Location: Belarus
Decomposition of Economic Growth in Belarus
During the last decade Belarus was one of the leaders of growth in the CEE region. Kruk and Bornukova (2013) have analyzed the sources of growth and found that capital accumulation was the main contributor to growth. The contribution of total factor productivity (TFP) to growth was, on the contrary, quite modest. On the sectoral level, capital accumulation was not always accompanied by the increases in TFP. Hence, the new growth policy, modernization, with the bottom line “more capital” may not be the best option for enhancing productivity-based growth. The competitive advantages of Belarus lie in the resource-based and non-tradable sectors, while the majority of the manufacturing sectors are lagging behind in productivity. Belarus has symptoms of a Dutch disease without the trade surplus, and the devaluation of 2011 did not cure it.
During 2003-2012, Belarus had an average growth rate of 7.1%, and during the ‘fat years’, i.e. 2003-2008, it was even higher – 9.5%. Intuitively, this prominent growth is questionable, as it was achieved in the context of dominating state ownership, centralized allocation of resources, government’s control at the factor and goods markets, as well as poor infrastructural reforms (for instance, according to the indices of the EBRD). The Belarusian case challenges the mainstream paradigm of growth in transitional countries, which assumes that the progress in market reforms is the key factor for high and sustainable growth.
The simplest and most widespread explanation of the Belarusian phenomena is based on ‘non-standard’ gains in productivity. This approach assumes that productivity is the engine of growth (World Bank (2012); Demidenko and Kuznetsov (2012)). To a large extent, these gains in productivity are seen as “artificial”, resulting from Russian injections into the Belarusian economy: cheap gas, specific schemes of oil trade, and preferences in access to the Russian markets (Kruk (2010)). However, under this approach, decomposing the growth in productivity by ‘natural’ and ‘artificial’ parts is hardly possible, as the impact of these factors is already hidden in the available data.
The IMF (2010) gave a substantially different explanation of Belarusian growth. They claimed that the average growth of 8.3% over the period of 2001-2008 was mainly capital-based with a contribution of 4.8 percentage points, while the contribution of productivity growth was only 3.0 percentage points (the rest of growth was explained by labor and cyclical factors).
The main reason behind the substantial difference in the explanation of growth factors is the statistical data on capital used during the growth accounting exercise. Belarusian official statistics reports the data on capital stock based on a direct survey of capital assets according to both gross and net (wealth) capital concept. However, the growth rates of capital are reported only for the gross stock of capital. These growth rates are questionable as they demonstrate ‘unnatural stability’ – they fluctuate around 2% for the last 20 years, despite the fact that investments during this period has displayed huge and volatile growth. Statistical offices in other CIS countries have reported similar dynamics of the capital stock. Voskoboynikov (2012), and Bessonov and Voskoboynikov (2008) show that this trend is a consequence of the statistical methodology used in Russia (which the Belarusian methodology is very similar to). In particular, the trend is driven by biased capital investments deflators (which are overestimated) from the periods of high inflation (1990-s and early 2000-s).
If official data is used as the capital input for the growth accounting exercise, the contribution of TFP to growth will be overestimated. Hence, in the studies of the World Bank (2012) and Demidenko and Kuznetsov (2012), the leading role of TFP may be due to the use of the official data on the capital stock.
Motivated by this concern, we use two different methods to evaluate the value of capital inputs (see Kruk and Bornukova (2013) for more details). The first alternative to using the data from direct capital survey is to exploit a perpetual inventory method (PIM): the historical assessment of initial capital stock is further adjusted by the flow of investments and depreciation. However, if there is a bias in deflators within the sample, the series will also be distorted. This problem may be eliminated if the initial stock will be selected at the moment when there is no bias in investment deflator, in the period of moderate inflation. We call this approach PIM-backward.
The second approach to constructing capital series exploits the concept of productive capital and the data on the flow of capital. It assumes that the productive capacity of a capital good depends on its age. The productive stock of a capital good (i.e. the gross stock adjusted by the age-efficiency profile) generates a flow – capital services. The latter is the productive stock adjusted by the user cost of the individual capital good. For the total output of an industry (or economy) one should aggregate the inputs by different capital goods, which in contrast to the net (wealth) concept depends not only on the value of capital goods, but also on their user costs. This approach has solid theoretical foundations, which is the reason it is prioritized in productivity studies.
From the view of available data in the case of Belarus, this approach has a number of powerful advantages. First, we use individual deflators for individual capital goods, which are expected to be less biased than total deflators for the industry. Second, we use heterogeneous depreciation rates for each capital good in each industry based on actual data of ‘accounting depreciation’, while we would have to use homogenous assumptions for each industry in the case of net (wealth) concept. Third, we can exclude residential housing from our measure of capital input.
There are, however, also disadvantages. First, data of newly employed capital goods (in direct surveys of capital assets) and data on capital investments differ rather substantially. Traditionally, the data on capital investments is treated as more reliable, but based on the direct surveys of capital assets we have to use the series of newly employed capital goods as a flow variable when running PIM. Second, we use exogenous real interest rate for computing unit user costs, but the results are very sensitive to our assumptions on the real interest rates across industries. Third, the necessity to exclude residential housing from the data (because of ‘mixed historical prices’) may be interpreted as a loss of information. Given the strengths and weaknesses of the approach, we prioritize it on the industrial level, but prefer the PIM-backward approach for an aggregate economy analysis.
Based on the PIM-backward measure for the total economy (see Figure 1), we may argue that the contribution of TFP to growth was more modest during the last decade than what was reported in the majority of previous studies on Belarusian growth. This finding is of fundamental importance for the growth agenda: only productivity-based growth may be treated as sustainable, since capital growth will slow down as the capital approaches its stationary value. We argue that only the policy directed to promotion of productivity is vital for growth prospects.
Figure 1. Contribution of Production Factors and TFP to the Growth of Gross Value Added (PIM-Backward Approach)The dynamics of productivity divided according to industries (see Table 1) display that the leaders in productivity growth are either industries that produce non-tradable goods (communications, finance, construction) or those that have a chance of ‘artificial productivity gains’ (chemical and petrochemical manufacturing, and fuel).
Table 1. Initial Level and Growth Rates of Productivity in Major IndustriesHowever, the theory suggests that the leaders in productivity growth should be the industries producing tradable goods. . This contradiction may be interpreted in two ways. First, one may argue that a more competitive environment and larger share of private ownership (which are seen in the financial industry, trade and catering) are the core reasons for high productivity level and growth rates in ‘domestic industries’. Second, an attractive position of ‘domestic industries’ may reflect a high level of domestic prices rather than ‘natural’ productivity. The base year for our computations is 2009, in which both the real effective exchange rate of the national currency and income were relatively high. The devaluation of 2011 fixed the problem only temporarily, since the inflation in 2011-2013 quickly eroded the benefits of the devaluation. Therefore, the indicators, in terms of 2009 prices, may capture the changes in nominal values as the main component of the productivity gains, while from a longer-term perspective it would be seen as mainly price movements without substantial progress in productivity. In our view, the second explanation is the main reason for the non-standard disposition of productivity levels and growth rates among industries.
If that is the case, the bigger picture looks as follows. Industries producing tradable goods suffer from the lack of progress in productivity, i.e. lose their competitive advantage; enhancements in total productivity are mainly due to industries with ‘artificial productivity gains’. The latter allows domestic prices to grow, making a productivity illusion of domestic industries. All together these symptoms are quite similar to the Dutch disease.
One more finding from the productivity analysis at the national level is the lack of productivity gains from reallocation of resources from less productive industries to more productive ones. A scatter-plot between capital accumulation growth rates and TFP growth rates (see Figure 2) demonstrates no clear relationship between them.
Figure 2. Growth Rates of Capital Input vs. TFP Growth Rates in Manufacturing Branches, 2006-2010.Notes: The sizes of the circles correspond to industry shares in value added.
However, if there was a free allocation of resources, more productive industries would accumulate more capital. Moreover, the same indicators under the PIM-backward approach demonstrate clear negative relationship. A ‘soft’ interpretation of this phenomenon assumes that the lack of reallocation of capital restrains the development of total productivity. A ‘tighter’ interpretation assumes that at least in some industries there is a trade-off between capital accumulation and productivity gains. For instance, in Kruk and Haiduk (2013) it is shown that spurring capital accumulation through the practice of directed lending leads to losses in efficiency through a number of channels. Hence, the simplest way to increase aggregate productivity is to depart from the centralized allocation of capital and unblock capital inflows to more productive industries and vice versa.
Figure 3 documents the mobility of labor markets across the manufacturing industries in Belarus. While one can expect that labor flow into more productive industries, it is not completely true for the Belarusian manufacturing sector.
