Since 1990, as part of its transition from central planning to a market economy, Hungary implemented a comprehensive liberalization of its economic system. This liberalization was achieved by correcting relative prices through subsidy cuts, reducing trade distortions, freeing most food prices, hardening enterprise budget constraints, approving new bankruptcy and banking laws, and privatizing state enterprises. As elsewhere in the region, these reforms were accompanied in the early 1990s by a sharp drop in output and a surge in inflation. Although the transition toward a market economy is ongoing, the decline in output has been halted, and a recovery has begun. This chapter describes the main influences on the evolution of output in Hungary since 1990, and examines Hungary’s future growth prospects with specific focus on the role that structural and macroeconomic policies can play in enhancing those prospects.
Growth During 1990–96
Following more than two decades of gradual reform, Hungary stepped up the pace of transition in 1990. Output began to decline that year, before falling sharply in 1991. The pace of decline moderated in 1992 and 1993—the year when output reached its lowest level. Between 1989 and 1993, GDP declined by a cumulative 18 ½ percent. Consistent with typical cyclical behavior during downturns, the bulk of this decline was due to a sharp drop in fixed investment (Figure 6.1). In 1993, the output decline reflected a marked deterioration in the external accounts as exports collapsed while import growth remained robust.
Contributions to Growth
(In percent)
Source: International Monetary Fund, World Economic Outlook, 1997.Thereafter, positive—though modest—output growth was restored, initially on the strength of investment and, following the implementation of the 1995 austerity program, on the contribution of the external sector, which more than offset a steep decline in private consumption. Activity subsequently accelerated sharply: GDP growth in 1997 is estimated at 4 percent, fueled by a combination of strong investment and continued expansion in the external sector.
This output growth pattern can be contrasted with those in other countries in the region. Annual GDP indices for Hungary, Poland, the Czech Republic, the Slovak Republic, and Slovenia in “stabilization time” (i.e., with the year in which stabilization was initiated in each country denoted as 0) are depicted in Figure 6.2. For Hungary, year 0 is 1990, when broad-based price liberalization (including the freeing of food prices and adjustments in energy prices) took place, financial policies were significantly tightened, and decisive structural reform efforts began.1 The figure reveals that, in each of the advanced transition countries, output declined steeply in the first and second year following the initiation of reform, but the process of recovery three years out was well established for most of the countries in the chart. By contrast, Hungary endured four consecutive years of negative output growth during the transition. Moreover, the pace of recovery was also slower in Hungary. Specifically, by 1996, GDP had increased between 12 percent and 24 percent from its minimum level for the other countries in the chart, while in Hungary, output had recovered by only 6 percent.2 To sum up, Hungary’s depression since 1990 was longer and its subsequent recovery flatter than in other advanced transition economies.
Real Output in Advanced Transition Countries
(Index;Year-l = I00)
Source: International Monetary Fund, World Economic Outlook, 1997.Two factors may explain this performance: The postponement of macroeconomic stabilization to the mid-1990s and the slowing of structural reform during 1993 to mid-1995. The postponement of macroeconomic stabilization is apparent from a few indicators. As shown in Figure 6.3, Hungary’s progress in reducing inflation has been relatively modest compared with other countries.3 Hungary’s current account deficit stood above 9 percent of GDP in 1993–94, compared to a surplus of 1 percent of GDP in 1990–92. Likewise, the deficit of the consolidated government stood above 7 percent of GDP in 1992–94, compared to a surplus of 1 percent of GDP in 1990 and a deficit of 3¼ percent of GDP in 1991.
