Location: Belarus

Intermediate and Capital Goods Import and Economic Growth in Belarus

Posted on May 9, 2016 | Policy Brief

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.

The Economic Complexity of Transition Economies

Posted on March 30, 2016 | Policy Brief

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‘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.

Non-Tariff Barriers and Trade Integration in the EAEU

Posted on February 29, 2016 | Policy Brief

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

The Inevitable Social Security Reforms in Belarus

Posted on February 8, 2016 | Policy Brief

In 2016, Belarus will face the need to reform its social protection policy. The three main directions of reforms will be to departure from subsidized tariffs, to reform the pension system, and to increase unemployment benefits. Needless to say, some of these reforms will be highly unpopular. The government needs not only to cut expenditures, but also to think about new ways of providing targeted social support.

Faced with an anemic growth over the last 5 years and a GDP decline of 3.9 percent in 2015, Belarus has to rethink its economic policy. While the government is so far reluctant to undertake serious structural reforms, the decrease in budget revenues and lack of access to international financing leaves the authorities with few other options than to reform the social security system. This push might actually be a good thing, as social security in Belarus needs to depart from its current non-sustainable model of subsidies for everyone, to a model of focused means-tested social support.

Subsidized Tariffs

A lot of government-set tariffs in Belarus are currently subsidized. Utility service tariffs and transport fees are lower than the costs of providing these services. This is especially true for the heating tariffs, which currently cover 10-20 percent of total costs.

The subsidization policies are inefficient, as they benefit the rich (who consume more) rather than the poor in need of government support. Moreover, in the case of energy tariffs, cross-subsidization leads to higher energy costs for the firms, making them less competitive. Both prospective creditors, the IMF and the Eurasian Fund for Stabilization and Development, demand that the subsidies are gradually removed.

Zhang and Hankinson (2015) estimate the effects of an increase of the heating tariff on welfare. They find that the burden of higher tariffs will mostly fall on low-income groups. In particular, if the heating tariffs increase to 100 percent of the costs, households from the lowest income quintile will spend over 16 percent of their income on energy. Therefore, the authors conclude that the government should introduce a targeted social assistance together with the tariff increase.

While tariff increases were already introduced in the beginning of 2016, a targeted social assistance is still only a project.

Unemployment Benefits

Despite calling itself a social economy, Belarus has inexplicably low unemployment benefits (currently below 10EUR per month in Minsk). These low unemployment benefits contribute to a very low registered unemployment rate – 1 percent in November 2015. The more adequate measure of unemployment, based on labor force surveys, is classified in Belarus. However, large-scale job cuts in the biggest state-owned enterprises suggest that unemployment is a real threat.

Akulava (2015) argues, that given the current situation on the labor market, unemployment benefits should be increased to at least the minimal subsistence level. However, unemployment benefits per se will not solve all the problems in the labor market, and Belarus needs more active labor market policies facilitating the retraining and reallocation of workers.

The IMF has also emphasized the need to introduce proper unemployment insurance. The government has already pre-announced an introduction of increased unemployment benefits, but the details and dates are still unclear. There is a risk that, as many other policies in Belarus, the unemployment support will favor the state-controlled part of the economy and only offer increased support for those laid off from state-owned enterprises.

Pension Reform

The Belarusian pension system has not change much since the Soviet times: it is still a pay-as-you-go redistributive system, with a pension age among the lowest in Europe (55 for women and 60 for men). The Pension Fund first registered a deficit in 2013, and given the ageing population, deficits will only deepen in the future.

Due to relatively low fertility rates (1.6 per woman) and increasing life expectancy, the Belarusian population is quickly ageing: In 2015, there are 4 persons of retirement age per 10 persons of working age, but in 2035, this ratio will be 6 per 10.

Lisenkova and Bornukova (2015) build a demographically accurate overlapping generations model of Belarusian economy to estimate the stability of the pension system. They find that if the current parameters do not change, the deficit of the Pension Fund will explode up to 9% in 2050 (line 55/60 in Figure 1).