Figure 3: Labor growth and TFP growth in industries of Belarusian manufacturing, (capital services approach).Notes: The sizes of the circles correspond to industry shares in value added.
Two distinct trends emerge in the labor market. On the one hand, some industries exhibit textbook behavior: increases in TFP are associated with increases in the number of people employed. The best example here is the fuel industry, which experiences TFP increases due to preferential oil prices. However, there are industries that gain TFP and lose labor at the same time. The chemical industry, machinery manufacturing and woodworking are examples of this pattern. These industries have experienced rapid capital accumulation, which, coupled with high gains in TFP, should have contributed to the increases in labor productivity. Surprisingly, though, these industries did not attract more labor. A possible explanation for this counterintuitive pattern is the excessive employment at the beginning of the period in question. In this case, a decrease in the number of people employed may have contributed to the increases of TFP.
Indeed, Figure 4 confirms our hypothesis: labor was flowing from the industries with lower labor productivity to the industries with higher labor productivity in general. Industries in which TFP increased and which were accompanied by a labor decrease, featured low labor productivity in the beginning of the period in consideration, more precisely in 2005. Only the chemical industry exhibited the unexpected behavior: it lost labor despite high initial productivity. By getting rid of excessive employment they were contributing to an increase in TFP.
Figure 4: Labor shifts into the sectors with higher labor productivity.Notes: The sizes of the circles correspond to industry shares in value added.
How is Belarus doing relative to other countries? We have compared Belarusian TFP to the TFP of the leader of transition, the Czech Republic, and to the regional leader, Sweden. The Czech Republic is more developed than Belarus (in 2010 Czech GDP per capita (PPP-corrected) was 1.73 times higher than in Belarus), and, theoretically, it should be much more difficult and costly for it to continue approaching the technological frontier. However, our findings suggest that the Czech Republic is catching up with Sweden in terms of TFP, and doing it faster than Belarus (see Figure 5).
Figure 5: TFP of Belarus and the Czech Republic relative to TFP of Sweden, (PIM-backward approach).Over the last 10 years, Belarus has closed only 5 percentage points of the gap with Sweden. The Czech Republic, where the contribution of TFP to growth was more substantial, has managed to close 8 percentage points of the gap.
In absolute numbers (in ‘international’ dollars of 2010), aggregate TFP in Belarus in 2010 was 2.92 versus 4.66 in the Czech Republic and 9.38 in Sweden (according to the PIM-backwards method). However, the aggregate picture does not reflect the situation in the sectors of the economy and industries of manufacturing.
Table 2: Comparative advantage of Belarusian industries: winners and losers (capital services approach)Table 2 documents the comparative advantages and disadvantages of the Belarusian economy in 2010 according to the capital services approach. Both the capital services approach and the PIM-backwards approach produce the same winners and losers list with the only difference being that the PIM-backwards method has the construction sector among winners. It is not surprising to see resource-based industries among the winners (mining and quarrying mainly reflects the extraction of potash, while the chemical industry benefits both from potash and from preferential process for Russian oil). Food manufacturing is among the winners mostly due to the price scissors in agriculture: food producers buy their inputs at very low prices. The non-tradable sectors are among winners, and the majority of the manufacturing sectors are among the losers. Again, this is similar to the symptoms of the Dutch disease. It is ironic that Belarus has symptoms of a Dutch disease without the trade surplus. Instead, the desire of the government to inflate wages combined with the preferences for Russia led to the development of the same diagnosis.
Belarusian economic growth is less TFP-led than is commonly believed. While the labor market proves to be relatively successful in its reallocation of employees and its contribution to aggregate increases in efficiency, the capital market is distorted by government interventions. Capital accumulation does not necessarily lead to increases in TFP, and the new modernization policy with the bottom line of “more capital” may not be the best option for enhancing growth. Our conclusion is that Belarus should find new sources for TFP-led growth.
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References
- Bessonov, V., Voskoboynikov.I. (2008). “Fixed Capital and Investment Trends in the Russian Economy in Transition.”, Problems of Economic Transition, 51(4), pp. 6-48.
- Demidenko, M., Kuznetsov, A. (2012). “Ekonomicheskiy rost v Respublike Belarus: factory i otsenka ravnovesiya” (Economic Growth in Belarus: Factors and Equilibrium Assessments), National Bank of the Republic of Belarus, Working Paper No.3.
- IMF (2010). “Sources of Recent Growth and Prospects for Future Growth”, IMF, Country Report No.10/16.
- Kruk, D., Bornukova, K. (2013). “Belarusian Economic Growth Decomposition”, unpublished manuscript.
- Kruk, D., Haiduk, K. (2013). “The Outcome of Directed Lending in Belarus: Mitigating Recession or Dampening Long-Run Growth?”, BEROC Working Paper Series, WP No.22
- Kruk, D. (2010). “Vliyanie krizisa na perspectivy dolgosrochnogo ekonomisheskogo rosta v Belarusi” (The Impact of Crisis on the Perspectives of Long-term Growth in Belarus), IPM Research Center Working Paper Seies, WP/10/07.
- World Bank (2012). “Belarus Country Economic Memorandum: Economic Transformation for Growth”, Country Economic Memorandum, Report No. 66614
- Voskoboynikov, I. (2012). “New Measures of Output, Labour and Capital in Industries of the Russian Economy”, Groningen Growth and Development Centre, Research Memorandum GD
The Customs Union Between Russia, Belarus and Kazakhstan: Some Evidence from the New Tariff Rates and Trade Flows
Author: Arevik Mkrtchyan, European University Institute.
This brief addresses the Customs Union between Russia, Belarus and Kazakhstan that was established in 2010. It argues that the external tariff schedule reflects a compromise between the interests of its members rather than simple expansion of Russian influence on the CU partners, and that the reduction in trade costs due to elimination of internal borders, benefits both the members of the CU and their external trade partners. Moreover, the impact of alleviated non-tariff trade costs on trade flows is strong and significant, while the tariff impact is insignificant for all members.
Can Anti-Smoking Campaigns Increase Obesity? Evidence from Belarus
Authors: Aliaksandr Amialchuk, University of Toledo, and Kateryna Bornukova, BEROC.
In this brief, we discuss the possible effects of an anti-tobacco campaign on obesity levels in Belarus based on results of Amialchuk et al (2012). Both smoking and obesity are among the main health concerns in Belarus. Negative correlation between smoking and body weight is well documented, but can anti-tobacco campaign cause an increase in obesity rates? Results of studies from developed countries provide mixed evidence. In Amialchuk et al (2012), we use household survey data from Belarus to establish the link between smoking and body mass index (BMI). We use cigarette prices and regional smoking prevalence as instruments for smoking, and find a negative effect of smoking on BMI. Moreover, using the quantile regression approach, we find that smoking has different effects on body weight for different BMI quantiles, with the largest negative effect in the upper part of the conditional BMI distribution. These findings suggest that anti-tobacco campaigns may slightly increase obesity rates, and campaigns should therefore ideally also include measures to promote a healthy lifestyle. On the other hand, the potentially modest weight gain from an anti-tobacco campaign is likely to be more than offset by the general improvements in health.
Smoking and Obesity in Belarus
Smoking prevalence in Belarus, like in many other transitional countries, is quite high. According to the Belarusian Household Survey of Income and Expenditure from 2010, the smoking rate was 26%, with a much higher prevalence of among men (49.3%) compared to women (9.5%).[1]
Despite the troubling levels of smoking prevalence, little has been done to combat smoking in Belarus. While most of the post-Soviet economies liberalized the tobacco industry, it remains under government control in Belarus. The profits of the state-owned cigarette producers, along with tobacco taxes, constitute an important part of Belarusian budget revenues. This might explain why the Belarusian government has not engaged in anti-tobacco campaigns in the past. However, Belarus is currently implementing Anti-Tobacco Plan for 2011-2015 in cooperation with the World Health Organization.
The Anti-Tobacco Plan includes a variety of anti-tobacco actions and measures. In particular, the government has plans to gradually increase tobacco taxes, introduce smoking-free zones and restrict smoking in public places, along with a massive informational campaign about the dangers of smoking and ways to quit. These measures have the potential to lead to a significant decrease in smoking prevalence. However, an unintended consequence of these policies might be an increase in overweight and obesity rates.
In fact, obesity is another important health problem of Belarus. In 1996-2008, (the period of analysis in Amialchuk et al (2012)), the mean BMI among adults was 26, which suggests that an average Belarusian adult is just on the borderline between healthy weight and overweight. In particular, 34% of adults are overweight, while approximately 15% of adults are obese. Moreover, the distribution of weight status has undergone substantial changes over time: the percentage of individuals in the right tail of the BMI distribution has increased over time, with the percentage of obese increasing faster than the percentage of overweight individuals.
