Project: FREE policy brief
Intermediate and Capital Goods Import and Economic Growth in Belarus
This policy brief presents estimation results of the influence of intermediate and capital goods (ICGs) imports on GDP growth taking into account changes in the exchange rate. The Belarusian economy substantially relies on ICGs imports, and my research indicates that imports of intermediate inputs negatively contribute to Belarus’ economic growth. The findings suggest that a devaluation of national currency can negatively influence both GDP growth and imports of intermediate goods. The negative influence on GDP growth is caused by a lower price competitiveness of the export sector, and the negative influence on imports of intermediate goods is due to a significant increase in the costs of imports.
According to endogenous growth theory technological progress is a key factor that enhances long-run economic growth (Grossman and Helpman, 1994). However, in developing countries scarce commercial activities in R&D limit technological progress (Grossman and Helpman, 1991). From this point of view, imports of ICGs play the same role in the development of the Belarusian economy (taking into account the nature of Belarusian manufacturing, which is mostly to assemble finished goods) as R&D activities in developed countries by transferring foreign technology and innovations (Coe et al., 1997; Mazumdar, 2001). In turn, Belarusian economic policy related to imports of ICGs is seriously conditioned by the foreign exchange constraint.
Imports of ICGs and GDP Growth
Imported ICGs (excluding energy goods) account for approximately 55% of all Belarus’ imports. Starting from 2001 up to 2010 high levels of GDP growth (7-8% on average) were associated with even higher growth levels of ICGs imports (see Figure 1).
Figure 1. Imports of ICGs in 2001-2014
Source: Belstat.
However, from 2011, average growth rate of GDP has decreased significantly from 7% in 2006-2010 to 2% in 2011-2014. This was coupled with a substantial drop in the average growth rates of ICGs imports. All these may indicate an insolvency of the current import-led growth (ILG) strategy of Belarus.
Moreover, using an Autoregressive-Distributed Lag (ARDL) approach (Pesaran et al., 2001) to study the long-run relationship between ICGs imports and GDP growth, it was found that a 1% growth in imports of intermediate goods caused a 2.7% decrease in real GDP (Mazol, 2015). The effect of capital goods imports is statistically insignificant.
The Toda-Yamamoto (TY) causality test (Toda and Yamamoto, 1995) clarifies this result, indicating unidirectional causality running from economic growth to imports of intermediate goods, and further to imports of capital goods (see Figure 2).
Figure 2. TY Causality Test
Note: * 10% level of significance; ** 5% level of significance; *** 1% level of significance. Source: Author’s own estimations.
Thus, instead of an ILG hypothesis, the findings establish presence of a GLI hypothesis for Belarus, supporting the view that for developing countries, trade is more a consequence of the rapid economic growth than a cause (Rodrik, 1995).
What is the intuition behind these results? The ILG strategy aims to improve efficiency and productivity, and can be appropriate only under two crucial conditions: first, it is necessary to acquire preferably advanced technology from abroad; and, second, there have to exist enough domestic technological capabilities and skilled human capital in order to successfully adapt new technologies from R&D intensive countries.
In Belarus, a violation of the first condition was caused by an ineffective industrial policy aimed to modernize state-owned enterprises (SOEs) (Kruk, 2014). In many cases, capital accumulation was accomplished without appropriate investment appraisal and efficient marketing strategies.
Furthermore, there is serious evidence against the second condition being fulfilled: the share of innovative goods of all shipped goods in the past 4 years have dropped by 5.5 percentage points – from 17.8% to 12.3% (Belstat); and the «brain drain» is still a big problem (mostly due to low salary levels in research areas).
Influence of Exchange Rate Policies
Through the cost of imported intermediates, the exchange rate has an important influence on the price competitiveness of the Belarusian economy. However, the Belarusian exchange rate has fluctuated widely since 2000s (see Figure 3). For example, between 2000 and 2014, the annual percentage change in the nominal effective exchange rate (NEER) has varied from approximately 135% to -2%, and the real effective exchange rate (REER) fluctuated between 23% and 11% annually.
Figure 3. The Exchange Rate 2000-2014
Source: Belstat, IFS.
The results from estimated ARDL models (Mazol, 2015) show that while a depreciation of the Belarusian currency negatively influences both the imports of intermediate goods and GDP growth, it does not have a statistically significant effect on the imports of capital goods.
Concerning the influence on intermediate inputs, the explanation is that there are two effects of exchange rate policy on trade. On the one hand, depreciation of national currency leads to growth in the domestic currency price of exports, which motivates national companies to expand production of exports – the derived demand effect. On the other hand, it increases the domestic currency price of imported intermediate inputs, decreasing the quantity of intermediate imports domestics companies can buy – the direct cost effect. The direct cost effect and the derived demand effect have opposite signs (Landon and Smith, 2007).
Additionally, devaluations in Belarus occur in most cases both to import source and export destination countries (first of all Russia). Thus, in the case of imports of intermediate goods, the impact of the direct cost effect is greater than the impact of the derived demand effect, leading to a negative effect on imports of intermediate goods.
Furthermore, the substantial reliance of the Belarusian export sector on imported inputs, combined with above-presented side effects, cause cost-push inflation in the export sector, which decreases its price competitiveness and, overly, the economic growth. This statement is confirmed by the fact that in the period 2002-2011, intermediate inputs were imported both under the permanent expansionary monetary policy and the fixed exchange rate policy (see Figure 3). As a result of such twin strategies, intermediate imports have become more and more expensive, while the price competiveness of Belarusian export goods have steadily declined (taking into account that most of its industrial part is shipped to Russia).
The reason why the exchange rate policy do not seem to have had an effect on capital goods imports is that machinery and equipment were typically imported in accordance with the government’s modernization plans. The realization of these plans often disregarded the current macroeconomic situation in Belarus, and the imports were made just for the sake of importing (to accomplish the plan).
Finally, starting in 2012, depreciation of the Belarusian ruble coincided with the economic recession caused primarily by structural problems that hit the country (Kruk and Bornukova, 2013). Therefore, the increase in flexibility of exchange rate policy had no additional effect on ICGs imports and economic growth in Belarus.
Conclusion
The findings presented here indicate that trade (in terms of ICGs imports) is more a consequence of the rapid economic growth in Belarus rather than a cause. The influence of imports of intermediate goods on GDP growth in the long run is negative. Additionally, the depreciation of the national currency has had a large negative effect on both intermediate imports and economic growth, while its effect on capital goods imports was statistically insignificant.
Thus, Belarusian economic policy based on imported technologies seems ineffective especially in recent years, most probably due to decreasing skills and the ability to imitate and innovate using foreign inputs. Therefore, policy should focus on abolishing the directive industrial management, which has led to a negative influence of ICGs imports on economic growth in Belarus.
Additionally, the country’s export strategy should be refined so that export destinations are different from import sources of intermediate goods that are used for export production. Moreover, the imports of capital goods should contribute to the development of new export markets, and monetary and fiscal policies should be refined in order to promote positive effects of currency valuation changes.
References
- Kruk D., Bornukova K. 2013. Decomposition of economic growth in Belarus. FREE Policy Brief Series, October 2013.
- Coe D., Helpman E., Hoffmaister A. 1997. North-south R&D spillovers. The Economic Journal 107(440): 134-149.
- Grossman G., Helpman E. 1991. Innovation and growth in the global economy. The MIT Press, Cambridge MA.
- Grossman G., Helpman G. 1994. Endogenous innovation in the theory of growth. Journal of Economic Perspectives 8: 23–44.
- Kruk, D. 2014. Stimulating growth in Belarus: Selecting the right priorities. FREE Policy Brief Series, November 2014.
- Landon S., Smith C.E. 2007. The exchange rate and machinery and equipment imports: Identifying the impact of import source and export destination country currency valuation changes. North American Journal of Economics and Finance 18: 3–21
- Mazumdar J. 2001. Imported machinery and growth in LDCs. Journal of Development Economics 65: 209-224.
- Mazol, A. 2015. Exchange Rate, imports of intermediate and capital goods and GDP growth in Belarus, BEROC Working Paper Series, WP no. 32.
- Pesaran M.H., Shin Y, Smith R.J. 2001. Bounds testing approaches to the analysis of level relationships. Applied Econometrics 16: 289–326.
- Rodrik, D. 1995. Getting interventions right how South Korea and Taiwan grew rich. Economic Policy 10: 53-107.
- Toda H.Y., Yamamoto, T. 1995. Statistical inference in vector auto regressions with possibly integrated processes. Econometrics 66: 225–50.
Coming to Terms with the Past – Challenges for History Teaching in Russian Schools
Russia is currently reforming its history teaching in basic schools. An original idea of producing one single textbook was abolished. Instead, three different textbook series for 6th to 10th graders, as well as teacher’s manuals and map books, have been written. They are all based on the same conceptual framework (kontseptsiia) and differ merely in pedagogical approaches. To facilitate teaching on topics in Russia’s millennium-long history where the professionals disagree on interpretations, a series of survey brochures are written on over twenty “difficult questions”. Contrary to the views by some observers in the West of a state-ordered streamlining of historical narratives, the new history textbooks offer the pupils an overview of how and why historians diverge in their interpretations and assessments of many events, personalities and transitions in the millennium-long Russian history.
How to educate the next generations on Russia’s past has been in the focus for more than a decade, and not only among the professional historians, history teachers and pedagogues. New textbook proposals have spurred debates in society at large.