Figure 1. The Pension fund deficits under different scenarios, in % of GDP

Source: Lisenkova and Bornukova, 2015

The authors also estimate different reform scenarios. An increase in the contribution rate and a decrease in the replacement rate (ratio of average pension to the average wage) do not seem feasible, as the current contribution rate of 29 percent is already too high, and the replacement rate is near the minimum set by the National Development Strategy 2020. The most obvious reform is then to increase the pension age for women, who retire 5 years earlier than men, despite having 10 years longer life expectancy. However, as can be seen from line 60/60 in Figure 1, equating the pension ages for women and men will not be enough to curb the deficits. Another simulated reform is to gradually increase pension age to 65 years for everyone, after increasing it to 60 for women only. This reform would mean that the deficits would be kept below 1 percent of GDP (and even generate a small proficit by 2035, although in a very long perspective the deficit will increase to 2 percent again (line 65/65)). In the very long run, Belarus needs to build a fully funded pension system.

The need to increase the pension age is already on the public debate agenda, and the authorities recognize the need for reforms. Needless to say, however, this move will be very unpopular.

Conclusion

The current economic crisis gives an opportunity and incentive to make Belarusian social policy more efficient. This policy brief describes the three major fields of reform. Subsidized tariffs are unfair and inefficient, but before removing subsidies the government should create a targeted system of social assistance to those in need. Increasing unemployment (and demands from the creditors) may force the government to change its unemployment benefit policy. The pension system needs reforms, but these would be difficult to implement due to unpopularity.

▪

References

Akulava, M. (2015), ‘Unemployment insurance as a tool of social protection’, BEROC policy paper series, PP no. 32 (in Russian)
Lisenkova, K., and Bornukova K. (2015), ‘Effects of Population Ageing on the Pension System in Belarus’, BEROC working paper series, WP no. 28
Zhang, F., and Hankinson, D. (2015), ‘Belarus Heat Tariff Reform and Social Impact Mitigation,’ World Bank Publications, The World Bank, number 22574

Local Self-Governance in the Republic of Belarus

Posted on June 1, 2015 | Policy Brief

Author: Aleh Mazol, BEROC.

This policy brief summarizes the results of our research on the development of local self-governance in the Republic of Belarus. The aim of this study was to analyze the existing system of local self-governance in the Republic of Belarus and to suggest directions for its improvement. The results show that the development of local self-governance should be directed to the reduction of concentration of the administrative-territorial division, real empowerment of local Councils of Deputies, improvement of the mechanism of alignment and balancing of local budgets, as well as the development of a financial base of local financial management and intergovernmental relations.

Expected Effects of Tobacco Taxation in Five Countries of the Former Soviet Union

Posted on May 18, 2015 | Policy Brief

Authors: Irina Denisova and Polina Kuznetsova, CEFIR.

In this policy brief, we discuss the results from a study of different dimensions of tobacco taxation policy in five former Soviet Union countries: Belarus, Kazakhstan, Kyrgyz Republic, Russia and Ukraine. We find that the increase in budget revenue from raising excises on filter cigarettes is high in all studied countries. Furthermore, due to a low elasticity of the demand for cigarettes, the increase in excise taxes needs to be substantial to lead to a noticeable improvement in public health.

The Role of Belarusian Private Sector

Posted on January 19, 2015 | Policy Brief

The development of a private sector and the expansion of its role in the economy is one of the key goals repeatedly announced by the Belarusian authorities. The reforms carried out in Belarus in 2006-2014 moved the country from 106th to 57th position in the World Bank Doing Business ranking. The official statement is that reforms boosted the rapid development of business initiatives and its impact on economic development. Unfortunately, there is no clear confirmation of this statement. The absence of a transparent and clear methodology in Belarusian statistics on how to evaluate the role of the private sector makes it difficult to evaluate the exact input of the Belarusian business in the economy and compare its role to other countries.

In the last 5 years, the Belarusian authorities have repeatedly highlighted the need to develop the private sector, perceiving it as the main source for sustainable economic growth and competitiveness of Belarus in the future.

However, it may be difficult to assess the real role of the private sector in the Belarusian economy. First, existing data do not allow a clear identification of the boundaries between the private and state-owned sectors in Belarus. Furthermore, there are certain methodological differences in identifying and evaluating the private sector between Belarusian official statistics, the World Bank approach and alternative methodologies. These methodological variations combined with data limitations result in significantly different estimates of the role of the private sector for the Belarusian economy. The problem concerns both the evaluation of the role of small and medium enterprises (SMEs) and the private sector in general.