The Link between Smoking and Obesity
The negative relationship between smoking and body weight is well-documented in the medical literature. This inverse relationship is mostly attributed to how smoking affects body weight by boosting metabolism and suppressing appetite. However, causality is usually difficult to establish: for example, a smoking person may also be more likely to eat unhealthy foods and care less about their health in general. Nevertheless, most of the previous studies have found a significant negative effect of smoking on body weight.
Since in many developed countries, the decrease in smoking prevalence coincided in time with the surge in both overweight and obesity rates, the question arises whether anti-smoking campaigns are in part responsible for the increase in obesity rates. However, the evidence on the effects of anti-tobacco campaigns on overweight/obesity rates in developed countries is mixed. Some studies do not find any significant effect on obesity (Nonnemaker et al, 2009).
Evidence from Belarus
As mentioned above, smoking behavior and BMI may be jointly determined, and to deal with the challenge of establishing causality, we utilize the method of instrumental variables analysis. We employ two instrumental variables in our estimation: (i) the mean number of cigarettes smoked per day in the same year-region-gender- and education group as the respondent, and (ii) the average yearly price per pack of cigarettes in the region where the respondent lives. Gilmore et al. (2001) identify important demographic and socio-economic differences in smoking rates, which dictates our use of gender and education categories (below secondary, secondary, university degree) to construct groups of observations that will be followed over time. The use of region as a grouping variable allows us to capture the social norm associated with smoking at the regional level. We exclude the individual’s own cigarette smoking when we create group-level means. Group-specific smoking prevalence is likely to be predictive of the individual’s own smoking preferences, but is unlikely to have a direct effect on individual’s weight status other than through the effect on individual’s smoking. After accounting for the fixed differences in average smoking among regions, gender, and education groups within each year, the source of variation that is available to identify the effect of the instrument on individual’s smoking is the differences in smoking prevalence among various interactions of year, region, gender and education categories.
We use lagged prices as instrument for current year cigarette consumption of the individuals in order to account for the addictive and inelastic nature of demand for smoking and the inability to quickly change smoking behavior after a price change. Furthermore, we use natural log of cigarette prices in order to account for the potentially non-linear effect on the number of cigarettes smoked. Cigarette prices are likely to influence an individual’s BMI only through its effect on smoking.
Other controls in our regressions include total personal income; household size; age; gender; single vs. married indicator; indicators of self-reported health status (good health, fair health, and poor health indicators); number of medical visits in the last 3 months; indicator for having been hospitalized in the last 12 months; indicator for whether health affects ability to work; sports practicing indicator; indicators for the educational attainment (university diploma, secondary education); and indicators for being currently employed, having ever worked, and being a student.
Our endogeneity-corrected estimates suggest that one additional cigarette per day would decrease BMI by roughly 0.23 units, and would reduce the probability of being overweight by approximately 2.5%. Furthermore, there is a small but significant effect on the likelihood of being obese: an additional cigarette smoked per day decreases the probability of being obese by 1.3%. Our results suggest an important implication that smoking is inversely related to body weight, and has some effect on obesity rates.
We also explore the difference in the effect of smoking on body weight across different quantiles of conditional BMI distribution. The largest effect is obtained for the 75th and 90th percentiles, and the smallest effects for the 10th and 25th percentiles. Smoking has a large effect on the body weight of individuals who are at the upper tail of the BMI distribution. These findings suggest that a reduction in smoking rate may lead to an increase in obesity rates by inducing weight gain among the population near the top end of the conditional BMI distribution.
While we found evidence of a possible increase in obesity rates resulting from the anti-tobacco campaign, it is important to remember that adverse health effects of smoking are numerous and the health benefits of smoking cessation are far in excess of the risk of weight gain. The current high prevalence of smoking and number of overweight individuals in Belarus constitute a major public health concern. Our results suggest that the prevalence of overweight and obesity might be exacerbated by the anti-tobacco campaign. From a policy perspective, an increase in obesity rates among the general population may be a reasonable concern for policy instruments targeted at reducing the overall smoking rates. It would therefore be wise to promote healthy eating habits and sports together with the anti-smoking campaign. However, the potentially modest weight gain from anti-tobacco campaign only is likely to be more than offset by the general health improvements associated with a decline in smoking rates.
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References
- Amialchuk, A., K. Bornukova, M. Ali, 2012. Smoking and Obesity Revisited: Evidence from Belarus. BEROC Working Paper Series, WP no. 19
- Gilmore, A.B., McKee, M., Rose, R., 2001. Prevalence and determinants of smoking in Belarus: A national household survey, 2000. European Journal of Epidemiology 17: 245-253
- Nonnemaker, J., Finkelstein, E., Engelen, M., Hoerger, T., Farrelly, M., 2009. Have efforts to reduce smoking really contributed to the obesity epidemic? Economic Inquiry 47, 366–376
[1] The social norms explain difference in smoking rates of men and women. In younger population, however, gender differences in smoking rates are less pronounced.
Directed Lending: Is It An Efficient Tool to Modernize the Economy?
Over the last couple of years, the growth rate of potential Belarus’ GDP declined. The government intends to revive economic growth by the policy of ‘modernization’, in practice pinned down to a drastic increase in the volume of capital investment, including by the means of directed lending. As the pre-crisis macroeconomic imbalances are at least partially cured, the government seems to be eager to apply a familiar policy tool. However, the empirical analysis of the effects of directed lending on total factor productivity and economic growth casts serious doubts on the efficiency of this policy tool.
Over the last couple of years, the growth rate of potential Belarus’ GDP declined. This conclusion is robust as suggested by the application of competing methodologies to assess potential GDP. For instance, the statistical filters, including the HP-filter, the Kalman filter, and the production function approach, produce different levels of potential growth, but generate similar growth rate dynamics, particularly the downward trend. From this perspective, the tendency for high and sustainable GDP growth in Belarus is increasingly compromised.
Economic authorities seem to be aware of that fact. For instance, the Ministry of Economy stresses the need to create a new, ‘highly productive’ sector in the national economy as the new engine of growth. An ambitious plan involves expanding the size of this sector to contribute to about half of the GDP growth rate, aimed at 12 per cent per annum by 2015. The creation of this ‘highly productive sector’ falls into recent policy initiative, called ‘modernization’. Under this banner, the government plans to renovate the capital stocks (primarily machinery, equipment, and transport vehicles) of a large number of state-owned enterprises. In a nutshell, this strategy may be seen as a way to facilitate technical progress embodied in capital.
What is necessary, according to the government, is to make a spurt in capital investments, often on a case-by-case basis. The government has a pool of enterprises to be modernized. The majority of them are unable to modernize themselves – i.e. radically increase capital investments – due to the lack of internal funds and poor access to external finance. Accordingly, directed lending is considered to be a useful policy instrument of modernization. In 2013, the Development Bank plans to considerably increase its credit portfolio (by about USD 0.5 billion) by financing projects at subsidized interest rates under the ‘modernization’ program. Recently, the government compiled a list of 67 agricultural enterprises liable to have an access to cheap loans for modernization purposes from the Development Bank. In addition, state-owned banks will continue the provision of policy loans that can be considered as directed ones.
With directed loans, we mean those loans that are typically granted to selected borrowers at interest rates lower than the market interest rates. In Belarus, directed lending has been an important policy tool over the last decade. Selective credit programs have been applied to prevent underinvestment and to stimulate output growth.
According to the estimations of Fitch Ratings (2010), almost a half of the outstanding loans in the Belarusian economy by the end of 2009, were directed ones. The IMF provided a slightly smaller, but still substantial figure of 46.2 percent (IMF, 2010). According to our own calculations, by 2011, the volume of directed loans amounted to about 40 percent of the total volume of outstanding loans. These loans have been made abundant in agriculture and housing construction sectors and, to a lesser extent, in manufacturing. This massive presence of selective credit in the national economy can be seen as a large factor contributing to the currency crisis of March 2011.
Accordingly, after the crisis, and following the necessity to ‘clear up’ the assets of the national banking system, the share of directed lending was reduced. We estimate that in 2012, the ratio of directed loans in total loans dropped to roughly 30 percent. However, the recent rhetoric of the development of ‘highly productive’ sectors and modernization is indicative of the intention to find new life for this old cloth. Directed lending is expected to revitalize enfeebling growth. In 2012, real GDP growth amounted to 1.5 percent against the background of the initial government plan of 8.5 percent.