Inflation in Advanced Transition Countries
Source: International Monetary Fund, World Economic Outlook, 1997.To what extent did the delay in macroeconomic stabilization hamper growth performance? A tentative answer to this question may be found in the empirical literature linking growth to inflation and fiscal performance. A number of empirical studies conclude that growth is adversely affected by inflation. Bruno and Easterly (1995) find that this negative relationship is apparent when inflation exceeds 40 percent. However, Sarel (1996) argues that growth is adversely affected by inflation rates as low as the high single digits, with a doubling of inflation from such levels lowering growth by almost 2 percentage points. Evidence presented in Box 6.1, based on a panel data set covering 25 eastern European countries, the Baltic countries, and the Commonwealth of Independent States, also suggests that both inflation and the size of government are statistically and economically significant determinants of growth performance. This evidence, in conjunction with the studies mentioned above, would suggest that Hungary’s failure to achieve a sizable and sustained reduction in inflation since 1990 significantly impeded its growth performance. If one takes the average inflation rate of the advanced central and eastern European countries in 1996 and Sarel’s estimates (which are based on a much broader sample than those in Box 6.1) as a base case, slow progress with inflation stabilization could have reduced Hungary’s growth rate by nearly 2 percentage points.4
As to the effect of fiscal imbalances on growth, according to Fischer and others (1996b), transition countries that imposed more restrictive financial policies, in the form of a pegged exchange rate and a tight fiscal stance, grew faster during 1992–95. Using their estimates, the relative deterioration in Hungary’s fiscal position could explain about ¾ percentage point of the growth shortfall relative to the other advanced transition countries in 1996.
In addition to the slow progress on the macroeconomic front, Hungary’s growth performance may also have been affected by a slowing of structural reform from 1993 to mid-1995. By 1993, Hungary had already made significant progress in establishing a market-based economy, and was assessed by the European Bank for Reconstruction and Development (EBRD) to be among the most advanced of the transition countries in this area.5 Among the notable achievements were that more than 90 percent of prices, weighted by their share in the consumption basket, had been freed of administrative controls; licensing and quota restrictions on trade had been virtually eliminated; small-scale privatization was almost complete; and the private sector already accounted for 50 percent of the economy. However, Hungary’s reform process slowed markedly from 1993 to mid-1995, when little headway was made in ensuring the long-term viability of the social security system, restructuring the financial system, or privatization. Moreover, despite efforts at fiscal retrenchment, the size of the public sector did not decline between 1990 and 1995, with the share of consolidated government expenditure remaining at about 50 percent of GDP in 1995.6 A consequence of the still-large size of the government sector is the high level of distortionary taxes required to finance it. In particular, the tax wedge on labor income created by contributions to social security remains among the highest in the world, with negative implications for labor market participation and output growth.
The importance of maintaining the momentum of structural reform is borne out by several studies. Sachs (1996) finds that, for a group of 25 countries from eastern Europe, the Baltic countries, and the Commonwealth of Independent States, reform (measured in terms of broad-based indices of liberalization) is positively correlated with GDP growth during 1989–95 and, therefore, that greater progress in the structural area leads to a smaller cumulative output loss and/or a faster recovery in activity.7 In addition, de Melo and others (1996) find that more than one-half the variation in growth across transition countries is related to differences in economic liberalization, with the latter’s importance depending on both the duration as well as the intensity of reform. Based on the index and econometric results presented in de Melo and others (1996), Hungary’s annual growth rate would have been ¼ percentage point higher had it achieved the same degree of liberalization as the Czech Republic in 1993 and in 1994.8
Third, Hungary’s growth performance may also be related to specific elements in the design of its reform program. A case in point relates to the establishment of the Bankruptcy Law in January 1992, which, by automatically activating bankruptcy or liquidation procedures in cases where obligations were overdue by as little as 90 days,9 forced into bankruptcy a number of economically viable firms affected solely by temporary liquidity problems.10 Moreover, for those firms impacted by the law, bankruptcy proceedings were excessively protracted, with resolutions requiring two years on average. About one-third of Hungary’s industrial enterprises are estimated to have been affected by the law in 1992–93, with particularly adverse effects on output in the export sector. This is not to say, however, that Hungary’s output performance would have been stronger had the law not been in place. On the contrary, the law was a key instrument in reforming the supply-side of the economy. Had some elements of the law been designed more carefully, the resulting output loss would have been more contained.
