Economic & static Project.
International Trade and Economic Growth in Post-Communist Central and Eastern Europe
ECON 479, Senior Seminar in Economics
Dr. Terry Olson
07/25/03
The break up of the Soviet Union and the collapse of the Communist rule presented the liberated or newly established independent states of Central and Eastern Europe (CEE) with a demanding challenge of establishing democratic institutions of political governance and transforming their centrally planned economic systems to market economies. On the economic front, different countries chose different strategies. Some adopted the “Washington Consensus” shock therapy reforms prescribed by the IMF and the World Bank, such as the prompt liberalization of prices and commercial transactions, privatization of large state owned enterprises, and establishment of effective bankruptcy laws (Aslund, 2001). Others chose a more gradual approach and implemented those reforms more slowly or chose other avenues of action (Kramer, 1999).
As a consequence, the countries in the region have produced examples of both economic success and economic failure. For example, according to the European Bank for Reconstruction and Development (EBRD), the size of the economy in Hungary increased by 2.5 percent annually from 1992 to 1998 while in Moldova it fell by 8.5 percent per year during the same period. Ukraine despite its proximity to Europe, large market, educated workforce, and a good balance of agriculture and industry saw a vast economic decline over the time period under consideration. Meanwhile, Poland, one of the most unstable countries economically in the 1980s, emerged as a regional economic power in the 1990s (Frye, 2002).
There are many relevant studies that try to explain these striking differences in terms of different domestic and international economic policy choices made by the countries in the region. With regards to exogenous possible influences, trade policy reform still remains one of the most important economic decisions that need to be accounted for and explained (Sachs and Warner, 1995). Indeed, it is one of the more frustrating, and yet intriguing endeavors in the field of economics to explain why, despite the near consensus that free trade benefits a country, trade barriers continue to persist. Central and Eastern Europe is a good case in point. As of 1999, only 57% of the 26 post-Communist countries rated by the EBRD achieved a liberalization ranking that indicated full liberalization of their trade and foreign exchange system, and only 27% reached the standards and performance norms of advanced industrial economies at any point between the period of 1991 to 1999 (Kennedy, 2002).
The primary goal of this study is therefore to test a possible relationship between a trade policy choice and economic growth rates in the countries of Central and Eastern Europe and the Baltic States over the last decade. The countries in the region are good cases to study, since they all made fundamental trade policy choices over the years after the fall of the Soviet rule and they have all experienced divergent paths of economic success.
The paper will proceed in five parts. Firstly, I will explore some theoretical implications of foreign economic policy, namely exports, imports and Foreign Direct investment (FDI) and political factors on the levels of economic growth in Eastern Europe and the Baltic states of the former Soviet Union. Secondly, I will define an econometric model and conceptualize the dependent and independent variables. Further, the model will be estimated using various econometric techniques in order to test the expectations set forth in the literature review. Finally, I will discuss the study’s findings and offer some conclusions.
Literature Review
In the context of transition to market economy, trade policy reform is one of the key areas to be accounted for. As Sachs and Warner (1995, p.2) point out:
The international opening of the economy is the sine qua non of the overall reform process. The liberalization not only establishes powerful direct linkages between the economy and the world system, but also effectively forces the government to take actions on the other parts of the reform program under the pressures of international competition. For these reasons, it is convenient and fairly accurate to gauge a country’s overall reform program according to the process of trade liberalization.
Many models of economic development suggest that poorer countries tend to grow more rapidly than richer countries, and thus the rich/poor gap should close over time (Frenkel and Romer, 1999). This is due to the fact that poorer countries can import capital and modern technologies from wealthier countries, reaping the “advantages of backwardness.” However, such a convergence has yet to appear globally. The gap between the theory and reality is easily explained by the fact that poorer countries have also tended to shun trade liberalization and remained closed to the world economy (Sachs and Warner, 1995). In the post-Communist world, where adoption of new technologies and management of ideas is essential for the restructuring of the state planned economy, trade takes especially important role in economic growth.
Exports and Economics Growth
In particular, export promotion may be one of the key strategies to foster the domestic economic improvement. According to Ram (1987) through an export oriented development strategy a country can raise its factor productivity and increase the rate of technological innovation. In addition, as the economy expands, the country tends to be integrated into international markets, which may increase its capacity utilization and gains from the economies of scale. The pressure of competition in the world market may also lead to better product quality by forcing the domestic industries to reduce inefficiencies.