Under selective credit programs, banks have been partially deprived of their autonomy to make decisions over the provision of credit. Thus, banks’ intermediation role has been circumscribed by the authorities. In theory, directed loans may spur capital accumulation as beneficiaries of these loans have access to cheap loans and thus invest and – arguably – produce more. In Belarus, there has also been an additional incentive, i.e. the necessity to substitute depreciating and outdated capital stock, inherited from the Soviet past. At the same time, political interference into the process of credit provision suggests that loans may be allocated to lower-yielding projects, and thus dampen growth rates of factor productivity and GDP (Fry, 1995). In addition, non-favored companies – typically from the private sector – face higher interest rates as their state-owned counterparts receive substantial discounts for their use of capital.
So far, these soft budget constraints in the financial system have allowed favored companies to receive loans up to three times cheaper, if judged by the level of real effective interest rates. Although private companies tend to be more efficient than state-owned enterprises in terms of factor returns and profitability, higher interest rates may reduce the volume of outstanding market loans. Furthermore, increases in the volume of cheap residential loans, which do not contribute directly to enhancement of productive capacity of the economy, may dampen the returns on investment further.
Governments have traditionally relied on selective credit programs by stressing positive externalities and spillovers for the economy as a whole (DeLong and Summers, 1991). Commercial banks care about private returns, while governments seek to maximize social returns by financing firms, which are capable of generating positive externalities. Unfettered operations of credit allocation mechanisms minimize allocation inefficiency and induce banks to minimize the costs of financial intermediation, thereby making credit more accessible.
How do these competing forces meet in Belarus and what are the effects of their joint working? In answering those questions, we have conducted an empirical analysis of the effects of directed lending on total factor productivity dynamics. The latter is considered to be a good proxy to observe the impact of selective credit programs on the efficiency of actor use.
The results of our econometric analysis show that over the period concerned, 2000–2012, the expansion of directed lending in Belarus has negatively affected total factor productivity dynamics and, subsequently, negatively contributed to the rates of GDP growth. A positive impact on growth, stemming from additional capital accumulation might nevertheless occur, but with a substantial lag. This likely positive impact is associated with the ability of banks to increase the volume of market loans alongside with the rising volume of directed loans. The option has been made possible only due to massive liquidity injections by the government and mainly the National Bank of Belarus. However, such injections are problematic to maintain over the medium to the long run as they have severe inflationary repercussions for the economy.
The effects of individual components of directed lending are mainly the same. In particular, loans for residential construction, provided to households in need, negatively affect total factor productivity. Moreover, it is through housing loans the adverse effects of directed lending upon factor productivity are mainly realized. The interest rate spread – between preferential interest rate and market interest rate – amplifies these negative relationships. Lower preferential rates result in larger losses in total factor productivity. Loans to agricultural firms have similar impact, although it has to be emphasized that the overall impact on total factor productivity approaches zero (not negative, as in the case of housing loans).
We also find that for Belarus, an increase in the total volume of directed loans leads to an increase in the volume of market loans. Both the National Bank and, to a lesser extent, the government, strive to minimize risks in the national banking system, which provide loans with smaller returns and/or non-performing policy loans. Similar challenges have been observed in China, where the Central Bank has been forced to recapitalize domestic banks to support economic growth after the global financial crisis of 2008. In 2007–2008, Chinese growth of 8–10 percent was driven by new lending averaging 30–40 percent of GDP, of which up to a quarter of the loans might have been non-performing, amounting to losses of 6–10 percent of GDP (Das, 2012).
In Belarus, the recapitalization policy, apart from its inflationary consequences, has other important effects. In particular, it prevents a dangerous trade-off between directed loans and market loans to resurface, whereby the former crowds out the latter as banks are unable to expand their portfolios due to the liquidity constraints.
Therefore, unless the expansion of directed loans would be checked, adverse effects of selective credit programs on productivity and growth would not evaporate, with negative consequences for the whole economy. Regarding policy recommendations, we claim that there is a need to fundamentally revise directed lending policies or to even minimize it to the extremes by allowing standard market mechanism for credit allocation to prevail in the national economy. Furthermore, we argue that directed lending, even after some cosmetic changes in the system design made in 2012, is not an efficient tool for economic growth promotion.
Tentative results of growth accounting made at the level of selected important industries suggest that the downward growth dynamics is associated with weak total factor productivity growth, i.e. disembodied technical progress. Improvement of total factor productivity seems to have the biggest potential for revival of economic growth. Therefore, the use of directed lending, as a policy instrument that hampers total factor productivity dynamics, may undermine prospects for long-term economic growth in Belarus.
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References
- Das, S. (2012). “All Feasts Must Come to an End– China’s Economic Outlook”, Euro Intelligence, 11 March, viewed 12 April 2012.
- DeLong, J.B. and L.H. Summers, (1991). “Equipment Investment and Economic Growth”, Quarterly Journal of Economics 106, 2, pp. 445–502.
- Fitch Ratings, (2010). “Directed Lending: On the Up or on the Way Out?”, Belarusian Banking Sector, May.
- Fry, M.J. (1995). Money, Interest, and Banking in Economic Development (John Hopkins University Press, Baltimore and London).
- IMF (2010), “Republic of Belarus: Fourth Review under the Stand-By Arrangement”, IMF Country Report 10/89, viewed 15 July 2012.
Fact or Fiction? The Reversal of the Gender Education Gap Across the World and the Former Soviet Union
In this policy brief, I discuss the reversal of the gender education gap in many countries around the world – a fact that is still not widely known, although is increasingly gaining attention. I describe recent studies that have documented this fact for both developed and developing countries and have provided evidence on the trend. As there has not been much analysis of the education gap in the former Soviet Union countries, I present some measures of the education gap in the USSR and FSU countries, and compare them to other countries around the world. Finally, I discuss the potential causes of the reversal identified in the literature and how the reversal of the gap is related to other gender disparities.
Becoming Entrepreneur in Belarus: Factors of Choice
This policy brief summarizes two papers by Maryia Akulava on entrepreneurship development in Belarus and outlines which factors affect the choice of becoming self-employed in Belarus. While one of the papers, “Choice of Becoming Self-Employed in Belarus: Impact of Monetary Gains”, focuses on the role of pecuniary benefits, the other paper, “Portrait of Belarusian Entrepreneur”, adopts a broader perspective by accounting for individual, sociological, and institutional factors.
Although the Belarusian government has repeatedly declared the importance of private entrepreneurship for the national economy, its role remains rather modest. In terms of private sector development, Belarus lags severely behind other post-socialist countries. Yet, over the last decade, some positive dynamics have been recorded. In particular, the number of small and medium enterprises (SMEs) per 1,000 people increased from 2.5 in 2003 to 7.2 in 2010. Still, this ratio is rather small in comparison with other post-socialist economies (Table 1) [3; 4; 5; 6].
Table 1. Number of Small Enterprises (SEs) per 1,000 People
| Number of SEs per 1000 people | |
| Belarus | 7.2 |
| Russia | 11.3 |
| Ukraine | 17 |
| Kazakhstan | 41 |
| United Kingdom | 46 |
| Germany | 37 |
| Italy | 68 |
| France | 35 |
| EU countries | 45 |
| United States | 74.2 |
| Japan | 49.6 |
Regarding the growth rates of SEs and individual entrepreneurs (IEs), the numbers leave much to be desired. Specifically, in 2009, the number of SMEs and IEs amounted to 62,700 and 216,000 respectively, while in 2011 – to 72.200 and 232,000. Therefore, despite the efforts of the authorities to encourage the development of private initiative, the number of SEs and IEs only increased by 15.2 and 7.4%, respectively.
Next, private sector employment remains rather low. It amounts to approximately 13%, while in the developed economies this figure varies between 60 and 70%. For instance, in the U.S., it amounts to 60%, in Germany and in France – around 65-70%, and in Japan – 85%. On the other hand, transition economies have smaller shares, including Russia – 17%, Kazakhstan – 20.6%, and Ukraine – up to 28.8%, [7].
Some important indicators are provided in Table 2 [8].
Table 2. Share of Small and Medium Business in Economic Indicators of Belarus
| Share of small sector | 2003 | 2008 | 2009 | 2010 |
| GDP | 8.2 | 11.2 | 11.4 | 12.4 |
| Volume of industrial production | 8.4 | 8.3 | 9.2 | 9.4 |
| Exports | 18.2 | 31.4 | 34.3 | 38.9 |
| Retail trade turnover | 9.2 | 27.8 | 29.5 | 28.2 |
| Economically active labor force | 13 | 13 | 13 | 13.1 |
Table 2 reveals an increased contribution of private entrepreneurs to the national economy. At the same time, the share of labor employed in the private sector remains unchanged at the level of 13%. This fact suggests that self-employment remains relatively unattractive for salaried workers.
So, what are the drivers of people’s choice? On the one hand, people might be reluctant to become entrepreneurs because of the prevailing social and cultural attitudes, or the lack of necessary experience. Post-socialist economies all share the legacy of planning and suppression of private initiative. On the other hand, government’s policies and regulations might ‘cool down’ enthusiasm or people simply have had or heard of some bad experiences. Thus, it is important to think of the reasons behind people’s choice and formulate policies to encourage entrepreneurship development in Belarus.
