17 resultados para Data envelopment analysis


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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 propose a nonparametric model for global cost minimization as a framework for optimal allocation of a firm's output target across multiple locations, taking account of differences in input prices and technologies across locations. This should be useful for firms planning production sites within a country and for foreign direct investment decisions by multi-national firms. Two illustrative examples are included. The first example considers the production location decision of a manufacturing firm across a number of adjacent states of the US. In the other example, we consider the optimal allocation of US and Canadian automobile manufacturers across the two countries.