After the breakdown of the Soviet educational system in history, one whole year passed when the subject of history even disappeared from the curriculum; the old textbooks on the 20th century in particular were recognized as full of myths; taboo subjects were omitted and propaganda clichés abundant. In lack of new textbooks, teachers were free to use materials from the vital press and journals of the glasnost period. Only a few years later, however, there was a plethora of newly written history textbooks, including translations such as the French historian Nicolas Werth’s on Russia in the 20th century (Werth 1992). These new textbooks were checked at the Ministry of Education and either authorized or recommended, depending on their pedagogical qualities. Among the pioneers of history schoolbooks should be mentioned Aleksandr Danilov and Liudmila Kosulina, whose works are printed in many new editions (see e.g. Danilov 2007).
In the 2010s, there were already a huge number of recommended and authorized textbooks on Russian history. Every schoolteacher in the Russian Federation had a plethora of handbooks with their accompanying pedagogical matters (‘blind history maps’, questionnaires, teacher’s manual, CD-ROMs, etc.) to choose from. Interpretations differed in these books. Children from two parallel schools in the same town could have read two contradictory presentations of a number of events, depending on the textbook author’s ideological framework.
In 2013, the president and the government approved the oft-repeated demand for ‘a unified, single history textbook for schools’ (edinyi uchebnik istorii). While president Putin had just hinted on what was wishful, the burdensome task to accomplish a sound standardization of history teaching fell on commissions in the academic community. The historians responsible for the new conceptual framework emphasize their striving towards de-politization of history (Chubarian 2013). The evolution of ‘history policy’ in neighboring states set a bad example, as parliaments, governments or even presidents legitimate the one and only correct historical facts or interpretations. The Council of Europe and OSSE use a similar ‘history policy’ adopting resolutions described as scientific accomplishments, not merely political attitudes. Institutes for the national memory, sometimes jointly with laws of the parliaments, dictate how historical personalities, events and political movements are to be characterized, and divergent presentations may be subject to judicial prosecution. Contrary to a widespread opinion in the West, Russian historians and politicians who are interested in history questions actually strive to avoid ‘history policy’ (Chubarian 2016).
Nonetheless, Russian parliamentarians have sometimes tried the same approach to counter the political use of past events. Examples can be quoted of how specific events during and after the First World War, as well as the Second World War 1939-1945 have been used to criticize the present-day Russian regime, its leaders or even its people (Miller & Lipman 2012) .
The process to achieve a new uniform history textbook was multifaceted. First, a ‘concept framework’ (kontseptsiia) was set up in a concise form. This included the main historical facts to be treated. It further enumerated tens of historical events, processes and changes that have been hotly debated. This framework was thereafter widened to become a ‘historical-cultural standard’ with detailed description of how each epoch in Russia’s millennium-long history would be presented in the new textbooks.
Russia decided to use a ‘linear system’ of history education’ (lineika), i.e., to teach chronologically from 5th to 10th class and use the 11th, final year for special courses. Six author groups and publishing houses participated in the contest for a set of new schoolbooks. Merely three of them were approved. Today, the first textbooks have appeared from the publishing companies Prosveshchenie (Enlightenment), Russkoe Slovo (Russian Word) and DROFA. The reformation will however be gradual as the older, authorized books can still be used. It will take at least until 2020 before these new history textbooks are the only standard ones.
Professional historians do not create history manuals for teachers, textbooks as well as auxiliary pedagogical matters in splendid isolation. Numerous seminars and colloquiums have been organized all over the country, where history teachers met with authors, discussed projects or shared their experiences from using pilot copies of the new books. Likewise, now that the first new textbook is used in schools, several hundred tutors will organize courses for teachers’ advancement and acquaintance with recent research.
The ‘conceptual framework’ was widely discussed in 2013–14 at teachers’ seminars all over Russia and at the First All-Russian congress of history teachers. The first new teacher’s manuals and textbooks have been presented by the authors at the Third history teachers’ congress held in Moscow in the first week of April 2016. Most sections at this congress concerned strict pedagogical and examination matters. For your humble servant, the most fascinating section at this congress was devoted to what has been termed as “difficult questions”.
Contrary to the views by some observers in the West of a state-ordered streamlining of historical narratives, with emphasis on the state and high politics level, these new textbooks give the teenage pupils a basic understanding on how and why historians diverge in their interpretations and assessments of many events, personalities and transitions in the millennium-long Russian history. Already at the first meetings with history teachers, over thirty such thorny historical riddles were mentioned. To give history teachers a better position, the publishing companies have engaged leading specialists to write up-to-date surveys of recent research and the present state of debates.
These surveys start with the century-long debates on the origins and character of the early medieval Russian state formation. How the rule of Ivan IV (Ivan the Terrible, Ivan Groznyi) has been evaluated is described in another survey. Similar debate surveys are due to appear on Peter the Great and other tsars.
Western observers of the Russian historical scene concentrate on how the country’s 20th century history is analyzed. These are also the matters that tend to divide the scholarly community as well as the general public in Russia. Consequently, teacher’s guidebooks on these topics are much in demand. They treat such complex questions as how the autocracy had progressed by the 1900s, what long-term processes and which events caused the downfall of the monarchy in 1917. Other surveys analyze Soviet nationality policies. The international situation in the 1930s and in the early phase of World War Two is carefully described. The Soviet Union during the Cold war is analyzed with references to the most recent findings in Russian and Western archives. Furthermore, the causes of the failure of Gorbachev’s perestroika and its effects are discussed in another survey.
In Russia, as elsewhere, anniversaries and centenaries tend to heighten an already eager public interest in history. For the approaching 100th anniversary of the Russian revolution, we likewise expect to find numerous collective monographs, encyclopedias, as well as re-printed memoirs and scores of unearthed archival documents in exhibitions. No doubt, however much professional historian complain of “the tyranny of jubilees” that divert from their chosen fields, the scholarly community in Russia will certainly take this opportunity to widen its research field to new aspects of the historical scenes during 1917.
Literature
- Chubarian, Aleksandr O. (2013) “Istoriia ubivaet Ivana Groznogo” (History kills Ivan the Terrible), Rossiiskaia gazeta, 4 September.
- Chubarian, Aleksandr O. (2016), “Voprosy k istorii” (Questions to History), Ogonëk, No 12, 28 March.
- Danilov, A.A. & L.G. Kosulina (2007), Istoriia. Gosudarstvo i narody Rossii: 9 klass (History. The State and peoples of Russia. 9th class), Moscow.
- Miller, A. & M. Lipman (2012), Istoricheskaia politika v XXI veke (History policy in the 21st century), Moscow.
- Werth, Nicolas (1992), Istoriia sovetskogo gosudarstva 1900 – 1991, Moscow (translation of Histoire de l’Union Soviétique. De l’Empire russe à la CEI, 1900 – 1991, Paris 1991).
Global Inequality – What Do We Mean and What Do We Know?
Concerns about global economic inequality have become central in today’s policy debate. This brief summarizes what is known about the development of inequality globally, emphasizing the difference between the developments within countries and between countries. In the former sense, inequality has risen in most countries in the world since the 1980s, but in the latter sense inequality, has (most probably) dropped. To ensure future progress in terms of continued decreasing global inequality, fighting increasing inequality within countries is likely to be central.
In recent years, the distribution of income and wealth has emerged as one of the most widely discussed issues in societies everywhere. US President Barack Obama has called rising income inequality the “defining challenge of our time”, the topic has been on the agenda at meetings of the World Economic Forum in Davos, and studies by the IMF and the OECD (e.g., OECD, 2014, and IMF, 2014) have associated income inequality with lower economic growth. Thomas Piketty’s best-selling book “Capital in the Twenty-First Century” (2014) has placed the topic center-stage well outside academic and expert circles. At the same time, some have argued that all the talk about increasing inequality is in fact wrong and that it misses what they perceive as the more important story, namely, the decreasing global inequality. So, which is it, and what conclusions can be drawn?
Different Ways of Viewing the Facts About Global Inequality
When people talk about global income inequality there are a number of things that could be referred to. First, one might think of the inequality within countries across the world. From this perspective, the question in need of an answer would be: “How has inequality within individual countries changed globally in recent decades?” The short answer is that it has increased in most places. This is certainly the case in most of the developed world since the 1980s, while in emerging markets and developing countries (EMDCs) there are greater differences across time and regions. Looking at disposable incomes at the household level (the most commonly used measure in international comparisons) most countries in Asia and Eastern Europe have seen marked increases of inequality, while the trend seems to have been the opposite in Latin America and in large parts of Africa. In level terms, the development has been one of convergence since, on average, the countries in Eastern Europe and Asia started at much lower levels than those in Latin America and Africa. The development has resulted in that inequality levels are today on average at similar levels, with a Gini coefficient of between 0.4 and 0.45, in Africa, Asia, and Latin America (see figure 1 below and IMF, 2015) The same is true for the average across OECD countries where inequality has increased the most in percentage terms in countries starting at low levels, with the US being an exception in that inequality has increased even though the level has always been at the higher end among developed economies (e.g., OECD, 2015). The European average is today around 0.3 while the household disposable income Gini in the US is just below 0.4.
Figure 1. Change in the net Gini Index, 1990-2012
Source: IMF, 2015.
