Modelling Synergies and Scope Economies between Farm Enterprises and Ecosystem Outputs in the Agricultural Sector in England and Wales
Interest has been growing in the nature of synergies in agroecosystems, prompted in part by growing concerns about the effects of environmental degradation on agricultural productivity and interrelations between agricultural outputs and ecosystem outputs. Most productivity analyses focus on technology, technical inefficiency and scale effects on productivity; yet scope economies derived from synergies can also have substantial effects that are likely to increase in the future. Scope economies take on special importance when farms diversify to halt declining biodiversity and other forms of environmental degradation. We present results of an empirical case study based on panel data on farms in England and Wales. A stochastic input distance function is estimated using Bayesian methods that enable economies of scope to be calculated between pairs of outputs based on the derivatives of the input distance function. Results confirm the presence of scope economies from diversity, providing prima facie evidence that diversity is beneficial in farming systems in England and Wales. But a number of challenges lie ahead to improve the data set and method of measuring scope economies for further substantiation of this evidence. Chief among them is the need to obtain a better measure of ecosystem outputs. The complexity of agroecosystems, with their diverse elements and numerous interactions between elements, presents a major challenge for data collection.
Performance Measurement of Extensive Beef Cattle Farms in Botswana
This paper examines the technical efficiency of extensive beef farms in different regions of Botswana and attempts to explain differences in regional performance in terms of environmental and economic constraints. Using a panel dataset of 26 agricultural districts (distributed across six agro-ecological regions) for the period 2004 to 2012, we estimate technical efficiency (TE) indices using a standard stochastic production frontier and meta-technological gap ratios (MTR) with a meta-frontier approach. The study finds that farmers use available technology suboptimally and produce far less than potential output. The average TE indices range from as low as 0.40 for Maun, 0.71 for Western and to 0.79 for the Southern region. The mean MTR also varies substantially across regions; high for Western (0.83), Southern (0.80) and Francistown (0.79) regions and low for the Maun region (0.39). A low MTR for the Maun region is attributed to the re-occurrence of FMD and human and wildlife conflict in this region, restricting the ability of farmers to fully reach their potential output. The results of this study have important implications for policy targeting. The study results allow us to identify the differences in productive performance between beef producers in each region of Botswana, and hence where policies to improve production technologies could be focused.
Agricultural Productivity, Efficiency and Growth in a Semi-Arid Country: Case Study of Botswana, 1979-2012
To improve the welfare of the rural poor and to decrease the dependence of the national economy on minerals, the government of Botswana has been spending 40% of the value of agricultural GDP on agricultural support services. Despite this massive investment, there is evidence that agricultural productivity has declined in recent years. This paper attempts to explore the reasons for this decline. We use secondary data from six regions of Botswana (covering the period 1979 to 2012) to construct a Fare-Primont index of productivity following the approach proposed by O'Donnell (2012). The results of the analysis show that annual TFP has gradually declined over the period. This decline is predominantly due to technological regress which is offset by some increase in scale and mix efficiency.
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.
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.