Popova, D., 2017. “Who Benefits from Fiscal Redistribution in Russia?”,in The Distributional Impact of Fiscal Policy: Experience from Developing Countries, edited by Gabriela Inchauste and Nora Lustig (Washington: World Bank, forthcoming).
- Gleb Shymanovich, 2017. “Poverty and Vulnerable Groups in Belarus: The Consequences of 2015-2016 Recession (in Russian)”, IPM Research Center Bulletin
- UNDP, 2016. “Regional Human Development Report 2016: Progress at Risk”, United Nations Development Programme, Istanbul Regional Hub, Regional Bureau for Europe and the CIS
Cross-Country Differences in Convergence in CESEE
Since 1989, there have been large differences in the convergence of the income levels of the former communist countries in CESEE with those in the US. Most Central European countries have seen a sharp rise in relative incomes, but many countries in former Yugoslavia and the CIS have not—indeed, some countries, including Moldova and Serbia, are now poorer than they were in 1989 (Figure 1).
Figure 1. Transition outcomes
Source: Total Economy Database and IMF staff calculations.
Figure 2. GDP level in Poland and Ukraine
Source: Total Economy Database and IMF staff calculations.
The difference between Ukraine and Poland is particularly stark. In 1989, both had similar income levels, but Poland is now more than three times as rich (Figure 2). As a result, cross-country income differences in CESEE remain large. In 1989, the Czech Republic, Russia, Slovenia and Croatia had the highest income per capita in 1989, about 4 times as high as in Albania and Moldova, the poorest in the group. Twenty-six years later, the differences are even larger. GDP per capita in Slovenia is 6 times as high as in Moldova (Figure 3).
Figure 3. Cross-country income differences
Source: Total Economy Database and IMF staff calculations.
What Explains Convergence Differences?
These differences in convergence do not seem to reflect data problems. True, GDP statistics in 1989 were not very good. It is hard to measure value added when prices are not quite right. Moreover, GDP at that time was probably not a good indicator or of consumer welfare. Much of what was produced was not wanted by consumers (e.g. military expenditures) and/or of low quality. Nevertheless, these issues apply to all post-communist countries in the regions—it is not clear that some countries suffered from data problems more than others.
Indeed, more direct measures of economic activity also suggest large initial output falls and large cross-country differences. Between 1990 and 1995 electricity consumption per capita fell by almost 40 percent in Ukraine and Moldova. By then electricity consumption in Poland had nearly recovered to the 1990 level (Figure 4).
Figure 4. An alternative measure of decline in economic activity
Source: IFA Statistics and IMF staff calculations.
Instead, several factors seem to have a played a role:
- The speed of transition to a market economy
- War and conflicts
- Boom-busts
- EU Membership
- Whether transition has been completed
Countries that reformed early had a shorter and shallower post-transition recession. The lower the EBRD transition index in 1995 (i.e., the less the economy was reformed), the sharper the output decline between the beginning of the transition and 1995 (Figure 5).
Figure 5. Market reforms and post-transition recession
Source: Total Economy Database and IMF staff calculations.
Why was this? In late 1989, a fierce debate broke out over what came to be called gradualism versus shock therapy. Many gradualists argued that the structural flaws of the economy would frustrate attempts at liberalization, and therefore that reforms should be implemented in a gradual, sequenced way. But for others—including key figures such as Leszek Balcerowicz in Poland—understanding the nature of the problem meant the opposite: reform was a seamless web that could only succeed if all the changes happened together, because liberal prices, improved governance, and a stable economic and financial environment were needed to reinforce one another; little could be achieved with a partial reform. The evidence from the past 25 years has vindicated the seamless web theory of transition. There is no doubt that some reforms took much longer than anticipated, including privatization, both of banks and companies. But it seems clear that the countries that made sweeping changes, and that kept at reform and stabilization have done well.[2] Countries that followed a more gradual path suffered from the decline of the old industries and did not get the boost from the growth of new firms. And in some countries bouts of macroeconomic instability repeatedly undermined reforms and sapped political momentum.
Weaker growth in the early transition years was not compensated by faster growth later. Countries, where output declines were deeper in early 1990s, did not see more rapid growth in subsequent years (Figure 6).
Figure 6. Permanent output losses in the early transition
Source: Total Economy Database and IMF staff calculations.
Wars and conflicts also played an important role. It is striking that the five countries with the lowest growth all had a war or serious conflict between 1990 and 2015 (Figure 7).
Figure 7. Wars and conflicts impact on long-term growth
Source: Total Economy Database and IMF staff calculations.
Avoiding boom-busts helped boost longer-term growth. Steady growth rates seem to be more conducive to higher long term growth than booms followed by busts. Between 2002 and 2008, Romania had capital inflows fueled boom and grew much faster than Poland, but thereafter it suffered a deep bust, and between 2002 and 2015, Poland has grown faster (Figure 8).
Figure 8. The hare and the tortoise
Source: Total Economy Database and IMF staff calculations.
EU accession was a powerful catalyst for reforms and upgrading of institutional frameworks. CESEE countries that joined the EU were required to bring their regulations and institutions up to Western European standards. There is a striking difference in the level of EBRD transition indicators between EU countries and non-EU countries (Figure 9).
Figure 9. EU accession as a reform catalyst
Source: EBRD and IMF staff calculations.
Thus, prospects of EU Membership have led to more reforms and, as a consequence, to stronger growth (Figure 10).
Figure 10. Market reforms and changes in income levels
Source: EBRD, Total Economy Database and IMF staff calculations.
Countries that upgraded their institutions to EU standards saw a decline in cross-country income differences. Countries that joined the EU in 2000s show clear pattern of convergence. The difference between Bulgaria and Slovenia has narrowed by 15 percent of Slovenia’s GDP since the former begun EU accession negotiations in 2000 (Figure 11, right panel). Similarly, a group of candidate and potential candidate countries, including Croatia (which joined the EU only in 2013) have converged as well (Figure 11, left panel).
Figure 11. Convergence within CESEE regions
Source: Total Economy Database and IMF staff calculations. Note: The EU has recognized Bosnia and Herzegovina as potential EU candidate countries.
By contrast, there was no convergence among the European CIS-countries. Russia, the richest of CIS countries grew by only 0.6 percent annually since 1989, while output per capita declined in Moldova and Ukraine. Only Belarus achieved growth rates comparable to non-CIS countries, but its largely unreformed economy may have approached the limits of the current extensive growth model (Figure 12).
Figure 12. Convergence in the European CIS region
Source: Total Economy Database and IMF staff calculations.
Countries that have a more completed transition are richer. There is a strong correlation between progress in market reforms and a country’s income level (Figure 13).
Figure 13. Market reforms and income level
Source: EBRD, Total Economy Database and IMF staff calculations.
Similarly, richer countries have a more vibrant private sector (Figure 14).
Figure 14. Market reforms and private sector share in the economy
Source: EBRD, Total Economy Database and IMF staff calculations.
Correlation does of course not mean causality but is it telling that there is no highly reformed poor country.
Convergence Post-2009 Crisis
Post-2009, catch-up has slowed down. Pre-crisis, convergence was rapid and widespread. In some countries, the GDP per capita gap to the US narrowed by more than 12 percentage points in 2003-08. Since 2010 only two-thirds of countries in the region have continued to catch-up with the US, while Ukraine and Slovenia saw a widening of income differences (Figure 15). And if we include the 2009 crisis, which was deeper in CESEE than in Western Europe, convergence has been even less.
Figure 15. Convergence pace pre- and post-crisis
Source: WEO database and IMF staff calculations.
More recently, there have also been large differences across regions: while the CIS was in recession, the non-CIS countries doing much better.
- The CIS countries suffered from falling commodity prices, and from the impact of sanction on Russia.
- By contrast, the non-CIS countries saw a gradual acceleration of GDP growth, on the back of a pick-up of domestic demand in the euro area. Labor markets in many EU New Member States (NMS) are tightening rapidly, and unemployment is quickly approaching pre-crisis lows, though GDP growth rates are well below those in the pre-crisis years.
How can we boost Convergence going forward?[3]
GDP per capita is the product of GDP per worker (labor productivity) and the share of the population that works (the employment rate):
Low GDP per capita can thus be the result of both low labor productivity and a low employment rate. In CESEE, both factors play a role:
- In most CESEE countries, the employment rate is below that in Western Europe (Figure 18). Low employment rates are a particular problem in SEE and some CIS countries.
- The labor productivity gap with Western Europe is still large, even though it has declined in the past twenty years.
Figure 16. Big differences in growth among regions
Source: WEO database and IMF staff calculations.
Figure 17. Labor markets in EU new member states
Source: Eurostat.
Figure 18. Labor utilization and productivity
Source: Total Economy Database, UN population statistics and IMF staff calculations.