Looking at other income inequality measures, such as top income shares, the picture is similar: inequality has increased in most countries for which we have data since the 1980s. While it is important to recognize that top income shares are a very different measure of inequality, it has been shown that there is a close relationship between top income shares and the Gini coefficient in terms of capturing both level differences across countries and trends in the development (e.g., Leigh, 2007 and Morelli, Smeeding and Thompson, 2015). This together with one of the main strengths of the top income measure, namely, the length of the time series, allows us to put the recent developments in a historical perspective.
Figure 2 shows the income share of the top decile group for a number of mainly developed countries over the 20th century, illustrating the surprisingly common trends over the past 100 years (but also important level differences). On average, top shares (driven mainly by what happened in the top 1 percent) dropped from the beginning of the century until about 1980 after which it has risen in a fanning-out fashion. The point of the figure is clearly not to illustrate any individual country but rather to illustrate the overall long-run trend. For details of the historical development of income as well as wealth distribution, see Roine and Waldenström (2015).
Figure 2. Top 10 percent income share over the 20th century
Source: World top income database (WTID).
While the overall picture of rising inequality in most countries over the past decades is pretty clear, the development between countries is less so. There are two main reasons for this. First, it depends on what is considered the unit of observation and how these units are weighted. Second, it depends on what one assumes about the vast gaps in data availability, in particular in EMDCs (see e.g., Lakner and Milanovic, 2013, for more details).
As explained by for example Milanovic (2012) there are essentially three different ways in which one might think about the global distribution of income: 1) Treat every country as one observation and use a country’s GDP per capita as the measure of income; 2) do the same as in 1) but give different weight to each country according to its population; 3) Treat individuals (or households) as the unit of observation regardless of where people live. In all three cases it is possible to line up all observations from the poorest to the richest (and, hence, also to calculate a Gini coefficient). In the first way of looking at the world, we treat everyone in each country as being represented by the country’s average income and we also give the same weight to Luxemburg and India. In the second case, we recognize that more people live in India and weight it accordingly but we still, by construction, force everyone in each country to have the country average, thus ignoring within country inequality. Only in the last approach do we actually take into account both relative population size and differences in development within countries. This clearly seems the most satisfactory way to look at what has happened, but it is also the most demanding in terms of data.
In terms of the first two approaches, inequality in the world has fallen in the past decades. This is especially clear when weighting countries by population size. Rapid growth in China and India has caused average incomes in the world’s most populous and initially poor countries to increase faster than the global average, implying a reduction in global inequality. Some may think that this is not surprising and only to be expected since these countries start at such low levels, but in fact, this development marks the reversal of a 200-year trend toward increasing global inequality. Even “catch-up growth” is certainly not to be taken for granted.
Now the real question is this: What has happened to the global income distribution if we take into account the recent increasing inequality within many countries, including China and India? The answer turns out to complicated and uncertain (see Lakner and Milanovic, 2013 for details) but in the end most of the evidence points to decreasing global inequality in this sense too. As François Bourguignon puts it in a recent article in the Foreign Affairs: “…the increase in national inequality has been too small to cancel out the decline in inequality among countries” (Bourguignon, 2016, p. 14).
To understand both of these counteracting forces it is illustrative to look at real income growth across the global income distribution. Figure 3 below is taken from a presentation by Branko Milanovic, organized by SITE in 2014 (and available online here). It shows the real income growth for different percentile groups in the global distribution over the period 1988-2008. Moving from left to right the figure shows positive but modest growth for the very poorest individuals in the world, and much higher growth for the groups just above, with rates increasing toward the middle of the global distribution. In the range of about 5 dollars/day (in PPP adjusted terms) growth has been the highest. By developed-country standards, these people are still very poor, but globally they are truly the “middle class” in the sense that they make up the middle of the global income distribution. Moving further right we see a sharp drop in real income growth at a level around the 80th percentile. This part of the distribution is mainly populated by the lower middle classes of the developed world, and here income growth has been essentially zero over the past decades. Moving further right we again see a sharp increase in real income growth illustrating the large gains going to individuals in the top of the global income distribution.
Figure 3 summarizes much of what has happened: the left part showing the rapid growth of income among most of the world’s relatively poor, while the right shows the increasing inequality in the developed world, with the top of the distribution gaining the most.
Figure 3. Real income growth at various percentiles of the global income distribution, 1988-2008 (in 2005 PPPs).
Source: Lakner and Milanovic (2013).
Why This Matters and What Should Be Done About Global Inequality?
The forces that explain what has happened are of course complex and differ over time and across countries but one thing seems clear, the growth of real incomes in developing countries as well as the relative decline of incomes in the lower end of the income distribution in developed countries have at least in parts been shaped by the same intertwined processes of globalization and technological development. Overall, these processes are powerful positive developments, but at the same time it is easy to see how those who perceive themselves as losers in these developments may try to resist them using their political voice. It is important to remember that globalization is the result of a combination of technology and political decisions, and consequently not an inevitable process. After all, the globalization backlash in the period 1914-1945 did not happen because the technological feasibility of the process suddenly disappeared.
The appropriate government responses are of course also likely to be different across countries, but here there are also some common factors that stand out. In the developing world, the most challenging aspects will have to do with maintaining state capacity and the ability to tax increasingly mobile tax bases. In many developing countries taxation will also be key, but here the challenge is more about creating a capable and accountable state in the first place. As succinctly and, I think, correctly put by Nancy Birdsall in a review of Thomas Piketty’s “Capital in the Twenty-First Century”: “(I)n the developing world, the challenge is not, at least not yet, the one Piketty outlines — that an inherent tendency of capitalism is to generate dangerous inequality that if left unchecked will undermine the democratic social state itself. The challenge is the other way around: to build a capable state in the first place, on the foundation of effective institutions that are democratically accountable to their citizens.”
References
- Atkinson, Anthony B. 2015. “Inequality – What can be done?” Harvard University Press.
- Birdsall, Nancy. 2014. “Thomas Piketty‘s Capital and the developing world”
- Ethics & International Affairs / Volume 28 / Issue 04 / Winter 2014, pp 523-538.
- Bourguignon, François, and Christian Morrison. 2002. “Inequality among World Citizens: 1820-1992”, The American Economic Review, Vol. 92, No. 4. (Sep., 2002), pp. 727-744.
- Bourguignon, François. 2016. “Inequality and Globalization. How the rich get richer as the poor catch up”, Foreign Affairs, Volume 95, Number 1, pp. 11-16
- Lakner, Christoph, and Branko Milanovic. 2013. “Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession.” WB Policy Research Working Paper 6719, World Bank, Washington.
- Leigh, Andrew. 2007. “How closely do top income shares track other measures of inequality?”, The Economic Journal, 117 (November), 589–603.
- OECD (2015), “Growth and income inequality: trends and policy implications”, OECD Economics Department Policy Notes, No. 26 April 2015.
- OECD. 2011. Divided We Stand: Why Inequality Keeps Rising. Paris: OECD Publishing.
- OECD. 2012. “Reducing Income Inequality While Boosting Economic Growth: Can It Be Done?” In Economic Policy Reforms: Going for Growth. Paris: OECD Publishing.
- Ostry, Jonathan David, Andrew Berg, and Charalambos G. Tsangarides. 2014. “Redistribution, Inequality, and Growth”, IMF SDN, February 17, 2014
- Milanovic, B. 2013. “Global Income Inequality by the Numbers: in History and Now.” Global Policy 4 (2): 198–208.
- Morelli, Salvatore, Smeeding, Timothy, and Jeffrey Thompson. 2015. “Post-1970 Trends in Within-Country Inequality and Poverty: Rich and Middle Income Countries”, Chapter in Atkinson, A.B., Bourguignon, F. (Eds.), Handbook of Income Distribution, vol. 2A, North-Holland, Amsterdam.
- Piketty, Thomas. 2014. “Capital in the Twenty-first Century”. Cambridge, Massachusetts: Harvard University Press.
- Pritchett, Lant. “Divergence, Big Time.” Journal of Economic Perspectives, Summer 1997, 11(3), pp. 3-17.
- Roine, Jesper, and Daniel Waldenström. 2015. “Long-Run Trends in the Distribution of Income and Wealth”, Chapter in Atkinson, A.B., Bourguignon, F. (Eds.), Handbook of Income Distribution, vol. 2A, North-Holland, Amsterdam.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Is Local Monetary Policy Less Effective When Firms Have Access to Foreign Capital?
Central banks affect growth in part by raising or lowering the cost of investment through their influence over local interest rates. We examine whether the ability of local firms to raise money abroad reduces the influence of local monetary policy authorities. Surprisingly, it does not. In fact, we find that firms that are able to raise equity capital from foreign investors are more responsive, not less, to local monetary policy shocks than those that raise capital only in the domestic market. These findings suggest that foreign investors confer an efficiency effect, improving the sensitivity of stock prices to local monetary policy shocks.
One means by which central banks affect economic growth is by influencing interest rates that impact the cost of financing for firms. For example, when a central bank lowers interest rates, those lower rates make new investment cheaper and more profitable. That encourages companies to invest more. Profits rise, firms hire more and we see growth in the economy as a whole.
When firms are able to raise money abroad, they are no longer as dependent on the local economy for financing. This potentially causes problems for central banks and other local monetary policy authorities who wish to influence the local economy by controlling interest rates.