Who Is a Belarusian Entrepreneur?
In Belarus, entrepreneurs are active mainly in the non-manufacturing sector, including trade (30% of all entrepreneurs), provision of different services (16.5%), construction (13%), logistics (7%), and real estate (7%). The most common reasons to start your own business include a sudden, but attractive, business opportunity (66%), and the availability of funding for project implementation (33%).
As for the gender and age profiles of Belarusian entrepreneurs, 64% are men and 36% are women, with an average age of around 40-42 years. The majority of entrepreneurs is religious (54%), married (69%), and has children (75%). Around 65% have higher education, and about one third of them were among the top 10% students of their classes. Entrepreneurs report a good health status: 64% of them consider themselves as ‘healthy’. This is not surprising, given that entrepreneurship in Belarus is ‘survival for the fittest’. An entrepreneur has to be ready to take risks, be energetic, active and to continuously search for new business opportunities. Moreover, entrepreneurs are optimists, who evaluate themselves as successful (77%) and happy (81%) people.
Sociological characteristics reveal strong reliance on social networks. In general, the number of relatives or friends involved in the business activities is about two times larger than for salaried workers. Besides that, a much larger share of entrepreneurs consider their parents wealthy and successful (45% and 82%), compared with employees (34% and 37%, respectively).
Belarusian entrepreneurs stay in business because they like what they do (53%), and think that their work is important for society (29%). Profits and income remain a strong, but are not a decisive reason (25%).
Although entrepreneurs and employees do not differ substantially in terms of their attitudes towards family, friends, health, financial stability, religion, and so on, there is still a notable distinction. Specifically, entrepreneurs tend to praise work, power and influence over other people, and also like political freedom. In addition, they value their function of a service provider to other people.
Moreover, entrepreneurs have more trust to colleagues, other business people and subordinates than salaried workers. This is not surprising, given the importance of horizontal networks mentioned above. It is important to note that more than 30% of respondents expressed their trust to political authorities despite the government-induced difficulties for entrepreneurship development in Belarus.
Analysis of institutional infrastructure for doing business detects a negative relationship between a publicly-stated favorable attitude of authorities towards entrepreneurs and their decision to work in the private sector. This can be explained in following way: a priori, the government’s stance on entrepreneurship is evaluated positively, or at least considered as not harmful. Moreover, a person considers himself as being too small to attract the ‘extractive attention’ of the authorities. However, a posteriori, entrepreneurs revise their initial views. Their experience tells us that the government’s attitude is far from welcoming.
As for corruption, the attitude is ambiguous. On the one hand, entrepreneurs generally disfavor corruption. On the other hand, those who seek to expand their businesses consider corruption a way to avoid ‘unnecessary troubles’ and to overcome barriers created by the excessive ‘red tape’ in the economy.
What Are The Obstacles For Doing Private Business In Belarus?
Belarusian entrepreneurs consider the following factors as barriers to business development: (i) inflation and macroeconomic instability (55%), (ii) lack of financing (31%), (iii) high taxes (27%) and complexity of tax system (18%), (iv) legal vulnerability (23%), and (v) toughness of state administrative regulation inspections, licensing and certification requirements (19%). These barriers are largely of macroeconomic and regulatory nature. Moreover, authorities conduct a policy of close-to-full formal employment. This policy is aimed at securing jobs for people even at loss-making and poorly performing companies, which are kept afloat by subsidizes and directed loans. As a result, employees prefer to trade risks of working in the private sector, for a stable employment in the sector of state-owned enterprises.
As for the main barriers, which impede business start ups financial constraints are the most common factor (33%), followed by high risks (25%), the lack of necessary business skills, a clear understanding what to do in the market (15% and 13% respectively), and unwillingness to work a lot (16%). In other words, financial constrains along with the lack of business education are the two most important domestic barriers.
These findings correspond to the results of the research on the impact of pecuniary benefits on entrepreneurs. In that study, education does not appear to have a significant influence on the level of earnings by entrepreneurs. The latter are ‘self-trained’ by the experience of starting a business in the uncertain environment of the 1990s and matured in the course of doing their business in unfriendly conditions. However, as the economy evolves, activities and contracts become more sophisticated. To survive in the changing environment, entrepreneurs have to acquire new skills and learn new methods and concepts of doing business.
So far, it appears that the quality of education obtained by the entrepreneurs does not match the skills required in the Belarusian economy. Thus, it is important to organize seminars, to hold training and to run business education programs for the future and current entrepreneurs in order to upgrade their skills and thus to contribute to their improved performance on the market.
Conclusion
An efficient development of the private sector in Belarus requires a drastic improvement of the domestic business environment. In order to encourage domestic entrepreneurship, the authorities should improve macroeconomic management and cut much of the ‘red tape’. Entrepreneurship possesses a great potential to contribute to growth and development. Surveys reveal that government policies constrain the development of the domestic private sector. Moreover, the high tax burden should be reduced, and some fiscal ‘sweeteners’ could be offered for business startups. In addition, a somewhat higher priority should be given to the improvement of the quality of business education, and make it more accessible for the current and future business people. If implemented, all these measures would supposedly have a fostering impact on the development of a dynamic private sector in Belarus.
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References
Akulava M. 2012. “Choice of Becoming Self-Employed in Belarus: Impact of Monetary Gains”.
Akulava M. 2012. “Portrait of Belarusian Entrepreneur”. Work in progress.
Djankov S., Miguel E., Qian Y., Roland G. and Zhuravskaya E. 2005. “Who are Russia’s Entrepreneurs?” Journal of the European Economic Association, MIT Press. Volume 3 (2-3), 04/05.
Djankov S., Miguel E., Qian Y., Roland G. and Zhuravskaya E. 2006. “Entrepreneurship in China and Russia Compared” Journal of the European Economic Association, MIT Press. Volume 4 (2-3), 04/05.
http://netherlands.mfa.gov.by/_modules/_cfiles/files/sme_belarus_2011_1670.pdf
http://www.tambov-rosnou.ru/monograf/files/ind4.htm
http://www.erce.ru/internet-magazine/magazine/27/389/
http://www.mspbank.ru/files/documents/Ukraine.pdf
Sulakshin S. “State Economic Policy and Economic Doctrine of Russia. To Smart and Ethic Economy”. Т. II.
http://netherlands.mfa.gov.by/_modules/_cfiles/files/sme_belarus_2011_1670.pdf
The Eurasian Customs Union among Russia, Belarus and Kazakhstan: Can It Succeed Where Its Predecessor Failed?
In 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union and imposed the Russian tariff as the common external tariff of the Customs Union. This resulted in almost doubling the external average tariff of the more liberal Kazakhstan. Russia has benefited from additional exports to Kazakhstan under the protection of the higher tariffs in Kazakhstan. However, estimates reveal that the tariff changes have resulted in substantial transfers from Kazakhstan to Russia since importers in Kazakhstan now purchase lower quality or higher priced Russian imports which are protected under the tariff umbrella of the common external tariff. Transfers from the Central Asian countries to Russia were the reason the Eurasian Economic Community (known as EurAsEC) failed, so this bodes badly for the ultimate success of the Eurasian Customs Union. What is different, however, is that the Eurasian Customs Union and its associated Common Economic Space aim to reduce non-tariff barriers and improve trade facilitation, and also to allow the free movement of capital and labor, liberalize services, and harmonize some regulations. Estimates by my colleagues and I show that if substantial progress could be made in trade facilitation and reducing non-tariff barriers, this could make the Customs Union positive for Kazakhstan and other potential Central Asian members. Unfortunately, so far the Customs Union has made these matters worse. On the other hand, Russia’s accession to the World Trade Organization will eventually substantially reduce the transfers from Kazakhstan to Russia, but this will need a strong political commitment from Russia which we have not yet seen. If that Russian political leadership is forthcoming, the Eurasian Customs Union could nonetheless succeed where its predecessor has failed.
In January 2010, Russia, Belarus and Kazakhstan formed the Eurasian Customs Union. Two years later, the three countries agreed to even closer economic ties, by signing the agreement to form a “common economic space.” Regarding tariffs, the key change was that the three countries agreed to apply the tariff schedule of the Customs Union as their common external tariff for third countries. With few exceptions, the initial common external tariff schedule was the Russian tariff schedule. Kazakhstan negotiated exceptions from the common external tariffs for slightly more than 400 tariff lines, but was scheduled to phase out the exceptions over a period of five years (World Bank, 2012). In addition, the members agreed to have the Customs Union determine the rules regarding sanitary and phyto-sanitary standards (SPS) and standards on good. Fearing transshipment of goods from China through Kazakhstan and from the European Union through Belarus, Russia negotiated and achieved agreement on stricter controls on the origin of imports from countries outside of the Customs Union. The common economic space (CES) stipulates that, in principle, there will be free movement of labor and capital among the countries, there will be liberalization of services on the CES and coordination of some regulatory policies such as competition policy.