As Aslund (2002) notes, however, in the case of post-communist transition in Central and Eastern Europe it was precisely the liberalization of the export sector that was controversial and more complicated than liberalization of imports. The latter was almost considered as a given:
Shortages prevailed in all socialist economies. Many products were not available at all, while others, notably cars and consumer electronics, were exorbitantly expensive. Therefore, the liberalization of imports enjoyed strong popular support. Furthermore, initially extremely low real exchange rates in the transition countries made all imports so expensive that price competition was out of question.
In fact, in a few cases, the International Monetary Fund (IMF), World Trade Organization (WTO), and the European Union (EU) had to encourage prospective Eastern European and Commonwealth of Independent States (CIS) members to raise their tariffs. The IMF viewed tariffs as means of raising revenues for the new regimes. The European Union required prospective members to raise their tariff rates to match those of the Union as a whole. WTO viewed some level of tariffs necessary so these countries are able to negotiate their lowering in the future.
The liberalization of imports, however, may not have a significant effect on economic growth in the long run. Indeed, Cernat and Vranceanu (2002) found no significant relationship between the level of protectionism on imports and economic growth rates in Central and Eastern Europe in the 1990’s. Such may be the case because the foreign direct investment (FDI) may have played a far more important role of fostering industrialization and capital development in the region than the process of import substitution, which has been well utilized by some Asian countries (Yaghmanain, 1994).
With respect to export liberalization, as mentioned above, the post-communist countries under analysis have performed very differently. As Aslund (2002) notes, a great divide erupted between East-Central Europe, including the Baltics, and the CIS countries. The latter continued to regulate exports heavily. The domestic prices of major export commodities - energy, metals, agricultural produce, chemicals, and lumber - stayed low but at the heavy expense to government and taxpayers. Social costs due to such regulation were further exacerbated by the inefficient production and corruption. Moreover, due to such inefficiencies and restrictions that they incurred from the European Union the CIS countries continued to trade primarily only amongst themselves and hence the market for their exported goods was relatively small and not expanding.
The East-Central European countries, on the other hand, were determined to “return to Europe” and to clearly break from the old socialist system (Kramer, 1999). As a result they promptly deregulated their exports and established stable exchange rates. Moreover, most of these countries became the prospective members of the European Union by concluding the accession agreements with the EU in the early 1990’s. These so called Europe Agreements provided for free trade in industrial goods within ten years, with the EU reducing protectionist measures faster than the East-Central European countries (Aslund, 2002). Such an expansion of market for their goods in Western Europe coupled with the fact that their currencies were still greatly depreciated, which made their exported goods cheaper abroad and imported goods more expensive at home, allowed the East-Central European countries to receive significant fiscal boost from their exports along with all other advantages stemming from the outward-oriented development strategy mentioned above (Fisher, Sahay, and Vegh, 1996).
Bearing in mind the fact that, as mentioned in the introduction, the post-communist countries of Central and Eastern Europe have enjoyed very divergent paths of economic success in the last decade of their transition and the information discussed above, the primary expectation of this study is that there should be a positive relationship between the amount of exports and economic growth rates in countries of Central and Eastern Europe and the CIS under analysis. The empirical results will show whether the findings of the similar studies about the experiences of other countries in different regions of the world hold in the case of the post-communist transition. For example, Balassa (1985) estimated a linear export equation for a sample of forty-three countries using the difference between actual and predicted exports as a measure of trade orientation and found a positive correlation between more outward-oriented trade policies and economic growth rates. Similarly, Feder (1983) has also found a positive correlation between exports and growth in developing countries.
Foreign Direct Investment and Economic Growth
Since the primary focus of this study is on economic growth as a function of external economic factors, another variable often cited in literature relevant to economic growth theory is Foreign Direct Investment. Here it serves as an alternative variable to the above considered export variable. Based on the series of studies compiled by Fabry and Zeghni (2001) and other analyses, it is reasonable to expect that FDI should have a positive effect on the growth of an economy. Such may be the case for several reasons.
Firstly, FDI is generally associated with transfer of technologies and know-how to the recipient country. In such way, Fabry (2001) argues, FDI upgrades the recipient country’s economy by creating better allocative and productive efficiencies. Secondly, FDI brings fresh investments to the recipient’s economy and thus stimulates it through the aggregate expenditures multiplier effect.
