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The authors would like to thank for their helpful comments Messrs. Flood, Chami, Flickenschild, Saadi-Sedik, Grigorian, Ding, Abiad, Gueorguiev, Klingen, Mody, and Szekely, and Mmes. Corbacho, Allard, Farhan, and Ohnsorge.
Transition economies are those that were initially organized on the basis of government ownership of the factors of production and central planning and changed their economic organization to market based systems. The sample in this paper includes economies in Central and Eastern Europe, the Baltics, Commonwealth of Independent States, and Mongolia. See Table 5 (Appendix I) for a detailed list of countries in each group.
See, for example, Aslund, Boone, and Johnson (1996); Berg and others (1999); Brunetti, Kisunko, and Weder (1997); Christoffersen and Doyle (1998); de Melo, Denizer, and Gelb (1996); Fischer, Sahay, and Végh (1996, 1998); Fischer and Sahay (2000); Havrylyshyn, Izvorski, and van Rooden (1998); Havrylyshyn and van Rooden (2000); Hernández-Catá (1996); Loungani and Sheets (1997); and Wolf (1997).
For example, Fischer and Sahay (2004), who focus on the role of institutional reforms in development, mention in passing that fiscal adjustment is associated with higher growth. Their growth regressions show a substantial and statistically significant positive coefficient for the fiscal adjustment variable.
These studies show that improving fiscal positions through the rationalization of the government wage bill and public transfers rather than increasing revenues and cutting public investment can foster higher growth even in the short term. See for example, McDermott and Wescott (1996); Alesina and Perotti (1996); Alesina, Perotti, and Tavares (1998); Alesina and Ardagna (1998); Buti and Sapir (1998); Alesina and others (1999); and von Hagen and Strauch (2001).
Hausmann, Pritchet, and Rodrik (2005) use the term “growth accelerations” to describe episodes where the per capita growth rate increases by more than 2 percentage points a year and is sustained for at least eight years. By looking at jumps in country medium-term trends they expect to gain insight into the sources of successful growth transitions. While the paper does not follow this exact definition of growth acceleration and methodology, the concept of acceleration being used is consistent with a definition of this type.
See Patillo, Gupta, and Carey (2005) for evidence on the importance of the composition of fiscal spending on growth in low-income countries.
Hsiao and Sun (2000, p.181) note that the decision to pool or not to pool the data depends on whether, yit, the ith individual observation of the dependent variable at time t, conditional on x, the independent variable(s) of interest, can be viewed as a random draw from a common population. This is the so-called exchangeability criterion. It implies that the individual and time subscript, it, is simply a labeling device. Observations on the dependent variable should be exchangeable so that, a priori, E(yit│x) =E(yjs│x). In other words, the expected probability of observing yit or yjs, conditional on x, the independent variable(s) of interest, should be the same. If this condition is satisfied, by pooling the data we can obtain more robust and precise parameter estimates. However, if individual outcomes are more appropriately viewed as stemming from a heterogeneous population, then the subscript it contains important information that can be used to determine the specific heterogeneous population from which the particular observation is generated.
The data are from the World Economic Outlook database of the International Monetary Fund.
In addition, the importance of the short-term effects ∆Xi,t-1 depends on the size of βk and on how long the effects of changes in Xi,t-1 persist through time. A change in Xi,t-1 produces an immediate (contemporary) change in Yi,t that is measured by βk. If at time t there is a change in Xi,t in the opposite direction to the change in Xi,t-1, then there are no more effects. But if the change in Xi,t-1 is sustained, then the impact will continue in subsequent periods and can be measured by ∆Xi,t-1.(1+ϕ)t, where t is the number of periods after the initial change. Thus, for example, three years after the initial change ∆Xi,t-1, the effect will be ∆Xi,t (1+ϕ)3. Since 0<ϕ< -1, the smaller the value of ϕ, the longer the sustained changes in X will persist through time.
Not all empirical studies include this variable. Its inclusion or not in the model, as discussed below in Section IV, does not affect the main results.
To be sure, countries began the transition in different years. This paper follows the transition dating convention in Havrylyshyn and others (1999). Most countries are considered to have started transition in 1992. The exceptions are Bulgaria, the Czech Republic, Hungary, Poland, Romania, and the Slovak Republic, which started the process in 1990, and Albania, which started transitioning in 1991.
Note that at this stage, only correlations between the two variables are analyzed. There is no discussion on issues related to causality.
The Eastern European countries are Macedonia, Albania, Bulgaria, and Romania. Romania had a low overall balance at the beginning of the sample period.
It is not entirely obvious why the “level” variable of the fiscal deficit in the model without inflation is not statistically significant. Since the variable turns statistically significant in the model with inflation, and inflation turns out to be statistically significant in all models across the board, there is a strong likelihood that Model 9 is misspecified.
The discussion focuses on Models 5 and 6, which are robust to the presence of outliers.
Note that by long-term growth, we simply refer to growth over the life of the model.
The experience of two countries (Mongolia and Belarus) is somewhat puzzling because at first sight they do not fit the strong positive association between fiscal adjustment and growth presented in Table 2 and discussed in this section. Belarus seems to have experienced fast acceleration of economic growth even though structural reforms have been limited and fiscal adjustment low. However, this result is driven by other important exogenous factors that helped boost growth in Belarus: the continuing sale by Russia of subsidized oil inputs, a geographically advantageous position for energy transportation, and favorable oil price developments. Mongolia, unlike Belarus, seems to have undergone significant fiscal adjustment but no acceleration in economic growth. Cheng (2003) suggests that favorable initial conditions may have contributed to the milder initial recession. However, the composition of fiscal adjustment in Mongolia may explain why fiscal adjustment was not associated with higher growth: most of the fiscal adjustment in Mongolia was revenue-based while the level of expenditures was kept relatively high. This suggests that the public sector may not have been sufficiently reformed and may have crowded out private sector activity.
The CMEA was composed of Bulgaria, Cuba, Czechoslovakia, former German Democratic Republic, Hungary, Mongolia, Poland, Romania, the former Soviet Union countries, and Vietnam.
While foreign direct investment averaged below 2 percent of GDP per year at the beginning of transition, by 1999 these flows reached about 4 percent of GDP per year.
Anecdotal evidence of unrecorded foreign remittances abound. For Armenia, unrecorded private remittances are thought to be in the form of “pocket money” from Armenians working in Russia. See Gelbard and others (2005) for more details.
The CIS-7 are Armenia, Azerbaijan, Georgia, the Kyrgyz Republic, Moldova, Tajikistan, and Uzbekistan.
Data limitations (consistency, validity, and reliability) did not allow us to probe deeper in this area.
The coefficient of variation is a measure of dispersion of a probability distribution. It is defined as the ratio of the standard deviation to the mean and allows comparison of the variation of populations that have significantly different mean values. Similar results were obtained, however, using just the standard deviation.