Growth in the Medium Term
This section employs an aggregate production function approach to assess the implications for Hungary’s medium-term growth rate—over the next four years—of recent investments in physical and human capital and improvements in productive efficiency, given initial factor endowments and progress to date with structural reform. It argues that, while slow progress with stabilization and a loss of momentum in structural reform may have held down growth thus far, success in attracting foreign direct investment, together with human capital improvements, augur rather well for Hungary’s future growth prospects, as long as policy shortcomings, such as the still high inflation rate, are rectified.
Physical Capital
As in other transition economies, Hungary’s stock of physical capital at the beginning of transition was built up from a series of investments guided by motives other than profit maximization. Since these investments were largely irreversible, the stock of “effective” capital under market conditions was less than the initial stock of capital. An estimate of the effective size of the capital stock—and hence of the degree of inefficiency of past investment—can be made by determining the amount of capital required to generate Hungary’s current level of output under market conditions, controlling for other factors including human capital and labor endowments.11 Assuming that misallocated investments cannot be diverted to productive uses, Borensztein and Montiel (1991) find that three-fourths of Hungary’s investment under central planning (equal, on average, to 29 percent of GDP in 1960–85) was unproductive.
The initial size of Hungary’s capital stock affects its future growth prospects via the productivity of investment, with the low level of Hungary’s effective capital stock implying a relatively high marginal product. This suggests, paradoxically, that the prospects for growth from new investment are more favorable than if efficiency under planning had been greater, and that a relatively modest investment rate could sustain relatively high rates of growth. Indeed, assuming an investment rate of 22 percent of GDP—well below the average for 1960–85 and below the current rate of 25 percent of GDP—Borensztein and Montiel’s cross-country growth regressions suggest that Hungary could achieve growth rates of 5–6 percent in the future (assuming that human capital and population growth rates are the same as in 1960–85), similar to rates achieved at present by the other advanced transition economies. While such regressions are suggestive, it is nevertheless worth examining whether other approaches give similar results.
Growth Determinants for Transition Countries: Panel Estimates
An extensive body of theoretical and empirical literature exists on the sources of growth in developing and industrial economies. While this literature may also be relevant to countries undergoing the transition from planning to a market economy, other factors may also come into play during this process. Enterprise restructuring, price liberalization, and private sector expansion, while not unique to transition, occur at a more accelerated pace in transition countries than in other economies, with potentially important implications for economic activity.
This box presents econometric estimates of the effects of various macroeconomic and structural variables on growth using a pooled cross-section-time series data set for 10 eastern European countries and 15 countries of the Baltic countries and the Common-wealth of Independent States during 1993–96. Data availability prior to 1993 is scant for a number of countries, which dictated the relatively small number of observations per country.
The class of models used in the empirical estimations allows for the inclusion of a time-variant country-specific factor, in addition to time-varying variables that are common across countries, and is of the form:
where gi, t is the annual GDP growth rate for country i in yeart t, μi is the country-specific term, xi, t is the vector of explanatory variables, and ∊i, t is a mean-zero disturbance term possibly with a time and/or group dependent variance. The country-specific term is a composite of time-invariant idiosyncratic factors affecting a country’s growth rate.
The right-hand side variables to be considered below consist of policy variables, macroeconomic variables, and structural variables. The set of policy variables consists of the government balance as a share of GDP and year-average consumer price inflation. The macroeconomic variables include foreign direct investment, total and private investment, domestic credit, and the volume of trade, all as a share of GDP. The list of structural variables includes the share of the private sector in GDP and the ratio of government expenditure to GDP, as well as measures of progress with structural reform put together by the EBRD. These include indices of price liberalization, reform of the foreign exchange and trading systems, and enterprise restructuring.
Consistent with the findings elsewhere in the literature (as discussed earlier in this chapter), the results presented below confirm the importance for growth of: (1) a stable macroeconomic environment; and (2) progress with structural reform. The results of the preferred specification are given in equation (2) below, where t-statistics (in parentheses) are based on (White) heteroskedastic-consistent standard errors:
Adjusted R2 = 0.748
F[30, 44] = 8.31; P-value = 0.000
where govexp is the share of primary government expenditure in GDP; plib is the EBRD’s index of cumulative price liberalization; avfdi is the average of current and lagged FDI as a share of GDP; log(infl) is the natural log of the average of current and lagged inflation, with the superscripts H, M, L indicating, respectively, average inflation in excess of 40 percent, between 8 percent and 40 percent, and below 8 percent; and ** (*) indicates significance at the 1 (5) percent level.
