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Source Of Total Factor Productivity Change: An Empirical Analysis Of Grain Producing Regions In Norway

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  • Habtamu ALEM

    (Norwegian Institute of Bioeconomy Research)

Abstract

In this article, we estimate the progress of Total Factor Productivity (TFP) in the Norwegian grain production sector. Previous studies conducted in TFP estimation can be criticized for estimated production function relied on the assumption that the underlying technology is the same for all regions and firms face similar environmental conditions. In reality, agricultural firms in different regions resource endowment, adoption of new technology, and innovation might be different because of farmers face different production opportunities. For this study, we classified the country into two main grain producing regions with district level of development, and hence production technologies. We used farm level balanced panel data for 19 years (1996-2014) with 1463 observations from farms specialized in grain production. We applied the ‘true' fixed effect stochastic frontier model to estimate region level efficiency and source of productivity changes. The result of the analysis shows that there has been a productivity improvement in the sector, and technical change has had the main source of productivity change.

Suggested Citation

  • Habtamu ALEM, 2017. "Source Of Total Factor Productivity Change: An Empirical Analysis Of Grain Producing Regions In Norway," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(6), pages 8-18, December.
    • Handle: RePEc:blg:reveco:v:69:y:2017:i:6:p:8-18
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    1. Lajos Baráth & Imre Fertő, 2017. "Productivity and Convergence in European Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(1), pages 228-248, February.
    2. Bert Balk, 2001. "Scale Efficiency and Productivity Change," Journal of Productivity Analysis, Springer, vol. 15(3), pages 159-183, May.
    3. Bernhard Brümmer & 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.
    4. Alvarez, Antonio & del Corral, Julio & Tauer, Loren W., 2012. "Modeling Unobserved Heterogeneity in New York Dairy Farms: One-Stage versus Two-Stage Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(3), pages 275-285, December.
    5. Giannis Karagiannis & Peter Midmore & Vangelis Tzouvelekas, 2004. "Parametric Decomposition of Output Growth Using A Stochastic Input Distance Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1044-1057.
    6. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    7. Laure Latruffe & Sophia Davidova & Kelvin Balcombe, 2008. "Productivity change in Polish agriculture: an illustration of a bootstrapping procedure applied to Malmquist indices," Post-Communist Economies, Taylor & Francis Journals, vol. 20(4), pages 449-460.
    8. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    9. Odeck, James, 2009. "Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers," Omega, Elsevier, vol. 37(5), pages 1007-1017, October.
    10. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    11. Berndt, Ernst R. & Christensen, Laurits R., 1973. "The translog function and the substitution of equipment, structures, and labor in U.S. manufacturing 1929-68," Journal of Econometrics, Elsevier, vol. 1(1), pages 81-113, March.
    12. 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.
    13. Diewert, W E, 1992. "The Measurement of Productivity," Bulletin of Economic Research, Wiley Blackwell, vol. 44(3), pages 163-198, July.
    14. James Odeck, 2007. "Measuring technical efficiency and productivity growth: a comparison of SFA and DEA on Norwegian grain production data," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2617-2630.
    15. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    16. Subal kumbhakar & Ana Lozano-Vivas, 2005. "Deregulation and Productivity: The Case of Spanish Banks," Journal of Regulatory Economics, Springer, vol. 27(3), pages 331-351, January.
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    Cited by:

    1. Bingfei Bao & Shengtian Jin & Lilian Li & Kaifeng Duan & Xiaomei Gong, 2021. "Analysis of Green Total Factor Productivity of Grain and Its Dynamic Distribution: Evidence from Poyang Lake Basin, China," Agriculture, MDPI, vol. 12(1), pages 1-16, December.

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    More about this item

    Keywords

    Productivity; Technology; sustainable development; and Region;
    All these keywords.

    JEL classification:

    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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