The role of family life-cycle events on persistent and transient inefficiencies in less favoured areas

Family farms dominate less favoured areas (LFAs) within Europe, and family life-cycle conditions, such as succession and retirement, affects how these farms adapt to changing circumstances. Past studies of on-farm technical efficiency have not directly addressed these conditions, but they may explain why some farms are more efficient than others, especially as the farm family model dominates most farming systems. Motivated by the UK's withdrawal from the EU and the debate around establishing replacement support policies, we apply a multi-step model to measure both transient and persistent inefficiencies using a panel of LFA cattle and sheep farms in Scotland over the period 2003–2020. We find a greater prevalence of persistent compared to transient inefficiency, which suggests that structural problems still exist. Farms with planned succession are found to have higher persistent efficiencies, whereas farmers nearing retirement have lower levels. Other factors, such as dependence on subsidy, off-farm activity and classification as severely disadvantaged tend to compound these lower efficiencies. We argue that life-cycle conditions should not be ignored in studies of farm technical efficiency. Within the scope of framing a new agricultural policy for UK administrations, these results inform the debate on support for LFAs, as well as the promotion of support towards generational renewal to ease transition across farm family life-cycle events.     

Input and output technical efficiencies of wheat production in Kerman, Iran

The Iranian government encourages farmers to produce wheat (a common agricultural enterprise) by increasing farm productivity and efficiency. In this paper, using a Cobb–Douglas frontier production function, a simple relationship between a farm‐level output‐based technical efficiency measure (the Timmer index) and an input‐based measure (the Kopp index) is first developed. Then, using 1995 data from 164 farms in Kerman province, Iran, the average Timmer and Kopp indexes were estimated at 0.93 and 0.91, respectively, and were found to be similarly affected by farm size (positively up to about 9 ha) and by input ratios, though with rather small explanatory power. Thus, there seems some but limited scope to increase the profitability of Iranian wheat production either by increasing the product, given input levels, or by decreasing inputs for the current level of wheat production. However, since wheat producers may be able to adapt their production process more easily and quickly by implementing new techniques, i.e. by more efficient combination of inputs, than by adopting new technology, correction of input over‐use can be regarded as a policy with speedy if limited effect in this case.     

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.     

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.     

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.     

Do family farms really converge to a uniform size? The role of unobserved farm efficiency*

We analyse the growth of family farms in Israeli cooperative villages during a period of economic turmoil. We use instrumental variables to account for the endogeneity of initial farm size, and correct for selectivity as a result of farm survival. We also include a technical efficiency index, derived from the estimation of a stochastic frontier production model, as an explanatory variable. Our aim is to check whether ignoring efficiency could have been the reason for convergence results obtained elsewhere in the literature. We found that technical efficiency is an important determinant of farm growth, and that not controlling for technical efficiency could seriously bias the results. In particular, larger farms are found to grow faster over time, while without controlling for technical efficiency the farm growth process seemed to be independent of initial farm size. The increasing polarisation of farm sizes in Israel has ramifications for the inefficiencies induced by the historical quota system, for the political power of the farm sector and for the social stability of farm communities.     

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.     

Economic efficiency in farm households: trends, explanatory factors, and estimation methods

Factors explaining differences in economic efficiency between farms are of major interest to owners, managers, and other stakeholders as they strive to improve earnings and improve the chances of firm survival. This study is undertaken to improve our understanding of interfarm differences in, and opportunities to improve, farm household efficiency in utilizing their land, labor, and capital resources to achieve household objectives. The technical, allocative, and scale efficiencies of farm households are estimated using a nonparametric, output-based data envelopment analysis (DEA) of a panel data set from 1993 to 2006. Single and double bootstrapping procedures are used to estimate technical efficiency. Initial technical efficiency assuming variable returns to scale (TEV) is estimated to be 0.83. Using single bootstrapping, the average bias-corrected TEV estimate is 0.70; using double bootstrapping, the TEV estimate is 0.72. Allocative efficiency is estimated to be 0.81. Scale efficiency is estimated to be 0.93. The only factor that is consistently associated with higher technical efficiency across analysis methods and years is larger farm size (as measured by the log of farm income). The significance of other factors changes with analysis methods.     

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.