Some, however, note that in the short run FDI can also have a detrimental economic effect. It pulls away qualified workers from public state owned enterprises to the private ones by offering them higher benefits than the government can (Mickiewicz, Rodasevic, and Varblane, 2001). Such process may cause high levels of structural unemployment. Yet, others argue that such short-term costs are far outweighed by the long-term benefits that FDI brings to the recipient country by enhancing the privatization of exactly such inefficient state owned enterprises (Cernat and Vranceanu, 2002). The rough numerical figures of economic development and FDI inflow’s in Central and Eastern European countries show that such countries as Hungary, Czech Republic and Poland, which attracted almost 60% of FDI in the whole region also developed the fastest. Bearing this possible correlation in mind combined with the information discussed above, it is thus reasonable to expect that there should be a positive relationship between FDI inflows and economic growth rates in East-Central European countries under analysis.
Democracy and Growth
However, the ability of the transition country to implement market reforms, to attract FDI and hence foster the country’s long-term economic growth may greatly depend on the domestic political factors. With particular relevance to the post-Communist experience, Hellman (1998), for example, argues that the main obstacles to the market economy reforms in the transition countries may stem from the early winners, dominant group of elites, who benefit from the market distortions of the transition and try to block further reform at high social cost. These, so called rent seekers, benefit from high tariff walls, export licensing, and artificial exchange rates as well as from state subsidies and regulation rather than profit in competitive markets. Therefore, Hellman (1998) suggests that robust political competition and diverse governing coalitions are essential to prevent the early winners from taking control of the state and sidetracking further reform. In similar words, Aslund (2001, p.5) notes:
The political goal of market reform is to impose the interests of the majority on the small rent-seeking elite, which amounts to a transition from dictatorship to democracy. Conversely, the main drama of the post-Communist transformation has been a struggle between radical market reformers and rent seekers, and the containment of rent seeking has been the chief reform task.
It is thus reasonable to expect that there should be a positive relationship between the higher degree of democracy and economic growth rates in Central and Eastern European countries under analysis. Those political systems which provide avenues for pro-reform coalitions and other groups to gain power, allow competition among the elites and interest groups, and hence are more likely to prevent particular industries or groups from “capturing the state” and in this way implement the needed economic reforms such as deregulation of exports, privatization of large state owned enterprises, and liberalization of prices should be more likely to attract FDI and foster their long-term economic growth.
Methodology
Based on the literature review, the following regression model will be estimated and the Ordinary Least Squares (OLS) and other correcting statistical tests will be run to determine the significance and direction of relationships among the variables of the study:
The data period will comprise the years from 1993 to 1999 and will include the following sample of 21 post-communist countries making the total number of cases (N) 147:
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Central Europe Poland Czech Republic Slovakia Hungary South-East Europe Romania Bulgaria Baltics Estonia Latvia Lithuania |
CIS Russia Belarus Ukraine Moldova Armenia Azerbaijan Georgia Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan |
Dependent Variable
GDPGROWTH will be measured as a percentage change of the real Gross Domestic Product in the countries under analysis. The data based on the report of the European Bank for Reconstruction and Development (2000) is obtained from Aslund (2002, p. 115).
Independent Variables
EXPORTS will be measured as the annual exports (in US dollars) from a given country divided by the real GDP of the respective country (in US dollars) for a given year. The ratio is then multiplied by one hundred in order to obtain percentage change figures from year to year. The data based on the United Nations Conference on Trade and Development World Investment Report (1999) and the European Commission (2000) report is obtained from Aslund (2002, p. 179).
LogFDI will be measured as a natural log of total Foreign Direct Investment in millions of dollars to countries under analysis. The data for this independent variable based on the figures published in the Transition Report of the European Bank for Reconstruction and Development (1999 and 2000) is obtained from Fabry and Zeghni (2001, p. 5).
DEMOCRACY is a measure of inclusiveness and accounts for a degree to which citizens in general and groups not represented in the legislature can freely voice their opinions about government policies. It also accounts for the degree to which the government powers are democratically determined by such factors as free and fair elections. The Freedom House Index will be used as a proxy for this variable. The index's score ranges from 1 to 6, with the lower score indicating a higher degree of civil liberties and democratic government and the higher score the lower degree of civil liberties and democratic government. The data for the countries under analysis for different years is available online at http://www. freedomhouse.org.
