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Total Factor Productivity Decomposition and Unobserved Heterogeneity in Stochastic Frontier Models

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  • Kellermann, Magnus A.

Abstract

This study examines in an empirical comparison how different econometric specifications of stochastic frontier models affect the decomposition of total factor productivity growth. We estimate nine stochastic frontier models, which have been widely used in empirical investigations of sources of productivity growth. Our results show that the relative contribution of components to total factor productivity growth is quite sensitive to the choice of econometric model, which points to the need to select the “right†model. We apply various statistical tests to narrow the range of applicable models and identify additional criteria upon which to base the choice of non-nested models.

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  • Kellermann, Magnus A., 2015. "Total Factor Productivity Decomposition and Unobserved Heterogeneity in Stochastic Frontier Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 44(1), pages 124-148, April.
  • Handle: RePEc:cup:agrerw:v:44:y:2015:i:01:p:124-148_00
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    Cited by:

    1. Christian Grovermann & K. B. Umesh & Sylvain Quiédeville & B. Ganesh Kumar & Srinivasaiah S. & Simon Moakes, 2018. "The Economic Reality of Underutilised Crops for Climate Resilience, Food Security and Nutrition: Assessing Finger Millet Productivity in India," Agriculture, MDPI, vol. 8(9), pages 1-12, August.
    2. Christian Stetter & Johannes Sauer, 2022. "Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 617-647, March.
    3. Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.

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