Determinants, differentiation, and development of short-term marginal costs in dairy production: an empirical analysis for selected regions of the EU

This work provides evidence on the determinants, cost differentiation, and development of short‐term marginal costs of dairy farms in important production regions of the European Union. The empirical study is based on the estimation of multi‐input multi‐output Symmetric Generalized McFadden cost functions using an unbalanced panel data set of the European Farm Accountancy Data Network. The results show considerable regional differences in the impact of the outputs, input prices, and fixed factors on marginal costs. Strong evidence can be found that marginal costs decrease over time and is further underlined by the development of derived regional aggregated short‐term supply curves. Marginal cost elasticities and correlation coefficients validate the hypotheses that a high degree of farm specialization, large milk output, and low milk prices are associated with lower marginal costs. Furthermore, the marginal cost spread in the data sample is analyzed. We show that milk output, milk yield, herd size, labor input, and fodder production can be attributed to significant marginal cost differentiation of farms, whereas for crop and animal output, grassland, stock of other animals, and depreciation only minor differentiation can be found.     

Technical efficiency of Kansas arable crop farms: a local maximum likelihood approach

This study uses local maximum likelihood (LML) methods recently proposed by Kumbhakar et al. (2007) to assess the technical efficiency of arable crop Kansas farms. LML techniques overcome the most relevant limitations associated to mainstream parametric stochastic and nonparametric frontier models. LML allows deriving farm‐level frontier parameter estimates. The relevance of using localized estimates is evidenced by the observed heterogeneity in production technologies. Technical efficiency scores derived from the LML approach [0.905] are higher than those of the DEA model under CRS [0.808] and SFA [0.804] and close to DEA‐VRS [0.917] ratings. Deriving reliable information about farm efficiency performance is relevant to identify inefficient farms and define adequate policy and management strategies. The use of refined methods has thus important implications.     

Technical and scale efficiency of crop and livestock farms in Poland: does specialization matter?

The technical and scale efficiency of Polish farms is analyzed using data envelopment analysis. Efficiency differences are measured according to farm specialization, in crop or livestock, at two points in time during transition, 1996 and 2000. The efficiency results are reviewed in light of confidence intervals provided by bootstrapping. Livestock farms are found to be, on average, more technically and scale efficient than crop farms. Scale efficiency is high for both specializations. Technical inefficiency appears mostly to be due to “pure technical” rather than “scale” inefficiency, and thus attributable to inefficient management practices. The evidence suggests that the low‐educational attainment of people engaged in agriculture is one important reason for these inefficient practices. In 2000, 64% of livestock farms and 86% of crop farms were operating under increasing returns to scale. Improvements in the land lease legislation and changes to the policy support to farmers' pensions could stimulate the land market and remove the incentives to keep a fragmented operational structure.     

Examining the relationship between farm size and productive efficiency: a Bayesian directional distance function approach

Achieving sustainable food security and increased farm income will depend on how efficient production systems are in converting available inputs to produce outputs. Using data from Malawi, we estimate a Bayesian directional technology distance function to examine the relationship between farm size and technical efficiency. Our results support the existence of an inverse relationship between farm size and productive efficiency, where small farms are more efficient than large farms. On average, farms exhibit inefficiency levels of 60%, suggesting that productivity could be improved substantially. Improving productive efficiency and food security will require farms to operate in ways where the size of cultivated area is matched by nonland production inputs such as labor, fertilizer, and improved seeds. The results highlight the need for policies that could incentivize farmers to adopt productivity‐enhancing technologies and, where possible, to allocate excess land to lease markets.     

Cost and environmental efficiency of rice farms in South Korea

We examine cost and nutrient use efficiency of farms and determine the cost to move farms to nutrient‐efficient operation using Data Envelopment Analysis (DEA) with a dataset of 96 rice farms in Gangwon province of South Korea from 2003 to 2007. Our findings show that improvements in technical efficiency would result in both lower production costs and better environmental performance. It is, however, not costless for farms to move from their current operation to the environmentally efficient operation. On average, this movement would increase production costs by 119% but benefit the water system through an approximately 69% reduction in eutrofying power (EP). The average estimated cost of each EP kg of aggregate nutrient reduction is approximately one thousand two hundred won. For technically efficient farms, there is a trade‐off between cost and environmental efficiency. We also find that the environmental performance of farms varies across farms and regions. We suggest that agri‐environmental policies should be (re)designed to improve both cost and environmental performance of rice farms.     

Environmental impacts of technological change in Bangladesh agriculture: farmers' perceptions, determinants, and effects on resource allocation decisions

This article measures the impact of modern technology adoption in raising farmers' environmental awareness and the impact of farmers' environmental awareness on resource use by utilizing survey data from 21 villages in three agro‐ecological regions of Bangladesh. The econometric analysis is based on the application of the Tobit model explaining farmers' environmental awareness in the first stage and a profit function examining environmental awareness and resource use relationships in the second stage. Results reveal that the “level” and “duration” of involvement with modern technology raises farmers' environmental awareness, and that farmers' environmental awareness reduces resource use including chemicals. Farmers, who are aware of the adverse environmental impacts of modern agricultural technology, use lower amounts of all inputs in order to avoid further environmental damage. Therefore, efforts to raise farmers' environmental awareness are expected to enhance intangible benefits accruing from a relatively less chemical‐intensive environment.     

