Estimation of Profit Functions When Profit is Not Maximum

This paper deals with derivation and implications of profit functions when profit is not maximum due to the presence of either technical inefficiency or allocative inefficiency, or both. We show that input demand and output supply, elasticities, and returns to scale are, in general, affected by these inefficiencies. We also show that the overall profit efficiency is not necessarily the product of technical and allocative efficiencies, meaning that technical and allocative inefficiencies are not necessarily independent. Estimation techniques are developed for both cross-sectional and panel data models. Working of the model is illustrated using a panel of 60 salmon farms.     

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.     

Input‐Specific Dynamic Productivity Change: Measurement and Application to European Dairy Manufacturing Firms

We propose a new method for measuring and decomposing input‐specific productivity change in a dynamic context. The resulting input‐specific dynamic Luenberger productivity change indicator is decomposed to identify the contributions of input‐specific dynamic technical, technical inefficiency and scale inefficiency changes. The empirical application of the paper focuses on panel data of large firms in the European dairy processing industry over the period 2005–2012. The results show similar patterns for dynamic input‐specific productivity change and its components for labour across European regions (Eastern, Western and Southern), while differences between regions are found regarding materials and investments.     

Is Input Mix Inefficiency Neglected in Agriculture? A Case Study of Pig‐based Farming Systems in England and Wales

The principal concern of this article is the relative importance of input mix as a source of inefficiency. Emphasis in efficiency analysis studies in agricultural production has historically focused on technical inefficiency as a single concept until methodological advances enabled it to be decomposed into pure technical inefficiency and scale inefficiency. But, this advance was insufficient to identify what we consider to be the major source of inefficiency in agricultural production, namely mix inefficiency. We consider that farm enterprises may be particularly susceptible to input mix inefficiency because of restrictions on movement around the frontier isoquant; delays in the adoption of improved technologies embodied in new vintages of production processes; risk as a source of friction in input allocation decisions; and the potential for inconsistency in simultaneously attempting to reach points of allocative efficiency and mix efficiency in input use. We use non‐parametric methods to calculate a Hicks–Moorsteen productivity index using panel data for a sample of specialised pig producers in England and Wales. This index is then decomposed into measures of technology, technical efficiency, scale efficiency and mix efficiency for an input orientation. Results of the analysis show that the estimated mean mix inefficiency (0.736) was substantially larger than mean technical inefficiency (0.975) and mean scale inefficiency (0.957) over the study period.     

The extent of resource use inefficiencies in cotton production in Pakistan's Punjab: an application of Data Envelopment Analysis

This paper attempts to identify sources of resource use inefficiency for cotton production in Pakistan's Punjab. The use of a non‐parametric method, Data Envelopment Analysis (DEA), is developed to study the relative technical and allocative efficiencies of individual farms which use similar inputs, produce the same product and operate under comparable circumstances. In the ‘cotton‐wheat’ system of Pakistan, there are a considerable number of farms that are both technically and allocatively inefficient. The use of DEA shows that the technique provides a clear identification of both the extent and the sources of technical and allocative inefficiencies in cotton production. However, both the interpretation of the farm level results generated and the projection of these results to a higher level require care, given the technical nature of the agricultural production processes.     

Farm size,relative efficiency and agrarian policy in Côte d'Ivoire: profit function analysis of rice farms

This paper examines the relative economic efficiency of small and large rice farms in Côte d'Ivoire using a profit function approach. No differences in the relative economic efficiency of small and large farms were found. This conclusion is robust under alternative model specifications. Agrarian reforms directed towards further concentration of landholding for large farms in Côte d'Ivoire cannot be justified based on economic efficiency. Results show that access to credit and use of modern rice varieties significantly increase profits. To improve technical efficiency of rice farms, an accelerated program to provide information, credit, improved seeds and other inputs is needed. When all the farms (i.e. large and small) are taken together, there is evidence of allocative inefficiency. Strategies are needed to remove such management related inefficiencies in rice production either through the development of a better market price information system or effective farmer-oriented technical training programs by rice extension workers.     

Efficiency estimation in a profit maximising model using flexible production function

This paper uses a flexible (translog) production function to estimate efficiency of 227 farms from West Bengal, India. We consider estimation of technical and allocative inefficiencies using a profit maximising framework which accommodates both endogenous and exogenous inputs. The maximum likelihood method of estimation developed in this paper is based on the production function and the first-order conditions of profit maximisation. Farm-specific technical and allocative inefficiencies are also estimated. Empirical results show that the mean level of technical efficiency is 75.46% while the best farm is 85.87% efficient (technically). So far as allocative efficiency is concerned the majority of the farms are found to be under-users of the endogenous inputs, viz., fertiliser, manure, human and bullock labour.     