To control for unmeasured exogenous economic conditions, dummy variables for each year are included. Such inclusion is important because countries in the region were exposed to similar exogenous shocks from the international economy. However, to control for unmeasured factors specific to individual countries, such as institutional legacies and the composition of the economy the dummy variable for each country is also included. Including fixed-effect dummy variables reduces concerns for omitted variable bias and thereby gives greater confidence in the results.
Finally e accounts for an error term for variables that were not included in the model but can explain variance in the dependent variable. Examples of such variables are inflation, income per capita, unemployment, etc.
Expectations
As established by the literature review, the following results are expected:
1.
2.
3.
Finally, it is expected that the dummy variables will allow identifying specific country differences with regards to their economic development over the years under analysis.
Statistical Implications of the Model
The Ordinary Least Squares (OLS) test will be used to regress the dependent variable GDPGROWTH against the independent variables operationalized above. The following items will be reported: the coefficients (including the observations if they have expected signs or not), t-ratios and p-values, which will allow to determine whether the obtained relationships between the dependent and independent variables are statistical significant at different confidence levels. In addition, a goodness of fit measure (R squared) will show how much variation in the dependent variable is explained by the variation in the independent variables. The closer R squared to 1, the more explanatory are independent variables of the dependent variable.
In addition, since the study deals with a time series cross sectional data it is expected that the problems of both heteroskedasticity and autocorrelation may be encountered. The former may be the case due to the fact that the variances of the error terms for different countries under analysis may differ. To correct for heteroskedasticity the White test will be used along with the appropriate command (hetcov) in the statistical software to correct for it (Hill, Griffiths, and Judge, 2001). The latter may be the case due to the fact that some variables in the data set such as exports and FDI may have overlapping values. To correct for autocorrelation the Durbin-Watson test will be used and the obtained value will be compared to the theoretical DW value accounted for the degrees of freedom. If the obtained DW value is lower than DW theoretical, then the model indicates that there is an autocorrelation problem and in such case appropriate methods will be used in the statistical software to try to correct for it.
Finally, to test if the independent variables are collinear, the tolerance coefficient will be reported whose value ranges from 0 to 1 and reflects the proportion of the variance not accounted for by other variables in the regression equation. The closer the coefficient is to 1, the less the collinearity among the independent variables. Finally the Ramsey RESET test will be used to evaluate if the regression equation is complete or unspecified and if there can be additional independent variables included to better explain the variance in the dependent variable (Hill, Grifiths, and Judge, 2001).
Results
The OLS regression results reported in Table 1 show that both Exports and LnFDI have positive coefficients as expected from the earlier developed theory. Moreover, the coefficient for LnFDI is statistically significant at 5% confidence level. Democracy variable, however, also exhibited a positive statistically significant sign at 10% confidence level but contrary to the earlier defined expectations. Adjusted R squared score indicated that the specified regression model explains 42.6% of the overall variability in the dependent variable GDPGROWTH.
A Goodness of Fit test indicates that at all reasonable levels of significance we can reject the null hypothesis that all Betas are equal to zero. Therefore, we can conclude that the model does have significant explanatory power. Analysis of the sample correlation coefficients between the pairs of two independent variables indicates that the model does not have a significant multicollinearity problem. All coefficients are much lower than the rule of thumb value of 0.8.
