4 resultados para manufacturing industries

em University of Connecticut - USA


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In this paper we analyze state level data for total manufacturing constructed from the Annual Survey of Industries for the period 1986-2000 using the nonparametric method of Data Envelopment Analysis (DEA). We assess the extent of surplus labor in the manufacturing sector in the individual states in India. The study also investigates whether the same states show the maximum incidence of surplus labor every year in the sample period and if there any evidence that the extent of surplus labor in manufacturing has been reduced or eliminated in the post-reform era. Our study shows the presence of considerable measure of surplus labor in all of the years in a majority of the states. Things have worsened rather than improved after the reform. Also, the regional distribution of surplus labor has remain fairly unchanged with the same states performing inefficiently both before and after the reform.

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We measure the capacity output of a firm as the maximum amount producible by a firm given a specific quantity of the quasi-fixed input and an overall expenditure constraint for its choice of variable inputs. We compute this indirect capacity utilization measure for the total manufacturing sector in the US as well as for a number of disaggregated industries, for the period 1970-2001. We find considerable variation in capacity utilization rates both across industries and over years within industries. Our results suggest that the expenditure constraint was binding, especially in periods of high interest rates.

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In this paper we use the 2004-05 Annual Survey of Industries data to estimate the levels of cost efficiency of Indian manufacturing firms in the various states and also get state level measures of industrial organization (IO) efficiency. The empirical results show the presence of considerable cost inefficiency in a majority of the states. Further, we also find that, on average, Indian firms are too small. Consolidating them to attain the optimal scale would further enhance efficiency and lower average cost.

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Input congestion occurs at a given input bundle when the assumption of free disposability of inputs does not hold and an increase in input leads to a decline in output. In this paper we employ the nonparametric method of Data Envelopment Analysis (DEA) to examine the question on input congestion with respect to labor, using state level data from the Annual Survey of Industries for the period 1986-87 through 1999-2000. When the standard assumption of strong disposability is relaxed for the labor inputs, the nonparametric analysis of state-level data from Indian manufacturing shows considerable measure of labor input congestion. While in selected states congestion comes from non-production workers as well, the principal source of labor congestion is production labor. There is no evidence that the problem of labor congestion has become less severe during the post-Reform years. It appears that market forces without any major institutional changes in enforcement of labor discipline cannot eliminate congestion.