Functional Forms of Stochastic Frontier Production Functions and Models for Technical Inefficiency Effects: A Comparative Study for Wheat Farmers in Pakistan

This paper considers translog and Cobb-Douglas stochastic frontiers in which the technical inefficiency effects are defined by three different models. The models involved are the time-varying inefficiency model, proposed by Battese and Coelli (1992), the inefficiency effects model for panel data, proposed by Battese and Coelli (1995), and the non-neutral frontier model, proposed by Huang and Liu (1994). Technical change is also accounted for in the frontier models. Predicted technical efficiencies of the wheat farmers and estimates of the elasticities of wheat production with respect to the different inputs and the returns-to-scale parameter are compared under the different model specifications.     

A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms

This paper introduces a stochastic frontier production model which accommodates firm-specific temporal variation in technical inefficiency. Unlike Cornwell, Schmidt and Sickles (1990), technical inefficiency is not modeled through the intercept of the production frontier, but through an error component model. The proposed model is a generalization of the Battese and Coelli (1992) model, which imposed a common temporal pattern upon all firms. In our application involving Spanish dairy farms, we find that the new model is preferred to the Battese and Coelli (1992) model on the basis of the likelihood ratio test. Results provide a new source of information on the different patterns of technical inefficiency change among the 82 farms in the sample.     

Technical efficiency during economic reform in Nicaragua: evidence from farm household survey data

This paper employs a translog stochastic frontier model to examine technical efficiency of maize and bean farmers in two selected regions of Nicaragua using farm-level survey data for the 1994–1995 crop year. The average technical efficiency levels are 69.8 and 74.2% for maize and beans, respectively. The results from the maize and beans translog frontier functions show that farmers’ human capital represented by the level of schooling, access to formal credit and farming experience represented by age contribute positively to production efficiency, while farmers’ participation in non-farm employment tends to reduce production efficiency.     

Stochastic error specification in primal and dual production systems

In this paper we derive both primal and dual‐cost systems in which the stochastic specifications arise from the model (random environment or measurement errors and optimization errors)—not tacked on at the end after the deterministic system is worked out. Derivation of the error structures is based on cost‐minimizing behavior on the firms. The primal systems constitute the production function and the first‐order conditions of cost minimization. We consider two dual‐cost systems. The first dual system is based on the cost function and cost share equations. The second dual system is based on a multiplicative general error production model that is an alternative to McElroy's additive general error production model. Our multiplicative general error model gives a clear and intuitive economic meaning to the error components. The resulting cost system is easy to estimate compared to the alternative cost systems. The error components in the multiplicative general error model can capture heterogeneity in the technology parameters even in a cross‐sectional model. Panel data are not necessary to estimate either the primal or dual systems. The models are estimated using data on 72 fossil fuel‐fired steam electric power generation plants (observed for the period 1986–1999) in the USA. Copyright © 2009 John Wiley & Sons, Ltd.     

Estimating Technological Change Using a Stochastic Frontier Production Function Framework: Evidence from U.S. Firm-Level Data

This paper presents a methodology for estimating an index of technological change using firm-level data in a stochastic frontier production function model that takes into account time-varying technical inefficiency. In contrast to the Solow divisia index approach, econometric estimation of the index with panel data allows the researcher to separate technical progress from the stochastic measurement error. Applying the econometric methodology to a panel of 908 publicly-traded U.S. firms from the COMPUSTAT database, we find evidence of a significant downturn in general technological change for the period, 1970– 1989, whereas the divisia index methodology applied to the same data shows stagnation. When the sample is divided into Manufacturing, Services, and Miscellaneous categories we find that estimates of technological change for the three groups display markedly different stochastic behavior and that the Services group is the source of the downturn.     

The stochastic frontier production function and average efficiency: An empirical analysis

This paper provides an empirical estimation of a stochastic frontier Cobb-Douglas production function using micro data from a cross-section of Brazilian manufacturing firms. Following a procedure developed by Aigner, Lovell and Schmidt incorporating both stochastic and efficiency disturbance terms in the estimating model, maximum likelihood techniques are used for the estimation of the stochastic frontier. A measure of mean technical efficiency is also developed and employed with the Brazilian data. Unlike the previous empirical exercises carried out with aggregated data, the efficiency disturbance with the Brazilian micro data estimates is not swamped by the stochastic disturbance.     

A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies

This paper presents a metafrontier production function model for firms in different groups having different technologies. The metafrontier model enables the calculation of comparable technical efficiencies for firms operating under different technologies. The model also enables the technology gaps to be estimated for firms under different technologies relative to the potential technology available to the industry as a whole. The metafrontier model is applied in the analysis of panel data on garment firms in five different regions of Indonesia, assuming that the regional stochastic frontier production function models have technical inefficiency effects with the time-varying structure proposed by Battese and Coelli (1992).     

Productive efficiency of French grain producers: A latent variable model

In this article we propose to implement a covariance structure analysis to deal with the estimation of a stochastic frontier production function on panel data and the measurement of a time-varying technical efficiency. First, this method solves the potential problem of correlations between input quantities and individual effects. Second, individual effects and efficiency measures can be recovered as a byproduct of the analysis through the so-called factor scores. We implement this approach by fitting to a balanced panel of French grain producers, a parsimonious version of the Cornwell, Schmidt, and Sickles [1990]'s model where technical efficiencies are individual-specific linear functions of time. A specification search shows that this model is preferred to the traditional production function. Results shed light on the temporal pattern of efficiency in the French grain production sector.The authors thank Jacques Mairesse, Quang Vuong, two referees, the editor, and session participants at the Econometric Society European Meeting, Cambridge, September 1991, at the Second European Workshop on Efficiency and Productivity Analysis, Louvain-la-Neuve, October 1991, at the Conference on Current Issues in Productivity, Newark, December 1991, and at the ENSAE-EHESS seminar, Paris, March 1992, for helpful comments and suggestions.     

On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

Analysis of the behavior of technical inefficiency with respect to parameters and variables of a stochastic frontier model is a neglected area of research in frontier literature. An attempt in this direction, however, has recently been made. It has been shown that in a “standard” stochastic frontier model that both the firm level technical inefficiency and the production uncertainty are monotonically decreasing with observational error. In this paper we show, considering a stochastic frontier model whose error components are jointly distributed as truncated bivariate normal, that this property holds if and only if the distribution of observational error is negatively skewed. We also derive a necessary and sufficient condition under which both firm level technical inefficiency and production uncertainty are monotonically increasing with noise-inefficiency correlation. We next propose a new measure of the industry level production uncertainty and establish the necessary and sufficient condition for firm level technical inefficiency and production uncertainty to be monotonically increasing with industry level production uncertainty. We also study the limiting probabilistic behavior of these conditions under different parametric configuration of our model. Finally we carry out Monte Carlo simulations to study the sample behavior of the population monotonic property of the firm level technical inefficiency and production uncertainty in our model.