The availability of efficiency estimation software -freely distributed via the internet and relatively easy to use -recently inflated the number of corresponding applications. The resulting efficiency estimates are used without a critical assessment with respect to the literature on theoretical consistency, flexibility and the choice of the appropriate functional form. The robustness of policy suggestions based on inferences from efficiency measures nevertheless crucially depends on theoretically well-founded estimates. This paper adresses stochastic efficiency measurement by critically reviewing the theoretical consistency of recently published technical efficiency estimates. The results confirm the need for a posteriori checking the regularity of the estimated frontier by the researcher and, if necessary, the a priori imposition of the theoretical requirements. JEL classification codes: C51, D24, Q12

The paper explores and analyses the catching up and falling behind processes in the European dairy sector over the period 2004–2011, using a stochastic metafrontier multiple output distance function for 24 EU Member States. The metafrontier estimates reveal considerable productivity differences in milk production across the EU at the regional (NUTS‐2) level. Milk yield per cow is the highest in the old Member States, especially in those regions located in the northwest of the EU, while the lowest productivity is observed in Eastern Europe. The same structure was found for both the TFP (Total Factor Productivity) levels and TFP growth. Moreover, the results for technical change suggest that farm sizes are not optimal in many regions in Central and Eastern Europe from a dynamic perspective. The comparative analysis suggests that in the new compared to the old Member States, fewer farms could benefit from the movement of the frontier. Moreover, there are no signs that poorly performing farms are catching up with the best performing farms in the EU regions/countries.

SummaryThis paper aims to contribute to a better understanding of possible causes of considerable production variability that characterised Russian agriculture during the last decade. The study investigates production risk and technical inefficiency as two sources that influence production variability. Using panel data from 1996 to 2001, an empirical analysis of 443 large agricultural enterprises from three regions in central, southern and Volga Russia is conducted. A production function specification accounting for the effect of inputs on both risk and technical inefficiency is found to describe production technologies of Russian farms more appropriately than the traditional stochastic frontier formulation.

Flexibility can be considered as a crucial factor of competitive advantage, especially under conditions of dynamically changing environments. Based on the classical microeconomic definition of flexibility, as introduced by Stigler, and some recent concepts developed in the production economics, this article proposes a primal flexibility measure for multi-product firms. When decomposed, this measure offers useful insights into possible sources of flexibility, especially by investigating the role of both scale and scope economies. This approach provides the theoretical basis to investigate the magnitude and sources of flexibility in the Polish agricultural sector during the transition period.

This paper analyses regional productivity and technical efficiency development in Russian agriculture. We formulate a regional stochastic frontier model by assuming that producers maximise return to the outlay. We control for regional heterogeneity and endogeneity/simultaneity in input decisions, technical efficiency and technical change by employing a two-step estimation procedure. In the first step, we use the system Generalized Method of Moments approach (system GMM), which gives consistent estimates of the production technology parameters. In the second step, we apply the standard stochastic frontier approach to estimate technical efficiency and its determinants.

In this paper, the NEIO approach is extended to allow for oligopsony power in successive markets of a value chain. Two price equations are deduced from simultaneous partial equilibria of the endogenous variables and are embedded in a VECM to account for a long-run cointegration relationship. The model is estimated via the Kalman-Filter to allow for time variation in the long-run parameters, and a dynamic factor model used to extract a common factor from the time-variant coefficients. The results are then used to calculate the industry average input conjectural elasticities. The framework is applied to German dairy value chain data over the time period of

Článek je zaměřen na analýzu tržní síly na trhu mléčných výrobků. Konkrétně článek identifikuje tržní sílu zpracovatelského trhu mléka ve 24 zemích Evropské unie. Analýza tržní síly je založena na tzv. markup modelu a aplikaci přístupu stochastické hraniční funkce. Výsledky prokazují tržní selhání na zpracovatelském trhu mléka v Evropské unii. Zmíněné zneužití oligopolní tržní síly není v průměru velké. Mezi analyzovanými zeměmi však existují významné rozdíly. Rozdělení tržní síly je sešikmené směrem k nižším hodnotám, což znamená, že většina společností disponuje nízkou nebo téměř žádnou tržní silou. Na druhou stranu zde však existují i společnosti (okolo 10 %) se značně vysokou tržní silou.

Abstract:The paper attempts to assess the development path of the Czech food processing and to identify the presence of idiosyncratic developments in industries. We elaborate it by using a fi tted production function for the construction of TFP and by decomposing TFP into a scale effect, a technical change effect and an effi ciency effect for total food processing and its selected branches. The results suggest that despite more than one decade of transition, serious adjustment problems exist, including problems on the capital market. Furthermore, contrary to the large differences among fi rms in the whole sample, the various sectors are rather homogeneous. TFP shows that although individual sectors have a few frontrunners, the majority of companies perform quite poorly. The scale effect is relatively small in food processing. Technical change has contributed positively to TFP in recent years, and the effi ciency effect varies rather strongly. Whereas scale effect and technical change have a similar pattern across industries, the effi ciency effect differs signifi cantly. There is also some indication that the effi ciency effect is affected by different sources. Finally, in addition to systemic effects, industry developments are characterized by idiosyncratic factors, especially in the Dairy industry.