Estimating product‐specific and multiproduct economies of scale with data envelopment analysis

Nonparametric cost frontier estimation and subsequent analysis of the relative efficiency of firms has historically been conducted without critically examining the shape of the cost frontier. The shape of the cost frontier has been examined using additional parametric estimation methods to recover potential cost savings from multiproduct and product‐specific economies of scale. This paper presents and tests an approach to estimate multiproduct and product‐specific economies of scale using data envelopment analysis. Data for the study are simulated assuming an underlying production technology. Nonparametric estimates of efficiency, multiproduct scale, product specific scale, and scope economies are compared to those of the assumed production technology. Results show that the nonparametric approach accurately estimates multiproduct economies of scale and product‐specific economies of scale under alternative inefficiency distributional assumptions.     

Measuring technical efficiency of dairy farms with imprecise data: a fuzzy data envelopment analysis approach

This article integrates fuzzy set theory in the data envelopment analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in conventional DEA is that input and output data are measured with precision. However, production agriculture takes place in an uncertain environment, and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data are known to lie within specified intervals and empirically illustrate this approach using a group of 29 dairy producers in Pennsylvania. Compared to the conventional DEA scores that are point estimates, the computed fuzzy efficiency scores are interval bound allowing the decision maker to trace the performance of a decision‐making unit at different possibility levels.     

Technology choice and efficiency on Australian dairy farms*

Deregulation of the Australian dairy industry, specifically the removal of price subsidies to ‘market milk’, as well as ongoing drought in many dairy regions, has placed considerable pressure on farm cash income and a search for ways in which dairy farms can be made to operate more efficiently. Using traditional farm survey data and a unique biannual data set on farm technology use, this paper estimates a stochastic production frontier and technical efficiency model for dairy farms in New South Wales and Victoria, determining the relative importance of each input in dairy production, the effects of key technology variables on farm efficiency, and overall farm profiles based on the efficiency rankings of dairy producers. Results show that production exhibits constant returns to scale and although feed concentration and the number of cows milked at peak season matter, the key determinants of differences in dairy farm efficiency are the type of dairy shed used and the proportion of irrigated farm area. Overall farm profiles indicate that those in the ‘high efficiency group’ largely employ either rotary or swing‐over dairy shed technology and have almost three times the proportional amount of land under irrigation.     

Representing climatic uncertainty in agricultural models – an application of state‐contingent theory

The state‐contingent approach to production uncertainty presents a more general model than the conventional stochastic production approach. Here we investigate whether the state‐contingent approach offers a tractable framework for representing climatic uncertainty at a farm level. We developed a discrete stochastic programming (DSP) model of a representative wheat–sheep (mixed) farm in the Central West of NSW. More explicit recognition of climatic states, and associated state‐contingent responses, led to optimal farm plans that were more profitable on average and less prone to the effects of variations in climate than comparable farm plans based on the expected value framework. The solutions from the DSP model also appeared to more closely resemble farm land use than the equivalent expected value model using the same data. We conclude that there are benefits of adopting a state‐contingent view of uncertainty, giving support to its more widespread application to other problems.     

Design efficiency for non‐market valuation with choice modelling: how to measure it,what to report and why*

We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior belief on the range of values for the utility coefficients. D‐, A‐, B‐, S‐ and C‐errors are compared as measures of design performance in applied studies and their rationale is discussed. An empirical example based on the generation and comparison of fifteen separate designs from a common set of assumptions illustrates the relevant considerations to the context of non‐market valuation, with particular emphasis placed on C‐efficiency. Conclusions are drawn for the practice of reporting in non‐market valuation and for future work on design research.     

Heterogeneity of Long‐run Technical Efficiency of German Dairy Farms: A Bayesian Approach*

In parametric efficiency studies, two alternative approaches exist to provide an estimate of the long‐run efficiency of firms: the dynamic stochastic frontier model and the generalised true random‐effects model. We extend the former in order to allow for heterogeneity in the long‐run technical efficiency of firms. This model is based on potential differences in firm‐specific characteristics and in firms’ inefficiency persistence. The model is applied to an unbalanced micro‐panel of German dairy farms over the period 1999 to 2009. Estimation of long‐run technical efficiency and inefficiency persistence is based on an output distance function representation of the production technology and estimated in a Bayesian framework. The results suggest that heterogeneity in long‐run technical efficiency of farms is mostly attributed to discrepancies in farm‐specific factors rather than differences in farms’ inefficiency persistence. Farm size is positively related to long‐run technical efficiency while subsidies exert a negative effect on the long‐run technical efficiency of farms. Inefficiency persistence is found to be very high, but heterogeneity in this persistence is low.     

