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A major econometric issue in estimating production parameters and technical efficiency is the possibility that some forces influencing production are only observed by the firm and not by the econometrician. Not only can this misspecification lead to a biased inference on the output elasticity of inputs, but it also provides a faulty measure of technical efficiency. We extend the Levinsohn and Petrin (2003) approach and provide an estimation algorithm to overcome the problem of endogenous input choice in stochastic production frontier estimation by generating consistent estimates of production parameters and technical efficiency. We apply the proposed method to a plant-level panel dataset from the Colombian food manufacturing sector for the period 1982-1998. This dataset provides the value of output and prices charged for each product, expenditures and prices paid for each material used, energy consumption in kilowatt per hour and energy prices, number of workers and payroll, and book values of capital stock. Empirical results find that the traditional stochastic production frontier tends to underestimate the output elasticity of capital and firm-level technical efficiency. The evidence in this research suggests that addressing the endogeneity issue matters in stochastic production frontier analysis.

This research proposes a parametric estimation of the structural dynamic efficiency measures proposed by Silva and Oude Lansink (2009). Overall, technical and allocative efficiency measurements are derived based on a directional distance function and the duality between this function and the optimal value function. The applicability of the parametric proposal is illustrated by assessing dynamic efficiency ratings for a sample of Dutch dairy farms observed from 1995 to 2005.

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The stochastic distance function model is extended to allow for the inefficiency component of the error term to be autocorrelated, as implied by a dynamic model of firm behavior. The autocorrelation parameter can then be interpreted as a measure of the persistence of inefficiency. The model is viewed from a state-space perspective, and Kalman filtering techniques are proposed for estimation. The model is applied to two panels of dairy farms from Germany and the Netherlands. The results suggest a very high degree of persistence of inefficiency through time.

Chemical pesticides constitute an important input in crop production. But their indiscriminate use can impact negatively agricultural productivity, human health, and the environment. Recently, attention is focused on the use of economic incentives to reduce pesticide use and its related indirect effects. The aim of this work is to assess the effectiveness of different economic instruments such as taxes and levies in encouraging farmers to decrease pesticide use and their environmental spillovers. A policy simulation model is employed using data from Dutch cash crop producers including two pesticide categories that differ in terms of toxicity and pesticides’ environmental spillovers. Four different instruments were selected for evaluation: pesticide taxes, price penalties on pesticides’ environmental spillovers, subsidies, and quotas. The results of the study indicate that even high taxes and penalties would result in a small decrease in pesticide use and environmental spillovers. Taxes that differentiate according to toxicity do not lead to substitution of high‐ with low‐toxicity pesticides. Subsidies on low‐toxicity products are not able to affect the use of high‐toxicity products. Pesticide quotas are more effective in reducing pesticide use and environmental spillovers.