Efficiency and technical progress in traditional and modern agriculture: evidence from rice production in China

Productive efficiency for Chinese hybrid and conventional rice production is estimated using a dual stochastic frontier efficiency decomposition model. Results reveal significant differences in technical and allocative efficiency between conventional and hybrid rice production, and indicate significant regional efficiency differences in hybrid rice production, but not in conventional rice production.     

Farms’ technical inefficiencies in the presence of government programs*

We focus on determining the impacts of government programs on farms’ technical inefficiency levels. We use Kumbhakar's stochastic frontier model that accounts for both production risks and risk preferences. Our theoretical framework shows that decoupled government transfers are likely to increase (decrease) DARA (IARA) farmers’ production inefficiencies if variable inputs are risk decreasing. However, the impacts of decoupled payments cannot be anticipated if variable inputs are risk increasing. We use farm‐level data collected in Kansas to illustrate the model.     

INTER-REGIONAL FARM EFFICIENCY IN PAKISTAN'S PUNJAB: A FRONTIER PRODUCTION FUNCTION STUDY

Agricultural production efficiency in four irrigated cropping regions of the Punjab province of Pakistan was compared on the basis of a probabilistic frontier production function estimated from whole-farm survey data for the year 1984-85. It is found that the gross income of farmers can be increased by 13% at the current levels of resource use if the production gap between ‘best practice’ and ‘average’ farmers is suitably narrowed in all cropping regions. This will increase profits by up to 40%. No significant difference in technical efficiency was found across the regions. Economic efficiency was similar across all cropping regions except in the cotton region, which had significantly lower economic efficiency due to higher allocative inefficiency, which in turn was attributable to the more dynamic production technologies being adopted in that region.     

Technical,allocative and economic efficiencies in swine production in Hawaii: a comparison of parametric and nonparametric approaches

Technical, allocative and economic efficiency measures arc derived for a sample of swine producers in Hawaii using the parametric stochastic efficiency decomposition technique and nonparametric data envelopment analysis (DEA). Efficiency measures obtained from the two frontiei approaches are compared. Firm-specific factors affecting productive efficiencies are also analyzed. Finally, swine producers, potential for reducing cost through improved efficiency is also examined. Under the specification of variable returns to scale (VRS), the mean technical, allocative and economic efficiency indices are 75.9%, 75.8% and 57.1%, respectively, for the parametric approach and 75.9%, 80.3% and 60.3% for DEA; while for the constant returns to scale (CRS) they are 74.5%, 73.9% and 54.7%, respectively, for the parametric approach and 64.3%, 71.4% and 45.7% for DEA. Thus the results from both approaches reveal considerable inefficiencies in swine production in Hawaii. The removal of potential outliers increases the technical efficiencies in the parametric approach anil allocative efficiencies in DEA, but, overall, contrary to popular belief, the results obtained from DEA are found to be more robust than those from the parametric approach. The estimated mean technical and economic efficiencies obtained from the parametric technique are higher than those from DEA for CRS models but quite similar for VRS models, while allocative efficiencies are generally higher in DEA. However, the efficiency rankings of the sample producers based on the two approaches are highly correlated, with the highest correlation being achieved for the technical efficiency rankings under CRS. Based on mean comparison and rank correlation analyses, the return to scale assumption is found to be crucial in assessing the similarities or differences in efficiency measures obtained from the two approaches. Analysis of the role of various firm-specific factors on productive efficiency shows that farm size has strong positive effects on efficiency levels. Similarly, farms producing market hogs arc-more efficient than those producing feeder pigs. Based on these results, by operating at the efficient frontier the sample swine producers would be able to reduce their production costs by 38-46% depending upon the method and returns to scale considered.     

Profit Based Efficiency Measures,with an Application to Rice Production in Southern India

Using non‐parametric methods, we estimate the foregone rents due to credit, allocative, and technical inefficiencies of subsistence farmers in Southern India. The lost rents are estimated directly from the Nerlovian efficiency index, and the results suggest the largest foregone rents derive from allocative inefficiencies and then credit inefficiencies. Also, results suggest that farms without well access experience larger losses than those with well access. Econometric results suggest education, the presence of tank water management efforts, and well access influence the level of foregone rent due to allocative and Nerlovian inefficiencies. Educational activities and policies to encourage better management of tanks are considered important for lowering the foregone losses.     

Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol,Philippines

We investigated the role of spatial dependency in the technical efficiency estimates of rice farmers using panel data from the Central Visayan island of Bohol in the Philippines. Household‐level data were collected from irrigated and rainfed agro‐ecosystems. In each ecosystem, the geographical information on residential and farm‐plot neighborhood structures was recorded to compare household‐level spatial dependency among four types of neighborhoods. A Bayesian stochastic frontier approach that integrates spatial dependency was used to address the effects of neighborhood structures on farmers’ performance. Incorporating the spatial dimension into the neighborhood structures allowed for identification of the relationships between spatial dependency and technical efficiency through comparison with nonspatial models. The neighborhood structure at the residence and plot levels were defined with a spatial weight matrix where cut‐off distances ranged from 100 to 1,000 m. We found that spatial dependency exists at the residential and plot levels and is stronger for irrigated farms than rainfed farms. We also found that technical inefficiency levels decrease as spatial effects are more taken into account. Because the spatial effects increase with a shorter network distance, the decreasing technical inefficiency implies that the unobserved inefficiencies can be explained better by considering small networks of relatively close farmers over large networks of distant farmers.     

Parametric Decomposition of Output Growth Using A Stochastic Input Distance Function

This article proposes a tractable approach for analyzing the sources of TFP changes (i.e., technical change, changes in technical and allocative inefficiency, and the scale effect) in a multi-output setting, while retaining the single-equation nature of the econometric procedure used to estimate the parameters of the underlying technology. The proposed approach relies on Bauer's cost function-based decomposition of TFP changes and the duality between input distance and cost functions. The empirical results are based on a sample of 121 UK livestock farms observed over the period 1983–92 and a translog input distance function.     

Farm Household Production Efficiency: Evidence from The Gambia

This article investigates the economic efficiency of farm households, with an application to The Gambia. The efficiency analysis is conducted not at the farm level but at the household level, thus capturing the importance of off-farm activities. Output-based measures of technical, allocative, and scale efficiency are generated using nonparametric measurements. An econometric analysis of factors affecting the efficiency indexes is then conducted using a Tobit model. Technical efficiency is fairly high indicating that access to technology is not a severe constraint for most farm households. The cost of scale inefficiency is modest. Allocative inefficiency by contrast is found to be important for the majority of farm households. On the basis of the Tobit results, imperfections in markets for financial capital and nonfarm employment contribute to significant allocative inefficiency.     

Measuring the economic inefficiency of Nepalese rice farms using data envelopment analysis

A data envelopment analysis of a sample of 76 Nepalese rice farmers reveals average relative economic, allocative, technical, pure technical and scale inefficiencies as 34, 13, 24, 18 and 7 per cent, respectively. The significant variations in the level of inefficiency across sample farms are attributed to the variations in the 'use intensities' of resources such as seed, labour, fertilisers and mechanical power. In addition, a second stage Tobit regression shows the variation is also related to farm-specific attributes such as the farmers' level of risk attitude, the farm manager's gender, age, education and family labour endowment. Based on the empirical findings, policy implications and development strategies for improving efficiency of Nepalese rice farms are briefly discussed.     

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.     

Firm behaviour under uncertainty: a simple parametric model

In this paper, we model production technology in a state‐contingent framework. We assume that all the firms use the same stochastic technology, but they may have different risk attitudes and information sets, and ex post they may operate in different production environments. Firms maximise ex ante their preference function subject to a stochastic technology constraint; in other words, they are assumed to act rationally, thereby leaving no room for either technical or allocative inefficiency. We provide a simple parametric functional form to represent the state‐contingent technology. Using simple numerical examples, we illustrate how optimal input–output choices are dramatically affected when firms have different preferences and information sets. Thus, we show that the observed disparateness of production choices among different firms can actually be attributed to the stochastic nature of the decision environment.     

RECENT DEVELOPMENTS IN FRONTIER MODELLING AND EFFICIENCY MEASUREMENT

In this paper recent developments in the estimation of frontier functions and the measurement of efficiency are surveyed, and the potential applicability of these methods in agricultural economics is discussed. Frontier production, cost and profit functions are discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers. The two primary methods of frontier estimation, econometric and linear programming, are compared. A survey of recent applications of frontier methods in agriculture is also provided.     

MEASURING FARM EFFICIENCY OVER TIME ON PHILIPPINE RICE FARMS

This paper measures farm-specific technical efficiencies of rice farms in Central Luzon, the Philippines, at discrete points in time. Stochastic frontier production functions are estimated from the International Rice Research Institute's Loop Survey for the years 1970, 1974, 1979 and 1982. From the results, a measure of relative technical efficiency is calculated for each farm for each year. The four distributions of technical efficiencies are examined. Results show that technical inefficiency is the major reason for deviation from the frontier production function. All four samples show a large range of inefficiency but in general efficiency has improved, particularly between 1979 and 1982.