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Spatiotemporal analysis of Korean ginseng farm productivity

Author

Listed:
  • Heesun Jang

    (Korea Energy Economics Institute)

  • Hyunhee Kim

    (Korea Environment Institute)

  • Hojeong Park

    (Korea University)

Abstract

The past two decades has seen new methodological debates on the identification of production function. Olley and Pakes (J Polit Econ 101(6):1149–1164, 1996), Levinsohn and Petrin (Rev Econ Stud 70(2):317–340, 2003), and Ackerberg et al. (Econometrica 83(6):2411–2451, 2015) introduced nonparametric approaches to control for the unobserved productivity in the estimation of production function, which requires the availability of panel data. There has been an another body of the literature that argued that models that are typically estimated on the basis of panel data can also be identified with repeated cross-sections under certain conditions (Verbeek and Vella, 2005). The objective of this paper is two-fold. First, built on the insight of Verbeek and Vella (2005), this paper proposes a new approach to estimate the nonparametric control function based on repeated cross-sections. This is important because in many studies there is a lack of panel data where agents are followed over time, while repeated cross-sections may be available. Second, using cross-sections of Korean ginseng farms over 2006 to 2013, we apply our method to examine the evolution of farm-level productivity over time and across major production regions. Comparing our method with the pooled OLS regressions, the results show that the materials input coefficients are underestimated in the OLS regressions, which is consistent with the data where farms in the large ginseng production regions use relatively less materials than those in the other regions.

Suggested Citation

  • Heesun Jang & Hyunhee Kim & Hojeong Park, 2020. "Spatiotemporal analysis of Korean ginseng farm productivity," Journal of Productivity Analysis, Springer, vol. 53(1), pages 69-78, February.
  • Handle: RePEc:kap:jproda:v:53:y:2020:i:1:d:10.1007_s11123-019-00560-x
    DOI: 10.1007/s11123-019-00560-x
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    References listed on IDEAS

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    1. Marc J. Melitz & Sašo Polanec, 2015. "Dynamic Olley-Pakes productivity decomposition with entry and exit," RAND Journal of Economics, RAND Corporation, vol. 46(2), pages 362-375, June.
    2. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    3. Carlo Fezzi & Ian J. Bateman, 2011. "Structural Agricultural Land Use Modeling for Spatial Agro-Environmental Policy Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 1168-1188.
    4. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Papers 2005-W04, Economics Group, Nuffield College, University of Oxford.
    5. Sieg, Holger & Zhang, Jipeng, 2012. "The importance of managerial capacity in fundraising: Evidence from land conservation charities," International Journal of Industrial Organization, Elsevier, vol. 30(6), pages 724-734.
    6. Heesun Jang & Xiaodong Du, 2018. "An Empirical Structural Model of Productivity and Conservation Reserve Program Participation," Land Economics, University of Wisconsin Press, vol. 94(1), pages 1-18.
    7. Kasahara, Hiroyuki & Rodrigue, Joel, 2008. "Does the use of imported intermediates increase productivity? Plant-level evidence," Journal of Development Economics, Elsevier, vol. 87(1), pages 106-118, August.
    8. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    9. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    10. Amil Petrin & Brian P. Poi & James Levinsohn, 2004. "Production function estimation in Stata using inputs to control for unobservables," Stata Journal, StataCorp LP, vol. 4(2), pages 113-123, June.
    11. Apurba Shee & Spiro E. Stefanou, 2015. "Endogeneity Corrected Stochastic Production Frontier and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 939-952.
    12. Griffiths, William E. & Hajargasht, Gholamreza, 2016. "Some models for stochastic frontiers with endogeneity," Journal of Econometrics, Elsevier, vol. 190(2), pages 341-348.
    13. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    14. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    15. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    16. Girma, Sourafel, 2000. "A quasi-differencing approach to dynamic modelling from a time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 98(2), pages 365-383, October.
    17. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    18. Wooldridge, Jeffrey M., 2009. "On estimating firm-level production functions using proxy variables to control for unobservables," Economics Letters, Elsevier, vol. 104(3), pages 112-114, September.
    19. Dolores Collado, M., 1997. "Estimating dynamic models from time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 82(1), pages 37-62.
    20. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Series Working Papers 2005-W04, University of Oxford, Department of Economics.
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