Table 1
Coefficient estimates for the GDP growth in Central and Eastern Europe from 1993 to 1999, dependent variable GDPGROWTH, OLS
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Variable Beta coefficient (t ratio) (se)
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Exports 0.0146 (0.979) (0.0149)
LogFDI 1.726** (2.089) (0.8264)
Democracy 1.359* (1.378) (0.9859)
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Dummy variable Beta coefficient (Russia – base country) (se) (1993 – base year) |
Dummy variable Beta coefficient (Russia – base country) (se) (1993 – base year)
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Poland 12.57*** (3.898)
Czech Republic 9.086** (4.049)
Slovakia 13.82*** (4.067)
Hungary 10.06*** (4.049)
Romania 7.554** (3.589)
Bulgaria 8.98** (4.089)
Estonia 11.433*** (4.106)
Latvia 10.11*** (4.067)
Lithuania 10.32** (4.567)
Turkmenistan -0.047 (5.690)
Uzbekistan 5.22 (5.784)
2 -0.27 (1.988)
2 5.73*** (2.134) |
Belarus 6.95* (5.067)
Ukraine -1.72 (3.667)
Moldova 3.90 (4.804)
Armenia 14.19*** (5.093)
Azerbaijan -0.04 (4.675)
Georgia 9.83** (5.030)
Kazakhstan -2.16 (4.400)
Kyrgyzstan 6.64* (4.790)
Tajikistan 2.34 (6.24)
2 7.98*** (2.250)
2 9.38*** (2.547)
2 8.59*** (2.697)
2 8.80*** (2.533)
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R squared 0.5399
R squared adjusted 0.4259
N 147
Variance of the estimate sigma**2 39.610
Standard error of the estimate sigma 6.2936
Corr (LogFDI, Exports)=-0.20479; Corr (Democracy, Exports)=0.12635;
Corr (Democracy, LogFDI)= -0.43175;
Durbin-Watson 1.4089
Statistical significance is noted as follows: *p<=.10; **p<=.05; ***p<=.01;
However, there is strong evidence for the first-order negative autocorrelation, meaning that if the error term for one observation is positive it is likely that the error term for the next observation will be negative This can be seen from the visual inspection of the residual plots, which indicate that sequential residuals change sign too frequently. The observation is also confirmed by the Durbin-Watson test. The observed DW value is lower than the lower critical value (1.4089<dl 1.443). Hence we can reject the null hypothesis that there is no first-order correlation. Such finding is not surprising bearing in mind the structure of the time-series cross-section data set under analysis. The values of the independent variables are entered year after year for each country, thus it is not surprising that the error terms for adjacent observations are correlated.
In addition, the test for heteroskedasticity indicates that the model has this problem as well. The Chi-square test statistic appears to be higher than the critical value for the Chi-square distribution with 1 degree of freedom at all reasonable levels of significance. Therefore we can reject the null hypothesis that the variance of the error term is not a function of the predicted value of the dependent variable. Again it is quite logical that the variance of the error term is not constant given the data set under analysis. It includes a sample of some similar but also very different countries whose dependent and independent variables vary significantly across time.
Given the above statistical problems, in order to make the OLS estimators of the coefficients of the independent variables more efficient the same model is run adjusted for autocorrelation (Table 2). The coefficient for the Exports variable, although not statistically significant, does have the expected positive sign. It indicates that for a 1% increase in exports the real GDP is likely to increase slightly by 0.01 percent. The coefficient for the LnFDI variable also has positive expected sign and is statistically significant. It indicates that for a 1 million (in U.S. dollars) increase in FDI the real GDP of the recipient CEE country increases by 2.22%. In contrast to the expectations developed in the literature review, the sign of the coefficient for the Democracy variable is positive as well. It indicates that for a 1-point increase in the political freedoms score (the higher the score the less political freedom in the country), the real GDP increases by 1.6%. Adjusted R squared score indicates that the regression model explains 48.4% of the overall variability in the dependent variable.
Table 2
Coefficient estimates for the GDP growth in Central and Eastern Europe from 1993 to 1999, dependent variable GDPGROWTH, OLS
Adjusted for Autocorrelation
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Variable Beta coefficient (t ratio) (se)
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Exports 0.0103 (0.8069) (0.0128)
LogFDI 2.220*** (2.681) (0.8208)
Democracy 1.6026* (1.459) (0.1.099)
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|
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Dummy variable Beta coefficient (Russia – base country) (se) (1993 – base year) |
Dummy variable Beta coefficient (Russia – base country) (se) (1993 – base year)
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Poland 11.34** (5.030)
Czech Republic 9.37** (4.049)
Slovakia 14.43** (5.195)
Hungary 9.36** (5.218)
Romania 7.04* (4.644)
Bulgaria 11.47** (5.127)
Estonia 12.15*** (5.150)
Latvia 10.67** (5.024)
Lithuania 9.95** (5.346) Turkmenistan 0.31 (6.652)
Uzbekistan 3.78 (6.615)
1994 -0.41 (1.653)
1995 5.27*** (2.044) |
Belarus 7.09 (5.672)
Ukraine -1.91 (4.715)
Moldova 5.69 (5.541)
Armenia 5.78*** (5.881)
Azerbaijan 0.86 (5.564)
Georgia 9.06** (5.891)
Kazakhstan -2.50 (5.441)
Kyrgyzstan 7.17* (5.738)
Tajikistan 3.36 (7.039) 1996 7.35*** (2.232)
1997 8.48*** (2.540)
1998 7.56*** (2.626)
1999 8.03*** (2.297)
|
R squared 0.5862
R squared adjusted 0.4836
N 147
Variance of the estimate sigma**2 35.628
Standard error of the estimate sigma 5.9689
Statistical significance is noted as follows: *p<=.10; **p<=.05; ***p<=.01;
________________________________________________________________________
In addition, most of the individual country and year dummy variables appear to be statistically significant. A clear pattern shows that the real GDP grew much faster in the countries under analysis in the period from 1995 to 1999 than in 1993 the base year. Coefficients of the country dummy variables indicate two groups of countries whose GDP growth patterns differ significantly. As mentioned in the literature review, a group of East-Central European countries who primarily oriented their economies to the West after the break up of the Soviet Union enjoyed much greater economic growth as compared to Russia and the rest of the CIS countries whose economies were still significantly dependent on their big neighbor in the period under analysis. A partial F-test shows that the growth in real GDP for all countries as a group does differ from that of Russia’s at 5% significance level (F*=1.91>F table=1.90).
