Dynamics of technical efficiency of sugar mills in India: Stochastic Frontier Approach (original) (raw)
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Journal of productivity analysis, 1992
Frontier production functions are important for the prediction of technical efficiencies of individual firms in an industry. A stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time. The best predictor for the technical efficiency of an individual firm at a particular time period is presented for this time-varying model. An empirical example is presented using agricultural data for paddy farmers in a village in India.
The study is an endeavor to test the validity of convergence hypothesis in Indian sugar Industry. For inferential purpose, data for 12 major sugar-producing states over the period 1974/75 to 2004/05 has been used. The technical efficiency and scale efficiency scores have been computed using the technique of full cumulative data envelopment analysis (DEA). From the empirical results, an average inefficiency to the tune of 35.55 percent has been observed in Indian sugar industry. The search for sources of technical inefficiency reveals that managerial inefficiency (i.e., pure technical inefficiency) is the dominant source and scale inefficiency is relatively scant source of it. The inference of the existence of catching-up (i.e., efficiency convergence) has been found valid during the pre-reforms period, which disappears during the post-reforms period. Moreover, the reforms process has been observed adversely affected the efficiency trends and thus, failed to exert any positive impact...
Efficiency of Indian Fertilizer Firms : A Stochastic Frontier Approach
2017
This paper examines the competitiveness of Indian fertilizer firms by computing their output oriented technical efficiency from 1993-94 to 2012-13, using the stochastic frontier approach. It reveals that the industry runs at 57 percent technical efficiency on an average and that there is scope for further improvement. The research also finds that the private sector fertilizer firms are more efficient than the public sector ones. In addition, it reveals that large and experienced firms are more efficient than small and new firms. This analysis concludes that the current level of R&D expenditure or imports do not improve the efficiency levels, especially in the short run. However, in the long run, R & D may play a crucial role in improving efficiency as in any manufacturing sector. The public firms can enter into technological collaborations with private firms to gain higher efficiency. The large number of technological collaborations noticed in this sector in recent times, therefore,...
This paper assesses the specific technical efficiency of dairy farmers by using the stochastic production frontier approach, which incorporates a model for technical inefficiency effects including innovativeness, economic status, age and schooling, on the production of the milk. The mean technical efficiency turns out to be two third of the total. Thus, the production of the milk can be increased by one third of the total without increasing the quantum of inputs. The results further indicate that the technical efficiency of milk producers is influenced positively by the innovativeness, economic status and schooling, whereas negatively by the age of the milk producers. The milk producers who are innovative and hailing from higher economic status have shown more ability in managing crisis. The farmers with low economic status and low level of schooling are found to be poor in managing crisis in their enterprises. Similarly, old age acts as a deterrent to the crisis managing ability of the farmers. The study suggests the need to promote young farmers and raising their schooling as well along with raising the level of education, imparting training to them for making them more enterprising. The study further suggests strengthening the resource base of the milk producers by providing low cost or costless capital/finance for purchasing the modern breeds of the milking animals.
Orissa journal of commerce, 2022
The purpose of this study is to measure the total factor productivity (TFP) of industrial sector in India at an aggregate level and find the impact of technical inefficiency and other input variables on TFP using stochastic frontier analysis approach. Based on the aggregated data for a period of 29 years, the output productivity is measured as net sales revenue of an industry in a particular year, whereas input is measured as the raw material cost, labor cost, capital employed and research and development (R&D) investment of an industry in a particular year. The TFP is measured based on the functional form of Cobb-Douglas model. The results of the study indicate that material, labor and R&D are the prime drivers of TFP for industrial sector and the industrial sector is suffering from poor productivity due to technical efficiency that is decreasing over time.
South African Journal of Economic and Management Sciences, 1999
Small developing countries have for long acquired significant benefits through preferential trading arrangements. However, these benefits have led to a proliferation of inefficient industries in the recipient countries. With the recent changes in the GAIT, these inefficient industries may close and thus lead to major economic and social problems in the recipient countries. This paper utilizes the frontier production function approach to examine the efficiency status of Fiji's sugar industry. The analysis reveals that a significant level of inefficiency exists at the farm level of Fiji's sugar industry. Some of the factors that were found to effect the level of efficiency are farming status, land class and ethnicity. These factors are then used to derive policy implications.
This study focuses on the inter-temporal and inter-state variations in technical and scale efficiency levels of Indian sugar industry. In the first stage, full cumulative data envelopment analysis (FCDEA) is used to derive efficiency scores for 12 major sugar producing states. The panel data truncated regression is employed in the second stage to assess the key factors explaining the observed variations in the efficiency levels. The results suggest that the extent of technical inefficiency in Indian sugar industry is about 35.5 percent per annum, and the observed technical inefficiency stems primarily due to managerial inefficiency rather scale inefficiency. Also, a precipitous decline in the level of technical efficiency has been noticed in the post-reforms period relative to the level observed in the pre-reforms period. The availability of skilled labour and profitability have been found to be most significant determinants of technical efficiency in Indian sugar industry.
Measuring technical efficiency with panel data
Journal of Econometrics, 1993
The study investigates farm level technical efficiency (TE) and its determinants in the state of West Bengal in India. A stochastic production frontier model has been applied for determining technical efficiency by using panel data on 17 agricultural production units over a period of 23 years. Maximum-likelihood estimates of the Cobb-Douglas stochastic frontier production function in a time-variant truncated normal distribution is appropriate for the measurement of technical efficiency of West Bengal agriculture in India. The estimated variance ratio indicates that 48.90 percent of the differences between the observed and the estimated output is caused by differences in farms' technical inefficiencies. However, the remaining variation is due to factors beyond farmers' control. The study shows that the agricultural farms in West Bengal exhibit increasing returns to scale in production. The study finds that farmers' education and agricultural extension are important determinants of technical efficiency. Other prominent determinants that have a significant contribution are farm size, crop diversification, number of available agricultural markets, the proportion of small landholders and input intensity. All these determinants, excluding the proportion of small landholders, have a largely positive impact on technical efficiency. The maximum-likelihood estimation (MLE) and principal component analysis (PCA) are applied to determine the effects of determinants on TE. Both methods give similar results.