Small and Medium Enterprises

One good example of the abovementioned data issue is the statistics for SMEs sector. Unlike the EU, Belarus does not include individual entrepreneurs to the micro organizations in the SME sector. This results in highly different estimates for the number of SMEs per 1000 inhabitants (Figure 1). If we follow the methodology of the National Statistical Committee of the Republic of Belarus (Belstat), the number is 9.7 firms per 1000 people. However, switching to the EU methodology (IFC report, 2013) raises the number significantly up to 35.9. Moreover, the inclusion of unregistered self-employed individuals involved in the shadow economy (which according to estimations of the authorities amount to at least 100,000 inhabitants) increases the number to 46.5 firms per 1000 people, which is above the level of many European countries.

Figure 1. SME density

Source: own estimations from Belstat data, Eurostat.

Private Sector

As for the private sector in general, the problem here is that the official statistics counts enterprises with mixed form of ownership and state presence to the private sector. This makes it difficult, if at all possible, to obtain the exact input of the private sector to the economy and see the dynamics of its change.

More specifically, there are three potential ways to assess the contribution of the private sector. Unfortunately none of them provides reliable estimates of the role of business. The first method is to use official data. The main problem here is that the private sector according to official statistics includes enterprises with state presence as well as large private companies that are under state control and not totally independent. Thus, the contribution of the private sector calculated based on these figures is likely overestimated.

The second method is to look at enterprises that do not report to the Belarusian ministries, following the methodology of the World Bank used in their evaluation of Belarus machinery industry (Cuaresma et al., 2012). Here, non-ministry reporting enterprises work as a proxy for a private firm, as in this case it doesn’t have to report directly to Belarusian ministries and is independent from the state.

The problem is that the majority of large private enterprises, even though there is no state share in them, are not in this list. In Belarus these enterprises often form a part of state concerns on the one hand and are independent on the other. The example here is JSC “Milavitsa”, one of the largest lingerie producers in EE, which is a part of the Bellegprom concern. Therefore, this methodology likely underestimates the role of the private sector.

The third way is to try to exclude state presence from the official data of the private sector. According to official statistics, the private sector includes several groups of enterprises, such as individual entrepreneurs, legal entities with/without state/foreign presence, etc. However, the absence of a clear distinction between these sub-groups allows for only rough estimates, through the extraction of the state presence.

As a result, all obtained numbers are qualitatively different from each other and there is no clear answer if any of them reflects the real picture.

For example, the contribution of the private sector in total employment according to the three different methods (Figure 2) provides the following results. Officially, in 2013 around 53% of the active labor force worked in the private sector. However, the exclusion of state presence in private property changes the results significantly and the share of the active labor force involved in the private sector drops to a level of 31%, while the non-ministry reporting enterprises employ around 18% of the active labor force.

Figure 2. Private sector in employment (%)

Source: own estimations from Belstat data.

The input of the private sector in the total production volume (Figure 3) is also very diverse depending on the method of evaluation. Official data show that the private sector is responsible for 80% of total production volume. However, the exclusion of state presence decreases the value to a level of just 26%, which is similar to the result demonstrated by the non-ministry reporting enterprises (25%).

Figure 3. Private sector in total production volume (%)

Source: own estimations from Belstat data.

At the same time, the absence of a clear definition of the private sector does not allow for obtaining reliable information about its effectiveness. If we take the rate of return on assets (ROA), again, there is a significant gap in the results of the different methods of estimation (Figure 4). ROA of the private sector according to official statistics is significantly lower than similar indicators based on the data obtained by the other two methods (in 2013: 1.17 vs. 2.4 and 1.3 respectively). Thus, the lower the “measured” state presence, the higher is the productivity of the private sector, especially in comparison with the effectiveness of the state sector (0.25).

Figure 4. Return on Assets (BYR/BYR)

Source: own estimations from Belstat data.

Conclusion

The above discussion has illustrated that diffuseness of data and the definition of the private sector is likely to create troubles for understanding the importance of the private sector in Belarus. This, in turn, may undermine the effectiveness of economic and political measures targeted towards this sector.