Conclusion
Although the regression results do not indicate a statistically significant relationship between exports and real GDP growth rates in Central and Eastern European countries under analysis the positive sign of the coefficient may indicate that some positive relationship between the two is likely. Those countries that liberalized their trading regime and especially wanted their goods to be marketable abroad had to invest in new technologies and improve their product quality. Efficiency gains from such process may have had positive spillover effect on their domestic economies. Another positive link between the two may be deduced from looking at the indicators of the individual country dummy variables. Clearly, a group of East-Central European countries such as Poland, Czech Republic and Slovakia enjoyed much greater economic growth than Russia and the CIS countries because they linked their economies to the Western markets and reaped significant benefits from the liberalized trading regime, especially useful for their export industries, with the countries of the European Union.
As expected from the literature review, a statistically significant positive relationship was found between the inflows of FDI into the CEE countries and their real GDP growth rates. These investments promoted industrialization and capital development in the recipient countries and enhanced the development of the private sector. Import of new technologies and innovative ideas also gave a significant positive boost to their economies.
Democracy coefficient sign, however, was opposite from the one expected by the developed theory. On the one hand, such findings may appear to support a null hypothesis that less democratic countries develop faster. Some scholars, for example, argue that in developing countries, an authoritarian regime can more effectively initiate important policy reforms than a democratic regime because of perceived weaknesses inherent in many democratic institutions. For instance, Nelson (1990) when explaining specific policy reforms in the newly industrialized countries (NIC’s) argues that without autonomy or insulation from the demands of particular social groups, the pursuit of policy reforms would be impossible. This is because effectively organized dominant social groups can form daunting barriers to economic reform and hence indicate a weakness in the democratic regime’s ability to implement substantial economic reform.
This particularly may true for international trade policies since, at least in the short run, they usually hurt some groups while benefit others through the redistribution of income in different sectors of the economy and labor adjustment costs (Krugman and Obstfeld, 2000). As Krugman and Obstfeld (2000) further note, it is the losers who are usually more organized and hence can preclude the subsequent rounds of trade liberalization. Thus, in order to overcome resistance from groups losing from reform in the short run, such as farmers and state-sector employees, some argue that governments need to concentrate power in executives who are ideologically committed to reform, backed by international financial organizations, and insulated from popular pressure (Nelson, 1990).
On the other hand, such limitation of political freedoms hypothesis can be hardly applied to the pos-communist transitions. Looking at the Table 2 results again, they clearly show that the pro-Western transition countries, especially the prospective members of the European Union, enjoyed the greatest amount of economic success. The unexpected positive sign of the Democracy variable may have been affected by the outliers resulting from the inclusion of country dummies for some specific CIS countries. For example, Table 2 shows that the real GDP growth rates for Armenia, Azerbaijan, and Kyrgyz Republic were significantly larger than Russia’s even though their political freedom scores are very low, much lower than of the aforementioned pro-Western group of countries. They were able to achieve such success not because they effectively used the power of their centralized governments as the null hypothesis discussed above suggests, but due to the vast endowment of natural resources. These particular countries are particularly rich in oil resources, thus their effective use may have enabled them to grow quite significantly at the expense of the market reforms, which may be beneficial in the long-run.