To raise labor productivity more investment is needed. The capital stock per worker in a typical CESEE economy is only about a third of that in advanced Europe. Domestic saving rare are too low in most the region; policies should, therefore, focus on institutional reforms that reduce inefficiencies and increase returns on private investment and savings.
Boosting total factor productivity (TFP) is important as well. CESEE countries have to address structural and institutional obstacles that prevent efficient use of available technologies or lead to an inefficient allocation of resources. The recent IMF CESEE report suggests the largest efficiency gains are likely to come from improving the quality of institutions (protection of property rights, legal systems, and healthcare); increasing the affordability of financial services (especially for small but productive firms), and improving government efficiency.
Conclusion
Since the fall of communism, there have been large differences in the convergence of income levels with the US among CESEE countries. Much of these differences reflect differences in policies. Countries that reformed more and earlier saw faster growth than countries that reformed less or later. Macro-stability also helped, and countries that avoided boom-busts tended to grow faster.
Continued convergence will require a higher investment, higher TFP, and higher employment rates. The capital stock per worker is still below that in Western Europe. Higher investment rates will require higher saving rates, lest large current account deficits emerge anew. Addressing structural and institutional obstacles would also help convergence, as it will support higher labor force participation and allow for a more efficient allocation of resources.
Notes and References
- [1] Bas B. Bakker is the Senior Resident Representative and Krzysztof Krogulski an economist in the IMF’s Regional Office for Central and Eastern Europe in Warsaw. The views expressed in this paper are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
- [2]This is not to say that the rapid and seamless approach was without problems, notably large losses of output and high unemployment in the short run. Thus, reform will always have to worry about the social safety net and, under some circumstances, may benefit from external assistance, which is where the IMF and others can come in.
- [3]The IMF addressed this question in depth in the spring 2016 issue of “CESEE Regional Economic Issues.”
Disclaimer: Opinions expressed in policy papers and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Financing for Development: Two Years after Addis
At the Third International Conference on Development Finance in Addis Ababa on July 13—16, 2015, the world committed itself to an action agenda to raise resources to realize the 2030 sustainable development goals. The question is how much progress the world has achieved two years down the road, when the initial enthusiasm and commitments are no longer in the immediate spotlight. This policy brief reports on the discussion from a conference on this topic, Development Day 2017, held in Stockholm on May 31.
The year 2015 has been lauded as a landmark year for sustainable development. As many as three major global agreements were negotiated and signed: the 2030 Agenda for Sustainable Development; the Paris Agreement on Climate Change; and the Addis Ababa Action Agenda (AAAA) on Financing for Development. The latter may be less known, but is essential to the ambition to achieve the first since it concerns how to finance the necessary investments to achieve the Sustainable Development Goals (SDG). The AAAA identified seven action areas spanning both the public and the private sectors, and involving both domestic revenues and international transfers (domestic public resources, domestic and international private business and finance, development cooperation, trade, debt and debt sustainability, systemic issues and science, technology and innovation). This event focused primarily on international commercial private capital flows, and indirectly on development cooperation as a facilitator and catalyst for such private transfers.
Combining good business and good development
A major theme of the conference was combining good business with good development. Should private companies also take responsibility for environmental and social sustainability, or is the “only business of business to do business”? If firms do engage in sustainability investments, does it eat into profits or does it rather create a competitive edge? Reading business journals, it is easy to get the impression that there is a win-win situation. This picture is, however, based on rather limited information and the relationship is fraught with methodological challenges as both profitability and sustainability investments may be driven by other factors (such as competent leadership), and firms performing well may have the capacity and feel the obligation to invest part of their surplus into corporate social responsibility (CSR). Hence, there may be a question of reverse causality.
At the conference, new research was presented using data on investments in low and middle-income countries from the International Finance Corporation that includes both measures of financial rates of returns and subjective ratings of environment, social and governance (ESG) performance. Simple correlations suggested a significant positive relationship, or a win-win situation. However, once care was taken to identify a causal effect from ESG on profits, the results became insignificant. That is, the causal effect of ESG investments on profits seemed neither positive nor negative. However, when looking at broader measures of private sector development, the results suggest that both profits and ESG investments have a positive impact on sector development. This implies that there are good reasons for the public sector to encourage ESG activities even beyond the direct sustainability benefits through for instance public-private partnerships but also regulations that encourage good behavior.
How should results like these be interpreted? The presentation spurred an interesting debate on what are reasonable expectations and whether “the glass is half full or half empty”. It was emphasized that systematically beating the market should not really be expected from any group of investments, so a half-full interpretation seems more plausible.
This debate also came up in a panel discussion on institutional investments in developing countries, and where the growing success of green bonds was presented. Though still small in absolute size (1-2% of the bonds coming to the market are green bonds), there has been an impressive growth in the last 3-4 years. Currently, the Swedish bank SEB is cooperating with the German government in developing a green-bond market in emerging markets. Some of the lessons emphasized from the green-bond market were the importance of being clear towards investors about the motivation and the value proposition, to package the information in a credible way emphasizing independent verification, and to continuously monitor and give feedback to investors.
From the institutional investor side, it was mentioned how important it is to tell investors a compelling story. This may be easier with regards to environmental sustainability relative to social sustainability, both in terms of conveying the urgency and in developing indicators that can be monitored and communicated. It was also argued that even though there are initiatives out there, emphasizing how sustainable investments can be competitive in terms of profitability (such as green bonds), it would also help to change the relative price on the other end of the spectrum, i.e. through regulations, taxes or other instruments that can make investments with particularly negative externalities less profitable.
Finally, an overarching theme of the discussion was the challenge to have institutional investments reach the places with the most needs, i.e. the fragile and least developed countries. If this is to happen, pension funds and insurance companies have to be allowed to take on more risks, and it would be essential to reduce the corporate risk in public-private partnerships (more on this below).
In a second panel discussion, different Swedish corporate initiatives, emphasizing sustainability, were showcased. For example, the Swedish steel producers’ association, Jernkontoret, showcased the Swedish steel industry’s vision 2050 with the target of domestically based steel production using hydrogen and with zero CO2 emissions. Another example is the Sweden Textile Water Initiative, launched in 2010 by major Swedish textile and leather brands together with the Stockholm International Water Institute, has created the first guidelines for sustainable water and wastewater management in supply chains. Currently working with 277 suppliers in 5 countries, the initiative features clear win-win situations and is now self-sustaining and in the process of going private.
Skandia, a major Swedish insurance company, emphasized the business costs of socially unsustainable situations with examples from the costs in Sweden of sick leave, and the costs for protection and security for Swedish retailers and mall developers. Positive preventive work focusing on rehabilitation and the development of blossoming and inclusive neighborhoods were featured. These examples showcased how the SDGs are feeding into the thinking and planning of the private sector in Sweden, and how important it is to identify the business cases for thinking about sustainability in order for this to become mainstream.
However, the case for private capital to be the panacea for reaching the SDGs is by no means obvious. The non-governmental organization Diakonia pointed out that for every dollar flowing into a developing country, more than two dollars are lost. The biggest loss is coming from illicit financial flows, and within this category, tax evasion is the biggest problem. While the private sector is key to development, the main contributions this sector can do for development is to pay taxes where they are due, abide by international standards, and be transparent and accountable to the citizens and governments in the countries where they operate.
Swedwatch, used two examples from Borneo and what is now South Sudan, to illustrate how investors at times turn a blind eye towards human rights and environmental abuses by private multi-national companies. Transparency, due diligence in evaluating human rights risks prior to investment decisions, and a readiness to push for compensation and remedy if abuse is still unearthed were pointed out as key components to avoid this type of malpractice.
Development cooperation as facilitator for private flows
The second main theme of the day dealt with the ability to use development cooperation as a catalyst for private investments.
Swedfund, the Swedish government’s development financier, emphasized the need to move fast and find a business model in which one dollar spent becomes ten dollars on the ground. Based on a business model around three pillars (societal impact, sustainability and financial viability) Swedfund focus on areas with relatively high risk and where private capital are in short supply, with the hope to foster job creation, inclusive growth and poverty reduction.
Sida, the Swedish main aid agency, showcased their guarantee instruments. Through partnerships with bigger actors such as the International Finance Corporation (IFC) of the World Bank group as well as local banks in developing countries, Sida can shoulder part of the default risks involved when trying to reach more high-risk investors (such as small and medium sized enterprises) with great potential development impact. In this way, one dollar from the public aid budget can lure a multiple of dollars in private capital towards sustainable development.
The OECD Development Assistance Committee (DAC) emphasized that governments generally lack a policy for how to deliver official development assistance (ODA) in a sustainable way and a strategy for how to enable capital flows from the private sector. A DAC initiative to better track all financial flows going towards development, beyond just ODA, was presented.
From the Center for Global Development, the case for using public resources to facilitate private sector insurance mechanisms against human disasters was presented (concessional insurance). Benefits emphasized from explicit insurance contracts included faster and better-coordinated payouts, more certainty that compensation will come, incentives to invest in disaster prevention (to reduce premiums) and involvement of commercial insurance professionals.
