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A stochastic frontier production function is defined for panel data on firms, in which the non-negative technical inetGciency effects are assumed to be a function of firm-specific variables and time. The inefficiency effects are assumed to be independently distributed as truncations of normal distributions with constant variance, but with means which are a linear function of observable variables. This panel data model is an extension of recently proposed models for inefTiciency effects in stochastic frontiers for cross-sectional data. An empirical application of the model is obtained using up to ten years of data on paddy farmers from an Indian village. The null hypotheses, that the inefficiency effects are not stochastic or do not depend on the farmer-specific variables and time of observation, are rejected for these data.

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Stochastic frontier analysis, Data envelopment analysis, Technical efficiency,

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.

This paper considers a statistical model for a production frontier that is consistent with the traditional (nonstochastic) definition of a production function given in microeconomic theory. Limiting cases of the model are the familiar average production function and an envelope production function. Maximum‐likelihood estimators for the parameters of the model are defined. The three related models are applied in the estimation of a production frontier for the Pastoral Zone of Eastern Australia with use of data from the Australian Grazing Industry Survey.