The dramatic decline of industry in the transitional economies of Eastern Europe has played a rather ambiguous role in the economics of transition. On the one hand, many economists have tended to bemoan the enormous decline in measured aggregate output as an unexpected calamity inconsistent with basic price theory, and to acclaim the recent upturn in official growth – largely due to increased industrial production - as a sign of genuine “recovery.”14 This view has been echoed by some of the politicians and general publics of the region, who place a lower value on the service economy and “speculation” than on goods manufacturing (as, indeed, do politicians and publics to some extent worldwide). On the other hand, an appreciation of the serious misallocation of resources produced by the socialist regimes’ industrial drive suggests that the degree of decline in industry may also be taken as an indicator of the degree of success in restructuring Jackman and Pauna ( 1997). The need for sectoral reallocation of labor, with the inevitability of periods of search and waiting between jobs, has even led some observers to claim that the level of unemployment may provide a measure of the success of the transition overall McAuley ( 1991).
This paper has attempted to enable a better understanding of the nature of the industrial decline and its consequences in transitional economies. In doing so, the paper has shown that the decline of Romanian industry is not simple and uniform: although all sectors of industry appear to be affected by net employment declines, all have engaged in some hiring as well. Furthermore, sectors of industry exhibit significant heterogeneity in the size of their net outflows, and in the extent of turnover of their employment. Concerning the destination of workers who leave jobs from which they were employed in industry in 1993, I find a roughly even split between jobs in other industries and in services, on the one hand, and marginal activities in agriculture, unemployment, and nonparticipation in the labor force, on the other. The probability of these alternative destinations appears to be a function of a number of measurable determinants, including age, gender, rural/urban location, educational attainment, and ownership of 1993 employer, helping to identify the groups of workers who have been successful in moving to new jobs and those who represent some of the main social costs of the transition.
While the data set used in this paper has the distinct advantages of being large and representative, as well as based on a questionnaire designed according to internationally accepted concepts, it bears emphasis that I am unable to measure a number of important factors that would be useful for a better evaluation of the labor reallocation process. Future research, with this data set or with others, could investigate such issues as the impact of the incidence of part-time work, secondary jobs, and self-employment. It could examine the 1994 states and the transitions from 1993 to 1994 and from 1994 to 1995. Particularly interesting might be an examination of workers who flow through unemployment in 1994. The specification could also be altered to take into account possible correlation of error terms over subsets of choices (e.g., by using a nested logit or multinomial probit framework). The sample and the set of issues could be expanded to include individuals older than working age and their retirement behavior - whether early or normal. Finally, other data sets would add useful information on such characteristics as wages and job quality, to permit better assessment of the degree to which labor market transitions are resulting in favorable outcomes.