Efficiency of Investor Owned Firms and Cooperatives Revisited

Providing a performance measure of any firm is a crucial issue, not only for the stakeholders of the firm, but also for policy makers, labor unions, and economists. The relevant performance measures should consider the objectives of the firm’s owners. The ownership structure of cooperatives is different from that of investors owned firms, which in principle implies the need of different tools to measure their performance. Typically, however, the performance of cooperatives and investor owned firm is mostly compared using the same approach. In this study, we use Data Envelopment Analysis (DEA) to compare the performance of dairy cooperatives and investor owned firms in major European dairy producing countries using a traditional approach, which views both types of firms as cost minimizers, and an alternative approach, which considers the objectives of the cooperatives. In the alternatives approach, two hyperbolic models were evaluated, one of them consider the firms to expand both output production and use of material to address the objective of the owners of the cooperatives. The performance of the cooperatives changes across the two approaches form being out performed by IOFs using the traditional approach to outperforming IOFs when using an approach that is in line with the objective of the cooperative.DEA, hyperbolic efficiency, cooperatives, Investor Owned Firms, Bootstrapping, Agricultural and Food Policy,

Comparative Analysis of Technical Efficiency in European Agriculture

Technical efficiency has long been analysed as a measure of farm performance, however most studies are restricted to a single country case. This paper presents a comparative analysis of field crop and dairy farm performance across eight EU countries, including two New Member States (NMS), focusing on long run stability and mobility patterns. The main research question is how relative performance of farms fluctuates over time, i.e. whether poorly performing farms remain always inefficient whilst some farms are always very efficient. Results show that on average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions, for all countries. Due to the unstable economic conditions, farms in NMS are more mobile than those in EU15.Farm technical efficiency, SFA, FADN, stability analysis, Farm Management, P52, Q12,

Efficiency of Investor Owned Firms and Cooperatives Revisited

Providing a performance measure of any firm is a crucial issue, not only for the stakeholders of the firm, but also for policy makers, labor unions, and economists. The relevant performance measures should consider the objectives of the firm’s owners. The ownership structure of cooperatives is different from that of investors owned firms, which in principle implies the need of different tools to measure their performance. Typically, however, the performance of cooperatives and investor owned firm is mostly compared using the same approach. In this study, we use Data Envelopment Analysis (DEA) to compare the performance of dairy cooperatives and investor owned firms in major European dairy producing countries using a traditional approach, which views both types of firms as cost minimizers, and an alternative approach, which considers the objectives of the cooperatives. In the alternatives approach, two hyperbolic models were evaluated, one of them consider the firms to expand both output production and use of material to address the objective of the owners of the cooperatives. The performance of the cooperatives changes across the two approaches form being out performed by IOFs using the traditional approach to outperforming IOFs when using an approach that is in line with the objective of the cooperative

Comparative Analysis of Technical Efficiency in European Agriculture

Technical efficiency has long been analysed as a measure of farm performance, however most studies are restricted to a single country case. This paper presents a comparative analysis of field crop and dairy farm performance across eight EU countries, including two New Member States (NMS), focusing on long run stability and mobility patterns. The main research question is how relative performance of farms fluctuates over time, i.e. whether poorly performing farms remain always inefficient whilst some farms are always very efficient. Results show that on average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions, for all countries. Due to the unstable economic conditions, farms in NMS are more mobile than those in EU15

EU farms’ technical efficiency and productivity change in 1990 – 2006

In this paper we analyse and compare various efficiency indicators for a number of European Union (EU) countries: Belgium, Estonia, France, Germany, Hungary, Italy, The Netherlands and Sweden. The availability of long period datasets between 1990 and 2006, allow us to concentrate on the long time trends in technical efficiency especially in Old Member States. This study is the first which may provide a comprehensive overview on the development in farm level efficiency across eight European countries. Our main results are the following. Generally, all countries have relatively high levels of mean technical efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly the majority of countries have better performance in dairy sectors in terms of higher levels of mean efficiency than in field crop production. A slightly decreasing trend however may be observed for all countries. Technical Efficiency estimates are largely in line with those obtained by previous studies. Stability analysis revealed that in average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions for all countries. However, these ratios slightly fluctuate around these values for one year to next year. Mobility analysis ranks countries according to the mobility of SFA scores within the distribution. Farms in New Member States are more mobile than those in EU15. Total productivity changes are analysed in two steps. First, we do not find a definite trend in total factor productivity changes. Second, we address the question whether total factor productivity changes converge or diverge over time. Using panel unit root tests our estimations reveal a convergence of productivity across old EU member countries during analysed period. Finally, we decompose the total factor productivity changes into its main elements. Field crop farm indicators generally present significantly higher volatility than dairy farms. Random effect panel regression of Total Factor Productivity Change on its components shows Technological Change as being the significant positive driver for crop farms, whilst Technical Efficiency Change followed by Technological Change are the most important for dairy farms. In addition we do not find significant impacts of CAP reforms in 1992 and 2000 on total productivity changes

EU farms’ technical efficiency, allocative efficiency, and productivity change in 1990-2006

FACEPA Farm Accountancy Cost Estimation and Policy Analysis of European Agriculture. European Community’s Seventh Framework Programme [FP7/2007-2013] agreement no. 212292EU farms’ technical efficiency, allocative efficiency, and productivity change in 1990-200