Consistent with our theoretical priors, the results imply that an increase in both inflation and the size of government lowers growth, while an increase in FDI and progress with price liberalization both raise growth. Specifically, a 1 percentage point increase in the share of FDI in GDP raises growth by almost 1 percentage point, similar to the results of Borensztein and others (who found a coefficient of 0.8 based on a sample of nontransition countries). With respect to the cumulative price liberalization index, plib, which is an ordinal variable, only the sign of the coefficient rather than its magnitude, is of relevance. The coefficient on plib is positive and highly significant. Also, inflation is found to have a negative effect on growth. Moreover, the effect of inflation on growth is found to vary with the level of inflation: a doubling of inflation from a high level (say from 50 percent to 100 percent) lowers annual growth by 1.7 percent, while doubling inflation from (say) 15 percent to 30 percent reduces growth by 2.1 percent, and increasing inflation from (say) 3 percent to 6 percent lowers growth by 2.8 percent. However, caution must be used when interpreting this result since the decreasing effect of inflation on growth may reflect the large movements in inflation over the current sample, which are due to price liberalization. As a result, the coefficient on log(inflH) may be picking up some of the positive growth effects associated with price liberalization, which may be imperfectly measured in the plib variable used in the above specification.1 Finally, a 1 percentage point reduction in the share of government in the economy raises growth by more than 0.15 percentage point. Interestingly, the government balance was found to have no independent impact on growth, suggesting that the effects of the deficit operate through the other terms in the regression (inflation and government expenditure).
The likelihood ratio test and the F-test supports strongly the choice of a fixed-effects model over the alternative model without country dummies.2 The country-specific parameters capture the possible effects on growth of time-independent variables, including the level of income at the beginning of transition, the cumulative decline in output, the degree of corruption, as well as specific features in the design of a country’s transition process. Each of the country-specific coefficients (not reported above) is significant at the 5 percent level.
1 It is noteworthy that, in an alternative specification of the model, the first difference of plib was found to have a highly significant negative impact on growth; in that specification, moreover, the magnitude of the coefficients on log(inflH) and log(inflM) were reduced, and the coefficient on log(inflL) was no longer significant. 2 The probability value is less than 1 in 100,000.Foreign direct investment is frequently argued to be a good predictor of an economy’s future growth performance, especially given FDI’s role as a vehicle for the international transfer of new technologies and management practices, and the empirical evidence on the complementarities between FDI and human capital and between FDI and domestic investment (Borensztein and others, 1995).12 Hungary has indeed been a leader in the region in attracting a large volume of FDI, with cumulative FDI during 1991–96 of $12.4 billion, almost three times as much as the next largest recipient (Russia).13,14 The magnitude of FDI is even more apparent when scaled against the size of the economy, with the ratio of FDI to GDP averaging 5 percent during 1991–96, compared with an average of less than 1¼ percent in the other economies of the region.15
Cross-country evidence suggests an economically and statistically significant relationship between the FDI/GDP ratio and growth performance, with Borensztein and others (1995) finding that a 1 percentage point increase in the former raises growth by 0.85 percentage point.16 In addition, empirical estimates presented in Box 6.1 would suggest a slightly larger coefficient (about unity); that is, a 1 percentage point increase in the FDI ratio raises growth by about 1 percentage point. If one assumes (conservatively) that the ratio of FDI to GDP in Hungary stabilizes at 3 percent of GDP during 1997–99 as the privatization process winds down, Hungary’s average FDI ratio during the 1990s would amount to about 4 percent of GDP. Using either Borensztein’s regression results or those in Box 6.1, one would conclude that Hungary’s medium-term growth rate is likely to be boosted by about 3 percentage points (with respect to other countries) on account of the increase in FDI alone.