This brief summarizes the results of Francis, Hunter and Kelly (2016), where we examine the extent to which monetary policy authorities’ influence differs across firms that are able to access foreign capital (also called “investable stocks”) and those that are largely dependent on the local market (also called “non-investable stocks”). Contrary to expectations, the evidence shows that firms that are able to raise foreign capital by being open to foreign equity investment are actually more sensitive to local monetary policy shocks than those that are not.
The perks and perils of financial liberalization
Over the last 30 years, the authorities in several less developed countries liberalized their domestic financial markets by allowing foreign ownership of local stocks. There are tremendous benefits for the local firms that became ‘investable’ as these countries liberalized, relative to firms that remained dependent solely on domestic stock markets. These include, inter alia, (1) being able to raise large tranches of foreign capital at lower rates than available in the domestic market, which reduces their financing constraints and increases their ability to invest, (2) substantial improvement in the liquidity of their stocks, (3) improvements in corporate governance and reporting (see Reese and Weisbach, 2002), and (4) greater efficiency with which their stocks incorporate value-relevant information.
Despite these benefits, there is widespread concern that liberalization comes with several problems. First, foreign capital flow (“hot money”) can cause excess volatility in local stock markets and exchange rates when foreign investors rapidly repatriate their funds. Second, local firms may become sensitive to foreign monetary policy shocks, and those foreign monetary shocks may be contrary to what is needed in the local economy. Third, and perhaps chief among the problems, is that if a large segment of domestic firms is able to raise capital abroad, then local monetary authorities may lose their ability to influence the domestic economy through their control of local policy interest rates. We examine this last concern in this policy brief below.
What does the research tell us?
One of the big challenges when measuring the impact of changes in monetary policy on an economy is the fact that the effects of investment started or stalled by changes in monetary policy may take months, or even years, to play out. The long time frame makes it very difficult to tell whether changes in monetary policy affect the macro economy. To solve this problem we follow in the footsteps of the former Chair of the U.S. Federal Reserve, Ben Bernanke (see Bernanke and Blinder, 1992, and Bernanke and Kuttner, 2005) and examine the impact of monetary policy shocks on stock returns. We do this because stock prices reflect anticipated changes in the economy and they are one of several channels through which monetary policy actions are transmitted to the real economy. That is, if local stock prices respond to monetary policy changes, it is likely the local economy will respond as well.
Because stock prices move in anticipation of future improvements in the economy, it is very important that we measure monetary policy surprises (also referred to as shocks) and not merely observed changes in monetary policy. To do this we model expectations about local monetary policy as a function of changes in oil price, changes in the U.S. Fed-funds rate (a proxy for changes in U.S. monetary policy), local industrial production growth, inflation rate and exchange rate changes. Details are described in the companion paper to this brief, Francis, Hunter and Kelly (2016).
We examine the impact of local monetary policy shocks on local stock returns. We find that for 17 of the 24 developing markets in our sample a one-standard-deviation surprise increase in local monetary policy interest rates results in an immediate and statistically significant 1.06% decline in the country’s overall stock market index. Interestingly, the unresponsiveness of the remaining seven stock markets to local monetary policy is not entirely due to the dominance of foreign (U.S.) monetary policy. In only four of the seven markets is foreign monetary policy simultaneously significant.
As noted above, one possible concern is that local monetary policy influences the investment and financing decisions of only non-investable firms. However, we find that firms that have access to foreign equity capital are at least as sensitive to local monetary policy shocks as are firms that are closed to foreign equity investment. In about 30 percent of our sample, Chile, Mexico, Venezuela, Jordan and Russia, firms that are open to foreign investment are even more sensitive than the ones that are closed. This evidence is consistent with the hypothesis that foreign investor participation in investable stocks improves the informational efficiency of investable firms’ stock prices, making them more sensitive to local monetary policy shocks. We call this an “efficiency” effect. This is counter to the predictions of the “integration” effect, whereby local stocks that are accessible to foreign investors are more responsive to foreign, not local, monetary policy shocks.
As an example, consider the impact of local monetary policy shocks on the returns of Brazilian stocks that are open and closed to foreigners, as depicted in Figure 1. In both panels the stock market is subjected to a one- standard-deviation surprise tightening of monetary policy, which is equivalent to 0.52% higher policy interest rates. In the top panel, the response is a statistically significant decline of 1.9% in the stock prices of firms that are open to foreign investment. In the bottom panel, the same monetary policy surprise translates into a statistically insignificant 0.9% lower prices for stocks that are closed to foreign investment. These findings are typical of the other countries in our companion study.
Figure 1. Impulse Responses of Brazilian Stock Returns to a One-Standard-Deviation Structural Shock in Local Monetary Policy
Investable stocks – open to foreign investment
Non-investable stocks – closed to foreign investment
Source: This figure reports impulse responses (center line) of investable and non-investable stock returns over 24 months in response to a one-standard-deviation structural shock in local Brazilian monetary policy. The impulse responses are obtained from a structural VAR model with eight endogenous variables: oil prices, the U.S. Fed-Funds rate, local industrial production growth, inflation, exchange rates and investable and non-investable Brazilian stocks. The left axis is in percent and the horizontal axis is months after a policy shock. The outer bands are probability bands used to determine statistical significance. The impulse response in a given period is significant, if both outer bands are on the same (lower or upper) side of the horizontal line at zero.
Ruling out alternate interpretations
One concern with the above results is that they might be driven by the simultaneous response of stock prices and monetary policy to emerging market crises that occurred during our sample period. However, the results when controlling for the Mexican and Asian currency crises are materially the same. The Russian default in 1998 is prior to the start of our data for Russia.
Additionally, one might be concerned that when we separate stocks into investable and non-investable, what we are really doing is separating firms on the sensitivity of their product markets to changes in the local economy. To examine this, we determine whether our results hold for stocks that operate in traded-goods markets and for those that operate in non-traded goods markets. We continue to find that investable stocks are more sensitive than non-investable stocks to local monetary policy in both markets.
Summary and policy implications
Our research suggests that firms that are open to foreign investment are at least as sensitive to local monetary policy as are firms that remain closed to foreign investment. These findings assuage a non-trivial concern among monetary policy authorities that while access to foreign capital has many benefits, it may come at the cost of a loss of ability to influence one’s own local economy. The primary policy implication of our work is that foreign investment in local stocks does not result in a loss of monetary policy control. In fact, our results suggest that foreign investment makes local firms more responsive to monetary policy shocks.
On the Timing of Turkey’s Authoritarian Turn
This policy brief examines the timing of Turkey’s authoritarian turn using raw data measuring freedoms from the Freedom House (FH). It shows that Turkey’s authoritarian turn under the ruling AKP is not a recent phenomenon. Instead, the country’s institutional erosion – especially in terms of freedoms of expression and political pluralism – in fact began much earlier, and the losses in the earlier periods so far tend to dwarf those occurring later.
Introduction
A growing field in economics emphasizes the importance of the media in shaping economic outcomes. Whereas the role of the media in informing voters is well established (Strömberg, 2015), recent research also points to the link between the rise of illiberal democracies (Mukand and Rodrik, 2016) and authoritarian control over media (Guriev and Treisman, 2015).
In few countries is the link between authoritarianism and restrictions on freedom of expression as pervasive as in Turkey. The Turkish government under the Erdoğan-led Justice and Development Party AKP has gutted the judiciary of most of its independence, and set it loose to crack down on critical media. These dire circumstances, however, contrast markedly with descriptions of Turkey from of a few years ago. Quite recently many analysts still deemed Turkey a “vibrant democracy”, and as late as in 2013 the foreign minister of Sweden proclaimed: “Erdoğan’s Turkey is on the right path.” This media shift raises concerns over the public portrayal of Turkey’s institutional development up until the last few years as well as the extent to which analysts may have misinterpreted Turkey’s institutional development over the past decade.
Measures of Freedoms
To this date, the most prominent source of measuring freedoms in the world is the Freedom House’s annual Freedom of the World reports (Freedom House, 2015), which designates countries into one of three statuses: Free, Partly Free, and Not Free, in ascending order in freedoms. In constructing these statuses, FH uses subscores for 7 subcategories, aggregated into 2 categories — Political Rights (hereby PR), with a range of 0 to 40 increasing in freedoms, and Civil Liberties (hereby CL), with a range 0 to 60 increasing in freedoms – for which each then gets its own 1-7 (with a low value indicating more freedoms and vice versa), and in turn these are used to classify a country as having a particular Freedom status. From the FH’s methodology section:
A country or territory is awarded 0 to 4 points for each of 10 political rights indicators and 15 civil liberties indicators, which take the form of questions; a score of 0 represents the smallest degree of freedom and 4 the greatest degree of freedom. The political rights questions are grouped into three subcategories: Electoral Process (3 questions), Political Pluralism and Participation (4), and Functioning of Government (3). The civil liberties questions are grouped into four subcategories: Freedom of Expression and Belief (4 questions), Associational and Organizational Rights (3), Rule of Law (4), and Personal Autonomy and Individual Rights (4).
The PR category thus focuses more on rights pertaining to politics, and is used also to construct an indicator variable for whether a country constitutes an electoral democracy or not. CL, as the name indicates, is more focused on liberties, including the right to freedom of expression, including media freedoms.
Somewhat curiously, Turkey’s ratings have barely budged over the last decade, and have been consistently classified as a Partly Free country. In 2005, FH assigned Turkey a 3 in both PR and CL, and the only change since then was a one-point drop in 2012’s CL rating down to 4.
