Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002

English and Welsh farm‐level survey data are employed to estimate stochastic frontier production functions for eight different farm types (cereal, dairy, sheep, beef, poultry, pigs, general cropping and mixed) for the period 1982 to 2002. Differences in the relative efficiency of farms are explored by the simultaneous estimation of a model of technical inefficiency effects. The analysis shows that, generally, farms of all types are relatively efficient with a large proportion of farms operating close to the production frontier. However, whilst the frontier farms of all types are becoming more efficient through time because of technical change, it is also the case that the efficiency of the average farm for most farm types is increasing at a slower rate. In addition, annual mean levels of efficiency for most farm types have declined between 1982 and 2002. The factors that consistently appear to have a statistically significant effect on differences in efficiency between farms are: farm or herd size, farm debt ratios, farmer age, levels of specialisation and ownership status.     

Mismeasurement and efficiency estimates: Evidence from smallholder survey data in Africa

Smallholder agriculture in sub-Saharan Africa is commonly characterised by high levels of technical inefficiency. However, much of this characterisation relies on self-reported input and production data, which are prone to systematic measurement error. We show theoretically that non-classical measurement error introduces multiple identification challenges and sources of bias in estimating smallholders' technical inefficiency. We then empirically examine the implications of measurement error for the estimation of technical inefficiency using smallholder farm survey data from Ethiopia, Malawi, Nigeria and Tanzania. We find that measurement error in agricultural input and production data leads to a substantial upward bias in technical inefficiency estimates (by up to 85% for some farmers). Our results suggest that existing estimates of technical efficiency in sub-Saharan Africa may be severe underestimates of smallholders' actual efficiency and what is commonly attributed to farmer inefficiency may be an artefact of mismeasurement in agricultural data. Our results raise questions about the received wisdom on African smallholders' production efficiency and prior estimates of the productivity of agricultural inputs. Improving the measurement of agricultural data can improve our understanding of smallholders' production efficiencies and improve the targeting of productivity-enhancing technologies.     

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.     

Analysis of the technical efficiency of state rubber farms in Vietnam

This study entails an analysis of the technical efficiency of natural rubber production by state farms in Vietnam. A time-varying stochastic frontier production function model for unbalanced data is estimated for 33 farms. Individual farm technical efficiencies are reported and discussed. One of the main results concerns the bimodal distribution of technical efficiency indices. A few farms operate near the production frontier while the bulk operate well away from the frontier. Some implications are drawn from the results as a guide to future policy research work in the rubber industry in light of recent moves by the Vietnamese government towards economic reform.     

鲤科鱼类池塘养殖技术效率的研究

本文应用随机边界产量函数对我国鲤科鱼类池塘养殖的技术效率进行了分析。通过对全国7个省283个渔场的鲤科鱼类池塘养殖生产情况的分析，表明我国鲤科鱼类池塘养殖总体技术效率水平较高，平均技术效率水平达到70．8％。本文还对影响技术效率的主要因子进行了分析，并就如何进一步提高我国水产养殖生产的技术效率进行了探讨。     

Estimation of input-oriented technical efficiency using a nonhomogeneous stochastic production frontier model

Technical inefficiency can be modeled as either input‐oriented (IO) or output‐oriented (OO). However, in the estimation of parametric stochastic production frontier models which use maximum likelihood method only the OO measure is used. In this article we consider a simple nonhomogeneous production function and estimate it with both IO and OO specifications. A sample of 80 Spanish dairy data (1993–1998) is used to estimate both models. We consider one output (liters of milk) and four variable inputs (viz., number of cows, kilograms of concentrates, hectares of land, and labor [measured in man‐equivalent units]). We find that returns to scale (RTS) and technical efficiency results derived from these models are different because either estimated technologies are different, or they are evaluated at different points. Using a Monte Carlo analysis we show that if RTS is close to unity differences in the estimates of RTS and technical efficiency are smaller. This holds true for estimates of both RTS and technical efficiency.     

The Impact of Direct Income Transfers of CAP on Greek Olive Farms’ Performance: Using a Non‐Monotonic Inefficiency Effects Model

We analyse the impacts of direct income transfers on the technical efficiency of Greek olive farms. We use a production frontier function and a non‐monotonic inefficiency effects model, which incorporates the influences of exogenous variables (subsidies, farm characteristics, etc.) on technical efficiency. The model is applied to 1995–2004 FADN data. The results show that direct transfers of the CAP had a negative and monotonic effect on technical efficiency, whereas the degree of specialisation had a non‐monotonic effect on technical efficiency.     