Importantly, though, it was emphasized that it is crucial that aid money are truly complementary in the sense that they crowd in private investments that otherwise would not have taken place (and not end up subsidizing private investors in donor countries). It was also emphasized that donors must not forget about the focus on the poorest and people in fragile states.
In some environments donors must shoulder 100% of the risk to lure private capital. In those cases alternatives must be considered. Sida emphasized the importance to match financial instruments with the appropriate context, i.e. there is a need to identify where different instruments should be used. For instance, big institutional investors need investments that are manageable, predictable, and of a reasonable size. Aid agencies can help through subsidized risk management, but also by helping build strong institutions in partner countries that can work as counterparts, and encourage public-private collaborations to package investment deals and reduce information asymmetries.
Where are we now?
Turns out that this is not a simple question to answer. The Ministry for Foreign Affairs presented the Swedish government’s priority areas – strengthening the implementation of SDG 5, 8, 14 and 16 (all goals can be found here: https://sustainabledevelopment.un.org/?menu=1300) – and reported from a recent follow-up meeting at the UN.
In principle the Addis Agenda identifies action areas and connects areas and actors, which makes it possible for systematic follow-ups, and an inter-agency task force produces an annual report of the general state of the implementation of the Addis Agenda. The Swedish government has produced a report on the implementation of the AAAA covering all seven action-areas with examples of progress. This initiative was commended at the UN meetings, and together with the private sector engagement, as showcased during the 2017 Development Day, it paints a rather positive picture of progress and engagement in Sweden.
However, globally, there are many uncertainties and challenges. The Center for Global Development reported on the budget proposal of the US president, which among other things includes a 32% cut to topline funding for the Department of State and Foreign Operations. There are also plans to eliminate the Overseas Private Investment Corporation and to zero out US food assistance. On the other hand, in this fiscal year, the US Congress (controlled by the Republicans) increased the amount going into foreign aid compared to what previous president Obama suggested. What will eventually come out of the current president’s budget proposal for the coming fiscal year is thus highly unclear.
Participants at the conference
- Rami AbdelRahman, Sweden Textile Water Initiative
- Frida Arounsavath, Swedwatch
- Owen Barder, Center for Global Development
- Eva Blixt, Jernkontoret
- Magnus Cedergren, Sida
- Penny Davies, Diakonia
- Raj Desai, Georgetown University and the Brookings Institution
- Ulf Erlandsson, Fourth Swedish National Pension Fund (AP4)
- Måns Fellesson, Ministry for Foreign Affairs
- Charlotte Petri Gornitzka, OECD-DAC
- Anna Hammargren, Ministry for Foreign Affairs
- John Hurley, Center for Global Development
- Lena Hök, Skandia
- Måns Nilsson, Stockholm Environmental Institute
- Mats Olausson, SEB
- Anders Olofsgård, SITE
- Anna Ryott, Swedfund
- Elina Scheja, Sida
Monetary Policy Puzzle in the Presence of a Negative TFP Shock and Unstable Expectations
The Belarusian economy has given birth to a very interesting phenomenon of extremely high real interest rates in a prolonged recession. Despite an expected intuitive guess about the linkage between them (high interest rates cause recession), the reality turned out to be more difficult. The era of high real interest rates was due to past mistakes in economic policy, which undermined the credibility of the latter and gave rise to high and volatile inflation expectations. However, the adverse output path following the too high interest rates was not essential. The recession was mainly predetermined by a negative Total Factor Productivity (TFP) shock. The shock itself forms a disagreeable and contradictive environment for monetary policy. Together with unanchored inflation expectations, this makes monetary policy ineffective and too risky.
Unusually high real rates and recession
Since the painful currency crisis of 2011, the Belarusian monetary environment has become extremely vulnerable in many respects. In 2011 and early 2012, the country faced (once again) a 3-digit inflation rate. While the inflation rate later went down gradually, it was not sufficient to enhance monetary stability in a broader sense. For instance, for nominal interest rates, the level of 20% per annum was an unachievable lower bound until 2016. Moreover, in 2013—2016, upside jumps in the nominal interest rates took place regularly (see Figure 1).
Figure 1.Nominal interest and inflation rates, % per annum
Source: Belstat. Note: Inflation rate is calculated on average basis for last three months on a seasonally adjusted basis and then annualized
Such combination of nominal interest and inflation rates has resulted in an extremely high and volatile level of real interest rates throughout the last 4 years. Real returns at the Belarusian financial market fluctuated in 2013—2016 within the range of 10-30% per annum. For instance, a median (monthly) value of the real interest rate on new loans in 2013—2016 was 17.6% per annum (in the beginning of 2017 it approached the level of 8-10% per annum). So, one may say that the real monetary conditions have been extremely tight in the last couple of years.
At the same time, in 2015—2016 Belarus has dipped into a prolonged and deep recession. During the last two years, the country has lost roughly 7% of its output. The combination of high real interest rates and a recession gave rise to a naive, but acceptable diagnosis: the excessively high interest rates caused (or at least contributed to) the recession. This view became popular in the domestic policy discussions. Furthermore, often this story transformed into a claim that ‘too tight monetary policy causes (or at least contributes to) recession’. Given this pressure, the National bank of Belarus (NBB) became accustomed to justifying its policy stance by considerations of financial stability given financial fragility. So, the economic policy discussion got into the discourse of these two extremes. Finally, it boiled down to the question whether ‘the monetary environment has stabilized enough in order to soften monetary policy’.
However, a naive story about the stance of monetary policy and the business cycle is not (fully) true in the case of Belarus in several respects.
Unanchored expectations drive interest rates
First, high interest rates at the financial market were not because of the excessively high policy rate of the NBB. It happened due to volatile, but still persistently high inflation expectations (Kruk 2017, 2016a). The latter visualized the loss of monetary-policy credibility by the general public.
Before 2016, the level of inflation expectations was persistently higher than the actual inflation, demonstrating an extremely slow (if any) convergence (see Figure 2). At the same time, the ex-ante level of real returns has remained relatively stable. When setting its policy rate, the NBB has taken into consideration existing inflation expectations, otherwise the high expected inflation would have been realized.
Figure 2. Actual and expected inflation, %
Note: Expected inflation has been estimated according to the methodology in Kruk (2016a).
So, in the recent past, the stance of the monetary policy could hardly be accused of generating too tight monetary conditions through the setting of an improper policy rate. The problem was (is) more severe, and one can argue about the inability (and the lack of willingness) of the NBB to anchor inflation expectations.
However, in the late 2016 and early 2017, the expected and actual inflation rates converged, mainly due to a contraction of the former. This introduced more stability into the monetary environment, in a broader sense. Kruk (2017, 2016a) shows that the turn of 2016—2017 has become a breakpoint for the monetary environment to return into a ‘normal’ stance (see Figure 3).
The NBB reacted to the milder monetary environment by a number of reductions in the policy rate (from 18% since August 2016 down to 14% since April 2017). However, a shift of both expected and actual inflation into the range between 5% and 9% may be interpreted as there being room for further reductions.
Figure 3. Classification of monetary environment stance in Belarus, probability estimates
Note: Classification and the methodology for estimates are based on Kruk (2016a). ‘Normal’ regime is characterized by reasonable and relatively stable real interest rates; ‘subnormal’ – too high real interest rate due to ‘inflation expectations premium’; ‘abnormal’ extremely volatile and mainly huge negative real interest rates due to the swings of actual inflation.
Therefore, as of today, one may argue that the long-expected time for a softening of the monetary policy has come, as the ‘expectations overhang’ has disappeared. However, such a view might be too optimistic. Kruk (2017) argues that the convergence of expected and actual inflation rates might be a temporary lucky combination, as there is a lack of evidence supporting a growing credibility of monetary policy among the general public. On the contrary, inflation expectations seem to have shrunk due to a depressed domestic demand and lower consumer confidence. So, even if expectations have contracted, they have not been anchored. Hence, ‘the expectations overhang’ may resurge at any time.
Monetary softening cannot neutralize structural recession
Even if we assume that the ‘expectations overhang’ has disappeared, it would still not mean that there is room for a new monetary stimuli. A naive story about high real interest rates that cause recession glitches once again when interpreting this linkage. Most frequently, countries face a cyclical recession (i.e. caused by temporary demand fluctuations). If that is the case, a negative impact of excessively high interest rates on output path is taken for granted.
However, the Belarusian story of recession is different. Kruk and Bornukova (2014) have shown that the country faced a negative TFP shock, which determined the weakening of the long-term growth rate. Kruk (2016b) shows that due to this shock, the long-term growth rate crossed the zero level approximately at the turn of 2014—2015, and dipped into a negative range later on. Hence, the Belarusian recession that started in 2015 was a combination of a negative contribution from both the long-term dynamics and the business cycle. Furthermore, since the second half of 2016, the negative contribution of the business cycle has faded out, and the recession was determined by the negative TFP shock almost solely (Kruk, 2017) so that, by 2017, the recession has become a purely structural phenomena.
