Publications   Empirical StudiesOldrich & Ludmila Kyn: Production Functions for Eastern Europe

1

DATA

Most of the data needed for estimations were obtained directly from the official statistical yearbooks of individual East European countries. The easiest was to get data for industrial sector in the breakdown to 15-20 industrial branches. Much more difficult and not always successful was our attempt to obtain or reconstruct comparable data for nonindustrial sectors, i.e. agriculture, transportation, construction and trade. The length of time series was in most cases from 1948-1950 to 1967-1968, however, for East Germany and Poland only much shorter time series were available.

The main difficulty which we faced in the process of data preparation were related to capital stock data. For some countries the capital stock had to be partially or fully constructed from the gross investments without knowing the actual replacement ratio and in the case of Rumania even without knowing the initial stocks of capital in individual sectors. In the case of Czechoslovakia and Poland the capital stock was also adjusted for the degree of utilization.

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The detailed description of data is given in the Appendix, at this place it will be sufficient to give only the following brief characterization:

(1)

  For Yit either gross value of output (GVO) in East European definition or GNP in Western definition was alternatively used.

(2)

 Labor Lit was expressed either in the average number of persons employed or in the number of manhours.

(3)

   For Kit the average stock of fixed capital, i.e. buildings, constructions, equipment and machines was used.

3

The gross value of output (GVO) was used, because for most countries no other data on output were available in the breakdown to industrial branches. 

The sole exception was Czechoslovakia for which also Western6 estimates of GN P were available and used. The frequent criticism of the use of GVO data may very well be correct for aggregate time series but not necessarily for the disaggregated approach followed in this paper. One advantage of GVO data is that they are truly independent observations. Unfortunately this is not true for some Western estimates of GNP for East European countries, which are "cross-sectionally" constructed from the "right-hand" variables K and L by summing up wages and some "reasonable" profit per capital. It is obvious that construction of "left-hand" variable from the "right hand" variables violates the elementary requirements of regression analysis.

In most cases, the only data available in the breakdown to sectors and branches of industry were those related to either the state or the socialist sectors. The socialist sector includes both state owned and cooperative establishments. It was impossible to get the data on output, labor and capital for the private sector in the needed breakdown. The exclusion of the private sector is not a serious limitation for recent years because its share in all concerned East European countries (except for Polish agriculture) became negligible. It is, however much less satisfactory for the early post-war years.

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The obvious disadvantage of the "gross value of output" is, that it makes the estimated parameters less comparable with the similar estimates for Western countries which are based on GNP.

 The "gross value of output" is likely to give relatively higher rates of technical change. This is an outcome of the fact that the indicator of the gross value of output has usually grown faster than GNP. The East European definition of output includes only the so called "productive" sectors and activities, which happened to have grown faster than the "nonproductive" sphere. In addition to that, the gross value of output includes the intermediate product, which has also frequently grown faster than the net product.

Very serious problems are related to the prices, in which the official data are valued. Many East European economists as well as Western scholars conclude, that the operation of the Soviet type economy leads to the "inflation of constant prices" and to the distortion of relative prices. The empirical evidence is sufficient enough to support this conclusion7 but unfortunately not sufficient to estimate how much the constant prices were inflated. Both the "inflation of constant prices" and the distortion of relative prices may result in biased estimates of the parameters of macroeconomic production functions. In the pure time-series analysis, the inflation of constant prices is likely to "inflate" the estimated rates of growth of the total factor productivity. In the pure cross-section analysis, the distortion of relative prices may lead to the biased estimates of capital and labor elasticities. In the combination of cross-section and time-series analyses both effects may appear. The "inflation of constant prices" is hard to eliminate, but the "relative prices" effect may be at least partially eliminated if sectoral dummy variables are introduced into the regression equations.

Another problem is related to the measurement of inputs. Ideally one should use quantities of labor and capital adjusted for the degree of utilisation. Due to the employment planning and to the rigid rules of labor allocation a certain amount of unutilised labor exists in many sector and industrial branches.

Unfortunately no reliable data about the degree of utilisation of labor are available. The best we can do, is to use the manhours worked, where possible, believing that the changes in the average duration of the working day reflect at least partially the variations in the utilization of labor. Capital was adjusted for the degree of utilization with the use of the shift coefficient and productive consumption of the electric power. The detailed description of the method used is given elsewhere.

 

 

 

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