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Comparing Parametric and Nonparametric Regression Methods for Panel Data: the Optimal Size of Polish Crop Farms

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Author Info

  • Tomasz Gerard Czekaj

    ()
    (Institute of Food and Resource Economics, University of Copenhagen)

  • Arne Henningsen

    ()
    (Institute of Food and Resource Economics, University of Copenhagen)

Abstract

We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs. The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test rejects both the Cobb-Douglas and the Translog functional form, while a recently developed nonparametric kernel regression method with a fully nonparametric panel data specification delivers plausible results. On average, the nonparametric regression results are similar to results that are obtained from the parametric estimates, although many individual results differ considerably. Moreover, the results from the parametric estimations even lead to incorrect conclusions regarding the technology and the optimal firm size.

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Bibliographic Info

Paper provided by University of Copenhagen, Department of Food and Resource Economics in its series IFRO Working Paper with number 2012/12.

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Length: 32 pages
Date of creation: Oct 2012
Date of revision:
Handle: RePEc:foi:wpaper:2012_12

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Keywords: production technology; nonparametric econometrics; panel data; Translog; firm size; Polish crop farms;

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  1. Barrett, Christopher B., 1996. "On price risk and the inverse farm size-productivity relationship," Journal of Development Economics, Elsevier, vol. 51(2), pages 193-215, December.
  2. Kumbhakar, Subal C. & Park, Byeong U. & Simar, Leopold & Tsionas, Efthymios G., 2007. "Nonparametric stochastic frontiers: A local maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 137(1), pages 1-27, March.
  3. Hsiao, Cheng & Li, Qi & Racine, Jeffrey S., 2007. "A consistent model specification test with mixed discrete and continuous data," Journal of Econometrics, Elsevier, vol. 140(2), pages 802-826, October.
  4. Barrett, Christopher B. & Bellemare, Marc F. & Hou, Janet Y., 2010. "Reconsidering Conventional Explanations of the Inverse Productivity-Size Relationship," World Development, Elsevier, vol. 38(1), pages 88-97, January.
  5. Inha Oh & Jeong-Dong Lee & Almas Heshmati, 2008. "Total Factor Productivity in Korean Manufacturing Industries," Global Economic Review, Taylor & Francis Journals, vol. 37(1), pages 23-50.
  6. Erik Mathijs & Johan F. M. Swinnen, 2001. "Production Organization And Efficiency During Transition: An Empirical Analysis Of East German Agriculture," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 100-107, February.
  7. Yves Croissant & Giovanni Millo, . "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, American Statistical Association, vol. 27(i02).
  8. Renner, Swetlana & Hockmann, Heinrich & Pieniadz, Agata & Glauben, Thomas, 2009. "On Flexibility in the Polish Farming Sector," 111th Seminar, June 26-27, 2009, Canterbury, UK 52841, European Association of Agricultural Economists.
  9. Darla Munroe, 2001. "Economic Efficiency in Polish Peasant Farming: An International Perspective," Regional Studies, Taylor & Francis Journals, vol. 35(5), pages 461-471.
  10. Marijn Verschelde & Marijke D’Haese & Glenn Rayp & Ellen Vandamme, 2013. "Challenging Small-Scale Farming: A Non-Parametric Analysis of the (Inverse) Relationship Between Farm Productivity and Farm Size in Burundi," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(2), pages 319-342, 06.
  11. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-68, October.
  12. Naisyin Wang, 2003. "Marginal nonparametric kernel regression accounting for within-subject correlation," Biometrika, Biometrika Trust, vol. 90(1), pages 43-52, March.
  13. Henderson, Daniel J. & Ullah, Aman, 2005. "A nonparametric random effects estimator," Economics Letters, Elsevier, vol. 88(3), pages 403-407, September.
  14. Gorton, Matthew & Davidova, Sophia, 2004. "Farm productivity and efficiency in the CEE applicant countries: a synthesis of results," Agricultural Economics, Blackwell, vol. 30(1), pages 1-16, January.
  15. Li, Qi & Racine, Jeff, 2003. "Nonparametric estimation of distributions with categorical and continuous data," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 266-292, August.
  16. Racine, Jeff & Li, Qi, 2004. "Nonparametric estimation of regression functions with both categorical and continuous data," Journal of Econometrics, Elsevier, vol. 119(1), pages 99-130, March.
  17. Svend Rasmussen, 2010. "Scale efficiency in Danish agriculture: an input distance--function approach," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(3), pages 335-367, September.
  18. Aw, B. -Y. & Hwang, A. R., 1995. "Productivity and the export market: A firm-level analysis," Journal of Development Economics, Elsevier, vol. 47(2), pages 313-332, August.
  19. Gallant, A. Ronald, 1982. "Unbiased determination of production technologies," Journal of Econometrics, Elsevier, vol. 20(2), pages 285-323, November.
  20. Lajos Zoltan Bakucs & Laure Latruffe & Imre Fertő & Jozsef Fogarasi, 2010. "The impact of EU accession on farms' technical efficiency in Hungary," Post-Communist Economies, Taylor & Francis Journals, vol. 22(2), pages 165-175.
  21. Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
  22. Livanis, Grigorios T. & Salois, Matthew J. & Moss, Charles B., 2009. "A Nonparametric Kernel Representation of the Agricultural Production Function: Implications for Economic Measures of Technology," 83rd Annual Conference, March 30-April 1, 2009, Dublin, Ireland 51063, Agricultural Economics Society.
  23. Andrew Dorward, 1999. "Farm size and productivity in Malawian smallholder agriculture," Journal of Development Studies, Taylor & Francis Journals, vol. 35(5), pages 141-161.
  24. Bernhard Br�mmer & Thomas Glauben & Geert Thijssen, 2002. "Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 628-644.
  25. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
  26. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
  27. Jeffrey Racine, 2008. "Nonparametric econometrics: a primer (in Russian)," Quantile, Quantile, issue 4, pages 7-56, March.
  28. Jeffery Racine & Jeffrey Hart & Qi Li, 2006. "Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models," Econometric Reviews, Taylor & Francis Journals, vol. 25(4), pages 523-544.
  29. Hockmann, Heinrich & Pieniadz, Agata & Goraj, Lech, 2007. "Modeling heterogeneity in production models: empirical evidence from individual farming in Poland," IAMO Discussion Papers 109, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
  30. Racine, Jeff, 1997. "Consistent Significance Testing for Nonparametric Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 369-78, July.
  31. Laure Latruffe & Kelvin Balcombe & Sophia Davidova & Katarzyna Zawalinska, 2004. "Determinants of technical efficiency of crop and livestock farms in Poland," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1255-1263.
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Cited by:
  1. Tomasz Gerard Czekaj & Arne Henningsen, 2013. "Panel Data Nonparametric Estimation of Production Risk and Risk Preferences: An Application to Polish Dairy Farms," IFRO Working Paper 2013/6, University of Copenhagen, Department of Food and Resource Economics.
  2. Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.

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