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A Meta Analysis of Farm Efficiency: Evidence from the Production Frontier Literature


  • Bravo-Ureta, Boris E.
  • Jara-Rojas, Roberto
  • Lachaud, Michee A.
  • Moreira, Victor H.


This study updates previous meta-analysis of farm-level frontier function studies in order to provide a detailed systematic and comprehensive analysis of the effects that different studyspecific attributes have on mean technical efficiency (MTE) scores. Before presenting the technical efficiency (TE) analysis, we provide an overview of the evolution of key methodological approaches that have been developed and applied to measure and examine TE. A detailed descriptive analysis is then performed for a meta-dataset that includes 408 farm level TE studies, published between 1981 and mid-2014. Some studies report several MTEs, resulting in 900 observations or cases. A key result from the descriptive analysis is that the Average of the Mean Technical Efficiencies (AMTE) reported for all studies is 74.2%. The AMTE across methodological attributes tend to be quite similar but several significant differences are observed when comparisons are made across geographical regions, income levels, and types of product. The paper goes on to report the results of meta-regressions estimated using the fractional regression procedure, which is well suited for dependent variables that are defined on the unit interval or as a fraction (between 0 and 1), as is the case with TE. In the concluding section, we provide some thoughts concerning recent work that uses stochastic production frontier methodologies to evaluate the impact of developments projects while addressing biases from observable and unobservable variables.

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  • Bravo-Ureta, Boris E. & Jara-Rojas, Roberto & Lachaud, Michee A. & Moreira, Victor H., 2017. "A Meta Analysis of Farm Efficiency: Evidence from the Production Frontier Literature," Research Reports 290067, University of Connecticut, Charles J. Zwick Center for Food and Resource Policy.
  • Handle: RePEc:ags:ucozrr:290067

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    Agricultural and Food Policy; Research Methods/ Statistical Methods;

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