Off‐farm work and technical efficiency on U.S. dairies

In this study, we investigate the impact of an increase in farm households’ off‐farm work on technical efficiency (TE) of U.S. dairies. We present a theoretical framework that implies that an increase in farm household off‐farm work decreases TE. We use two nationally‐representative samples of U.S. dairies (2010 and 2005 Agricultural Resource Management Surveys) and a parametric approach (stochastic frontier analysis) to empirically test the hypothesis. Results are generally consistent with the hypothesis and show that an increase in off‐farm work by the farm household is associated with a significant decrease in TE. In addition, results show that there is a statistically significant difference in TE between small, medium, and large farms. Small farms are associated with significantly higher off‐farm work and have lower TE than large farms, which implies that less off‐farm work by households with larger farms is at least partially responsible for the evidence of economies of scale in the U.S. dairy industry.     

A Parametric Approach to Estimating Eco‐Efficiency

The concept of eco‐efficiency is becoming increasingly popular as a tool to capture economic and environmental aspects of agricultural production. The literature to date has exclusively used the Data Envelopment Analysis (DEA) approach to measure producers’ eco‐efficiency. We show that it can also be estimated using a Stochastic Frontier Analysis (SFA) approach. Our approach not only allows controlling for random noise in the data but also permits an analysis of the potential substitutability between environmental pressures. We provide an empirical application of our model to data on a sample of Spanish dairy farms.     

A copula‐based approach to the simultaneous estimation of group and meta‐frontiers by constrained maximum likelihood

Existing approaches to the meta‐frontier estimation consist of two stages where the estimates of the local frontier parameters obtained in the first step are used to estimate meta‐frontier parameters by means of a linear or quadratic minimisation procedure in the second. Since it was shown by Schmidt (Review of Economics and Statistics 58: 238) that the second step is equivalent to constrained maximisation of a likelihood function, we extend this idea and offer a copula‐based approach to the estimation of the parameters of both meta‐ and group frontiers in a one‐step setting. In this way, we ensure a single data‐generating mechanism for the estimated parameters, expand the set of potential meta‐frontiers and account for the fact that shocks to the individual production units may be correlated with shocks to the local technological environment as a whole. We apply our estimation methodology to a data set on the world agriculture and find that the deviations from the group frontiers are positively correlated with deviations from the meta‐frontier, which is a conclusion that is impossible to reach without accounting for stochastic dependence between the two deviation types represented by a copula.     

The state‐contingent approach to production under uncertainty*

The central claim of this paper is that the state‐contingent approach provides the best way to think about all problems in the economics of uncertainty, including problems of consumer choice, the theory of the firm, and principal–agent relationships. This claim is illustrated by recent developments in, and applications of, the state‐contingent approach.     

Off‐farm work,technical efficiency,and rice production risk in Taiwan

This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off‐farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off‐farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off‐farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off‐farm work are more efficient than their counterparts without off‐farm work. In addition, farmers with off‐farm work face higher production risk and this result is robust for the entire distribution.     

Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis

By applying a DEA (Data Envelopment Analysis) framework and Tobit analysis, this paper aims to measure 32 Italian airports’ technical efficiency and investigate how several characteristics impact on their productivity and sustainability. Our findings show that some Italian hubs are technically efficient, although smaller airports that are dominated by low-cost carriers prove to be not least productive. Another conclusion of this paper is that efficiency and environmental impact is independent of an airport’s size, although the size matters in determining an airport’s superior performance. This article highlights how the Italian public shareholder’s system became decisive to increase efficiency in small airports due to the lack of private financing.     

Hidden action,risk aversion and variable fines in agri‐environmental schemes*

This note analyses the design of agri‐environmental schemes for risk‐averse producers whose input usage is only observable by costly monitoring. The scheme penalises producers in proportion to input use in excess of a quota. A striking result is that if the scheme is designed in such a way that producers always comply with the quota, risk aversion is not relevant in determining the level of input use.     

Eco‐efficiency of high‐yielding variety rice cultivation after accounting for on‐farm environmental damage as an undesirable output: an empirical analysis from Bangladesh

This study computes the eco‐efficiency of high‐yielding variety (HYV) rice production by including an on‐farm environmental damage index (OFEDI) as an undesirable output using data envelopment analysis. It then identifies its determinants by applying an interval regression procedure on a sample of 317 farmers from north‐western Bangladesh. Results reveal that the mean level of the OFEDI‐adjusted production efficiency (i.e. eco‐efficiency) is 89 per cent, whereas ignoring OFEDI adjustment (i.e. with OFEDI = 0) reduces the mean level of efficiency to 69 per cent, implying that the production of undesirable output or on‐farm environmental damage induces an efficiency loss of 20 per cent with significant differences across regions. The proportion of farmers’ income from HYV rice agriculture, land ownership, extension services and socio‐environmental living standard are the significant determinants of improving eco‐efficiency. Policy implications include investments in extension services and land reform measures to increase land ownership, which will synergistically improve eco‐efficiency of HYV rice production in Bangladesh.     