Therefore, in order to obtain the most efficient value of the coefficient for the Democracy variable it may be beneficial to exclude country dummy variables, which may contain the result distorting outliers. Indeed, the OLS regression of the restricted model, without the country dummies, indicates the negative statistically significant coefficient for the Democracy variable as expected from the literature review. It indicates that for a 1 unit increase in the political freedoms score (the higher the score the lower the level of political freedoms in the country) real GDP declines by 0.54%.
Bearing the above discussion in mind, the most appropriate prescription for economic success for the countries in transition would contain several factors. On the political front, the countries should make their political systems more transparent and democratic and in this way allow for participation of groups in the debate for the most appropriate government policies. Such strategy may successfully contain the rent seekers who often times benefit from the transition process at the high social cost to society. The more democratic countries will also be more likely to attract Foreign Direct Investment, which as the evidence above shows would have a significant positive effect on their economies. On the international economic front, they should liberalize their trading regime and actively participate in the exchange of goods and services in the international markets and reap the advantages from the efficiency gains at home.
Bibliography
Aslund, Anders. 2002. Building Capitalism: the Transformation of the former Soviet Bloc. Cambridge, New York: Cambridge University Press.
Aslund, Anders. 2001. “Building Capitalism: Lessons of the Postcommunist Experience.” Carnegie Endowment for International Peace Policy Brief. Available at http://www.ceip.org
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Fabry, Nathalie. 2001. “The Role of Inward-FDI in the Transition Countries of Europe: An Analytical Framework.” Chapter 1 in Fabry, Nathalie and Sylvain Zeghni. 2001. Transition in Asia and Eastern and Central Europe: A Closed Door Two Open Windows? Nova Science Publishers, Inc. Huntington, NY.
Feder, Gershon. 1983. “On Exports and Economic Growth.” Journal of Development Economics, 12: 59-73.
Fischer, Stanley, Ratna Sahay, and Carlos A. Vegh. 1996. “Stabilization and Growth in Transition Economies: The Early Experience”. Journal of Economic Perspectives 10 (2):45-66.
Frankel, Jeffrey and David Romer. 1999. “Does Trade Cause Growth?” American Economic Review, 89 (3) 379-399.
Frye, Timothy. 2002. “The Perils of Polarization: Economic Performance in the Postcommunist World.” World Politics, 54: 308-337.
Hellman, Joel. 1998. “Winners Take All: The Politics of Partial Reform in Postcommunist Transitions.” World Politics, 50 (2) 203-234.
Kennedy, Ryan. 2002. “The State as Trade Barrier: Fragments of Economic Accountability and Trade Policy.” Paper presented at the annual International Studies Association-Midwest conference in St. Louis, MO. Obtained by the co-participant of the conference Justinas Juknys.
Kramer, Mark. 1999. “The Changing Economic Complexion of Eastern Europe and Russia: Results and Lessons of the 1990s.” SAIS Review, 19.2: 16-45.
Krugman, Paul and Maurice Obstfeld. 2000. International Economics: Theory and Policy. Boston: Addison-Wesley Publishing.
Mickiewicz, Tomasz, Slado Radosevic, and Urmas Varblane. “FDI in Central Europe: Short-Run Effects in Manufacturing.” Chapter 2 in Fabry, Nathalie and Sylvain Zeghni. 2001. Transition in Asia and Eastern and Central Europe: A Closed Door Two Open Windows? Nova Science Publishers, Inc. Huntington, NY.
Nelson, Joan. 1990. “Introduction: The Politics of Economic Adjustment in Developing Countries,” in Joan Nelson, ed., Economic Crisis and Policy Choice: The Politics of Adjustment in the Third World. Princeton: Princeton University Press.
Sachs, Jeffrey and Andrew Warner. 1995. “Economic Reform and the Process of Global Integration.” Brookings Papers on Economic Activity, 1: 1-95.
Yaghmaian, B. 1994. “An Empirical Investigation of Exports, Development and Growth in Developing Countries: Challenging the Neo-Classical Theory of Export-led Growth.” World Development, 22:1977-95.
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i
EXPORTS
β
β
i
GDPGROWTH
+
å
+
å
+
+
+
+
=
)
5
5
(
)
4
4
(
3
3
2
2
1
1
0