A Stochastic Frontier Production Function with Flexible Risk Properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures.An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.     

THE DETERMINATION OF OPTIMAL RATIONS FOR PIGS FED SEPARATED MILK AND GRAIN*

This paper demonstrates a procedure for determining economically optimal rations which avoids problems that arise in conventional analysis of experimental results. It consists of maximising a suitably constrained profit per unit time objective function, itself formed from functions obtained from pig fattening experiments under special Australian conditions. The relevant functions-for consumption of milk and wheat, time to slaughter and percentage lean meatare first demonstrated, followed by a brief discussion of results obtained. Specifcally, it is noted that optimal diets differ according to whether the criterion adopted is profit per pig or profit per pig per week, that dairy farmers fattening pigs should feed substantial quantities of grain, and that the optimal diets are very stable to changing prices. More generally, the procedure avoids the statistical difficulties of conventional analysis of experiments arising from the estimation of weight-gain functions based on actual quantities of food consumed.     

TIME AND RECURSIVENESS IN LIVESTOCK FEEDING TRIALS*

In livestock feeding experiments the problem of recursiveness arises because the quantity of feed consumed by an animal is a function of its past history of feeding. The problem is most acute where experiments are designed to analyse sub ad lib feeding. The analysis of such experiments encounters two important problems. The first is that the actual quantity of feed consumed is an endogenous variable and is not directly under the control of the experimenter or the livestock producer. The second problem is the mathematical complexity of the relationships involved. A solution is suggested as a quasi reduced-form model.     

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.     

What's driving innovation in small businesses in Australia? The case of the food industry

There is strong evidence that innovation is a primary driver of a nation's economic growth. As Australia continues to compete in the global economy, it is imperative that businesses should be innovative to improve their performance. In this paper, we evaluate the status and main drivers of innovation in small businesses in the food sector in Australia. Discrete choice modelling and bootstrapping procedures are applied to a panel of firm‐level data collected through the ABS Business Characteristics Survey (2006–2007 to 2010–2011 for the Australian Bureau of Statistics’ Business Longitudinal Database Confidential Unit Record File) to investigate the factors affecting the likelihood of small food businesses to innovate. Results show that businesses are more likely to innovate if they collaborate, have higher information and communication technology intensity, and use science, technology, engineering and mathematics skills. We also found that small food businesses, even at the subsector level, do combine different types of innovation when innovating. The propensity to innovate also increases for small businesses that have flexible working arrangements, face moderate‐to‐strong market competition, operate overseas and seek finance through debt and equity. The relative importance of these factors was found to vary between agricultural and nonagricultural food subsectors.     

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).     

ESTIMATION OF A PRODUCTION FRONTIER MODEL: WITH APPLICATION TO THE PASTORAL ZONE OF EASTERN AUSTRALIA

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.     

Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project

This paper investigates the technical efficiency of two samples of maize producers in eastern Ethiopia, one involving farmers within the Sasakawa-Global 2000 project and the other involving farmers outside this program. The study uses stochastic frontier production functions in which the technical inefficiency effects are assumed to be functions of the age and education of the farmers, together with the time spent by extension advisers in assisting farmers in their agricultural production operations. For the cross-sectional data obtained for the 1995/96 agricultural year, Cobb-Douglas stochastic frontiers are found to be adequate representations of the data, given the specifications of the translog stochastic frontiers for farmers within and outside the project. The empirical results indicate that farmers within Ihe SO 2000 project are more technically efficient than farmers outside the project, relative to their respective technologies. The mean frontier output of maize lor farmers within the SG 2000 project is significantly greater than that for the farmers outside the project.     

IDENTIFICATION OF FACTORS WHICH INFLUENCE THE TECHNICAL INEFFICIENCY OF INDIAN FARMERS

The agricultural production of Indian farmers is investigated using a stochastic frontier production function which incorporates a model for the technical inefficiency effects. Farm-level data from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) are used. Variables considered in the model for the inefficiency effects include the age and level of education of the farmers, farm size and the year of observation. The parameters of the stochastic frontier production function are estimated simultaneously with those involved in the model for the inefficiency effects. This approach differs from the usual practice of predicting farm-level inefficiency effects and then regressing these upon various factors in a second-stage of modelling. The results indicate that the above factors do have a significant influence upon the inefficiency effects of farmers in two of the three villages considered.     

A model for technical inefficiency effects in a stochastic frontier production function for panel data

A stochastic frontier production function is defined for panel data on firms, in which the non-negative technical inefficiency 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 inefficiency 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.