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Productivity improvement in Korean rice farming: parametric and non-parametric analysis

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  • Kwon, Oh Sang
  • Lee, Hyunok

Abstract

The published empirical literature on frontier production functions is dominated by two broadly defined estimation approaches – parametric and non‐parametric. Using panel data on Korean rice production, parametric and non‐parametric production frontiers are estimated and compared with estimated productivity. The non‐parametric approach employs two alternative measures based on the Malmquist index and the Luenberger indicator, while the parametric approach is closely related to the time‐variant efficiency model. Productivity measures differ considerably between these approaches. It is discovered that measures of efficiency change are more sensitive to the choice of the model than are measures of technical change. Both approaches reveal that the main sources of growth in Korean rice farming have been technical change and productivity improvements in regions of the country that have been associated with low efficiency.

Suggested Citation

  • Kwon, Oh Sang & Lee, Hyunok, 2004. "Productivity improvement in Korean rice farming: parametric and non-parametric analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 1-24.
    • Handle: RePEc:ags:aareaj:117965
    DOI: 10.22004/ag.econ.117965
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    3. Kang, Hye-Jung & Choi, Ji-Hyeon, 2013. "What Drives the Productivity Change of the Korean Food Processing Industry?: A Stochastic Frontier Analysis Using Firm-Level Panel Data, 2001-2009," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 36(1), pages 1-20, May.
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    7. Tleubayev, Alisher & Bobojonov, Ihtiyor & Götz, Linde & Hockmann, Heinrich & Glauben, Thomas, 2017. "Determinants of productivity and efficiency of wheat production in Kazakhstan: A Stochastic Frontier Approach," IAMO Discussion Papers 253397, Institute of Agricultural Development in Transition Economies (IAMO).
    8. Ajetomobi, J. O. & Adedeji, I. A., 2016. "Productivity Growth of ECOWAS Common Crops: A Tale of Two Competing Frontier Methods of Analysis," Agroeconomia Croatica, Croatian Society of Agricultural Economists, vol. 6(1), pages 1-16, November.
    9. Sauer, J.F., 2005. "“Efficiency Flooding”: Black-Box Frontiers and Policy Implications," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(1), pages 17-52.
    10. Álvaro Ramírez Suárez, 2013. "Análisis de eficiencia económica de fincas arroceras: una aplicación de una función determinística de ingresos brutos frontera," Revista Lebret, Universidad Santo Tomás - Bucaramanga, vol. 5, pages 213-240, December.
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    14. Jun Ho Seok & Hanpil Moon & GwanSeon Kim & Michael R. Reed, 2018. "Is Aging the Important Factor for Sustainable Agricultural Development in Korea? Evidence from the Relationship between Aging and Farm Technical Efficiency," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    15. Johannes Sauer & Klaus Frohberg & Henrich Hockmann, 2006. "Stochastic efficiency measurement: The curse of theoretical consistency," Journal of Applied Economics, Universidad del CEMA, vol. 9, pages 139-166, May.
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    17. K Hervé Dakpo & Philippe Jeanneaux & Laure Latruffe & Claire Mosnier & Patrick Veysset, 2018. "Three decades of productivity change in French beef production: a Färe‐Primont index decomposition," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(3), pages 352-372, July.

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