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A comparison of stochastic frontier approaches for estimating technical inefficiency and total factor productivity

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  • James Carroll
  • Carol Newman
  • Fiona Thorne

Abstract

This article compares standard stochastic frontier models for panel data with a number of recently developed models which attempt to control for unobserved heterogeneity in the inefficiency component. Results are used to construct a generalized Malmquist Total Factor Productivity (TFP) index for the Irish tillage sector. While our application yields similar general TFP trends across models, it is evident that this new class of model leads to fewer theoretical inconsistencies in the production frontier. Furthermore, inefficiency estimates across models are critically compared and the potential benefits of controlling for unobserved heterogeneity are highlighted.

Suggested Citation

  • James Carroll & Carol Newman & Fiona Thorne, 2011. "A comparison of stochastic frontier approaches for estimating technical inefficiency and total factor productivity," Applied Economics, Taylor & Francis Journals, vol. 43(27), pages 4007-4019.
  • Handle: RePEc:taf:applec:v:43:y:2011:i:27:p:4007-4019
    DOI: 10.1080/00036841003761918
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    References listed on IDEAS

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    1. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980.
    2. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    3. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    4. Mehdi Farsi & Massimo Filippini, 2004. "Regulation and Measuring Cost-Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 25(1), pages 1-19, August.
    5. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    6. Carol Newman & Alan Matthews, 2006. "The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach," Journal of Productivity Analysis, Springer, vol. 26(2), pages 191-205, October.
    7. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    8. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    9. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    10. Carol Newman & Alan Matthews, 2007. "Evaluating the Productivity Performance of Agricultural Enterprises in Ireland using a Multiple Output Distance Function Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(1), pages 128-151, February.
    11. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    12. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    13. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
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    Cited by:

    1. A. Wondemu Kifle, 2016. "Working Paper 237 - Decomposing Sources of Productivity Change in Small-Scale Farming in Ethiopia," Working Paper Series 2332, African Development Bank.
    2. A. Tonini, 2012. "A Bayesian stochastic frontier: an application to agricultural productivity growth in European countries," Economic Change and Restructuring, Springer, vol. 45(4), pages 247-269, November.
    3. repec:jed:journl:v:43:y:2018:i:3:p:119-142 is not listed on IDEAS
    4. Cathal O'Donoghue & Thia Hennessy, 2015. "Policy and Economic Change in the Agri-Food Sector in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 46(2), pages 315-337.
    5. Asif Reza Anik & Sanzidur Rahman & Jaba Rani Sarker, 2017. "Agricultural Productivity Growth and the Role of Capital in South Asia (1980–2013)," Sustainability, MDPI, Open Access Journal, vol. 9(3), pages 1-24, March.
    6. Cathal O'Donoghue & Thia Hennessy, 2014. "Chapter 03: The Agri-Food Sector," Chapters from Rural Economic Development in Ireland,in: Rural Economic Development in Ireland, edition 1, chapter 3 Rural Economy and Development Programme,Teagasc.

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