In February 2012, the Eurasian Economic Commission began functioning. It is intended to act as the regulatory authority for the Customs Union in a manner similar to the European Commission for the European Union.
The Economics of Tariff Changes — Gains for Russia and Losses for Kazakhstan
Some proponents of the Eurasian Customs Union have argued that as a result of the Customs Union firms in the three countries will have improved market access through having tariff free access to the markets in all three countries. Prior to 2010, however, along with other countries in the Commonwealth of Independent States (CIS), the three countries had agreements in place that stipulated free trade in goods among them. Thus, the Customs Union could not provide improved market access due to reducing tariffs on goods circulating among the three countries.
Since the common external tariff was essentially the Russian tariff, there was little change in incentives regarding tariffs in Russia. The big change occurred in Kazakhstan, who had a much lower tariff structure than Russia prior to implementing the Customs Union tariff. Despite the exemptions, Kazakhstan almost doubled its tariffs in the first year of the Customs Union (see World Bank, 2012). The increase in tariffs on many items which were not produced in Kazakhstan but produced in Russia, led to a substantial increase in imports from Russia and displacement of imports from Europe. Many of Russia’s manufacturing firms, which were not competitive in Kazakhstan prior to the Customs Union, were now able to expand sales to the Kazakhstani market. This represents gains for Russian industry. Given the deeper manufacturing base in Russia compared with most of the CIS countries and the resulting uneven benefits of the common external tariff in favor of Russia, acceptance of the common external tariff has been a fundamental negotiating position of Russia regarding acceptance of members in the Customs Union.
Some cite the expanded Russian exports in Kazakhstan as evidence of success of the Customs Union. But the displacement of European imports, to higher priced or lower quality imports from Russia, represents a substantial transfer of income from Kazakhstan to Russia and is an example of what economists call “trade diversion”. Moreover, it is the reason the World Bank (2012) has evaluated the tariff changes of the Customs Union as a loss of real income for Kazakhstan.
Furthermore, the three countries together (and even a broader collection of CIS countries) constitute too small a market to erect tariff walls against external competition. They would lose the benefits of importing technology from advanced countries and would rely on high priced production from within the Customs Union. Some would argue that there are political benefits of trade to be taken into account, but experience has shown that when a customs union is inefficient and the benefits and the costs of the customs union are very unequal, the customs union can inflame conflicts (see Schiff and Winters, 2003, 194-195).
Non-Tariff Barriers — Extremely Costly Methods of Regulating Standards Worsened by the Customs Union
Non-tariff barriers, in the form of sanitary and phyto-sanitary (SPS) conditions on food and agricultural products and technical barriers to trade (TBTs) on goods, are a very significant problem of the Customs Union. There are standards based trade disputes between Belarus and Russia on several products, including milk, meat, buses, pipes and beer (see Petrovskaya, 2012). Anecdotal evidence indicates that Kazakhstani exporters complain bitterly regarding the use by the Russian authorities of SPS and TBTs measures, either to extract payments or for protection.
If the Customs Union could make substantial progress on reducing these barriers, it would be a significant accomplishment. My colleagues and I have estimated that progress on the non-tariff barriers and trade facilitation could outweigh the negative impact of the tariff changes for Kazakhstan (see World Bank, 2012). Unfortunately, so far the Customs Union has taken a step backward on both non-tariff barriers and trade facilitation.
A big problem in reducing standards as a non-tariff barrier is that standards regulation, in all three countries, is still primarily based on the Soviet system. As a holdover from the Soviet era, mandatory technical regulations are employed where market economies allow voluntary standards to apply. This regulatory system makes innovation and adaption to the needs of the market very costly as firms must negotiate with regulators when they want to change a product or how it is produced. Legislation in both Russia and Kazakhstan calls for conversion to a system of voluntary standards, but this is happening too slowly in all three countries. The problem is that the Customs Union has worsened the situation. Technical regulations are now decided at the level of the Customs Union, so firms that previously negotiated with their national standards authority, have had to now get agreement from the Customs Union. This has reportedly caused further delays, impeding innovation and the ability of firms to meet the demands of the market.
A second problem with efforts to reduce the non-tariff barriers is that the Customs Union is trying to harmonize standards of the three countries by producing mandatory technical regulations. The alternative is to use Mutual Recognition Agreements (MRAs). Experience has shown that no customs union has been able to broadly harmonize standards based on mandatory technical regulations, with the exception of the European Union. In fact, even in the European Union, they have had to use MRAs and only harmonized technical regulations after decades of work. While each member of the Customs Union is expected to create a system of mutual recognition of certificates of conformity, these certificates are not presently recognized in the other countries of the Customs Union. There is little hope for a significant reduction in standards of non-tariff barriers unless the system of mutual recognition is more widely recognized and adopted.
Trade Facilitation —Participation in International Production Chains Made More Difficult by the Customs Union
Customs posts between the member countries have been removed and this has reduced trade costs for both exporters and importers in the three countries. Russia’s concerns regarding transshipment have, however, led to an opposite impact on trade with third countries, i.e., the costs of trading with countries outside the Customs Union have increased. Participation in international production chains has become a key feature of modern international production and trade. If goods cannot move easily in and out of the country, multinational firms will look to other countries to make their foreign direct investment and for international production sharing. Addressing this significant problem will take a change of emphasis on the part of Russia.
Russian WTO Accession —Liberalization That Will Significantly Reduce Transfers to Russia
It has apparently been agreed by the Customs Union members that the common external tariff of the Customs Union will change to accommodate Russia’s WTO commitments. As a result, the applied un-weighted average tariff will fall in stages from 10.9 percent in 2012 to 7.9 percent by the year 2020 (see Shepotylo and Tarr, forthcoming).[1] This will have the effect of lowering the trade diversion costs of Kazakhstan. In addition, the Customs Union will be expected to adapt its rules on standards to conform to commitments Russia made as part of its WTO accession commitments. In the case of Belarus, it remains to be seen if it will implement the changes, as this will increase competition for its industries.
Conclusion — the Need to Russia to Exercise Political Leadership for Standards and Trade Facilitation Reform for Success of the Customs Union
In 1996, the same three countries formed a customs union. Later the same year, they were joined by Kyrgyzstan, then by Tajikistan and in 2005 by Uzbekistan. As Michalopoulos and I (1997) anticipated, the earlier Customs Union failed because it imposed large costs on the Central Asian countries, which had to buy either lower quality (including lower tech goods) or higher priced Russian manufactured goods under the tariff umbrella. The present Customs Union also started with the Russian tariff, which protects Russian industry and suffers from the same problem that led to the failure of the earlier Customs Union. Nonetheless, the present Customs Union could succeed. Crucially, due to Russia’s accession to the WTO, the tariff of the Customs Union will fall by about 40 to 50 percent.[2] This will make the Customs Union a more open Customs Union, very significantly reduce the transfers from Kazakhstan to Russia, and thereby reduce the pressures from producers and consumers in Kazakhstan on their government to depart from enforcement of the tariffs of the Customs Union. Further, the present Customs Union aims to reduce non-tariff barriers and improve trade facilitation, as well as it has “deep integration” on its agenda, i.e., services liberalization, the free movement of labor and capital and some regulatory harmonization. Although, to date, the Customs Union has moved backwards on non-tariff barriers and trade facilitation, one could optimistically hope for substantial progress. In the important area of non-tariff barriers, given the common history of Soviet mandatory standards, Russia will have to take the lead in moving the Customs Union toward a system of voluntary standards where no health and safety issue are involved, and toward a system of mutual recognition agreements and away from commonly negotiated technical regulations. On trade facilitation, Russia will have to reverse its pressure and find a way to allow the freer movement of goods with third countries while addressing its transshipment concerns.
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References
- Michalopoulos, Constantine and David G. Tarr (1997), “The Economics of Customs Unions in the Commonwealth of Independent States,” Post-Soviet Geography and Economics, Vol. 38, No. 3, 125-143.
- Petrovskaya, Galina (2012), “Belarus, Rossia, Ukraina. Obrechennye na torgovye konflikty” (Belarus, Russia, Ukraine. Doomed for trade conflicts), Deutsche Welle, June 14. www.dw.de/dw/article/0,,16023176,00.html.
- Schiff, Maurice and L. Alan Winters (2003), Regional Integration and Development, Washington DC: World Bank and Oxford University Press.
