Transient and Persistent Technical Efficiencies in Rice Farming: A Generalized True Random-Effects Model Approach

Phuc Trong Ho (), Michael Burton, Atakelty Hailu and Chunbo Ma
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Phuc Trong Ho: Faculty of Economics and Development Studies, University of Economics, Hue University, 99 Ho Dac Di Street, Hue City 530000, Vietnam
Michael Burton: School of Agriculture and Environment, University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
Atakelty Hailu: School of Agriculture and Environment, University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
Chunbo Ma: School of Agriculture and Environment, University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia

Econometrics, 2024, vol. 12, issue 3, 1-18

Abstract: This study estimates transient and persistent technical efficiencies (TEs) using a generalized true random-effects (GTRE) model. We estimate the GTRE model using maximum likelihood and Bayesian estimation methods, then compare it to three simpler models nested within it to evaluate the robustness of our estimates. We use a panel data set of 945 observations collected from 344 rice farming households in Vietnam’s Mekong River Delta. The results indicate that the GTRE model is more appropriate than the restricted models for understanding heterogeneity and inefficiency in rice production. The mean estimate of overall technical efficiency is 0.71 on average, with transient rather than persistent inefficiency being the dominant component. This suggests that rice farmers could increase output substantially and would benefit from policies that pay more attention to addressing short-term inefficiency issues.

Keywords: transient and persistent efficiencies; stochastic frontier; generalized true random-effects model; Bayesian estimation; rice farming; Mekong River Delta (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2024
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