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This paper was presented at the Fund-Bank conference on the Macroeconomic Situation in Eastern Europe, June 4-5, 1992. The authors would like to thank E. Maciejewski, L. Mendonca, L. Nagle, T. van der Willigen, N. E. Weerasinghe, and E. Zervoudakis, for their assistance, and John Huizinga, Malcolm Knight, Carmen Reinhart, Alan Stockman, Rachel van Elkan, Peter Wickham, and the participants in the Fund-Bank conference for helpful comments and discussions.
Eastern Europe is defined here to include, in addition to the BCR countries, Poland and Hungary.
These figures are based on official statistics which may not fully take into account the growth in private sector activity (Berg and Sachs (1991)). Proper measurement of the private sector would not, however, reverse the tendency exhibited by the official numbers, given the relatively small initial shares of private activity in GDP in these countries. For a somewhat different explanation of why official statistics may overstate the extent of the output decline, see Osband (1991).
As pointed out earlier, in the short run the sectors where relative profitability increased might find it difficult to expand, owing to difficulties in attracting resources. During this period, all sectors might be contracting, though they should be contracting at very different rates if structural change is really taking place.
For all three countries in the sample, the output decline was concentrated in the industrial sector, and we use disaggregated data on output, prices, etc., from this sector to estimate the model. The necessary data were available for Czechoslovakia and Romania on a monthly basis, while the data available for Bulgaria permitted only a more qualitative assessment.
The unified exchange rate obtained in the first daily interbank auction on February 19 was leva 28.25 per U.S. dollar, compared with leva 7 per U.S. dollar used in most trade transactions up to then. The leva appreciated thereafter, fluctuating in the range of leva 16-19 per U.S. dollar for most of the year. Near the end of the year the amplitude of the fluctuations increased, and the rate was leva 21.81 per U.S. dollar at end-December 1991.
These estimates are based on seasonally adjusted data. Actual unadjusted indicators exaggerate the decline in the first half (and, similarly, the recovery in the second half).
Data for the year as a whole are not yet available.
This section draws heavily on Aghevli, Borensztein and van der Willigen (1992). Other useful references include Begg (1991), Dyba and Svejnar (1991), European Economy (1991), and Prust and IMF Staff Team (1990).
The data on exports correspond to information on deliveries (“dodavky”) for exports provided by enterprises and not to exports as recorded in customs or balance of payments data. The data appear to be roughly consistent with the national income accounts, which show a decline in exports of about 5 percent in volume terms in 1991. Data on the volume of exports from the balance of payments show much larger declines.
Romania’s recent economic history, as well as the economic reform program after 1989 are discussed in detail in Demekas and Khan (1991).
In this calculation, trade in transferable rubles has been converted into dollars at the commercial cross exchange rate with the Romanian leu.
The official rate of the leu had already been devalued twice in 1990 by a cumulative 50 percent.
Although Romania imported little of its oil from the CMEA area during the 1980s, it was dependent on the USSR for almost all of its natural gas imports and most of its electricity imports. Total primary energy imports, in tons of oil equivalent, fell by 15 percent in 1990 and an additional estimated 41 percent in 1991.
Data on employment are available on a less disaggregated basis than those on output.
The “CMEA shock” contains both structural and macroeconomic elements. On the structural side, one factor behind the collapse in trade has been increased competition from world markets. On the macroeconomic side, foreign exchange constraints and/or tightness of policies may have reduced the demand for exports among the CMEA-member countries.
While an important part of the reallocation of resources is likely to involve an expansion in non-industrial activities (for example financial and other services), structural change is also likely to involve a substantial reallocation of resources within the industrial sector itself.
While Stockman (1988) estimates essentially the same regression for a set of industrial countries, he is testing for a different effect, namely evidence of a “real business cycle” in the form of significant industry-specific shocks. There is, in fact, a small literature on the decomposition of output changes into industry-specific, regional, and national components. Stockman’s methodology was applied here mainly because it imposes fewer structural assumptions on the data than some of the other papers in this literature.
The estimation of equation (1) was carried out by pooling data from 14 industrial sectors for the BCR countries and Poland (data from the other PCPEs were not available), on samples that begin on the dates of each country’s “big bang,” defined as before with reference to the date of the first major price liberalization.
Again, this factor is defined relative to the--hopefully neutral--shock to the energy industry in the four countries.
For example, if industries that utilize underpriced inputs intensively are doing so because they have a high elasticity of substitution, the DRC criterion would nevertheless reveal these industries to be among the most uncompetitive, even though in fact they would be hurt relatively less by raising the price of the relevant inputs.
The transformation is necessary because DRCs are not a monotonic measure. The transformation is such that, the higher is the measure, the more competitive is the sector.
The increase in energy and other input prices would have a large impact on output if enterprises were liquidity-constrained, or if they faced limited substitution possibilities because, for example, of adjustment costs.
Disaggregated price and output data from the industrial sectors in the three countries were collected for this purpose. The number of sectors varied slightly across countries: 16 for Bulgaria; 19 for the CSFR; and 13 for Romania. Data were available for the whole of 1991 for the CSFR and Romania, but only through the third quarter of 1991 in the case of Bulgaria.
Which specific supply and demand shocks have played a role is investigated in the next subsection.
The necessary data were unavailable in the Bulgarian case.
All input prices, as well as the stock of credit, are deflated by the aggregate industrial price index.
Lack of disaggregated real wage data prevented us from incorporating real wages directly into the supply function. Also, lagged (rather than contemporaneous) employment was used in the specification, in order to avoid problems of simultaneity bias, and also to allow for the fact that production takes time.
While this specification only crudely reflects the “Calvo-Coricelli” hypothesis, it could represent a model in which the real stock of credit simply represents another input (like labor and capital) into the firm’s production function.
The apparent reason was multicollinearity arising from the correlation between the fixed-effect coefficients and the employment variable.