Identification of Factors Which Influence the Technical Inefficiency of Indian Farmers (original) (raw)
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Journal of Productivity Analysis, 1997
A stochastic frontier production function incorporating a model for technical inefficiency effects (Battese and Coelli, 1995) is applied to field data on paddy farmers from 29 villages in the ‘Office du Niger’ in Mali. Four ‘conventional factors’ (land, labor, fertilizer and machinery) are considered as inputs of production. The technical inefficiency effects in the stochastic frontier were related to firm-specific
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.
Technical inefficiency effects among paddy farmers at the 'Office du Niger', Mali, West Africa
RePEc: Research Papers in Economics, 1996
A stochastic frontier production function incorporating a model for technical inefficiency effects (Battese and Coelli, 1995) is applied to field data on paddy farmers from 29 villages in the 'Office du Niger' in Mali. Four 'conventional factors' (land, labor, fertilizer and machinery) are considered as inputs of production. The technical inefficiency effects in the stochastic frontier were related to firm-specific variables, institutional factors, social organisation, ecological considerations and health factors. Data were obtained from an economic survey conducted during two consecutive agricultural seasons (1989 and 1990) on 844 farms of the Office du Niger. The null hypothesis of the absence of technical inefficiency effects was rejected. A supportive 'institutional environment' and a coherent organisation of land use were the best correlates of technically efficiency. The social environment was also found to contribute to technical efficiency of the paddy farmers: within the village, the greater the degree of ethnic cohesion, the greater the efficiency of the farmers. Health status of households had an effect in that 'healthy' families tended to be more technically efficient than 'unhealthy' ones. Farmers with more extensive sorghum cultivation were less efficient as paddy farmers. These results may help agricultural policy makers formulate strategies. Technical efficiency may be improved by intensifying agricultural training regarding one specific crop and, through the control of parasitic diseases which place a burden on family households.
1989
A frontier production function of Cobb-Douglas type is defined for panel data, Yit = exp(xit~ + Vit-Ui) ' t = 1,2,...,Ti; i = 1,2,...,N, where the Vit-random variables are assumed to be independent and identically distributed as N(0, o~) random variables, independent of the non-negative U.-random variables, which are assumed to be independent and identically 1 distributed truncations (at zero) of the N(D, 0 2) distribution. The random variable, U i, contributes to the technical inefficiency of the i-th firm for the T. time periods for which observations are 1 available. It is assumed that these firm effects are time invariant. The numbers of observations on the different firms are not required to be the same. The technical efficiency for the i-th firm is defined in terms of the ratio of its mean production to the corresponding mean production if the firm effect was zero. A predictor for this measure of technical efficiency is presented. The model is applied in the analysis of farm-level data from an Indian village involved in ICRISAT's Village Level Studies. The dependent variable involved is gross total value of output for individual farmers in the agricultural years for which data are available. The independent variables depend on the hectares of irrigated and unirrigated land, hours of family and hired labour, hours of bullock labour and the value of input costs, such as fertilizer, organic matter, pesticides and machinery costs. Hypotheses, such as the homogeneity of family and hired labour, are considered. Predictions of the productive efficiency of individual farmers are presented.
Applied Economics and Finance, 2019
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.
2002
The purpose of this study was to analyse the determinants of technical efficiency of small scale farmers in Nigeria and the effect of policy changes on technical efficiency, using the stochastic frontier methodology. Results of analysis indicates that the farmers have an average farm size of 1.56 hectares. It is also indicated that both family and hired labour were extensively used in farm production. The analysis shows a wide variation in the estimated technical efficiencies, ranging between 0.18 and 0.91, and a mean value of 0.63, indicating a wide room for improvement in the technical efficiency. The results of simulation of policy variables show that the level of technical efficiency would significantly increase with rising level of education and farming experience.
African Journal of Agricultural Research, 2013
This paper estimates technical efficiency and identifies factors that explain differentials in technical efficiency for affected and non-affected households. We use time-varying and time-invariant inefficiency models of production. The results show that fertilizer, labour, seeds, and age are found to have contributed significantly to technical efficiency for affected farm households under both time varying and time-invariant models. On the other hand, only fertilizer contributed significantly to technical efficiency of non-affected farm households. In general, results show that Malawian farmers are generally technically efficient. Nevertheless, there is still scope for improvement of the productivity of small-scale farmers, as some farm households, particularly female headed households with mortality, are still operating at low levels of efficiency. Two main policy issues emerge from the results of this study. Firstly, all types of obstacles that could limit the use of farm inputs should be removed. This should include complete liberalisation of purchase and distribution of such inputs and the development of some low-cost technology to reduce labour constraints on the farm. Secondly, there is need to develop social capital in smallholder farming through the recommencement of farmers' clubs or by setting up agricultural cooperatives.
Journal of Agriculture and Food Sciences, 2022
The study examined the determinants of technical efficiency among lowland rice farmers in Enugu State, Nigeria. Primary data were sourced from rice producers through the use of welldesigned questionnaires. The study was conducted in four agricultural zones of Enugu State, during the 2017/2018 cropping season. Multistage and simple random sampling technique was employed to select 300 sampled rice farmers for the study. Cobb-Douglas stochastic production frontier function was used for the analysis. The result revealed that (98%) of random variation in the output of farmers was because of their inefficiency in their use of productive inputs in the study area. .Apart from farm size with estimated coefficient of (0.0531), fertilizer (0.0329), seed (0.2319), labour (0.0804) and agro-chemical (0.1711) were underutilized by the rice farmers. The average technical efficiency for the farmers was 0.71 implying that, on the average, the respondents are able to obtain 71% of potential output from a given mixture of production inputs. Thus, in a short run, there is a minimal scope (29%) of increasing the efficiency, by adopting the technology and techniques used by the most technically efficient farmer. High cost of inputs (MS=3.69), bad roads (MS=3.67), poor credit accessibility (MS=3.40) and inadequate storage facilities (MS꞊2.90) were found to be the major constraints of the rice farmers. The study recommends that in order to improve efficiency of resource use by the farmers in the study area, more of labour, seed, fertilizer and agro-chemicals should be utilized.
The study measures farm level technical efficiency among paddy farmers of Hailakandi district of Assam on the basis of farm level primary data of 265 cultivators for the peak cropping season of 2009-10. A translog stochastic production frontier is estimated and selected non-input factors are modeled to explain variations in technical inefficiency across cultivators. Age, education levels and proportion of land leased in and HYV cultivation have positive influences on farm level technical efficiency. However indebtedness and percentage of self consumption of farm produce have negative influences. Government support through agricultural extension services is found insignificant. Mean technical efficiency is found to be around 69 percent. Finally the study observes decreasing returns to scale and a negative association between farm size and technical efficiency. JEL Classification: D24, N55
Sustainability, 2022
This research was conducted to explore the factors affecting the technical efficiency (TE) of rice producers and its determinants at the farm level. We used a multi-stage sampling procedure to collect cross-sectional data from 800 rice growers in the Uttar Pradesh state of India, and a stochastic frontier model (SFA) was applied. The results showed that the mean technical efficiency was 72%, suggesting scope for a substantial increment in rice productivity exists while using the current level of inputs and technologies. Furthermore, the MLE results revealed that labor, irrigation, and hybrid seeds had a constructive impact on technical efficiency, while experience and tenure status showed a negative impact on technical efficiency. As unraveled by the results of the study, it can be concluded that the technical efficiency of rice farmers can be improved through timely access to credit and agricultural information delivered to them via extension services. The study, therefore, recomme...