From a monetary policy stance, this gives rise to a new challenge. Although the majority of methodologies still assess the output gap to be negative (but not far away from zero), the output gap will soon be closed automatically because of continuing negative TFP shocks (Kruk, 2017). In a sense, the negative TFP shock contributes to the closing of the output gap in the same way as monetary policy does. However, it does this job in an opposite manner (i.e. by squeezing the trend growth, and not by stimulating the business cycle), it leaves almost no room for monetary policy. It creates a situation where a reasonable loosening of the monetary policy may immediately turn into an excessive one. Taking into account that the dormant inflation expectations can resurge, monetary policy decisions resembles walking on the edge.
Conclusions
Today’s policy discussion in Belarus is extensively concentrated around the search for the best monetary policy to fight the recession. However, this formulation of the problem is a mistake in itself. Today’s contradictions in monetary policy are simply a reflection of the bulk of accumulated structural weaknesses in the economy. Today, monetary policy can hardly do anything to stabilize output. The solutions for ending the recession, and enhancing growth should be found in structural policies, not in the sphere of monetary policy. As for monetary policy, it can, at this moment, hardly contribute to output stabilization (without challenging price stability). To do so, it has to ensure an anchoring of the inflation expectations first.
References
- Kruk, D. (2017). Monetary Policy and Financial Stability in Belarus: Current Stance, Challenges, and Perspectives (in Russian), BEROC Policy Paper Series, PP No.43.
- Kruk, D. (2016a). SVAR Approach for Extracting Inflation Expectations Given Severe Mnonetary Shocks: Evidence from Belarus, BEROC Working Paper Series, WP No. 39
- Kruk, D. (2016b). The Reasons and Characteristics of Recessiion in Belarus: the Role of Structural Factors (in Russian), BEROC Policy Paper Series, PP No. 42.
- Kruk, D., Bornukova,K. (2014). Belarusian Economic Growth Decomposition, BEROC Working Paper Series, WP no. 24.
“New Goods” Trade in the Baltics
We analyze the role of the new goods margin—those goods that initially account for very small volumes of trade—in the Baltic states’ trade growth during the 1995-2008 period. We find that, on average, the basket of goods that in 1995 accounted for 10% of total Baltic exports and imports to their main trade partners, represented nearly 50% and 25% of total exports and imports in 2008, respectively. Moreover, we find that the share of Baltic new-goods exports outpaced that of other transition economies of Central and Eastern Europe. As the International Trade literature has recently shown, these increases in newly-traded goods could in turn have significant implications in terms of welfare and productivity gains within the Baltic economies.
New EU members, new trade opportunities
The Eastern enlargements of the European Union (EU) that have taken place since 2004 included the liberalization of trade as one of their main pillars and consequently provided new opportunities for the expansion of trade among the new and old members. Growth in trade following trade liberalization episodes such as the ones contemplated in the recent EU expansions could occur because of two reasons. First, because countries export and import more of the goods that they had already been trading. Alternatively, trade liberalization could promote the exchange of goods that had previously not been traded. The latter alternative is usually referred to as increases in the extensive margin of trade, or the new goods margin.
The new goods margin has been receiving a considerable amount of attention in the International Trade literature. For example, Broda and Weinstein (2006) estimate the value to American consumers derived from the growth in the variety of import products between 1972 and 2001 to be as large as 2.6% of GDP, while Chen and Hong (2012) find a figure of 4.9% of GDP for the Chinese case between 1997 and 2008. Similarly, Feenstra and Kee (2008) find that, in a sample of 44 countries, the total increase in export variety is associated with an average 3.3% productivity gain per year for exporters over the 1980–2000 period. This suggests that the new goods margin has significant implications in terms of both welfare and productivity.
In a forthcoming article (Cho and Díaz, in press) we study the patterns of the new goods margin for the three Baltic states: Estonia, Latvia and Lithuania. We investigate whether the period of rapid trade expansion experienced by these countries after gaining independence in 1991—average exports grew by more than 700% between 1995 and 2008 in nominal terms, and average imports by more than 800%—also coincided with increases in newly-traded goods by quantifying the relative importance of the new goods margin between 1995 and 2008. This policy brief summarizes our results.
Why focus on the Baltics?
The Baltic economies present an interesting case for a series of reasons. First, along a number of dimensions, the Baltic countries stood out as leaders among the formerly centrally-planned economies in implementing market- and trade-liberalization reforms. Indeed, those are the kind of structural changes that Kehoe and Ruhl (2013) identify as the main drivers of extensive margin increases. Second, unlike other transition economies, as part of the Soviet Union the Baltics lacked any degree of autonomy. Thus, upon independence, they faced a vast array of challenges, among them the difficult task of establishing trade relationships with the rest of the world, which prior to 1991 were determined solely from Moscow. Lastly, as former Soviet republics, the Baltic states had sizable portions of ethnic Russian-speaking population, most of which remained in the Baltics even after their independence. At least in principle, this gave the Baltic economies a unique potential to better tap into the Russian market.
Defining “new goods”
We use bilateral merchandise trade data for Estonia, Latvia and Lithuania starting in 1995 and ending in 2008, the year before the Global Financial Crisis (GFC). The data are taken from the World Bank’s World Integrated Trade Solution database. The trade data are disaggregated at the 5-digit level of the SITC Revision 2 code, which implies that our analysis deals with 1,836 different goods.
To construct a measure of the new goods margin, we follow the methodology laid out in Kehoe and Ruhl (2013). First, for each good we compute the average export and import value during the first three years in the sample (in our case, 1995 to 1997), to avoid any distortions that could arise from our choice of the initial year. Next, goods are sorted in ascending order according to the three-year average. Finally, the cumulative value of the ranked goods is grouped into 10 brackets, each containing 10% of total trade. The basket of goods in the bottom decile is labeled as the “new” goods or “least-traded” goods, since it contains goods that initially recorded zero trade, as well as goods that were traded in positive—but low—volumes. We then trace the evolution of the trade value of the goods in the bottom decile, which represents the growth of trade in least-traded goods.
Findings
For ease of exposition, we present the results for the average Baltic exports and imports of least-traded goods, rather than the trade flows for each country. Results for each individual country can be found in Cho and Díaz (in press). We report the least-traded exports and imports to and from the Baltics’ main trade partners: the EU15, composed of the 15-country bloc that constituted the EU prior to the 2004 expansion; Germany, which within the EU15 stands out as the main trade partner of Latvia and Lithuania; the “Nordics”, a group that combines Finland and Sweden, Estonia’s largest trade partners; and Russia, because of its historical ties with the Baltic states and its relative importance in their total trade.
Least-traded exports
Figure 1 shows the evolution over time of the share in total exports of the goods that were initially labeled as “new goods”, i.e., those products that accounted for 10% of total trade in 1995. We find that the Baltic states were able to increase their least-traded exports significantly, and by 2008 such exports accounted for nearly 40% of total exports to the EU15, and close to 53%, 49% and 49% of total exports to Germany, the Nordic countries, and Russia, respectively. Moreover, we find that the fastest growth in least-traded exports to the EU15 and its individual members coincided with the periods when the Association Agreements and accession to the EU took place. Finally, we discover that the rapid increase in least-traded exports to the EU15 during the late 1990s and early 2000s is accompanied by a stagnation of least-traded exports to Russia. This suggest that, as the Baltics received preferential treatment from the EU, they expanded their export variety mix in that market at the expense of the Russian. Growth in least-traded exports to Russia only resumed in the mid 2000s, when the Baltics became EU members and were granted the same preferential treatment in the Russian market that the other EU members enjoyed.
Figure 1. Baltic least-traded exports
Source: Cho and Díaz (in press).
Least-traded imports
Figure 2 plots the evolution of Baltic least-traded imports between 1995 and 2008. We find that new goods imports also grew at robust rates, but their growth is about half the magnitude of the growth in the least-traded exports—the least-traded imports nearly doubled their share, whereas the least-traded exports quadrupled it. The least-traded imports from the EU15 and its individual members exhibited consistent growth throughout. On the other hand, imports of new goods from Russia—which had also been growing since 1995—started a continuous decline starting in 2003. This change in patterns can be attributed to the Baltics joining the EU customs union. Prior to their EU accession, the average Baltic tariff was in general low. Upon EU accession, the Baltics adopted the EU’s Commercial Common Policy, which removed trade restrictions for EU goods flowing into the Baltics, but—from the perspective of the Baltic countries—raised tariffs on non-EU imports, in turn discouraging the imports of Russian new goods.
Figure 2. Baltic least-traded imports
Source: Cho and Díaz (in press).
Are the Baltics different?