- Shepotylo, Oleksandr, and David G. Tarr (2008), “Specific tariffs, tariff simplification and the structure of import tariffs in Russia: 2001–2005,” Eastern European Economics, 46(5):49–58.
- Shepotylo, Oleksandr, and David G. Tarr (forthcoming), “Impact of WTO Accession on the Bound and Applied Tariff Rates of Russia,” Eastern European Economics.
- Shymulo-Tapiola, Olga (2012), “The Eurasian Customs Union: Friend or Foe of the EU?” The Carnegie Papers, Carnegie Endowment for International Peace, October. Available at: www.CarnegieEurope.eu,
- World Bank (2012), Assessment of Costs and Benefits of the Customs Union for Kazakhstan, Report Number 65977-KZ, Washington DC, January 3, 2012. Available at: http://documents.worldbank.org/curated/en/2012/01/15647043/assessment-costs-benefits-customs-union-kazakhstan
[1] The final “bound rate” of Russia is higher at 8.6 percent on an un-weighted average basis; but there are about 1,500 tariff lines where the applied rate of Russia is below the bound rate. The applied weighted average tariff will fall from 9.3 percent in 2012 to 5.8 percent in 2020.
[2] Russian tariffs fall more on an un-weighted average basis than they do on a weighted average basis. See Shepotylo and Tarr (forthcoming).
Monetary Policy in Belarus since the Currency Crisis 2011
In the second half of 2010, the National Bank of Belarus carried out a soft monetary policy to stimulate domestic demand. Until March 2011, the country experienced strong economic growth. There was an increase in real incomes with a parallel increase in the negative trade balance and the reduction of international reserves. Stimulating policy became one of the reasons for the formation of a multiplicity of exchange rates on the foreign exchange market. Beginning of March and until the end of October 2011, there was an official and gray currency market in the country. High domestic demand and rapid devaluation processes led to the deployment of an inflationary spiral, which in turn meant a decrease in the growth of real incomes.
Assessing Inflation Persistence in Belarus
Author: Igor Pelipas, BEROC.
Generally speaking, inflation persistence can be defined as the speed at which inflation returns to its equilibrium level after a shock. Since 1995, the dynamics of inflation in Belarus is affected by the various internal and external shocks, which, in turn, cause the structural breaks in the corresponding historical data. The deep currency crisis in 2011 led to a huge increase of inflation, and reached a three-digit value. In the current year, the reduction of inflation is one of the most vital problems for the Belarusian authorities. In this context, the understanding of inflation persistence in Belarus is of great importance for appropriate monetary policy and macroeconomic stabilization measures. Additionally, the issue of inflation persistence is topical in the debates on the possibilities of inflation targeting in Belarus. There is an extensive body of literature on the inflation persistence in the US, the EU member states, and in other countries. Inflation persistence, however, has not yet been a subject of analysis in Belarus. In this policy brief, we have attempted to fill the gap by presenting the results of an inflation persistence assessment in Belarus.
Do Economic Sanctions Work?
Analysts have interpreted the recent openings in Myanmar and North Korea as the finally successful result of years of international pressure and economic sanctions. At the same time, debate is hot on the scope for similar measures in Iran, Syria, and, closer to us, Belarus and Hungary. Does economics have anything to say on this? What can we learn from the analysis of past experiences?
On February 29th, after decades of frustrating attempts by the outside world with sticks and carrots, but mostly economic and diplomatic isolation, North Korea announced that it would suspend its enrichment of uranium and its tests of weapons and long-range missiles. It would even allow an inspection by the International Atomic Energy Agency, the first one since the country walked out of the Nuclear Non-Proliferation Treaty in 2003. The recently inaugurated leader, young Kim Jong Un, asked, in exchange, some tons of food aid and the promise of talks. Some believe this was inspired by another recent unexpected “opening”: the turn-of-the-year developments in Myanmar, where a cease-fire and the release of many of the political prisoners prompted a slow but sure thawing in the country’s diplomatic relations with the rest of the world. Some months on, the government’s intentions to move from a military dictatorship to greater pluralism still seem sincere enough. Many have interpreted these events as the finally successful result of years of international pressure and economic sanctions on the two countries. Is the tide turning for sanctions enthusiasts?
At the same time, though, concerns are rising that EU member Hungary is moving in quite the opposite direction, after a change in the constitution that endangers the independence of the media, the judiciary and the central bank. Hungarians protesting in the streets are openly talking about authoritarian evolution drawing parallels with the behavior of the government in Belarus, which only months ago attracted harsh criticism – and stringent sanctions. Hungary might follow suit in this respect as well: its credit line with the IMF is still hanging from a thread, and the EU threatened law suit over the constitutional changes, while a potential limitation of the country’s voting rights in Brussels is whispered as the “nuclear option”.
Although the situation looks increasingly, explosive both in Syria and Iran, even in these cases the hopes of the international community rest exclusively on economic coercion. Syria’s economy is now under severe pressure, after even the Arab League imposed sanctions. This is first time such a decision is taken against a fellow member. Near all trade and financial relations have been cut off, with the exception of some banks in Lebanon and perhaps a few business friends in China and Russia that might still offer assistance to Bashar Assad’s regime. But the country’s foreign reserves, already low one year ago at the offset of the crisis, should be running out by now, and inflation is rising as many consumption goods become scarce. At the same time, although Saudi Arabia is arming the rebel groups, a military intervention sanctioned by the international community seems unlikely, given the recent Libyan precedent.
The sanctions faced by Iran over its nuclear program are also growing to unprecedented severity, and also in this case military action does not seem to be considered an option – except by (understandably) jumpy Israel. Given the stage that the nuclear program has reached, and the level of protection built around it, bombing is not likely to stop it. Experts say that a successful US-lead operation could at most delay it some ten years. Arguably, this would only result in an even angrier Iran equipped with nuclear weapons, in ten years from now. Hence it would appear much more fruitful to try to change the population’s attitude, so that Iranians themselves can in turn affect their political leaders’ attitude, even if this needs replacing the regime altogether. This way the prospect of a nuclear Iran would not look as scary.
As the international community considers over and over its stance in all these thorny situations, a legitimate question in everybody’s mind is: What is the likelihood that the sanctions will work? Does the economic literature have anything to say on this matter?
Achieving the Goal
According to Richard Baldwin, Professor of International Economics at the Graduate Institute of Geneva, “[i]t would be difficult to find any proposition in the international relations literature more widely accepted than those belittling the utility of economic techniques of statecraft.” In other words, a prominent scholar’s synthesis of the literature is that economic sanctions do not work. The anecdote most widely cited by advocates of sanctions is of course South Africa. The economic pressure imposed on the country in the mid-1980s certainly contributed to the strain that the inefficient and costly apartheid regime was increasingly suffering, finally leading to its dismissal. At the opposite end of the spectrum stands Iraq, where neither the comprehensive sanctions nor the oil-for-food program, in principle a quite clever combination of sanctions and aid, could achieve anything. The success of the following military intervention is also a subject of debate, though not one I will address here. Some have drawn the conclusion that the discriminating factor lies in how important for the target regime is the recognition of and identification with the sanctioning part. Others argue the probability that the sanctions succeed is linked to the cost born by the target, or by the sanctioning part (also called the sender), or other observable factors. If truth be told, these are both quite special cases, hard to generalize. But then again, one could argue that every episode involving international disputes is a special case. It follows that the systematic study of economic sanctions with the evaluation of their effects is not a straightforward task at all.
The first step to evaluate the success of imposed economic sanctions is to establish what the goal is. In the most basic terms, there are two types of explicit goals. In some cases, the imposition of an economic sanction is purely punitive towards a policy or act of a regime, or towards the regime itself, and aims at expressing disapproval from the initiating part, when inaction can signal complicity. Hoffman [8] was one of the first to suggest that “sanctions are mostly adopted to alleviate cross pressure situations, resulting when a (foreign) government faces demands for action but war is undesirable”. In this case, it makes little sense to talk about success or failure, as the imposition of sanctions is a goal in itself.
In the extreme case, this type of sanctions aims at destabilizing the target regime, inducing political change. This seems to be part of the aim of actions taken against Syria, although an end to the Iranian theocracy, and Lukashenko’s regime in Belarus, for that matter, would certainly be welcome as well. An analysis of the historical records from 1914 to 1989 [4] reveals that the probability of success with this goal has been 38% when the regime was very stable to start with and up to 80% in “distressed” countries. The single most important factor of success is hence, not surprisingly, the pre-sanctions stability of the political system in the target country. In some cases, paradoxically the imposition of sanctions stimulated political cohesion in the target country – the so called rally-round-the-flag effect. This is what seems to be happening, at least at this stage, in Hungary. The evidence suggests that there is a threshold of political cohesion above which external intervention strengthens the target government. According to Lindsay [13], three factors make it more likely that sanctions produce political integration rather than regime collapse:
- If they are seen as an attack on the whole country rather than on a specific faction
- If identification with the sanctioning part is weak or even negative
- If no alternative to the sanctioned course of action is available or perceived as better
In this light, measures that can be manipulated to punish only or prevalently the regime’s domestic supporters and political base are to be considered as superior. Travel bans and freezes of assets, foreign bank accounts and property of functionaries are examples of this type of measures. Financial restrictions, in addition to be perceived as comparatively fairer, have also been more effective in the past. Moreover, also to the point that the sanctions should not, if possible, hurt everyone indiscriminately, they are preferable to measures that hurt the productive sector, like trade restrictions.