Labor
The demographic profile of Hungary’s population suggests that the size of the labor force will increase only marginally (0.3 percent a year) during 1997–2000. However, the effective labor supply will be boosted during this period by improvements in educational attainment. As shown in Table 6.1 below, secondary school enrollment increased markedly between 1970 and 1992, while enrollment in tertiary education also rose. The illiteracy rate also declined (albeit from a low level). Increased participation in formal education will serve to im-prove Hungary’s growth potential by raising the average skill level of workers, since the human capital of workers entering the labor force will exceed that of those they replace through retirement.
Enrollment and Illiteracy Rates
Statistical Yearbook of Hungary, 1995.
Figure for 1995.
Enrollment and Illiteracy Rates
| 1970 | 1980 | 1992 | |||
|---|---|---|---|---|---|
| Enrollment (percent of age group enrolled) | |||||
| Secondary school | 63 | 70 | 81 | ||
| Tertiary | 12.9 | — | 15.3 | ||
| (Percentage of population)1 | 0.8 | 0.9 | 1.82 | ||
| Illiteracy rate | |||||
| (percentage o f population age 15 and above) | 2 | 1 | — | ||
Statistical Yearbook of Hungary, 1995.
Figure for 1995.
Enrollment and Illiteracy Rates
| 1970 | 1980 | 1992 | |||
|---|---|---|---|---|---|
| Enrollment (percent of age group enrolled) | |||||
| Secondary school | 63 | 70 | 81 | ||
| Tertiary | 12.9 | — | 15.3 | ||
| (Percentage of population)1 | 0.8 | 0.9 | 1.82 | ||
| Illiteracy rate | |||||
| (percentage o f population age 15 and above) | 2 | 1 | — | ||
Statistical Yearbook of Hungary, 1995.
Figure for 1995.
Based on the regression results of Levine and Renelt (1992), the increase in the labor force and in secondary school enrollment from its 1980 rate should raise Hungary’s medium-term potential growth rate by about ¼ percentage point. This figure probably underestimates the effect of improved education on growth in the most recent period. For example, the number of students in secondary and tertiary schools increased by 8 percent and 54 percent, respectively, during 1993–95.
Factor Productivity
A major objective of reforms undertaken during the transition is to improve total factor productivity (TFP). Structural reform can affect TFP through two channels. First, existing resources may be reallocated to more productive uses. Policies that further this objective are those that create incentives for more efficient resource allocation (e.g., subsidy reductions, smaller government); facilitate resource mobility (e.g., greater efficiency in financial intermediation); and enhance competition in the domestic economy (e.g., elimination of trade barriers, and establishment of the commercial and legal institutions of a market economy). Second, TFP can be boosted by the upgrading of technologies. Greater openness to trade and investment provides a conduit for the international transfer of advanced production techniques and technical knowledge, thereby enabling transition countries to close the technology gap with industrial countries.
Evidence from developing countries suggests that improvements in TFP have been an important factor in sustaining economic growth. Between 1971 and 1993, increases in TFP accounted for nearly one-half (1½ percentage points) of per capita growth among developing countries. Among successfully adjusting developing countries that have sustained reform, TFP’s contribution to per capita growth increased to 2½ percentage points (International Monetary Fund, 1993). Individual country studies confirm the importance of reform for growth in total factor productivity. For example, in the case of Chile, Lefort and Solimano (1994) find that the contribution of TFP to output growth increased strongly in the period following the implementation of structural reforms, with the rate of growth of TFP rising from about ½ percent a year before reform to 1¼ percent thereafter.17 In the case of Korea, Lee (1996) finds that distortionary tax/tariff incentives reduce TFP growth. Fischer (1993) finds that tariff protection weighted by the volume of trade reduces the efficiency of resource allocation.