Figure 1 shows that the Baltic states were able to increase their least-traded exports by a significant margin. A natural question follows: Is this a feature that is unique of the Baltic economies, or is it instead a generalized trend among the transition countries?
Table 1: Growth of the share of least-traded exports (percent, annual average)
Source: Cho and Díaz (in press).
Table 1 reveals that the new goods margin played a much larger role for the Baltic states than for other transition economies such as the Czech Republic, Hungary and Poland (which we label as “Non-Baltics”), for all the export destinations we consider. Moreover, we find that while until 2004—the year of the EU accession—both Baltic and Non-Baltic countries displayed high and comparable growth rates of least-traded exports, this trend changed after 2004. Indeed, while there is no noticeable slowdown in the Baltic growth rate, after 2004 the Non-Baltic growth of least-traded exports to the world and to the EU15 all but stops, with the only exception being the Nordic destinations.
Conclusion
The Baltic states, and in particular Estonia, are usually portrayed as exemplary models of trade liberalization among the transition economies. Our results indicate that the Baltics substantially increased both their imports and exports of least-traded goods between 1995 and 2008. Since increases in the import variety mix have been shown to entail non-negligible welfare effects, we expect large welfare gains for the Baltic consumers experienced due to the increases in the imports of previously least-traded goods. Moreover, the literature has documented that increases in export variety are associated with increases in labor productivity. Our findings reveal that the Baltics’ increases in their exports of least-traded goods were even larger than their imports of new goods, thus underscoring the importance of the new goods margin because of their contribution to labor productivity gains.
References
- Broda, Christian; and David E. Weinstein, 2006. “Globalization and the gains from variety,” Quarterly Journal of Economics, Vol. 121 (2), pp. 541–585.
- Chen, Bo; and Ma Hong, 2012. “Import variety and welfare gain in China,” Review of International Economics, Vol. 20 (4), pp. 807–820.
- Cho, Sang-Wook (Stanley); and Julián P. Díaz. “The new goods margin in new markets,” Journal of Comparative Economics, in press.
- Feenstra, Robert C.; and Hiau Looi Kee, 2008. “Export variety and country productivity: estimating the monopolistic competition model with endogenous productivity,” Journal of International Economics, Vol. 74 (2), pp. 500–518.
- Kehoe, Timothy J.; and Kim J. Ruhl, 2013. “How important is the new goods margin in international trade?” Journal of Political Economy, Vol. 121 (2), pp. 358–392.
Independent Media and Contemporary Military Doctrines
Governments often take unpopular measures. To minimize the political cost of such measures policy makers may strategically time them to coincide with other newsworthy events, which distract the media and the public. We test this hypothesis using data on the recurrent Israeli-Palestinian conflict. We show that Israeli attacks are more likely to be carried out when the U.S. news are expected to be dominated by important (non-Israel-related) events on the following day. In contrast, we find no evidence of strategic timing for Palestinian attacks.
The role of media in today’s conflicts is enormous. Parties to conflicts use propaganda in state-sponsored media and enroll state-sponsored trolls in social media to gain domestic public support for their military campaigns and, more generally, to raise own popularity. Involvement of Russia in Syria and Eastern Ukraine and its coverage on Russia-sponsored TV is a forceful illustration of this. Some most devastating conflicts used state media to enroll paramilitary. For example, Yanagizawa-Drott (2014) estimated that 51,000 perpetrators in Rwandan genocide were persuaded to participate in mass killings by RTLM radio.
Not all the media are under control of parties involved in conflicts. What is the role of independent media during conflicts? It is one thing to use the dependent media to portray one’s participation in conflict in a slanted manner; it is another to change one’s military strategy in order to improve one’s image in the independent media. Do military choose the timing and the weapon for their offences depending on the expectation of how their actions will be portrayed by the independent media? A statement on June 4, 2002, by Major General Moshe Ya’alon, then the Israel Defense Forces (IDF) chief of staff designate and until recently the defense minister of Israel, strongly suggests this is the case for the Israeli-Palestinian conflict. Mr. Ya’alon said: “This is first and foremost a war of ideology, and as such the media factor, the psychological impact of our actions, is critical. If we understand that a photograph of a tank speaks against us on CNN, we can take this into account in our decision as to whether or not to send in the tank. We schedule helicopter operations for after dark so they cannot be photographed easily. … Such considerations are already second nature to us. Officers … must understand that there are strategic media considerations. The tension between the need to destroy a particular building or to use a tank or helicopter, and the manner, in which the world perceives these actions, can affect the ultimate success or failure of the campaign. Even if we triumph in battle, we can lose in the media and consequently on the ideological plane.”
Our recent paper “Attack When the World Is Not Watching? U.S. News and the Israeli-Palestinian Conflict” (Durante and Zhuravskaya, 2017) forthcoming in the Journal of Political Economy investigates how Israeli military changes the planning of its operations in Gaza and the West Bank in the face of coverage by US media. In particular, we test whether Israeli authorities choose the timing of their attacks strategically to coincide with other newsworthy events so as to minimize the negative impact of their actions on U.S. public opinion by avoiding U.S. media coverage of their military operations, especially when they might lead to civilian casualties.
Methodology
We compile a list of fully exogenous events from forward-looking political and sports calendars in the U.S. between 2001 and 2011 and verify which of these events actually dominate US TV news, leaving little or no time to coverage of other events. Then, we compare the timing of these events to the timing of Israeli attacks on a daily basis.
We also use another, more continuous measure of whether the U.S. media and the public are distracted by other important events, namely the length of top three non-conflict-related news stories during evening news on three U.S. TV networks, where the evening newscasts are limited to 30 minutes, namely ABC, CBS, and NBC. As Eisensee and Stromberg (2007) point out, due to the competition between networks for audience, we can measure the importance of newsworthy events featured on the evening broadcasts because more important stories appear before less important stories, and they are longer.
Results
Timing of Israeli attacks and their coverage in US media
We find that both the incidence and the severity of Israeli attacks increased sharply when U.S. news were dominated by other events, such as US primaries and caucuses, general elections, and Presidential inaugurations. The probability that Israel carried out an attack against Palestinians rose to 53.2% one day before these important U.S. events from 38.7% on days that did not coincide with these events (over our observation period of 11 years, which includes heavy fighting during the Second Intifada). Figure 1 illustrates this finding. Attacks which coincide with the major political and sports events are also more deadly; as a consequence, the number of victims of Israeli attacks per day is 1.51 times higher during the days that coincide with major political and sports events compared to days that do not coincide with major events.
Figure 1. IDF attacks and exogenous predictable newsworthy events in the U.S.
Source: Durante and Zhuravskaya, 2017.
Using another measure, the length of top three non-conflict-related news stories during evening news on three U.S. TV networks, we also find that Israeli attacks are significantly more likely to occur and are more deadly when top three non-conflict-related news are longer on the following day.
Does it matter which military operation?
As some military operations are more costly to postpone than others, one should expect that only attacks that are less costly to more be strategically timed to other important events. This is exactly what we find: the timing of special targeted-killing operations, which are considered as extremely urgent by IDF, is not related to U.S. news cycle. In addition, one should expect military operations to be timed to other newsworthy events only when they are likely to generate negative publicity. As negative publicity about the conflict is mainly associated with civilian casualties, and civilian casualties are more likely when the operations are executed with heavy weapons, we find that the relationship between occurrence and severity of Israeli attacks and U.S. newsworthy events on the following day holds only for operations that involve the use of heavy weapons. We also check that the attacks are only timed to predictable newsworthy events.
Why tomorrow’s coverage matters more?
Israeli attacks get news coverage in U.S. media both on the day of the attack and one day later. Why, then, Israel times its attacks to news pressure on the following day rather than on the same day? To answer this question, we analyzed the content of news broadcasts and found that the type of coverage of Israeli attacks differs substantially between same-day and next-day reports. While the same-day and next-day news stories are equally likely to report information on the number of victims, news stories that appear on the day after the attack are much more likely to present personal stories of civilian victims and include interviews with their relatives or friends. Furthermore, next-day coverage is significantly more likely to include emotionally charged visuals of burial processions and scenes of mourning. Anecdotal evidence suggests that it is both easier and safer for a foreign journalist to get details of the story on the next day; and that the next day affords an opportunity to produce emotionally charged videos of funerals. Figure 2 illustrates these findings.
Figure 2. Comparison of the content of news casts about attacks that aired on the same day as an attack and on the day following the attack.
Source: Here you can write notes to the figure, graph or table. Do not forget to state the source of the figure, graph or table.
Since people react more strongly to personal stories than to statistics and facts, and since information transmitted only through words is less likely to be retained than information accompanied by images, it is not surprising that Israel times its attacks to predictable international newsworthy events expected on the following day, as the next-day news stories are more damaging to Israel’s public image.