The PR and CL, as well as their subcategory, scores are available on FH’s website. Using these, the graphs below plot the evolution of the PR and CL total scores for Turkey between 2005-2015 (which is the period for which FH provides this data), as well as the 25th, 50th, and 75th global percentiles from the annual world distribution of the respective scores. The latter allows gauging not just the absolute performance of Turkey but also that relative to the rest of the world.
Figure 1. Freedom House Category Scores
Note: The red lines in the upper (lower) graph indicate the Political Rights (Civil Liberties) score. The dashed gray lines indicate the 25th, 50th, and 75th percentiles.
Turkey’s PR score (upper graph) is relatively flat over the decade with a 4-point drop after 2013, while the CL score (lower graph) has been falling since 2010 and was stagnant in the period before. Whereas Turkey started the period with a CL score just below the median country, it ended closer to the 25th percentile. None of the years show any indication of expanding freedoms during AKP’s rule.
The disaggregation of these scores into subcategories sheds further light on which of the latter have driven the former. For Turkey, especially relevant subcategories are the political pluralism and freedom of expression. The former refers to the degree to which people can organize in political groupings, credible opportunities for a political opposition, freedom from outside interference, and political rights for ethnic minorities. (This has clear links with the political barriers to entry such as the ten-percent threshold, the banning of political parties, and the persecution of Kurdish political activists in Turkey.) The latter subcategory refers to freedoms related to media, culture, religion, and academics, as well as the degree of freedom from government surveillance. Turkey’s subscores are plotted below, grouped by PR and CL:
Figure 2. Freedom House Subcategory Scores
In Figure 2, there is rather striking fall in both the political pluralism (red in upper graph) and freedom of expression (blue in lower graph). The other subscores tend to be more stagnant over time, and the only subcategory that exhibited any significant positive momentum during the period is Electoral Process, although by 2015 it had reverted to its 2005 value. The falls in political pluralism and freedom of expression are large in magnitude, from 12 to 9 in the former, and 12 to 8 in the latter. Taking the latter decrease at face value would imply that Turkish citizens in 2015 have two-thirds of the freedoms of expression that they enjoyed in 2005. Moreover, the clear majority of the falls in both these variables occured before 2013 – the post-2013 fall in freedom of expression accounts for only one fourth of the total fall observed since 2007.
Given the degree to which civil liberties have eroded faster than that of political rights in Turkey, this begs the question how its inherent degree of illiberalism has evolved relative to other democracies. For this purpose, I plot the Freedom of Expression subcategory (a part of the CL score) against the PR score for the 2015. This latter score is used by FH to classify countries into whether they can be called ‘electoral democracies’ or not (CL subcategories have no bearing on this classification):
“An ‘electoral democracy’ designation requires a score of 7 or better in subcategory A (Electoral Process) and an overall Political Rights score of 20 or better.”
FH thus classifies Turkey as an electoral democracy – its Electoral Process is consistently above 7 (see upper graph in Figure 2) and PR score above 20 (see Figure 1). But are there many FH-classified electoral democracies with similar levels of freedom of expression? Figure 3 answers this question:
Figure 3. Freedom House Subcategory Scores
Note: Green = Autocracy, blue = Democracy, Red = Turkey. The dashed green/blue lines indicate the median values for autocracies/democracies.
In 2015, Turkey is much closer to the median autocracy than the median democracy in terms of freedom of expression. Numerous autocracies have higher levels of freedom of expression than Turkey, and only two other electoral democracies have lower values of this variable: Bangladesh and Pakistan.
Consequently, Turkey today is a clear outlier due to its freedom of expression deficit among the countries classified as electoral democracies by FH. Yet the slide in Turkeys’ freedoms did not start in the last couple of years but has remained a pervasive feature of its institutional trajectory during the last decade.
Much of Turkey’s erosion of freedoms would not be as visible using only the most aggregate seven-point scaled ratings, as these obfuscate important changes within the rating scores. A shift in analysts’ focus to more disaggregated data may thus be useful in order to detect warning signs in a more timely fashion.
Finally, the severe deficit in freedoms in countries nonetheless classified by Freedom House as electoral democracies raises the issue of whether there should be a lower freedom bound to inclusion into the group of democracies in the world. And if so, what should determine such a lower bound?
References
- Freedom House, 2016, “Freedom of the World 2016.”
- Guriev, Sergei, and Daniel Treisman, 2015, “How Modern Dictators Survive: An Informational Theory of the New Authoritarianism”, NBER Working Paper No 21136.
- Meyersson, Erik, and Dani Rodrik, “Erdogan’s Coup”, Foreign Affairs, May 26th, 2014,
- Mukand, Sharun, and Dani Rodrik, 2016, “The Political Economy of Liberal Democracy”,working paper.
- Rodrik, Dani, 2014, “A General’s Coup”, mimeo.
- Strömberg, David, 2015, “Media and Politics”, Annual Review of Economics, 7: 173-205.
The Economic Complexity of Transition Economies
‘Diversification’ is a constant concern of policy-makers in resource rich economies, but measurement of diversification can be hard. The recently formulated Economic Complexity Index (ECI) is a promising predictor of economic development characterizing the overall complexity and diversity of the economy as a system. The ECI is based on the diversity and ubiquity of a country’s exports. This brief uses ECI to discuss the economic diversity of transition economies in the post-Soviet decades, and the relationship between economic diversification and per capita income.
The search for and construction of appropriate predictors of economic development are among the main goals of economists and policy-makers. Education, infrastructure, rule of law, and quality of governance are all among the commonly used indicators based on inputs. The recently formulated Economic Complexity Index (Hidalgo and Hausmann, 2009) is a new promising predictor of economic development characterizing the overall complexity and diversity of the economy as a system.
Indeed, the importance of production and trade diversification for economic development has been highlighted by the economic literature. Numerous studies have found a positive relationship between diversified and complex export structure, income per capita and growth (Cadot et al., 2011; Hesse, 2006; Hausmann et al., 2007). In line with this, Hausmann et al. (2014) demonstrate the predictive properties of the ECI for economic development and GDP per capita, which implies that the ECI can serve as a useful complement to the input-based measures for policy analysis by reasoning from current outputs to future outputs.
This brief uses the ECI to discuss the evolution of economic diversification, its relationship to per capita income in transition economies in the post-Soviet decades, and its policy implications.
How is economic complexity measured?
The economic complexity index (ECI) is a novel measure that reflects the diversity and ubiquity of a country’s exports. The index considers the number of products a country exports with revealed comparative advantage and how many other countries in the world export such goods. If a country exports a high number of goods and few other countries export these products, then its economy is diversified (a wide range of exports products) and sophisticated (only a few other countries are able to export these goods). Thus, the measure tries to capture not a specific aspect of the economy, but rather its overall sophistication.
For example, Japan, Switzerland, Germany and Sweden have been in a varying order at the top of the ranking of the Economic Complexity Index from 2008 until 2013. This means that these countries export a large number of highly sophisticated products.
In contrast, Tajikistan is among the countries at the bottom of the world ranking by the ECI with raw aluminum, raw cotton and ores making up 85% of all Tajikistan’s exports in 2013. However, not only are Tajikistan’s exports concentrated among very few narrow products, these products are also ubiquitous and the ability to export them does not require knowledge and skills that can be used in the production and exports of many other products.
As the index for each country is constructed relative to other countries’ exports, it is comparable over time.
What can we learn from the economic complexity of transition economies?
The economic complexity index can serve as a useful indicator for understanding transition economies in the post-Soviet period. A strong relationship between GDP per capita and economic complexity is found in the sample of transition economies in Figure 1. This figure presents the relationship for the last year for which data is available for the sample of 13 post-Soviet states and Poland. As can be seen in Figure 1, the economic complexity is positively related to income per capita. This is especially true for Poland, Estonia, Lithuania, Latvia and Russia, who all have higher than average economic complexity and high levels of per capita income. While Belarus and Ukraine also have diverse and complex economies, they have somewhat lower income per capita than the first group.
Figure 1. Economic Complexity and GDP per capita
Source: Data on GDP per capita is from the World Bank, and the data on the Economic Complexity Index is from the Observatory of Economic Complexity.
Natural resource-rich, or rather, oil-rich countries are the exception from the abovementioned correlation. Most transition countries with below than average economic complexity are characterized by low income per capita levels, except for Kazakhstan and Azerbaijan, which are oil-rich countries. Still, the overall picture is straightforward: countries with a complex export structure have a higher level of income.
One of the advantages of a systemic measure like export complexity is its straightforward policy application. The overall diversity and sophistication of the economy can thus be a complementary measure for the assessment of economic progress and development to GDP and GDP per capita, which are more susceptible to the volatile factors such as commodity prices.
Figure 2 shows the development of economic complexity for 14 post-Soviet countries and Poland between 1994 and 2013 (due to data availability issues, only one year is available for Armenia).
First, we see that the economic complexity has diverged over time, although there is some similarity in the rankings among countries over time. The initial closeness is likely related to the planned nature of the Soviet economy that aimed to distribute production among Soviet Republics. In the post-Soviet context, however, the more complex economies (Estonia, Belarus, Lithuania, Ukraine, Latvia, Russia) kept or increased their sophistication and diversity of exports. Poland is the leading economy in terms of complexity, both in the beginning and towards the end of the sample period. Belarus, the second most complex economy in 2013 and the most complex economy in several years prior, shows an increasing trend in its sophistication of exports. Although its GDP per capita is noticeably lower than what would be expected from such a sophisticated economy, the complex production structure may explain its ability to withstand a permanent high inflation and external macroeconomic shocks. Some others, e.g., Tajikistan and Azerbaijan, saw a decreasing trend in economic complexity; Georgia and Kazakhstan, notably, lost in economic complexity but also in their ranking among their peers.
