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SOME ASPECTS OF TECHNICAL EFFICIENCY MEASUREMENT ON FARMS

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Ziolkowska J.
Zagadnienia Ekonomiki Rolnej
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2008
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issue 2(315)
54-68
EN
Productivity and efficiency constitute basic criteria for assessment of economic entities. The paper presents considerations concerning technical efficiency. The considerations were illustrated by empirical research on the basis of data originating from farms rated in the 'List of 300 best farms' ranking for years 2005 and 2006 (panel). Calculations were performed with the use of non-parametric method of Data Envelopment Analysis (DEA). Initial data for DEA model (effect oriented BCC) adopts Y - for income from sales increased by subsidies, X1 - for area of cropland, X2 - for costs of power and materials, X3 - for labour cost with secondary costs of labour and X4 - for amortization. In effect technical efficiency indicator VRS has been obtained together with scale efficiency indicator (SCALE). Highest mean VRS value (0,909) was obtained by purchased objects whereas, best results of SCALE indicator (0,979) have been reached by leaseholders, what essentially was to be expected just in that group. Unfortunately, high value of VRS indicator does not always translate into high rentability of sales (ROS).
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Homogeniczny bootstrap Simara i Wilsona w estymacji miary efektywności technicznej

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Prędki A.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
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2012
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issue 884
103-117
EN
The main use of DEA is to calculate an estimate of the Farrell technical efficiency measure. By defining the statistical model, the stochastic version of the method is received, enabling us to derive the asymptotical form of sampling distribution of the estimate (called the DEA estimator). However, the distribution depends on unknown constants, which make deriving estimates of dispersion measures quite difficult. Thus, as an alternative, I used Simar and Wilson’s homogeneous bootstrap, a relatively simple and frequently used bootstrap procedure available in a software package for Frontier Efficiency Analysis with R (FEAR). The method is illustrated with an empirical example based on real data from the Polish energy sector.
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