Conclusion
These results have broader implications. Policy makers in other policy domains and other countries may also strategically manipulate the timing of their unpopular actions to coincide with other important events that distract the mass media and the public. Examples of unpopular policies characterized by suspicious timing abound: Silvio Berlusconi’s government passed an emergency decree that freed hundreds of corrupt politicians on July 13, 1994, the day Italy qualified for the FIFA World Cup final. Russian troops stormed into Georgia on August 8, 2008, the opening day of the Beijing Summer Olympics. Political spin-doctors often release potentially harmful information in tandem with other important events. This is exemplified by a notorious statement from the former UK Labour Party’s spin doctor, Jo Moore, who, in a leaked memo sent to her superiors on the afternoon of 9/11, said that it was “a very good day to get out anything we want to bury” (see http://www.telegraph.co.uk/news/uknews/1358985/Sept-11-a-good-day-to-bury-bad-news.html (accessed on July 7, 2015) and http://www.theguardian.com/politics/2001/oct/10/uk.Whitehall (accessed on July 7, 2015)).
Overall, policy makers’ strategic behavior may undermine the effectiveness of mass media as a watchdog, thus reducing citizens’ ability to keep public officials accountable
References
- Durante, Ruben; and Ekaterina Zhuravskaya, 2017. “Attack When the World Is Not Watching? U.S. News and the Israeli-Palestinian Conflict”, Journal of Political Economy (forthcoming)
- Eisensee, Thomas; and David Stromberg, 2007. “News Droughts, News Floods, and U.S. Disaster Relief,” Quarterly Journal of Economics, 05, 122 (2), 693–728.
- Nevo, Baruch; and Shur Yael, 2003. The IDF and the press during hostilities, Jerusalem: The Jerusalem Democracy Institute, pp. 84-85, available at http://en.idi.org.il/media/1431355/IDFPress.pdf, accessed on May 18, 2016.
- Yanagizawa-Drott, David, 2014. “Propaganda and Conflict: Evidence from the Rwandan Genocide,” Quarterly Journal of Economics, 129(4), pp.1947-1994.
Intergenerational Mobility of Russian Households
To understand the nature of income inequality one needs to know how persistent the inequality is across generations. The same inequality levels could conceal different intergenerational mobility. We utilize the Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility. We find that although a sizeable upward intergenerational educational mobility, there is a pronounced occupational immobility and a low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially their mothers.
Sizeable and non-decreasing inequality in Russia poses a threat to social stability and long-term sustainability. Inequality in Russia has remained high throughout the transition period, and even slightly increased in the 2000s; the Gini inequality index rose from 0.397 in 2001 to 0.416 in 2014. The ratio of average incomes of the highest decile to those of the lowest decile also increased from 13.9 to 16 during this same period. This income gap is driven primarily by the gap between incomes of the top decile and all of the others: the top decile is estimated to have thirty percent of total monetary income in the economy. Furthermore, income inequality originates in earnings inequality: the top decile of wage earners gets thirty five percent of total wage earnings in the economy.
A key question is how persistent the inequality is, given that the same inequality levels could conceal different intergenerational mobility. In particular, social stability is challenged when income inequality is stable across generations, or put differently; there is little intergenerational mobility. Economic developments of the last 25 years seem to increase the risks of getting this problem in Russia.
Data and research methodology
We employ Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility (Denisova and Kartseva, 2016). The RLMS-HSE questionnaires in 2006 and 2011 contain questions on dates of birth, education and occupation of the father and mother of the respondent when the respondent was 15 years old.
To study occupational and educational mobility, we use the subsample of respondents of 25-55 years old and utilize the information on education and occupation of the respondent and his/her parents. We then estimate whether the parental education level predicts the probability that children have a university degree, a secondary or a junior professional degree.
To study intergenerational occupational mobility, we estimate influence of parental occupation on the probability that the child works as a manager, a professional, a technician or professional associate, a clerk, a qualified worker or an unskilled worker.
To study the child-parent income correlation based on RLMS is trickier. There is a panel component in RLMS but it is not long enough to study intergenerational mobility directly since we for most cases are not able to observe both parents and children during their working ages. To overcome the problem we impute wages for parents. In particular, we choose respondents aged 25-35 (children) in 2006 (and 2011). We then identify respondents born in the period 1945-1961 (1945-1966 for children in 2001) (‘parents’) and use the labor market information for this group as of 1995 (2001 as robustness check) to impute parental wages. We estimate a wage equation (separately for males and females) on the sample of ‘parents’ and then use the estimated returns (coefficients) and the reported age and education of respondent’s mother and father to impute wages of respondent’s parents.
We follow Björklund and Jantti (1997) to estimate the child-parent correlation of earnings based on the equation:
delta= β0 + β1X+ β2 delta_father + β3 delta_mother + ε
where delta=log(wage/average wage in respective sample), X – age, education, settlement type, region. Standard errors are clustered on primary sampling unit.
Intergenerational educational mobility
Our analysis shows that the education of parents, high professional (university) and secondary professional in particular, is a major determinant of children’s education. Moreover, there are clear signs of upward educational mobility across generations for both males and females: the coefficients in the transition parent-child matrix are significantly higher above the diagonal (Table 1).
Table 1. Father-child education matrix
Source: Authors’ calculations based on RLMS
The probability to have a university degree is 2.4 percentage points higher if the mother’s education is at university level (as compared to secondary school), and 2.1 percentage points higher if the father’s degree is at university level (as compared to secondary school). A secondary professional degree of parents also increases the probability of a child getting a university degree by about 1 percentage point. The probability of having secondary professional degree decreases if the father or mother has a university degree.
Intergenerational correlation of occupations
There are signs of sizeable occupational rigidity between generations, especially for the top two occupational groups (managers and professionals). The probability that a child works in the same occupational group is the highest for parents-professionals: it is 40% for fathers-professionals and 35% for mothers-professionals. Surprisingly, it is also rather high for parents employed as skilled workers – about 20%. These patterns survive controlling for other variables.
Income mobility
The correlation of parent-child wages measured for 2006 data are presented in Table 2. The results point to the sizeable average intergenerational rigidity of relative wages: the wage elasticity of children’s wages with respect to parental wages is about 0.4. This is at the level of the intergenerational wage rigidity in the US (Solon 1999).
There is sizeable gender asymmetry in the rigidity: we observe a high and significant correlation of son-mother wages, but an insignificant correlation of son-father wages. There is no significant correlation of daughter-parents wages.
Table 2. Parent-child income correlations, 2006
Source: Authors’ calculations based on RLMS
Conclusion
Generational poverty stemming from low intergenerational income mobility is a threat for sustainable development in any country. The economic and social development in transition seems to increase the risks of having this problem in Russia. Our estimates show that although there is sizeable upward intergenerational educational mobility in Russia, there is a pronounced occupational immobility, and low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially mothers. These findings are worrisome signals important for the design of policies of sustainable development.
References
- Björklund, Anders; and Markus Jantti, 1997. “Intergenerational Income Mobility in Sweden Compared to the United States,” American Economic Review, 87(5), 1009–18.
- Denisova, Irina; and Marina Kartseva, 2016, “Intergenerational Mobility of Russian Households”, mimeo
- Solon, Gary, 1999. “Intergenerational Mobility on the Labor Market,” Chapter 29 in Handbook of Labor Economics, Vol.3 edited by O.Ashenfelter and D.Card , 1761-1800.
Operating and Financial Hedging: Evidence from Trade
There is a large and growing literature that has modeled how real policies affect and interact with financial policies. It is important to consider such an interaction since a firm, just as a single value-maximizing agent, should make its strategic decisions optimally, taking into account all of its multi-dimensional facets (contracts with employees and suppliers, situation with market competitors, innovation, foreign-market operations and others – on the real side, and capital structure, dividend policy, IPO, hedging behavior – on the financial side). This policy brief introduces a new type of hedging exchange-rate risks through matching currencies of export revenues and import costs, and shows how it substitutes out financial hedging using currency derivatives.
Exchange-rate exposure and financial hedging around the world
Many firms are exposed to exchange-rate fluctuations in one way or the other. Because volatility is typically considered to be bad for a firm – either because small firms are risk-averse or because it may reduce the value of a risk-neutral firm through costly distress or agency costs – firms attempt to hedge it. Indeed many successfully do so. Bartram et al. (2009) report that about 60% of non-financial firms around the world use financial derivatives (forwards, futures, swaps, etc.), with the most popular type being currency derivatives (44%). These large numbers indicate the importance of risk management in general and hedging exchange-rate shocks in particular. There is also a considerable heterogeneity across countries. According to their investigation based on a subsample of world firms, currency derivative usage ranges from 6% in China and 15% in Malaysia, to 37% in the United States and 48% across Europe, to 80% in New Zealand and 88% in South Africa.
There is also some cross-sectional variation across firms. Geczy et al. (1997) report that among U.S. firms those with greater growth opportunities, tighter financial constraints, extensive foreign exchange-rate exposure and economies of scale in hedging activities are more likely to use currency derivatives.