Alternatively, sanctions are designed to compel a specific policy change in the target country. This is the case of Hungary and its new constitution, and formally of Iran, which is only required to drop its quest for nuclear weapons. The emerging consensus in the sanctions literature is that concessions are most likely at the threat stage [11]. Nevertheless, there are cases where the threat of sanctions fails and sanctions are then actually imposed. And, although the success rate becomes lower at this stage, there are examples where the target yields only after the sanctions are imposed. It might seem tempting then to investigate whether observable variables can predict the likelihood of success in these cases, because this would teach us something about the current crises around the world. However, trying to understand when and why sanctions have success based on the analysis of empirical data is complicated by a number of challenges.
First of all, there are at least two sources of censoring in the sample of imposed sanctions: because it is only a specific type of disputes that reach this stage, the evaluation based on them will be biased. The first reason why these are special cases is due to the fact that imposed sanctions have already failed at the threat stage. Hovi et al. [9] look at this situation from a game-theoretic perspective and argue that, if sender and target are rational, a threat of sanctions could fail because of one of three reasons: 1) it is not credible, so no actual sanctions will follow the threat; 2) it is not sufficiently potent, meaning that the target considers sanctions to be a lesser evil than yielding; 3) it is noncontingent, i.e. the target expects sanctions to be imposed regardless of whether it yields or not. If any one of these is true, then the target that did not yield at the threat stage will not yield after sanctions are imposed either (or no sanctions will be imposed if alternative 1 is true). Imposed sanctions will work only if at least one of these factors is initially not known with certainty, or wrongly perceived by the target: if the target believes the threat non credible, but then sanctions are actually imposed; if the target was wrong in judging the cost of the sanctions and realizes it only after sanctions are actually imposed; or if the target thought that sanctions would be imposed regardless of its behavior, but is subsequently persuaded that, in fact, the sanctions will cease if it yields. Otherwise, with perfect knowledge and rational decision-making, sanctions that are actually imposed are bound to fail precisely because they were imposed, i.e. because they failed at the threat stage.
Further selection occurs even earlier than the threat stage. The literature has examined thoroughly how strategic interaction during the sanction episode affects sanctions outcomes and duration (for example, [15], [7], [14], [5], [6], [12]). Much fewer studies have undertaken the possibility that states also act strategically before episodes, when choosing whether to challenge the status quo and how much to demand of the target. Theories around this stage of the “game” are referred to as endogenous demand theories. Krustev [11] proposes the idea that perhaps “strategic demands can account for the widely cited discrepancy between the frequent use of sanctions and the modest success rate of these instruments”. His game-theoretic model has the implication that oftentimes sender governments strategically choose hard cases, because “the uncertain prospects that the target agrees to a large demand might outweigh the certain prospects of receiving minor concessions”. This also results in a low observed success rate.
Beyond the difficulties related to selection, another challenge that the analyst faces is to isolate the effect of sanctions. Usually, sanctions are not adopted in a vacuum, but rather complement other types of actions (e.g. diplomatic pressure, military action), which interact with the success of the measures. Similarly, there is the issue of unintended consequences, that also affect the costs on both parts, and hence the likelihood of success. Most importantly, some of these unintended effects might change the situation so drastically that talking about success or failure does not make sense anymore.
Unintended Consequences
Besides the success or failure with the specific goals they are intended to obtain, economic sanctions bring about a host of more or less foreseeable unintended consequences as well. One especially undesirable outcome of trade sanctions has recently been brought to attention from the analysis of former Yugoslavia [2]. Under a regime of import restrictions, private and public actors might be pushed towards the use of unlawful methods in order to avoid the sanctions and reach the international market through unofficial ways. An unhealthy cooperation between politicians, organized crime and smuggling networks might then establish itself and persist even beyond the duration of the sanctions.
This consideration speaks against isolating the target country from trade flows. A case in itself concerns, though, trades which already lie on the boundary of lawfulness and little contribute to the productive sector, such as arms traffic. These can and should be decisively stopped. Aside from the security benefits to such a move, this also has the potential to dry up a significant source of revenue for the contested leadership.
Be it on credit or on trade, it goes without saying that any restriction will hurt the economy. The political consequences of an economic downturn caused by the sanctions are not easy to foresee. Recent research on fragile states [3] studies the relationship between national incomes and two types of political violence: repression, i.e. unilateral violence by the incumbent government, and civil conflict, two-sided use of violence on the part of the state as well as insurgent groups. The link with the national income prospects is given by the consideration that both parts, deciding whether to resort to violence, evaluate the cost and benefits of violent action. The incumbent government has a cost-advantage, being able to dispose of the state resources. The costs for potential insurgent factions go down with deteriorating economic conditions, for example in presence of high unemployment, because then those involved have less to lose. Insurgence then becomes more likely. This theory is consistent with the last century’s worth of evidence, including the recent wave of revolutions in the Arab world, suggesting that countries seeing a decline in incomes move towards democracy considerably faster. The evidence is anecdotal, though, and more rigorous empirical analysis [1] revealed no significant pattern.
Moreover, the step between opposition insurgence and the establishment of a new, possibly democratic, regime might not be rapid at all, as the Syrian tragedy is reminding us of every day. The question is then whether the leverage of economic measures from outside is likely to make any difference during this phase. As analysts push for the political and logistical backing of the international community to the revolt in Syria, and as Saudi Arabia is arming the rebels, we must consider that also measures aimed at supporting eventual opposition factions, or the democratic system in general, might have undesirable consequences. Comparative statics in the context of the same theoretical framework referred to above show that, for example, the promise of financial assistance conditional on free multi-party elections may raise the incumbent’s perception of instability and hence raise the risk of repression and increased looting, unless combined with reforms to strengthen executive constraints. Even pressure for the release of political prisoners might set out a ransom system, with perverse incentives to taking more and more prisoners to be exchanged with economic assistance – this might still be a risk in Myanmar, given the abundance of political prisoners still held by the government.
Another important difference between trade and financial restrictions is that the former are likely to result in accumulation of debt. The burden of this debt, that the sanctioned regime is responsible for, will weigh on the future growth of the country, hence on future generations of taxpayers and potentially on a future government, which ideally should not be held accountable for the course of action chosen today by a contested leadership. Alternatively, in the case of a collapse of the economy, the debt could be defaulted. This risk is on the countries or financial institutions that today lend money to the sanctioned regime. In other words, interrupting trade without at the same time closing the lines of credit would put the sanctioning part or third part lenders in the least desirable situation.
In some cases, the target has the possibility to resort to alternative lenders in third countries. Although this is preferable to a situation where the sanctioning part itself bears the risk on the debt, it is not ideal because it frustrates the sanctioning effort. An innovative proposal has been put forward by Jayachandran and Kremer [10], related to the legal doctrine of odious debt. They propose that any debt incurred by a particular regime, that could be argued to be contracted without the consent of the people and not for their benefit, is declared by some supranational institution illegitimate and nontransferable to successor regimes. This would create disincentive for lenders in third countries, and potentially eliminate equilibria with illegitimate lending. Even this type of loan sanctions hurt the economy and hence ultimately the population; however they create a long-run benefit for the population by preventing the accumulation of an unjust debt that today finances mismanagement, looting or repression and tomorrow has to be repaid by someone who never agreed to incur it. It would be very interesting to see this solution implemented in practice!
Conclusion
In short, sanctions are difficult to implement so as to reach the intended goal and minimize the unintended effects, but are maybe even more difficult to study systematically. International disputes are often complicated matters, situations that evolve over long time horizons. The traditional research question of when sanctions work might not be the most relevant one. Including in the analysis the strategic behavior occurring at the threat stage, and even before that, is a first step, although basing policy on the prediction that threats work better than sanctions does not strike me as a very useful conclusion.
The fact that evaluation is problematic and generalization almost impossible does not mean, however, that the study of sanctions is useless altogether. Economic analysis may still be informative for decision-making, and produce innovative ideas on the design of supranational institutions for conflict management, like the proposal on odious debt illustrates.
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