A Methodological Note on a Stochastic Frontier Model for the Analysis of the Effects of Quality of Irrigation Water on Crop Yields

A stochastic frontier model is proposed for analysis of crop yields, which considers the effects of differing quality of irrigation water, in addition to different inputs and factors associated with technical inefficiency of production. The parameters of the production frontier involved are assumed to be a function of other variables, which measure the quality of the irrigation water.

An Investigation of Production Risk, Risk Preferences and Technical Efficiency: Evidence From Rainfed Lowland Rice Farms in the Philippines

Risk plays a vital role in farmers' decisions on input allocations and, therefore, output supply. This paper provides empirical evidence on the estimation of production risk, risk preferences and technical inefficiency. An eight-year panel data set is used for 46 rice farmers from a representative rainfed lowland environment in Central Luzon, Philippines. The heteroskedastic and stochastic frontier frameworks are reconciled and extended to accommodate the risk preferences of farmers in an analysis of production risk. Results show that technical inefficiency is overstated in risky production environments where farmers are risk-averse.production risk, risk preferences, technical efficiency, Productivity Analysis, Risk and Uncertainty,

Metafrontier Functions for the Study of Inter-regional Productivity Differences

The paper uses the concept of metafrontier functions to study regional differences in production technologies. The paper has three components. The first deals with the analytical framework necessary for the definition of metafrontier functions. The second component studies the properties of the metafrontier estimated using nonparametric data envelopment analysis (DEA). The third component focuses on the estimation of metafrontiers within the parametric framework of stochastic frontier analysis (SFA). The empirical application of the models uses cross-country agricultural sector data. The DEA and SFA metafrontiers are presented and discussed.

Metafrontier Functions for the Study of Inter-Regional Productivity Differences

The paper uses the concept of metafrontier functions to study regional differences in production technologies. The paper has three components. The first deals with the analytical framework necessary for the definition of metafrontier functions. The second component studies the properties of the metafrontier estimated using nonparametric data envelopment analysis (DEA). The third component focuses on the estimation of metafrontiers within the parametric framework of stochastic frontier analysis (SFA). The empirical application of the models uses cross-country agricultural sector data. The DEA and SFA metafrontiers are presented and discussed

Technical Change and Productive Inefficiency Change in Norwegian Salmon Farming: The Influence of Regional Agglomeration Externalities

This paper analyses the factors explaining productivity and efficiency differences across salmon aquaculture farms, with an emphasis on agglomeration externalities. We specify a stochastic frontier production model with agglomeration indexes included in both the frontier production function and the technical inefficiency model. The frontier model is estimated on a rich panel data set with 2,738 observations on 577 farms. Our results confirm the importance of agglomeration externalities for the productivity and technical inefficiency of salmon farms. Both frontier output and technical efficiency increase with increasing regional industry size. There is a negative relationship between overall productivity and regional farm density, suggesting the presence of negative biological congestion externalities. These results have implications for the Norwegian government’s regulation of the industry, since the government, to a large extent, has determined the spatial distribution of salmon production through a licence system

Production Functions for Wheat Farmers in Selected Districts of Pakistan: An Application of a Stochastic Frontier Production Function with Time-varying Inefficiency Effects

Two models of technical inefficiency with a stochastic production frontier are considered in this paper. In the first model, it is assumed that the frontier itself does not vary with time, while in the second, the frontier is allowed to move. These models are applied to four years of panel data on wheat farmers in four districts of Pakistan Faisalabad and Attock in the Punjab, Badin in Sindh, and Dir in the NWFP. Using essentially the same stochastic frontier production function in each of the four districts involved, different stochastic specifications for the inefficiency effects are obtained for die different districts. Technical efficiencies of production of the individual farmers are predicted in each year in which they are observed. Varying patterns of technical inefficiency are observed. The null hypothesis (of no technical inefficiency) cannot be rejected in only one district. In the other districts, while inefficiencies appear to be present in all of them, they are declining at a fairly rapid pace in one. The results highlight the importance of analysis at a disaggregated level because it is clear that both the rate of technical change and relative efficiencies vary across regions and explicit cognisance must be taken of this both in research and policy formulation.