Demand for meat and dairy products by Turkish households: a Bayesian censored system approach

We extend the Tobit (censored) linear equation system procedure to utility‐theoretic demand functions, along with a mapping mechanism to impose the adding‐up restriction implied by consumer utility maximization theory—a theoretical restriction very often ignored in previous empirical studies with censored demand systems. In this context, the Bayesian Markov Chain Monte Carlo (MCMC) procedure is applied to the censored linear approximate almost ideal demand system (LAIDS) for 12 food products, using data from the Turkish Household Expenditure Survey. All own‐price elasticities are negative and expenditure elasticities positive. Uncompensated own‐price elasticities for rural households are generally much higher than those for their urban peers, though demand for most food products are own‐price elastic for both types of households. The differential patterns in demand elasticities between urban and rural households become even more evident (almost twice) as relatively more expensive foodstuffs are consumed, showing that accessibilities to alternative products have made rural Turkish households more cognizant toward price changes in foods. Household characteristics play a key role in food expenditures, notably so in urban areas, and regional and seasonal differences are also present.     

Reducing nutrient loads from dairy farms: a bioeconomic model with endogenous feeding and land use

Growth trends of animal farming pose a threat to water quality around the world. To find cost‐efficient means to reduce nutrient loads from agriculture, detailed information on the abatement measures need to be incorporated in bioeconomic models. This study presents a theoretical framework that covers both animal and crop operations on farms. It describes the farmer decision making problem and incorporates nonlinear functions to capture the economic and biological aspects of the problem. The model is applied to Finnish dairy farms. The abatement cost functions are derived for nitrogen and phosphorus. Results indicate that abatement measures on fields should precede dietary changes.     

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.     

Land inequality and economic growth: a dynamic panel data approach

The growing body of literature devoted to studying the impact of inequality on economic growth has centered its attention on the income distribution effect, even though the theoretical relationships are more related to assets distribution. While some recent studies have tried to overcome this limitation by introducing asset indicators, they meet new constraints when dealing only with time-invariant measurements for this explanatory variable. This article provides a theoretical discussion and some novel empirical tests to better understand the relationships between assets distribution and economic growth. We assembled a new panel database that includes observations for more than 30 countries over the last three decades. The data include a time-varying variable for changes in the Land Gini index over this period that enables us to overcome the limitations of previous studies. A system general method of moments (GMM) estimator is used to generate truly unbiased and consistent estimates for the parameters of interest. We explore some of the likely channels through which asset distribution and economic growth may be linked, paying particular attention to the role of secure property rights and the relations between land ownership and education. We find robust and significant negative signs for land inequality in the growth regressions, indicating that changes in asset distribution are an important factor for economic development.     

Specialization,diversification, and productivity: a panel data analysis of rice farms in Korea

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm‐level panel data, the analysis studies farm productivity in a multi‐input multi‐output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize.     

Technical efficiency and farm size: a conditional analysis

The relationship between technical efficiency and size might be affected by farm heterogeneity. We analyse this relationship conditional on a set of control variables. These control variables are chosen using a production model where technical efficiency is introduced as a parameter. As a result, technical efficiency affects both the input demand and the output supply of a profit maximising producer. The empirical application explores these issues using panel data of dairy farms in Spain.     

Outsourcing and efficiency: the case of Spanish citrus farming

Outsourcing in agriculture has traditionally been seen as a managerial strategy of smaller farms to achieve higher levels of efficiency. In this article, we provide empirical evidence supporting the existence of a positive relationship between outsourcing and efficiency in Spanish citrus farming. Outsourcing is measured by the proportion of outsourced labor and capital in farms' total use of these production factors, i.e., the higher the proportion of outsourced inputs, the higher the degree of outsourcing. Making use of data envelopment analysis techniques, we compute input‐specific reductions required to achieve technical efficiency at the farm level. Our results show that attainment of technical efficiency leads to a reduction in the use of both farms' own and outsourced production factors. Furthermore, the degree of outsourcing increases as farms move to their technically efficient productive plans. In addition, outsourcing labor and capital allows farms to achieve efficiency regardless of their size. In our view, this result has a clear implication for policy makers. Instead of trying to improve Spanish citrus farms' competitiveness by pursuing an increase of their average size, policy measures should be adopted to enhance farmers' managerial skills and the efficiency of those external service firms and co‐operatives that are effectively performing basic cultivation tasks.     

Technical efficiency,herd size,and exit intentions in U.S. dairy farms

The U.S. dairy industry has seen major restructuring in recent decades. A sharp decline in the number of U.S. dairy farms and an increase in average herd sizes have accompanied exits, which have been concentrated among smaller herds. Given that more productive farms are better positioned to increase operation size and to continue operation, we hypothesize that the more technically efficient farms are better able to expand and also have stronger incentives to continue production. Using data from the USDA's 2010 ARMS Phase III, Dairy Production Practices and Costs and Returns Report, we estimate technical efficiency using stochastic production frontier analysis with endogenous inputs. The efficiency estimate is then incorporated into the analysis of exit intention and herd size. The results confirm our hypotheses that smaller and less efficient farms are more likely to exit and that more efficient dairy farms tend to expand herd size. Moreover, farms without successors but with older and more educated operators are more likely to exit.