Operational hedging
So what are potential alternatives to hedging exchange-rate exposure through currency derivatives? The literature has suggested other ways of reducing such cash-flow volatility – through operational hedges. The examples include diversifying the company’s operations and production geographically (as in Allayannis et al., 2001). The authors provide an example of Schering-Plough (a United States-based pharmaceutical company) that in their 1995 annual report suggested that hedging using financial instruments was not considered cost-effective, since the company operated in many foreign countries where the currencies would not generally move in parallel. More recent studies (e.g. Kim et al., 2006; Hankins, 2011) also support the geographical diversification of production and acquisition of foreign subsidiaries as important channels of operational hedging, and as such they can act as substitutes for financial hedging.
These papers are also part of the larger literature on the interrelations between real and financial strategies, and in particular the literature that has modeled how real policies, aimed at lowering operational risks (or alternatively increasing operating flexibility), reflect in various financial decisions (such as e.g. capital structure). Examples of such policies include the use of flexible manufacturing systems that allow changing the level of output, the product mix, or the operating “mode” (as in Brennan and Schwartz, 1985; He and Pindyck, 1992; and Kulatilaka and Trigeorgis, 2004); employing a contingent workforce (e.g. part-time and seasonal labor, as in Hanka, 1998 or workers on temporary contracts, as in Kuzmina, 2014); adopting a defined contribution, rather than a defined benefit or pension plan (as in Petersen, 1994); and many others.
Trade-related operational hedges
In Kuzmina and Kuznetsova (2016), we explore a different type of operational hedging – the one arising from exporting final goods and importing intermediate inputs from abroad at the same time. As previous literature has suggested, firms that export their final goods are naturally more exposed to exchange-rate risks due to their foreign-denominated contract obligations that have to be translated into domestic currency when the transaction clears in the future, the so-called transaction exposure of companies (Glaum, 2005). As long as volatility is costly for firms, higher exchange-rate exposure leads to more financial hedging, so previous papers indeed find a positive correlation between exporting and currency hedging (e.g. Geczy et al., 1997; He and Ng, 1998; Allayannis and Ofek, 2001).
This argument would similarly apply to firms that import their intermediate inputs from abroad, since they are similarly exposed to exchange-rate fluctuations on the cost side. In our paper, we attempt to provide new evidence on these channels, as well as to introduce a novel explanation to why not all firms hedge using financial derivatives. We show that firms that export and import at the same time hedge less using currency derivatives, and especially when volatility of exchange rate is high. We argue that when firms both export and import at the same time, their net foreign-denominated position (and thus exchange-rate exposure) becomes lower on average, and hence there is less incentive to hedge against it. This is consistent with foreign-currency matching of costs and revenues, which is a phenomenon also observable in other data. Although in our data we cannot observe currency of individual transactions for each firm, we do so in another project based on the data from Russia. Our calculations for Russian data, based on the whole universe of import and export declarations, suggest that for the major currencies, the probability of importing in the same currency is higher than in any other currency when a firm also exports in this currency. For example, out of all firms that have exports in Euro and some imports, 82% would import in Euro. The similar number for the U.S. dollar is 71%. Such trade-related operational hedge may arise naturally for firms in the global world, thus reducing their need to use financial instruments.
Germany as an interesting laboratory
To test our hypotheses, we use hand-collected data on a sample of German public firms during 2011-2014. Germany is a particularly relevant country for testing our hypotheses for at least three reasons.
First of all, it is the world’s third largest exporter and importer and the top one in Europe. Second and most importantly, if we want to explore currency risk arising from exporting and importing, at least some (and preferably many) of the export and import transactions have to occur in a foreign currency. This means that, for example, looking at the U.S. data would not give us a lot of power in identifying our mechanism, since according to Goldberg and Tille (2008), only 5% of all U.S. export contracts are set in a currency other than the U.S. dollar. On the other hand, more than half of German exports and imports outside the euro area are denominated in a currency other than the Euro, and in particular about 30-40% of all contracts are set in U.S. dollars. This means that our measured shares of non-euro zone exports and imports will actually have a large component of non-euro-denominated contracts, and we will have more power to measure the actual exchange-rate exposure arising from exporting and importing. Finally, we analyze the largest companies in Germany – those that trade on the Prime Standard segment of the Frankfurt Stock Exchange, since they have to disclose their use of derivatives due to the highest accounting and transparency requirements of this listing. These mandatory disclosure rules enable us to collect the data on hedging from companies’ annual reports and perform the analysis.
Identification strategy and results
To start the analysis, we provide some cross-sectional correlations. We find that firms in industries with more out-of-euro-zone exporting (importing) have a higher propensity to hedge using currency derivatives. In particular, a firm in an industry with 10pp higher export (import) shares has on average a 10.5pp (28.9pp) higher probability of currency hedging.
Although many industries simultaneously export and import a lot, others have a substantial imbalance in terms of export and import shares. We are therefore interested in whether this translates into different hedging behaviors. By adding the interaction between export and import shares in our regression specifications, we find that firms that simultaneously export and import hedge less than firms that just export or import. This is consistent with our hypothesis that firms decrease their effective exchange-rate exposure by having both revenues and costs in foreign currency and implies that operational hedging through matched currencies is a substitute for financial hedging.
In order to strengthen the result, we complement our cross-sectional correlations with a difference-in-differences methodology. To do this, we compare firms in industries with higher and lower out-of-euro-zone export and import shares during times of higher and lower exchange-rate volatility. We find that the higher the exchange-rate volatility, the larger this substitution effect is. This finding is stronger than a simple cross-sectional correlation between exporting, importing and hedging (which can be driven by omitted factors), since it uses an arguably exogenous volatility shock to show that operational hedging substitutes for financial hedging precisely during times when firms have highest incentives to hedge. The results are robust to using a set of control variables and firm and year fixed effects.
Implications
From an applied perspective, the interrelation between operational and financial strategies of the firm suggests that the decisions of the CEO and CFO should be complementary to each other to achieve the value-maximization goal of the firm. From a policy perspective, they imply that exogenous changes in government policies aimed at certain organizational changes in the firm (e.g. export promotion policies) could have indirect consequences for their riskiness and financing decisions.
References
- Allayannis, G., J. Ihrig, and J. P. Weston (2001), “Exchange-rate hedging: Financial versus operational strategies”. American Economic Review 91 (2), 391-395.
- Allayannis, G. and E. Ofek (2001), “Exchange rate exposure, hedging, and the use of foreign currency derivatives”, Journal of International Money and Finance 20 (2), 273-296.
- Bartram, S. M., G. W. Brown, and F. R. Fehle (2009), “International evidence on financial derivatives usage”, Financial Management 38 (1), 185-206.
- Brennan, M. and E. S. Schwartz (1985), “Evaluating natural resource investments”, The Journal of Business 58 (2), 135-157.
- Geczy, C., B. A. Minton, and C. Schrand (1997), “Why firms use currency derivatives”, Journal of Finance 52 (4), 1323-1354.
- Glaum, M. (2005), “Foreign-Exchange-Risk Management in German Non-Financial Corporations: An Empirical Analysis”, Springer.
- Hanka, G. (1998), “Debt and the terms of employment”, Journal of Financial Economics 48 (3), 245-282.
- Hankins, K. W. (2011), “How do financial firms manage risk? Unraveling the interaction of financial and operational hedging”, Management Science 57 (12), 2197-2212.
- He, H. and R. S. Pindyck (1992), “Investments in flexible production capacity”, Journal of Economic Dynamics and Control 16 (3-4), 575-599.
- He, J. and L. K. Ng (1998), “The foreign exchange exposure of Japanese multinational corporations”, Journal of Finance 53 (2), 733-753.
- Kim, Y. S., I. Mathur, and N. Jouahn (2006), “Is operational hedging a substitute for or a complement to financial hedging?” Journal of Corporate Finance 12 (4), 834-853.
- Kulatilaka, N. and L. Trigeorgis (2004), “The general flexibility to switch: Real options revisited”, Real options and investment under uncertainty: classical readings and recent contributions, 179-198.
- Kuzmina, O. (2014), “Operating flexibility and capital structure: Evidence from a natural experiment”, American Finance Association Conference, Philadelphia.
- Kuzmina O. and O. Kuznetsova (2016), “Operating and Financial Hedging: Evidence from Trade”, CEFIR Working paper.
Petersen, M. (1994), “Cash flow variability and a firm’s pension choice: A role for operating leverage”, Journal of Financial Economics 36, 361-383.
To Commemorate the 1917 Revolution in Russia – Occasions More for Reflections than for Celebrations
The centennial of the 1917 revolution in Russia provide opportunities for the public to refresh knowledge of the tumultuous events that dramatically changed the country’s history. Conferences, television series and debates, exhibitions at historical and art museums are some of the activities that will illuminate the February and October revolutions in 1917. The complex, intertwined and contradictory historical process and the following tragic Civil war 1918 – 1922 calls for careful, objective and dispassionate approaches and evaluations.
