The Estimation of Meta-Frontiers by Constrained Maximum Likelihood
AbstractExisting approaches to the meta-frontier estimation are largely based on the linear programming technique, which does not hinge on any statistical underpinnings. We suggest estimating meta-frontiers by constrained maximum likelihood subject to the constraints that specify the way in which the estimated meta-frontier overarches the individual group frontiers. We present a methodology that allows one to either estimate meta-frontiers using the conventional set of constraints that guarantees overarching at the observed combinations of production inputs, or to specify a range of inputs within which such overarching will hold. In either case the estimated meta-frontier coefficients allow for the statistical inference that is not straightforward in case of the linear programming estimation. We apply our methodology to the world¡¯s FAO agricultural data and find similar estimates of the meta-frontier parameters in case of the same set of constraints. On the contrary, the parameter estimates differ a lot between different sets of constraints.
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Bibliographic InfoPaper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 1011.
Date of creation: 2010
Date of revision:
technical efficiency; meta-frontiers; constrained maximum likelihood;
Find related papers by JEL classification:
- O40 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-07-17 (All new papers)
- NEP-ECM-2010-07-17 (Econometrics)
- NEP-EFF-2010-07-17 (Efficiency & Productivity)
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