Figure 2. Economic Complexity of Transition Economies
Source: Data on GDP per capita is from the World Bank, and the data on the Economic Complexity Index is from the Observatory of Economic Complexity.
Conclusion
This brief revisited the economic complexity of transition economies and its evolution since the 1990s. The post-Soviet and other transition countries have had diverging economic development paths: Some have managed to build complex production economies, while others’ comparative advantage remains in raw materials. These differences are also reflected in their income levels.
Across the world, economic diversification is associated with higher per-capita income. As the brief showed, this relationship also holds for the post-Soviet countries; policy-makers should take economic diversification seriously. Increasing economic complexity may well pave the path to higher income levels.
References
- Cadot, O., Carrère, C., & Strauss-Kahn, V. (2011). Export diversification: What’s behind the hump?. Review of Economics and Statistics, 93(2), 590-605.
- Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Simoes, A., & Yildirim, M. A. (2014). The atlas of economic complexity: Mapping paths to prosperity. Mit Press.
- Hausmann, R., Hwang, J., & Rodrik, D. (2007). What you export matters. Journal of economic growth, 12(1), 1-25.
- Hesse, H. (2006). Export diversification and economic growth. World Bank, Washington, DC.
- Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. proceedings of the national academy of sciences, 106(26), 10570-10575.
Important Policy Lessons from Swedish-Russian Capital Flows Data
A recent study of capital flows between Sweden and Russia provides many policy lessons that are highly relevant for the current economic situation in Russia. In line with studies on other countries, bilateral FDI flows were more stable than portfolio flows, which is important for a country looking for predictable external sources of funding. However, much of the FDI flows came with trade and growth of the Russian market. The sharp decline in imports and fall in GDP is therefore bad news also when it comes to attracting FDI. The conclusion is (again) that institutional reforms and reengaging with the West are crucial policies to stimulate both the domestic economy and encourage much-needed FDI.
In a recent paper (Becker 2016), I take a detailed look at the trends and nature of bilateral capital flows between Sweden and Russia over that last 15 years. Although the paper focuses on the capital flows of a relatively small country like Sweden with Russia, it sheds some light on more general theoretical and empirical issues associated with FDI and portfolio flows that are highly relevant for Russia today.
Measuring Bilateral FDI
One general qualifier for studies of bilateral capital flows is however the reliability of data; Not only is a significant share of international capital flows routed through offshore tax havens which makes identifying the true country of origin and investment difficult, but also many investing companies are multinationals (MNEs) with operations and shareholders in many countries so it is hard to have a clear definition of what is a “Swedish” or a “Russian” company. In addition, when different official data providers, in this case Statistics Sweden (SCB) and the Central Bank of Russia (CBR), report capital flows on the macro level, there are large discrepancies.
Private companies also gather company level data on FDI that can be aggregated and compared with the macro level FDI data. This data is on gross FDI flows and should not be expected to be the same as the net macro level FDI flows data but is a bit of a “reality check” of the macro data.
Figure 1. Average annual FDI flows
Sources: SCB, CBR, fDi Market, MergerMarkets
The reported annual average flow of FDI from Sweden to Russia varies from around USD500 million to USD1.2 billion depending on the data source. Russian flows to Sweden are rather insignificant regardless of the source but the different sources do not agree on the sign of the net flows (Figure 1).
The differences between data sources suggest that some caution is warranted when analyzing bilateral FDI flows. With this caveat in mind, there are still some clear patterns in the capital flows data from Sweden to Russia that emerge and carries important policy lessons in the current Russian economic environment.
FDI vs. Portfolio Investments
There is a large literature discussing the distinguishing features of FDI and portfolio flows (see Becker 2016 for a summary). Some of the key macro economic questions include which type of flows provides most international risk sharing; are most stable over time; or most likely to contribute to balance of payments crises when the flows go in reverse. In addition, there are potential differences in terms of the amount of international knowledge transfers and how different types of capital flows respond to institutional factors.
Figure 2. FDI and portfolio investments
Source: SCB
Figure 2 shows that FDI has been much more stable than portfolio flows in the years prior to and after the global financial crisis as well as in more recent years. Although all types of capital flows respond negatively to poor macroeconomic performance, and the stock of portfolio investments swing around much faster than FDI investments, i.e., portfolio flows go in reverse more easily and can contribute to external crises. This makes FDI a more preferable type of capital flow for Russia.
FDI and Trade Go Together
Since FDI is a desired type of capital flow, it is important to understand its driving forces. The first question to address is whether FDI and trade are substitutes or complements. Since the bulk of FDI comes from MNEs that operate in many countries, we can imagine cases both when FDI supports existing trade and cases when it is aimed at replacing trade by moving production to the country where the demand for the goods is high.
In the case of Sweden and Russia, the macro picture is clear; FDI has increased very much in line with Swedish exports to Russia (Figure 3). Both of these variables are of course closely correlated with the general economic development in Russia, but even so, the very close correlation between FDI and trade over the last 15 years suggests that they are compliments rather than substitutes.
Figure 3. Swedish Exports and FDI to Russia
Source: SCB
Most FDI is Horizontal
FDI flows are often categorized in terms of the main motivating force for MNEs to engage in cross-border investment: vertical (basically looking for cheaper inputs), horizontal (expanding the customer base), export-platform (producing abroad for export to third countries) or complex (a mix of the other reasons) FDI.
Looking at the sectoral composition of FDI from Sweden to Russia (Figure 4), most investments have come in sectors where it is clear that MNEs are looking to expand their customer base. Even in the case of real estate investments, a large share is IKEA developing new shopping centers that host their own outlets together with other shops. Communication and financial services are also mostly related to service providers looking for new customer. Only a small share is in natural resource sectors that would be more in line with vertical FDI, while there are very few (if any) examples of MNEs moving production to Russia to export to third countries.
Figure 4. Sectors of Swedish FDI to Russia
Source: SCB
Policy conclusions
The above figures on bilateral capital flows from Sweden to Russia carry three important policy messages: 1) FDI is more stable than portfolio flows; 2) Trade goes hand in hand with FDI; and 3) FDI to Russia has mostly been horizontal and driven by an expanding customer base.
In the current situation where Russia should focus on policies to attract private capital inflows, the goal should be to attract FDI. Instead, the government is now looking for portfolio inflows in the form of a USD3 billion bond issue. But FDI is a more stable type of international capital than portfolio flows and also come with the potential of important knowledge transfers both in terms of new technologies and management practices.
However, as we have seen above, FDI inflows have in the past been correlated with increased trade and an expanding Russian market. In the current environment, where imports with the West declined by 30-40 percent in the last year, GDP fell by around 4 percent, and the drop in consumers’ real incomes have reached double digits in recent months, it is hard to see any macro factors that will drive FDI inflows.
Instead, attracting FDI in this macro environment requires policy changes that remove political and institutional barriers to investments. The first step is to fulfill the Minsk agreement and contribute to a peaceful solution in Ukraine that is consistent with international laws. This would not only remove official sanctions but also provide a very serious signal to foreign investors that Russia plays by the international rulebook and is a safe place for investments from any country.
The second part of an FDI-friendly reform package should address the institutional weaknesses that in the past have reduced both foreign and domestic investments. It is telling that many papers that look at the determinants of FDI flows to transition countries include a ‘Russia dummy’ that is estimated to be negative and both statistically and economically significant (see e.g. Bevan, Estrin and Meyer, 2004 and Frenkel, Funke, and Stadtmann, 2004). One factor that reduces the significance of the ‘Russia dummy’ is related to how laws are implemented. Other studies point to the negative effect corruption has on FDI.
Reducing corruption and improving the rule of law are some of the key reforms that would have benefits far beyond attracting FDI and has been part of the Russian reform discussion for a very long time. It was also part of the reform program that then-President Medvedev presented to deal with the situation in 2009 together with a long list of other structural reforms that would help modernize the Russian economy and society more generally.
As the saying goes, don’t waste a good crisis! It is time that Russia implements these long-overdue reforms and creates the prospering economy that the people of Russia would benefit from for many generations.
References
- Becker, T, 2016, “The Nature of Swedish-Russian Capital Flows”, SITE Working paper 35, March.
- Bevan, A, Estrin, S & Meyer, K 2004, “Foreign investment location and institutional development in transition economies”, International Business Review, vol. 13, no. 1, pp.43-64.
- Frenkel, M, Funke, K & Stadtmann, G 2004, “A panel analysis of bilateral FDI flows to emerging economies”, Economic Systems, vol. 28, no. 3, pp. 281-300.
Highly Educated Women No Longer Have Fewer Kids
This policy brief summarizes evidence that the cross-sectional relationship between fertility and women’s education in the U.S. has recently become U-shaped. The number of hours women work has concurrently increased with their education. The theory that the authors advance is that raising children and home-making require parents’ time, which could be substituted by services such as childcare and housekeeping. By substituting their own time for market services to raise children and run their households, highly educated women are able to have more children and work longer hours. The authors find that the change in the relative cost of childcare accounts for the emergence of this new pattern.