During the transition, Hungary undertook a substantial liberalization of its trading environment, reducing average tariffs and import surcharges rapidly during 1996 and 1997 (Chapter IX). Partly in response, the degree of openness (measured by the trade ratio) has increased from 38 percent of GDP in 1990 to 70 percent of GDP in 1996. Moreover, the orientation of trade has also shifted, with 65 percent of trade now taking place with European Union countries. Based on the econometric results of Fischer (1993), greater openness and reduced protection is likely to boost future TFP growth by ¼ percentage point.
Removing Obstacles to Growth
Output in Hungary expanded by a modest 1 percent in 1996, largely—as argued in the previous section on growth during 1990–96—owing to slow progress with macroeconomic stabilization. Nevertheless, as discussed above, several factors suggest that Hungary is now poised to see its growth rate pick up significantly, especially because of its superior performance in attracting FDI. This said, however, future prospects will continue to be circumscribed if progress is not made in durably reducing inflation toward single-digit levels.
To make concrete the benefits to medium-term growth prospects from lower inflation, the empirical results from the previous section may be brought to bear. In their medium-term macroeconomic forecast, authorities target a gradual decline in inflation to 8 percent by 2000. Based on empirical estimates reported above and this target, the planned disinflation could raise potential growth by Wi percentage points.18 The analysis in the previous three subsections suggested, meanwhile, that factor accumulation (FDI, effective labor) and improvements in TFP flowing from greater openness could boost Hungary’s growth rate by 3 percentage points. Therefore, decisive improvements on the stabilization front in line with authorities’ targets would be consistent with a medium-term sustainable growth rate of about 6 percent.
References
Blanchard, Olivier, 1996, “Theoretical Aspects of Transition,” American Economic Review, Vol. 86, No. 2, pp. 117–22.
Borensztein, Eduardo, Jose De Gregorio, and Jong-Wha Lee, 1995, “How Does Foreign Direct Investment Affect Economic Growth?” NBER Working Paper 5057 (Cambridge, Massachusetts: National Bureau of Economic Research).
Borensztein, Eduardo, and Peter Montiel, 1991, “Savings, Investment, and Growth in Eastern Europe,” IMF Working Paper No. 91/61 (Washington: International Monetary Fund).
Bruno, Michael, and William Easterly, 1995, “Inflation Crises and Long-Run Growth,” NBER Working Paper 5209 (Cambridge, Massachusetts: National Bureau of Economic Research).
de Melo, Martha, Cevdet Denizer, and Alan Gelb, 1996, “Patterns of Transition from Plan to Market,” World Bank Economic Review, Vol. 10, No. 3, pp. 379–424.
European Bank for Reconstruction and Development, 1995, “Transition Report” (London: EBRD).
European Bank for Reconstruction and Development, 1996, “Transition Report” (London: EBRD).
Fischer, Stanley, 1993, “Macroeconomic Factors in Growth,” Journal of Monetary Economics, Vol. 32, pp. 485–512.
Fischer, Stanley, Ratna Sahay, and Carlos Végh, 1996a, “Stabilization and Growth in Transition Economies: The Early Experience,” Journal of Economic Perspectives, Vol. 10 (Spring), pp. 45–66.
Fischer, Stanley, Ratna Sahay, and Carlos Végh, 1996b, “From Transition to Market: Evidence and Growth Prospects” (mimeo, International Monetary Fund).
Hernandez-Cata, Ernesto, 1997, “Liberalization and the Behavior of Output During the Transition from Plan to Market,” IMF Working Paper No. 97/53 (Washington: International Monetary Fund).
International Monetary Fund, 1993, World Economic Outlook (Washington: International Monetary Fund, October).
Lee, Jong-Wha, 1996, “Government Interventions and Productivity Growth,” Journal of Economic Growth, Vol. 1, No. 3 (September), pp. 391–414.
Lefort, Fernando, and Andres Solimano, 1994, “Economic Growth After Market-Based Reform in Latin America: The Cases of Chile and Mexico” (unpublished, World Bank).
Levine, Ross, and David Renelt, 1992, “A Sensitivity Analysis of Cross-Country Growth Regressions,” American Economic Review, Vol. 82, No. 4, pp. 942–63.