The implementation of a clear, unified and transparent methodology of how to estimate the role of business and what exactly can be treated as a private sector in statistics would allow for a better understanding of the obstacles and barriers that the private sector is dealing with, as well as to help developing effective measures of business support. Until then, the official statistics should not stick to just one definition of the private sector. Instead, it can use all three abovementioned gradations, as a better reflection of the realities of Belarusian business.

References

Cuaresmo, J., Oberhofer, H., Vincelette, G. (2012).‘Firm Growth and Productivity in Belarus: New Empirical Evidence in the Machine Building Industry’, World Bank, Policy Research Working Paper No. 6005.
‘Business Environment in Belarus 2013.Survey of Commercial Enterprises and Individual Entrepreneurs’, IFC, Report.

Stimulating Growth in Belarus: Selecting the Right Priorities

Posted on November 17, 2014 | Policy Brief

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Belarus is suffering from a substantial decline in economic growth potential. Both the government and academic researchers are discussing a number of options for stimulating the growth rate and enhancing its stability. The government tends to focus on equipment investments as the priority for growth stimulation. However, academic researchers have revealed huge unused potential for growth in institutional environment in Belarus. In this brief, we deal with the issue of selecting the right priorities in growth stimulation policies.

Nowadays emerging markets as a whole, and especially countries of Central and Eastern Europe (CEE) and the CIS region suffer from the problem of declining growth potential (IMF, 2013). Belarus is not an exception from this trend. However, the situation in Belarus is distinct from the regional patterns since the majority of factors behind the declining growth potential in Belarus differ from those in other CEE and CIS countries. While the IMF (2013) emphasizes constraints for capital accumulation as the core challenge for the CEE region, the major problem in Belaurs is the lack of productivity growth. Capital accumulation has in fact been huge and ineffective in Belarus in recent years (Kruk and Bornukova, 2014). Hence, a key issue for Belarus for restoring output growth, and enhancing its sustainability, is total factor productivity. Some degree of consensus about this priority exists both in the academic sphere and among economic policy makers. However, further questions about the sources of productivity growth generate ambiguous solutions, which result in different growth strategies.

Embodied Technical Progress versus Neutral Productivity Growth

Two years ago, the Belarusian government initiated a so-called modernization campaign. The idea of this campaign was to accomplish rapid re-equipment of large Belarusian firms, which was expected to increase their productivity. The government considers this channel to be self-sufficient, hence staking on it almost exclusively.

At the same time, a number of both academic (World Bank, 2012; Cuaresma et al., 2012; Kruk and Bornukova, 2014) and economic policy studies (IMF, 2012) emphasize the necessity of institutional changes for productivity growth. Gains in productivity herewith are expected due to improved incentives by firms and more efficient allocation and usage of factor inputs by firms.

From an academic perspective, the first approach may be interpreted as one based on technical progress embodied in capital (embodied technical progress, ETC). In other words, equipment investments are to provide productivity growth per se (De Long and Summers, 1991; Greenwood et al., 1997; Hernstein and Krusell, 1996). More recent studies provide evidence on the importance of this mechanism for a modern transition agenda (Skare and Sinkovic, 2013).

The second approach deals with so-called neutral productivity growth (NPG), i.e. productivity gains independent of the quantity of either capital or labor inputs. NPG can be divided into a number of channels: neutral technical change, technical efficiency (characterized by the distance between the actual position of the firms and the production frontier), scale economies, and allocative efficiency (Coelli et al., 2005).

Impact of NPG and ETC on Productivity: Complementary or Substitutive?

As a rule, growth models do not assume any trade-off between NPG and ETC. For instance, a firm that succeeds to implement a new technology (independent on capital of labor inputs) will generate higher productivity. This will attract additional inputs – capital and labor – given higher factor returns due to productivity gains. New capital (equipment), in turn, may generate additional gains in productivity. Hence, productivity growth may stem from both tracks complementing each other. In this sense, the issue of decomposing actual sources of productivity growth – capital or technology itself – becomes largely meaningless.

The idea of the Belarusian modernization – that ETC comes first and other things do not matter – substantially changes this growth pattern. Rapid technical re-equipment makes the lack of financial sources for investments roughly inevitable, as national savings can hardly be enough for a surge in investments. The government in Belarus partially solves this problem through centralized reallocation of financial resources. However, this reallocation negatively impacts allocative efficiency (Kruk, Haiduk, 2013). Further, it is likely to have a similar adverse effect on technical efficiency and scale economies. Hence, in Belarus the trade-off between ETC and NPG arises: artificially pushing ETC suppresses NPG.