Resource use efficiency under self‐selectivity: the case of Bangladeshi rice producers

The paper jointly evaluates the determinants of switching to modern rice and its productivity while allowing for production inefficiency at the level of individual producers. Model diagnostics reveal that serious selection bias exists, justifying the use of a sample selection framework in stochastic frontier models. Results revealed that modern variety selection decisions are influenced positively by the availability of irrigation and gross return from rice and negatively by a rise in the relative wage of labour. Adoption of modern rice is higher in underdeveloped regions. Seasonality and geography/location does matter in adoption decisions. Stochastic production frontier results reveal that land, labour and irrigation are the significant determinants of modern rice productivity. Decreasing returns to scale prevail in modern rice production. The mean level of technical efficiency (MTE) is estimated at 0.82. Results also demonstrate that the conventional stochastic frontier model significantly overestimates inefficiency by three points (MTE = 0.79). Policy implications include measures to increase access to irrigation, tenurial reform and keeping rice prices high to boost farm returns and offset the impact of a rise in the labour wage which will synergistically increase the adoption of modern rice as well as farm productivity.     

Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model*

The main objective of this paper is to evaluate and analyse technical efficiency (TE) levels for hillside farmers under different levels of adoption of soil conservation in El Salvador and Honduras. A switching regression model is implemented to examine potential selectivity bias for high and low level adopters, and separate stochastic production frontiers, corrected for selectivity bias, are estimated for each group. The main results indicate that households with above-average adoption show statistically higher average TE than those with lower adoption. Households with higher adoption have smaller farms and display the highest partial output elasticity for land. Constraints in the land and credit markets are likely explanations for these differences. In addition, all estimated models show that TE has a positive and significant association with education and extension.     

Financial comparisons of under‐vine management systems in four South Australian vineyard districts*

Conventional viticultural practice in Australia and elsewhere involves removal of under‐vine vegetation using herbicides or cultivation. Concerns over the long‐term effects of herbicides on soil health, evolution of resistant weeds and possible impacts on human health motivate the search for alternative weed management options. Industry‐supported trials on commercial vineyards in four South Australian regions investigated standard practices of straw mulch and bare earth created with herbicides, compared to under‐vine cover crops, focusing on soil health attributes (soil carbon, soil microbiological processes, etc.) and grape yields in 2016 and 2017. Measured yields with the Control (herbicide) treatment were combined with published district grape prices and yields over the 12‐year (2006–2017) period, defining multivariate distributions of gross revenues ($/ha). Assuming all treatments produce grapes of equal quality and price as the Control, our results showed median per‐hectare gross margins greater than the Control in the Barossa district, lower than Control in Riverland, and mixed results in Langhorne Creek and Eden Valley. Multi‐year risk profiles, based on decadal whole‐farm (50 ha) cash flows for each treatment, were calculated using Monte Carlo analysis, based on historical yield and price distributions. These risk profiles showed the under‐vine treatments may result in major differences in long‐term vineyard financial viability.     

Socioeconomic aspects of rice‐fish farming in Bangladesh: opportunities,challenges and production efficiency*

In spite of the potential for rice‐fish farming in Bangladesh, it has been adopted by relatively few farmers because of socioeconomic, environmental, technological and institutional constraints. Rice monoculture remains the main farming system in Bangladesh even though integrated rice‐fish farming is the best farming system in terms of resource utilisation, diversity, productivity, production efficiency and food supply. Only a small number of farmers involve in integrated rice‐fish farming. This study concludes that rice‐fish farming is as production efficient as rice monoculture and that integrated performs better in terms of cost and technical efficiency compared with alternate rice‐fish farming. Integrated rice‐fish farming can help Bangladesh keep pace with the current demand for food through rice and fish production. However, a lack of technical knowledge of farmers, high production costs and risks associated with flood and drought are inhibiting more widespread adoption of the practice.     

Annual and cropping season environmental production conditions effects on smallholder technical efficiency in sub‐Saharan Africa: Evidence from Ethiopia

This article investigates the impact of environmental production conditions on smallholder farmers’ technical efficiency in Ethiopia for wheat, maize, and sorghum farming. We use a household panel data set with annual and cropping season environmental production conditions to estimate the technical efficiency scores. The results show that including environmental production conditions in the stochastic frontier has a significant impact on farmers’ technical efficiency scores. Technical efficiency scores improve when environmental production conditions are incorporated in the stochastic frontier. Thus, accounting for environmental production conditions reduces the inefficiencies that otherwise may be attributed to the characteristics of smallholder farmers.