Sachs, Jeffrey, 1996, “The Transition at Mid-Decade,” American Economic Review, Vol. 86, No. 2, pp. 128–33.
Sarel, Michael, 1996, “Nonlinear Effects of Inflation on Economic Growth,” Staff Papers, International Monetary Fund, Vol. 43 (March), pp. 199–215.
Measured by the annual change in their index of liberalization, de Melo and others (1996) find that 1990 was indeed the year of most intense reform in Hungary. For the other economies, time 0 was as follows: Poland (1990); Czech Republic (1991); the Slovak Republic (1991); and Slovenia (1990).
Despite the less severe nature of Hungary’s recession, by 1996, its cumulative output loss was only slightly less than the average of the other advanced transition countries.
Of course, Hungary was spared high inflation at the outset of reform as a result of significant progress made with price liberalization over the previous two decades.
This estimate is calculated as the product of Sarel’s coefficient on the logarithm of inflation (—2.48) and the difference in the logarithm of inflation in Hungary in 1996 (24 percent) and the logarithm of average inflation in 1996 in Poland, the Czech Republic, the Slovak Republic, and Slovenia (11 percent). The estimated effect of inflation on growth presented in Box 6.1, which is based on a sample of transition economies, is similar to that found by Sarel.
De Melo and others (1996) confirm Hungary’s ranking as among the top reformers in 1993.
Total government spending in 1995 remained unchanged from its 1990-GDP share because subsidy reductions were offset by increases in spending on social security and debt servicing.
This is consistent with Hernandez-Cata (1997) who finds that, although the initial contraction of aggregate output is much steeper for a strong reformer than for a slow reformer, the subsequent recovery occurs earlier and is more rapid. On balance, he finds that the cumulative loss is lower for the strong reformer.
According to indices of liberalization from de Melo and others (1996), the Czech Republic was the most advanced reformer in 1993—94, with a weighted index of 90 in each year, whereas Hungary, Poland, the Slovak Republic, and Slovenia had a weighted average index of 0.84, 0.84, 0.83, and 0.82, respectively.
The automatic 90-day trigger was repealed at the end of 1992.
In addition, during this period, many large state-owned enterprises were able to evade the law either because of their close links to state banks, which continued to extend credit, or through special debt-resolution channels, which entailed a large element of debt forgiveness.
This methodology attributes all the inefficiency to capital investment and assumes that all existing capital is fully employed. Therefore, the resulting estimate may overstate the degree of wasteful investment.
Borensztein and others (1995) do not distinguish between privatization-related and other FDI.
Hungary’s position in attracting regional FDI flows reflects, inter alia, its relatively advanced stage of implementation of market reforms and price stabilization; its geographic proximity to major trading partners; the quality of its labor force; the size and income of its domestic market; and tax incentives to foreign investors. The importance of reform for attracting FDI is supported by a recent EBRD survey of investors (EBRD, 1995), which finds that countries that are comparatively advanced with reform and stabilization have attracted a relatively large share of regional FDI. Selowsky and Martin (1996) draw similar conclusions about the relationship between reform and FDI, based on the de Melo and others (1996) index of liberalization.
The quality of Hungary’s FDI, as measured by the per capita income level of the source country, was also relatively high, with Germany, the United States, and Austria contributing about 60 percent of total FDI during 1993–94.
Albania, Belarus, Croatia, Czech Republic, Estonia, Latvia, Lithuania, Macedonia, FYR, Moldova, Poland, Romania, Russia, the Slovak Republic, Slovenia, and Ukraine.
Estimates from Borensztein and others (1995) are based on time-averaged data over 10-year blocks. Given the lags that are likely to be present, it is sensible to assume that Hungary’s future prospects will be influenced not only by future FDI but also by the relatively high rates of FDI in the past. This is the underlying assumption in the exercise below.
Lefort and Solimano (1994) find that the most important factors in explaining the increase in TFP growth were greater external openness (measured by reductions in import protection) and the increase in financial deepening (proxied by the real level of interest-bearing deposits in the banking system).
Calculated on the basis of the average inflation rate during 1997–2000.