Criterions for Assessing Effectiveness of NPG and ETC

A misbalance between the ETC and NPG resulting from an artificial ETC stimulation raises serious concerns about the desirability of this policy. However, the ‘modernization ideology’ uses a counter-argument: productivity gains from ETC may be sufficiently large to allow sacrificing potential gains from NPG growth.

From this perspective, we can compare both channels through the following criterions:

How large is the productivity effect from both channels

In order to get a quantitative assessment, we employ the model by Greenwood et al. (1997) that dissect NPG and ETC for a balanced growth path (the equilibrium trajectory when capital and output grow with the same rates). We apply our estimates of the Belarusian growth parameters to the model. For assessing ETC growth rate, we employ an approach by Hernstein and Krusell (1996). The latter produces an assessment of an average ETC productivity growth in 2005-2012 from -1.55 up 6.40% (depending on the measures of correspondent prices). The mean of the corridor seems to be rather close to the one Hernstein and Krusell (1996) estimate for developed countries (3-4%). Hence, in the current exercise we use a value of 3.5% for the Belarusian ETC. In this manner, we get the estimates of output growth-rate returns on growth rate of NPG (1.69) and ETC (0.41). This means that a change in the growth rate of NPG by 1 percentage point results in 1.69 percentage point increase of output growth rate, while the latter will increase by only 0.41 in case of 1 percentage point increase of ETC. However, the range in which NPG and ETC may vary due to government policies is highly important as well.

How large is the sensitivity of NPG and ETC to government stimulation?

Economic modelling assumes that, once an economy is on a balanced growth path (the stock of capital grows by the same growth rate as output), the ETC growth rate is exogenously determined by global technology gains. In this case, an attempt to push ETC by excessive capital accumulation will only generate a savings-investment misbalance. Hence, this kind of stimulus policy makes sense only if the economy has not yet entered the balanced growth trajectory. Whether this is the case for Belarus is still an open question, although findings in Kruk and Bornukova (2014) signal that this path has already been achieved.

Existing options for stimulating NPG seem to be much more numerous. First, technical efficiency and scale economies may progress substantially due to a changing environment, with more intense competition and tighter budget constraints. Such environment will force firms to increase their flexibility and adaptability, which will finally result in more technical efficiency and more proper scaling. Second, Belarus has accumulated great growth potential in the sphere of allocative efficiency. Due to long periods of inefficient capital accumulation, its proper reallocation can provide up to 10% growth of output (Kruk and Bornukova, 2014).

What are the costs of growth stimulation?

In the case of NPG, there are actually no direct costs. Enhancing more flexibility and adaptability for firms, along with establishing tough budget constraints does not require new financial injections. These goals may be achieved through legislative activity, implementing new practices and standards into business activities.

As for ETC, a number of undesirable outcomes may be interpreted as costs. First, while stimulating productivity growth due to technology background, artificial ETC stimulation may further dampen allocative efficiency in Belarus. Second, an attempt to boost it requires sources for additional investments, which typically exceed available savings. Hence, the country is likely to face a deficit of savings-investments balance. The latter is to determine current account deficit, the necessity of external borrowings, and vulnerability of financial market.

Conclusion

In the last two years, Belarus has spent considerable effort towards modernization and re-equipment of large industrial enterprises. However, the most important outcome from the Belarusian experience – artificial stimulation of ETC – is likely not worth the effort as it might hinder allocative efficiency. Because of such practices, Belarus has faced an unfavorable trade-off between ETC and NPG.

However, this trade-off should not be treated as a predetermined one. It is possible and desirable to avoid it. In the long term, the growth should stem from both tracks – NPG and ETC. However, in a shorter perspective, more returns in terms of welfare may be obtained through a more efficient allocation of resources, improvements in the institutional environment, and more flexibility and adaptability by firms.