In 2012, the European Commission published a special report on “women in decision making positions”, suggesting legislation to achieve balanced representation of women and men on company boards. Some countries such as Norway, France, Italy, Belgium and the Netherlands have already taken legal measures in that direction. Trends in women’s education give hope that such goals may be achieved as women are increasingly occupying more prestigious and demanding careers. Indeed, in today’s world, women have surpassed men in higher education in most developed countries (Goldin et al 2006; Hazan and Zoabi 2015a).
What are the consequences of this important development for fertility? Historically, highly educated women have had fewer kids than less educated women (see, for example, Jones and Tertilt 2008). This relationship is deep rooted in the economic and sociological literature to the extent that many theories have already been proposed to explain this relationship. Leading explanations rely on the difficulty to combine children and career (Mincer, 1963; Galor and Weil, 1996) and the quantity-quality tradeoff (Becker and Lewis, 1973; Galor and Weil, 2000; Hazan and Zoabi 2006). The shift in women’s education coupled with more demanding careers for women means that if the cross-sectional relationship between women’s education and fertility is stable over time, then future fertility rates will continue to decline from their already historically low levels.
In Hazan and Zoabi (2015b) we find, however, that the cross-sectional relationship between women’s education and fertility has changed from monotonically declining until the 1990s to a U-shaped pattern during the 2000s. This change is due to a substantial increase in fertility among women with advanced degrees who increased their fertility by 0.7 children, or by more than 50%. This is illustrated in Figure 1, which plots the cross-sectional relationship between fertility and women’s education in 1980 and during the period 2001-2011.
Figure 1: Fertility Rates by Women’s Education, 1980 and the 2000s.
What can explain the rise of fertility among highly educated women during the period that saw the largest increase in the labor supply of highly educated women? We argue that the rise in college premium increased the demand for child-care and housekeeping services by highly educated women and a rise in the supply for such services by low educated women. This ‘marketization’ weakened the tradeoff between career and family life and enabled highly educated women to pursue demanding career without giving up on their desired family size.
To establish the relationship between the rise in the college premium and fertility of highly educated women, we use data from the March CPS for the period 1983-2012. We estimate the average hourly wage in the “child day-care services” industry and allow it to vary by state and year. In addition, we compute the hourly wage of all women in the 25-50 year-old age group who reported a positive salary income. Figure 2 presents the fitted values of the average of this variable for each of our five educational groups. The figure shows that childcare has become relatively more expensive for women with less than a college degree but relatively cheaper for women with a college or an advanced degree.
Figure 2: Linear Prediction of the Log of the Ratio of Average Wage in the Childcare Industry to Average Wage in the Five Educational Groups 1983–2012
To utilize the micro data we estimate regression models where the dependent variable is a binary variable that takes the value of one if a woman, living in a specific state in a specific year gave birth during that year and zero otherwise. Our main explanatory variable is the labor cost in the child daycare industry divided by the own wage of that woman. We show that there is a highly statistically significant and economically large negative correlation between this measure of childcare cost and the probability of giving a birth. In our empirical analysis we find that this change in the relative cost can account for about one-third of the increase in the fertility of highly educated women. We use a battery of tests to show that this correlation is not driven by selection of women into the labor market, by the endogeneity of wages, or by specific years over the last three decades.
Figure 3: 2000s Actual and Hypothetical Fertility under the 1980s prices of Childcare
Figure 3 uses the estimates from the regression models described above and shows a hypothetical fertility for 2001-2011 under the 1983-1985 relative childcare cost. The figure shows that the hypothetical fertility curve is obtained by a clockwise rotation of the actual fertility curve around the group of women that has some college education.
Direct evidence on paid childcare services is consistent with this view. Figure 4 shows the average weekly paid childcare hours by all women aged 25-50 in 1990 and 2008. The figure has two salient features. First, in each of these years, paid childcare is increasing with women’s education. Secondly, between 1990 and 2008, paid childcare hours have stagnated for women with up to some college education but have sharply increased for highly educated women.
Figure 4: Paid Childcare Weekly Hours for Women aged 25-50.
We then rule out potentially other explanations. What if the increase in labor supply stems from women who did not give birth during that year? To address this concern we shows that the cross-sectional relationship between education and usual hours worked for the sub-sample of women age 15-50 who gave birth during the reference period exhibit the same positive correlation. Another concern might be that it is in fact the spouses who respond to a birth by lowering their labor supply enabling their wives to work more. Find that men who are married to highly educated women work more than men who are married to women with lower levels of education. Interestingly, fathers to newborns work more than husbands who do not have a newborn at home, regardless of the education of their wives. More importantly, usual hours worked by fathers to newborns monotonically increased with their wives’ education. Thus, the spouses of highly educated women are not the ones substituting in childcare for their working wives.
Another concern our model may raise is that marriage rates differ across different educational groups. If married women have higher fertility rates and if more educated women have higher marriage rates, more educated women’s higher fertility rates may not be caused by the availability of relatively cheaper childcare and housekeeping services, but rather simply by their higher marriage rates. We find that the fraction of women with advanced degrees who are currently married is somewhat lower than that of women with college degree.
Figure 5: Number of birth per 1,000 White Women in the US in Age Groups 35-39, 40-44 and 45-49: Women with Advanced Degrees (2001-2011) and Historical Rates.
A final potential explanation might be related to recent advancements in Assisted Reproductive Technology (ART) that enable women to combine long years in school without scarifying parenthood. We address this possibility in three ways. First, we show that historical levels of fertility rates among women above age 35 were higher than the levels during the 2000s (see Figure 5). This stands in contrast to the argument that highly educated women were not able to have higher fertility rates in the past due to medical reasons. Secondly, we note that ART accounts for less than 1% of births occurred during the 2000s. Finally, fifteen U.S. states have infertility insurance laws that provide coverage to infertile individuals. We compare fertility patterns by women’s education in these states to the rest of the country and find no difference in fertility rates during the 2000s between the two groups of states.
The results of this study have several implications. For public policy, it highlights potential benefits from pro-immigration policies. Unskilled immigrants can potentially have positive effect on fertility via an increase in the supply of cheap home production substitutes. For many developed countries that are facing aging and shrinking population this may be something to consider. It also has consequences for economic growth. Given the strong correlation between parents’ education and kids’ education, an increase in the relative representation of kids coming from highly educated families means that the next generation is going to be relatively more educated. These are good news for economic growth.
References
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- Moshe Hazan and Hosny Zoabi. Do highly educated women choose smaller families? Economic Journal, 125(587):1191–1226, 2015b.
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Strategic Aid Financing
Donor countries often face a Samaritan’s dilemma when trying to implement political conditionality in bilateral aid. Giving through multinational organizations can mitigate this problem: Recipient nations are de-facto competing for funds, which restores their incentives to comply even with non-enforceable conditions. Donor nations might therefore find it useful to set up multinational aid funds, rather than to disseminate aid bilaterally, even if they have to give up control over where the money is spent.
In the last decade, global challenges like climate change or the fight against epidemics have become the focus of aid projects. In order to make progress on these large-scale issues, donor nations increasingly recognize that simply giving money to a developing region does not ensure success. Instead, the impact of aid spending depends crucially on efforts undertaken in the partner countries. Reforms of the local economic and judicial system, fighting corruption and general good governance are just a few of the demands on donor countries’ wish lists.
However, many of the conditions set by donating governments are hard to enforce, especially since they nowadays often fall in the category of “political conditionality,” aiming at broader political improvements rather than simple, measurable economic indicators (see for example Molenaers et.al., 2015). The crucial question for aid giving countries therefore remains how to strategically structure aid, so that recipient governments can be incentivized to cooperate also on intangible or non-enforceable conditions.
The Samaritan’s Dilemma
Indeed, the theoretical literature on aid conditionality finds that optimal contracts should be self-enforcing, i.e. the threat of aid sanctions should be large enough to ensure that the recipient government has an interest in fulfilling the conditions (see for example Scholl, 2009). That, however, might be easier said than done: Svensson (2000) argues that the threat of cutting aid in case conditions are violated is hard to credibly sustain, at least for individual donor countries. They often face political constraints to spend a certain amount of money on aid. This opens the possibility for a classic hold-up problem: If the donor country cannot commit to giving aid only conditional on reform efforts, the recipient country, knowing it will receive assistance in any case, has no incentive to implement costly reforms. From the donor’s perspective, this is also known as the Samaritan’s dilemma.
Multinational Funds Can Help
Svensson goes on to argue that transferring the responsibility of allocating aid to a multilateral organization might solve the Samaritan’s dilemma outlined above. He notes that if donors are lacking a commitment technology (that helps them to actually implement aid sanctions in case a recipient government shirks on the agreed aid conditions), “delegation of part of the aid budget to an (international) agency with less aversion to poverty will improve welfare of the poor.” Such organizations will have less of a commitment problem and should therefore better be able to enforce aid conditionality.
Competition Restores Incentives
There is, however, no a priori reason to think that multilateral organizations have a different objective than individual donor countries in terms of eliminating poverty and achieving growth and prosperity for developing countries. After all, these organizations’ founding principles are set by the donor countries that fund them. An international organization’s objective, as represented by how it actually allocates funds across causes and recipient countries, should reflect an aggregation of the individual preferences of donor nations.