Over the last years, Russia has officially sponsored or encouraged great historical commemorations, e.g. the bicentennial of the war against Napoleon in 1812 and the centenary of the outbreak of the First World War. In contrast, this year’s commemoration of the 1917 revolution(s) in Russia – the first in February and the other in October (old style calendar) – pose a whole range of difficult questions. In the contemporary school curriculum in Russia, the most often used concept is ‘the Great 1917 Revolution in Russia’, thereby avoiding the previous, inappropriately counter posed February vs. October revolution. Instead, emphasis shifts to a continuous spectrum of revolutionary processes on different levels of the state and in various social groups throughout 1917. Likewise, this concept captures the multi-ethnic character of the revolution better than ‘the Russian revolution’.
In this brief, I outline the expected results from professional historians and archivists, by academic institutions and museums. In a forthcoming study of recent Russian historiographic debates (Samuelson, 2018), I intend to analyze also the changing official assessments of the 1917 revolutions.
In the Soviet era until the glasnost in the late 1980s, party-controlled historians described the ‘Great Socialist October revolution’ tendentiously, with many obfuscations and ‘white spots’. Not only were the opponents of the Bolsheviks depicted in caricature forms; also, the later oppositionists to Stalin’s party line were eliminated from the 1917 history, or mentioned merely for the alleged mistakes. In the West, on the other hand, there existed a plethora of interpretations of the Russian revolution, reflecting ideologies and worldviews of liberals, conservatives, as well as exiled Russian politicians (see e.g. Mazour, 1971 or Laqueur, 1967).
In the decades since the fall of the Soviet Union, Russian historians have profoundly enriched our knowledge of the 1917 revolutionary process as well as the ensuing Civil war. ‘Un-persons’ like Lev Trotsky, and hundreds of other who were expelled later from the Communist party, got back their due place in history. Works have been published of monarchists, liberals and socialists who led the Provisional governments during 1917. Historical studies by exiled scholars, as well as memoirs by politicians and diplomats that were once published in the West, have now been reprinted by Russian publishing companies (for the best survey, see Gennadyi Bordiugov, 2013 (1,520 pages!!)).
In today’s Russia, there co-exist an abundance of interpretations and assessments of the 1917 revolutions. The February strikes and uprising in Petrograd triggered the abdication of tsar Nikolay II, led to the founding of a republic and the formation of new government. The revolutionary changes outside the capital, throughout the whole empire, took quite different forms and only in recent years, regional scholars could describe them objectively.
Naturally, the fundamental changes in the political landscape in Russia after the return from exile of Vladimir Lenin in spring 1917 have attracted interest by scholars. Solid biographies of Lenin by Dmitrii Volgogonov (1994), Vladlen Loginov(2017), Anatolii Latyshev(1996) and Elena Kotelenets(2017), to mention only a few, give the Russian public a more nuanced figure than the more hagiographic works published in the Soviet epoch. The British historian Catherine Merridale (2016) gives a fascinating narrative of how Lenin’s return from exile in Switzerland would completely change the perspectives of the revolution. The renowned Russian specialist Vladimir Buldakov wrote profound reinterpretations of the ‘Red Troubled times’ (Krasnaya smuta) of 1917 in the first of a series of path-breaking research in the central and regional archives (Buldakov 2010, 2015).
As we approached the centennial of this decisive and deeply divisive year in Russia’s long history, many observers wondered how it was to be officially observed. Just like similar jubilee years, for example in 1989 of the French Revolution, it seemed obvious that this was not a time for triumphant celebrations as had been the case of the annual October Revolution holiday (on 7th November, new calendar) in the Soviet era. On the other hand, it would equally be unfortunate to pass over in silence this eventful revolutionary year. So by support from the Ministry of Culture, the Russian Historical Society (abbrev. RIO) set up a vast program of conferences, round tables, exhibitions and publications. Universities all over the Russian Federation will organize gatherings for historians and students. Central and regional archives arrange exhibitions, the explicit purpose of which is, not to give any definite value judgments, but to let the public form their own views on the personalities by pondering over original documents on Tsar Nikolai II and the tsarist family, the politicians of various parties, as well as on Lenin, Bolsheviks and others of the Left.
The call from the Russian political leaders has been to strive for a balanced, as dispassionate as possible, reassessment of the 1917 revolution in Russia. The ensuing civil war 1918–1922 created a generation-long, deep division among Russians, inside the country and in exile. Just as was the case in other countries, e.g. Finland and Spain, where civil wars scarred the national fabric in the 20th century, at present, the goal should be for reconciliation and mutual understanding of the historical actors on all sides of the political spectrum.
This spring, the Siberian branch of the Academy of Sciences in Novosibirsk organized a round-table on the 1917 revolution. Dozens of scholars presented their research findings and opinions on various events in the region; the protocol’s understatement that “the discussions had often a polemical character” indicate that the Russian revolution is still a subject of hot controversies, even in academic circles. On 29–31 March, the Moscow State University arranged the first of several grand international conferences planned this year. In twenty sessions, hundreds of scholars from all over Russia and from foreign countries gave papers on widely different aspects of the revolutionary processes. Likewise, universities in Samara, Volgograd, Cheliabinsk and other cities have announced their forthcoming conferences on the 1917 Revolution.
The main depository of political archives, RGASPI, in Moscow has contributed over 800 archival documents to a special exhibition, ‘1917. The Code of the Revolution’ at the Central Museum of Contemporary Political History. (https://www.sovrhistory.ru/events/exhibition/58becc2aa0e5981d9da515c4, accessed 31.03 2017). Two grand exhibitions projects with less-known archival documents attempt to give new perspectives, first, on Tsar Nikolai II, and, later this year, on Vladimir Lenin; both are of course well-known personalities, but the archivists and museums’ commissars hope to inspire visitors to renew their perspectives. In St. Petersburg, besides conferences, round-tables and exhibitions, there will be theatrical performances to reproduce dramatic events of 1917 and precisely on the streets and squares where they once upon a time took place. Russian Internet sites will provide pieces of contemporary news from 1917 for each day (https://project1917.com/).
Publishing houses have started new series devoted to the 1917 revolution in Russia, and the shelves in bookshops give abundant ‘food for thought’ for eager readers. Here one can find not only Trotsky’s own renowned History of the Russian Revolution written in his exile in the USSR. There are also memoirs by officers in the White Army during the Civil war, and a multitude of new popular-history works that reflect today’s ‘lessons of history’. The leading publishing company Rosspen will edit an archival documentary series, and compile an encyclopedia on the 1917 Revolution, thus hopefully summing up what has been accomplished in the former states of the USSR concerning the dramatic year of 1917 that was to profoundly change not only the country’s history, but even global history for many years ahead.
References
- Dmitrii Volkogonov, Lenin: A New Biography, New York, 1994;
- Vladlen Loginov, Lenin: How to become a leader, Glasgow 2017;
- Anatolii Latyshev, Rassekrechennyi Lenin (The declassified Lenin), Moscow 1996;
- Elena Kotelenets, Bitva za Lenina. Noveishie issledovaniia i diskussii (The Fight over Lenin: Recent research and discussions), Moscow 2017.
- Catherine Merridale, Lenin on the train (Swedish edition Lenins resa: Vägen till revolutionen 1917), London 2016.
- Vladimir Buldakov, Krasnaya smuta: Priroda i posledstviia revoljutsionnogo nasiliya (The Red Troubled Times: The nature and consequences of revolutionary violence), Moscow 2010;
- Vladimir Buldakov, Voina, porodivshaia revoliutsiiu (The War that brought along the revolution), Moscow 2015.
- Lennart Samuelson, Sovjetepoken i backspegeln.The Soviet Epoch in the Rear-view Mirror’, forthcoming in 2018
- Anatole G. Mazour, The Writing of History in the Soviet Union, Stanford: Hoover University Press, 1971;
- Walter Laqueur, The Fate of the Revolution: Interpretations of Soviet History from 1917 to the Present, London: Macmillan, 1967.
- Gennadyi Bordiugov (ed.), Mezhdu kanunami: Istoricheskie issledovaniia v Rossii za poslednie 25 let, Moscow: AIRO-XXI, 2013
The photograph to this policy brief shows Bolshevik leader Vladimir Lenin and other Russian exiles in Stockholm, 13 April 1917, on their way from Switzerland, to change the course of the Russian Revolution and world history of the 20th century. Social democrat Ture Nerman is talking with Lenin (4th from right, with umbrella).; behind them – mayor Carl Lindhagen and Aleksandra Kollontay, radical feminist who spent World War One here and in the 1930s to return to Stockholm as ambassador of the USSR.
Note: This Swedish photograph is in the public domain in Sweden because one of the following applies: (i) The work is non-artistic (journalistic, etc.) and has been created before 1969, (ii) The photographer is not known, and cannot be traced, and the work has been created before 1944.