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.     

ALTERNATIVE PRODUCTION FRONTIER METHODOLOGIES AND DAIRY FARM EFFICIENCY

This paper estimates technical efficiency (TE) measures using four alternative production frontier models, and evaluates the sensitivity of the results to the choice of methodology. The Cobb-Douglas functional form along with data for 1982 and 1983 from 404 dairy farms located throughout six northeastern states in the US are used in the estimation. A general conclusion is that, broadly speaking, frontier function models are neutrally upwardly scaled versions of the OLS or average model. A second conclusion is that different models yield markedly different efficiency levels across firms. However, the correlation between the indexes from the various methods is high, which implies that the ordinal ranking of firms according to their measured level of technical efficiency appears to be independent of the method used for a given year. By comparison, the correlation between efficiency indexes for the same method across time, although positive, is much lower than the previous set of correlations. Correlation analysis of efficiency versus farm size and of efficiency versus returns over variable costs, based on the alternative models, yielded consistent results.     

Are small‐scale rice farmers in eastern India really inefficient? Examining the effects of microtopography on technical efficiency estimates

The article analyzes how controlling for differences in land types (defined by position on a low‐scale toposequence) affects estimates of farm technical efficiency for rice farms in eastern India. Contrasting previous research, we find that farms are considerably more technically efficient when efficiency estimates are carried out at the plot level and control for plot characteristics rather than at the farm level without such controls. Estimates show farms cultivating modern varieties are technically efficient and plots planted with traditional varieties on less productive lands (upland and midupland) operate close to the production frontier. Significant technical inefficiency is found on more productive lands (medium and lowland plots) planted with traditional rice varieties. The finding that these smallholder rain‐fed rice farms are efficient cultivators on some plots contrasts with previous findings of farm‐level inefficiency (i.e., rejects overarching explanations linked to farm operator ignorance or lack of motivation) and suggests more complex explanations are required to address the inefficiency that is present.     

Measuring technical efficiency in the stochastic varying coefficient frontier model

Due to the assumption that the best practice methods refer to each input separately instead of the whole set of inputs used by a firm, the benchmark technology as defined in the stochastic varying coefficient frontier model may be infeasible and theoretically improper whenever the maximum response coefficients are not coming from the same production unit. To overcome this problem, we propose alternative measures of output-oriented and single-factor technical efficiencies inspired from the maximum likelihood formulation of the nonneutral frontier model. The empirical results indicate that there are significant differences between the two in terms of the estimated efficiency scores but not significant differences we detected in terms of the efficiency ranking.     

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.     

MEASUREMENT OF TECHNICAL EFFICIENCY IN THE NORTH-WEST FRONTIER PROVINCE OF PAKISTAN

The objective of this study is to measure technical efficiency, using a translog frontier production function on cross-sectional data from 397 farms in the North-West Frontier Province of Pakistan in 1988–89. The estimated farm level technical efficiency is found to be dependent upon levels of credit and education, farmers' ages and the extent of land fragmentation. Lack of education, restricted credit and fragmented holdings are found to be causes of inefficiency; hence policies which consolidate holdings, provide credit or educate farmers will tend to improve efficiency in agriculture.     

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.     

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.     

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.     

Measuring managerial efficiency: the case of commercial greenhouse growers

Recently the managerial decision making process has been given new attention, both in theoretical studies as well as in empirical research explaining differences in farm results. However, while critical to explaining efficiency, managerial ability has been difficult to measure and therefore often ignored. This study attempts to measure managerial ability. It divides the decision making process into four steps: goal formulation, planning, monitoring and evaluation. The quality of each step is measured in a panel of 26 specialised flower producers, The impact of decision making on the firms' efficiencies is measured by means of a stochastic frontier production function. A one‐step procedure is used in which technical and decision making parameters are jointly estimated. The results show positive associations between firm efficiency and the quality of decision making (especially monitoring and firm evaluation), indicating that this procedure has been potentially successful and is a move towards successfully measuring a critical input.     

Productivity in Chinese Provincial Agriculture

Technical change, technical efficiency and multifactor productivity indices are reported for a multiple-output, multiple-input production technology using Chinese provincial data for the 1979-95 period. Results show significant variation in productivity change from year to year and province to province. Using panel methods, we regress the three production indices on several factors important in explaining productivity changes. Decollectivisation in the early 1980s accounts for a significant expansion of the frontier, while rural industrialisation decreased agricultural productivity. Productivity is also sensitive to relative grain prices, to natural disasters such as flood and drought, and proximity of the provinces to coastal areas.