In a new study, Simon and Valasek (2016) argue that precisely this stage of preference aggregation enables multilateral organizations to better implement aid conditionality. How non-earmarked funds given to multilateral organizations are allocated is determined in a bargaining process between representatives of the different donating nations. Individual preferences might differ; the bargaining outcome thus has to reflect a compromise between them. The bargaining position of each donor will in part depend on intrinsic values, but importantly also on the reform efforts and willingness to cooperate of the potential recipient nations. Intuitively, the better the government of an aid receiving country behaves, the better the bargaining position of donor countries lobbying on its behalf.
This constitutes a new strategic reason for pooling resources in large aid funds rather than implementing aid bilaterally: When resources are pooled, recipient nations have to compete for their share of aid. It is precisely the heterogeneity of donor country preferences that induces (or enhances) such competition. Bilateral aid relations thus cannot replicate the effect to the same extend. This competition restores incentives to invest in costly reforms and circumvents the hold-up problem.
Conclusion
Donor nations should consider pooling their resources in multinational funds when they fear that their partner governments are reluctant to implement political reforms. This is especially relevant for aid aimed at common global issues like climate change or disease control.
Simon and Valasek show that the payoff from joining an aid fund is especially high when donor nations represented in the fund have relatively homogenous goals for their foreign aid programs, but differ in terms of where in the world they would like to send their aid money. Then the disadvantage from losing the direct say over which recipient nations get the most funds is far outweighed by the gain from inducing investment and reform incentives in the aid receiving nations.
References
- Molenaers et al. (2015): “Political Conditionality and Foreign Aid,” World Development Vol. 75.
- Scholl (2009), “Aid Effectiveness and Limited Enforceable Conditionality,” Review of Economic Dynamics 12(2).
- Simon & J.M. Valasek (2016), “The Political Economy of International Aid Funds,” Working Paper.
- Svensson (2000): “When is Foreign Aid Policy Credible? Aid Dependence and Conditionality,”, Journal of Development Economics Vol. 61.
Non-Tariff Barriers and Trade Integration in the EAEU
It is a commonly held view that the Eurasian Economic Union (EAEU) is a political enterprise (Popescu, 2014) that has little economic meaning other than redistribution of oil rents (Knobel, 2015). With a new reality of low oil prices and reduced rents, a legitimate question is how stable this Union is, or whether there is any hope for mutual economic benefits that can provide incentives to all the participants to maintain their membership in the Union? Our answer is yes, there is hope, but only if countries, especially Russia, make progress on deep integration such as services liberalization, trade facilitation, free movement of labor and especially in the reduction of the substantial non-tariff barriers (NTBs). NTBs are hampering trade both within the Union (World Bank, 2012; Vinokurov, 2015), as well as against third country imports. Our research shows (see Knobel et al., 2016) that all the EAEU members will reap benefits from a reduction of NTBs against each other, but they will obtain considerably more substantial gains from a reduction in NTBs against imports from the EU and China.
Since the early stages of creation of the Customs Union (CU) between Belarus, Kazakhstan, and Russia back in 2010, the economic benefits of the CU have been questionable. The main reason for this in Kazakhstan was the increase in its import tariffs in order to implement the common external tariff of the CU, which initially was Russia’s external tariff (Tarr, 2015). Kazakhstan almost doubled its average tariff from 5.3% to 9.5% (Shepoltylo, 2011; Jondosov and Sabyrova, 2011) in the first year of its CU accession. Belarus did not increase its average tariff, but the structure of its tariffs shifted toward a protection of Russian industry.
In 2015, the CU was transformed into the EAEU, and Armenia and Kyrgyz Republic have joined the EAEU. These two countries are WTO members; Kyrgyzstan entered the WTO in 1998, and Armenia in 2001. In 2014, the simple average most-favored nation (MFN) applied tariff rate in Armenia was 3.7%, and 4.6% in the Kyrgyz Republic. Due to differences between Armenia and Kyrgyzstan’s WTO commitments and the EAEU tariff schedule, the new members of the EAEU are not implementing the full EAEU tariff schedule. That is, they have numerous exemptions. However, they have started a WTO commitments modification procedure.
Despite adverse impacts from the higher import prices from implementing the common external tariff of the EAEU in Armenia and the Kyrgyz Republic, there are potentially offsetting gains. Given the importance of remittances to the Kyrgyz Republic, the benefits coming from the right of workers to freely move and legally work inside EAEU likely dominate the tariff issues. Armenia also benefits from the free movement of labor, receives Russian gas free of export duties, and wants to preserve the military guarantee granted by Russia through the six-country Collective Security Treaty Organization.
In the case of Belarus, it receives Russian oil and natural gas free of export-duties, which, when oil prices were high, tended to dominate their calculus. Kazakhstan hopes for more FDI as a platform for selling to the EAEU market; but President Nazarbaev has expressed concerns that the EAEU is not providing net benefits to his country.
To date, the members have judged participation to be in their interest, but with the plunge in the price of oil and gas, the calculus could swing against participation in the EAEU. That is why it is so important to achieve progress with deep integration in the EAEU. One of the most important areas of deep integration for the EAEU is the substantial reduction of non-tariff barriers in goods trade, both between the EAEU members and against third countries. Estimates by the Eurasian Development Bank (Vinokurov et al., 2015) reveal that NTBs account are 15% of the value of intra-union trade flows.
In our paper, Knobel et al (2016), we estimate substantial gains to all the EAEU members from a reduction of NTBs. We employ a global computable general equilibrium model with monopolistic competition in the Helpman-Krugman style based on Balisteri, Yonezawa, Tarr (2014). Estimates of the ad-valorem equivalents of NTBs were based on Vinokurov et al (2015) for the EAEU member countries and Kee, Nicita, Olarreaga (2009) for non-members.
We find that the effects of deep integration are positive for all countries of the EAEU. Armenia’s accession to the EAEU will have a strong positive effect only if coupled with a decrease of non-tariff barriers. Armenian accession is associated with an increase in external tariffs, which causes a negative economic impact and decrease in output.
The effect of deep integration in the EAEU will be even greater if any spillovers effect reducing NTBs for EAEU’s major trading partners are present. Knobel et al. (2016) simulate a 50% decrease in “technical” NTBs inside the EAEU and a 20% spillover effect of reduction NTBs toward either the EU and USA or China. Reduction of NTBs in trade with the EU and the USA dominates the comparable reduction of NTBs with China for all countries of the EAEU in terms of the welfare gain. Armenia’s welfare gain with a spillover effect towards the EU is 1.1% of real consumption compared to 1.02% with a spillover effect towards China. Growth in welfare in Belarus will be 2.7% with a EU spillover versus 2.5% with a spillover effect towards China. Kazakhstan’s gain in real consumption is also greater in the first (EU+USA) case: 0.86% versus 0.66% (with spillover towards China). Russia’s gain in real consumption in the case of a spillover effect with the EU is 2.01% versus 0.63% in the case of China.
Summing up, our findings suggest an answer to the recent concern about stability of the EAEU. We think that eliminating NTB, hampering mutual trade, and decreasing NTBs in either European or Chinese direction could provide mutual economic benefits that could tie countries of the EAEU together, thereby giving a much needed solid economic ground for the Union.
References
- Balistreri, Edward J., Tarr, David G. and Hidemichi Yonezawa (2014). Reducing trade costs in east Africa : deep regional integration and multilateral action (No. 7049).
- EEC (2015) Eurasian economic integration: facts and figures, (in Russian).
- Kee, Hiau Looi, Nicita, Alessandro, and Marcelo Olarreag (2009) Estimating Trade Restrictiveness Indices, Economic Journal, 119, 172–199.
- Knobel, Alexander (2015) Eurasian Economic Union: Prospects and Challenges for Development, Voprosy Ekonomiki, 2015, No. 3, pp. 87—108. (in Russian).
- Knobel, Alexander, Andrey Lipin, Andrey Malokostov, David G. Tarr, and Natalia Turdyeva (2016) Non-tariff barriers and trade integration in the EAEU, mimeo
- Plekhanov, Alexander and Asel Isakova (2012) Customs Union and Kazakhstan’s Imports (July 1, 2012). CASE Network Studies and Analyses No. 422.
- Popescu, Nicu (2014), “Eurasian Union: the real, the imaginary and the likely,” Chaillot Paper – No. 132, European Union Institute for Security Studies, September 9.
- Shepotylo, Oleksandr (2011), “Calculation of the tariff rates of Kazakhstan before and after the imposition of the customs union common external tariff in 2010.” Available as part of World Bank (2012), Assessment of Costs and Benefits of the Customs Union for Kazakhstan, Report Number 65977-KZ, Washington DC, January 3, 2012.
- Tarr, David G. (2015) The Eurasian Economic Union among Russia, Belarus, Kazakhstan and Armenia: Can it succeed where its predecessor failed? Paper prepared for the BOFIT conference of the TIGER project, Helsinki, Finland, September 16, 17, 2015
- Vinokurov, Evgeny, Mikhail Demidenko, Igor Pelipas, Irina Tochitskaya, Gleb Shymanovich, Andrey Lipin (2015) Measuring the Impact of Non-Tariff Barriers in the Eurasian Economic Union: Results of Enterprise Survey. EDB Centre for Integration Studies Report no. 30, EDB: Saint-Petersburg.
- World Bank (2012), Assessment of Costs and Benefits of the Customs Union for Kazakhstan, Report Number 65977-KZ, Washington DC, January 3, 2012