References

Cuaresmo, J., Oberhofer, H., Vincelette, G. (2012). ‘Firm Growth and Productivity in Belarus: New Empirical Evidence from the Machine Building Industry’, World Bank, Policy Research Working Paper No. 6005.
De Long, J., Summers, L. (1992). ‘Equipment Investment and Economic Growth’, Quarterly Journal of Economics, 106, 2, pp. 445-502.
Greenwood, J., Hercowitz, Z., Krusell, P.(1997). ‘Long-Run Implications of Investment-Specific Technological Change.’ American Economic Review, 87, 3, pp. 342–362.
Hornstein,A., Krusell, P. (1996). ‘Can Technology Improvements Cause Productivity Slowdowns?” In NBER Macroeconomics Annual 1996, eds. Julio J.Rotemberg and Ben S. Bernanke. Cambridge, MA: MIT Press.
IMF (2013). ‘Central, Eastern and Southeastern Europe: Faster, Higher, Stronger – Raising the Growth Potential of CESEE’, Regional Economic Issues, October 2013.
IMF (2012). ‘Republic of Belarus: Selected Issues’, IMF Country Report No.12/114.
Kruk, D., Bornukova, K. (2014). ‘Belarusian Economic Growth Decomposition’, Belarusian Economic Research and Outreach Center, Working Paper No.24
Skare, M., Sinkovic, D. (2013). ‘The Role of Equipment Investments in Economic Growth: Cointegration Analysis’, International Journal of Economic Policy in Emerging Economies, 6, 1, 2013.
World Bank (2012). ‘Belarus Country Economic Memorandum: Economic Transformation for Growth’, Country Economic Memorandum, Report No. 66614.

Liquidity and Monetary Policy in Belarus

Posted on March 24, 2014 | Policy Brief

High inflation and devaluation expectations after the 2011 currency crisis force Belarusian monetary authorities to seek non-conventional policy measures. Instead of using the refinancing rate as an instrument on the money and credit markets, the National Bank of Belarus resorts to liquidity squeezes, which drive up the rouble interbank rates. The banks have to raise deposit and loan rates in response. As a result, households continue to keep savings in the national currency deposits, while firms struggle to keep up with the payments. This situation, however, will have to end soon.

Belarusian economy is characterized by state ownership domination and various (including political) constraints. This often makes it tempting for the Belarusian authorities to resort to untraditional policy measures, or use the conventional policies in unexpected ways. A good example is Belarusian monetary policy in 2012-2013. In 2011 Belarus experienced a severe currency crisis: the exchange rate of the Belarusian rouble (BYR) crumbled from 3011 BYR per USD in January 2011 to 8470 BYR in December 2011. Prices followed the currency and doubled: in 2011 the inflation rate was 108%. Due to high government influence on the labor market and competition from the Russian labor market, real incomes quickly recuperated (Bornukova, 2012). But the owners of the deposits in Belarusian roubles took a hit – their savings lost almost a half of real value. More and more people converted their deposits into USD or other foreign currency. Inflation and devaluation expectations were soaring (Kruk, 2012).

The National Bank of Belarus clearly realized that the proper response would be to increase the interest rates: this policy measure would partially compensate the losses of rouble deposit holders, make rouble deposits attractive again and curb the growth in lending, one of the major causes of the currency crisis.

However, there is a catch. Formally, the main monetary instrument of the National bank is the refinancing rate. Yet, despite the name, this is not the rate at which the National bank is refinancing the commercial banks. Officially, it is only a “basis for setting interest rates on the operations involving liquidity provision to banks”. The problem is that most of the floating rates, especially those on concessional loans, have the refinancing rate as its basis rate. Very high refinancing rate would hurt debt-financed organizations, in particular in agriculture and construction. And the National bank found a compromise: the refinancing rate would remain relatively low; but the National bank would regulate the money market through liquidity squeezes: it would offer liquidity to the commercial banks only at a much higher collateral loan and overnight rates. The lack of liquidity due to a squeeze would drive up the interest rates on the interbank market.

Figure 1: Main interest rates in Belarus in 2012-2014

Source: The National Bank of the Republic of Belarus.

Figure 1 shows the main interest rates in Belarus in 2012-2014. The refinancing rate was steadily decreasing throughout the whole period. The overnight rate (which moves together with the collateral loan rate), also set by the National bank, for some period was almost two times higher than the refinancing rate, reaching 70 percent at its peak. The overnight rates mostly exceeded the rate set in the interbank market. The interbank rate reflects the market price of liquidity. The National bank influences this rate by offering (or not) liquidity to the state-owned commercial banks.

