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Estimating random effects production function models with selectivity bias: an application to Swedish crop producers

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  • Heshmati, Almas

Abstract

In this paper, the estimation of production functions and measurement of the rate of technical change is performed when selectivity bias is expected, A sample selection model consisting of a selection and a regression equation is estimated using Heckman's two-stage method. It is discussed in the context of a production function where the underlying technology is represented by a translog functional form. For the regression, a random effects model with heteroscedastic variances is assumed. This model and an alternative conventional model retaining heteroscedasticity without considering selectivity bias are estimated using the Generalized Least Squares method. The data used are a large rotating panel data set from Swedish crop producers over the period 1976-1988. The empirical results from the comparison between these two models show that the introduction of heteroscedasticity and the integration of sample selection in the production relationship is important. The impact of a correction for selectivity bias on the results, in terms of input elasticities and returns to scale is found to be significant.
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  • Heshmati, Almas, 1994. "Estimating random effects production function models with selectivity bias: an application to Swedish crop producers," Agricultural Economics, Blackwell, vol. 11(2-3), pages 171-189, December.
  • Handle: RePEc:eee:agecon:v:11:y:1994:i:2-3:p:171-189
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    9. Greene, William H, 1981. "Sample Selection Bias as a Specification Error: Comment," Econometrica, Econometric Society, vol. 49(3), pages 795-798, May.
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    Cited by:

    1. Vangelis Tzouvelekas & Peter Midmore & Konstantinos Giannakas & Konstantinos Mattas, 1999. "Decomposition of Olive Oil Production Growth into Productivity and Size Effects : A Frontier Production Function Approach," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 51, pages 5-21.
    2. Tzouvelekas, Evaggelos, 2000. "Approximation Properties and Estimation of the Translog Production Function with Panel Data," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 1(1), January.
    3. Almas Heshmati & Mkhululi Ncube, 2004. "An Econometric Model Of Employment In Zimbabwe¡¯S Manufacturing Industries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 29(2), pages 107-130, December.
    4. Almas Heshmati & Ilham Haouas, 2011. "Employment Efficiency and Production Risk in the Tunisian Manufacturing Industries," Working Papers 602, Economic Research Forum, revised 07 Jan 2011.
    5. Heshmati, Almas & Ncube, Mkhululi, 1998. "An Econometric Model of Employment in Zimbabwe's Manufacturing Industries," SSE/EFI Working Paper Series in Economics and Finance 277, Stockholm School of Economics, revised 15 Aug 2003.
    6. Almas Heshmati & Subal C. Kumbhakar, 1997. "Estimation Of Technical Efficiency In Swedish Crop Farms: A Pseudo Panel Data Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1-3), pages 22-37.
    7. Vavra, Pavel & Colman, David, 2003. "The analysis of UK crop allocation at the farm level: implications for supply response analysis," Agricultural Systems, Elsevier, vol. 76(2), pages 697-713, May.
    8. Anjana Bhattacharyya & Arunava Bhattacharyya & Krishna Mitra, 1997. "Decomposition of Technological Change and Factor Bias in Indian Power Sector: An Unbalanced Panel Data Approach," Journal of Productivity Analysis, Springer, vol. 8(1), pages 35-52, March.

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