The National bank has successfully used liquidity squeezes as an instrument of stabilization on the currency market. As Figure 2 shows, the two major spikes in the interbank rate coincided with the higher rates of currency devaluation. The first major devaluation episode began in the autumn of 2012. At that time the market reacted to the increased lending and the news about the ban on the exports of “solvents”, which meant Belarus would have to pay back to Russia the customs duties on oil. On the other hand, the periods of high liquidity and low interbank rates were usually followed by devaluation episodes.

Figure 2: Changes in the exchange rate and the interbank rate, 2012-2014

Source: The National Bank of the Republic of Belarus.

In the summer 2013 devaluation speeded up once again, fueled by the potassium scandal. The National bank responded with lower liquidity and higher rates, which reached peak values of 50% and higher in September 2013.

Of course, this policy had other effects besides calming the currency market. As Figure 3 demonstrates, deposit and credit rates mainly reacted to the changes in the interbank rate, with peaks in the autumn of 2012 and summer-autumn of 2013. Enormously high deposit rates (often higher than 40 percent) delivered a hefty real rate of return given inflation of 22 percent in 2012 and 16 percent in 2013. Rouble deposits were growing throughout the period. But someone had to pay those rates.

Figure 3. Short-run deposit and loan rates for firms and individuals

Source: The National Bank of the Republic of Belarus.

High real rates became a burden for firms and households. The commercial banks had to stop many of their long-term individual lending programs (mainly those financing housing purchases). Instead, the banks put their efforts into the development and promotion of short-term consumer credit, which was virtually non-existent just a couple of years before. Many firms switched to cheaper loans in U.S. dollar, but the National bank quickly shut down these practices by introducing restrictions on foreign currency loans. Credit growth slowed down, and did not decline only due to the government-sponsored lending programs and a boom in consumer credit.

High loan rates together with the growing wages and low sales suffocated the firms. Average profitability across the country is declining since summer 2012, reaching the record low profit margin and negative aggregate net profits in December 2013 (see Figure 4). The lack of liquidity lead to the crisis of payments: accounts receivable and accounts payable on the 1st of February 2014 were 24.7 and 31.6 percent higher than a year before.

Figure 4. Average profit margin in Belarus, 2012-2014

Source: The National Statistical Committee of the Republic of Belarus

Today Belarus experiences high pressure for devaluation. The international currency reserves are depleted; the current account balance is in the red for a long time. The exporting enterprises quickly lose competitiveness due to low productivity. For the first time since 2009 GDP growth is virtually non-existent (and even negative in the first months of 2014). Some of the main trading partners – Russia, Ukraine and Kazakhstan – have already devaluated their currencies and face uncertain prospects for growth. It looks like the successful practice of fighting devaluation with liquidity squeezes at the cost of the real economy will have to end soon.

References

Kateryna Bornukova, 2012. “Devaluation of 2011 and real incomes in Belarus (in Russian),” BEROC Policy Paper Series 9, Belarusian Economic Research and Outreach Center (BEROC).
Dzmitry Kruk, 2012. “Inflation Expectations and Probable Trap for Macro Stabilization”, FREE policy brief, http://freepolicybriefs.org/2012/02/27/inflation-expectations-and-probable-trap-for-macro-stabilization/
National Bank of the republic of Belarus, Statistics. http://nbrb.by/engl/
The National Statistical Committee of the Republic of Belarus. http://belstat.gov.by/homep/en/main.html

The Application of Composite Leading Indicators on the Single Economic Space Economies

Posted on February 10, 2014 | Policy Brief

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This brief is based on a CEFIR research project aimed at the short-term forecasting of socio-economic development of the member-countries of the Single Economic Space (SES), conducted for the Eurasian Economic Commission in 2013. This project focused on compiling composite leading indicators that could allow policymakers to identify phases of a business cycle and to forecast its turning points. We suggest a methodology for the selection of components of the Composite Leading Indicators (CLIs) for industrial production, and apply this methodology to predict industrial production in SES member states. Our methodology performs well for Russia and Kazakhstan, and slightly less so for Belarus.