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Labor Productivity Growth in the Kansas Farm Sector: A Tripartite Decomposition Using a Non-Parametric Approach

Published online by Cambridge University Press:  15 September 2016

Amin W. Mugera ,
Michael R. Langemeier  and
Allen M. Featherstone
Amin W. Mugera
Affiliation:
Institute of Agriculture and in the School of Agriculture and Resource Economics at the University of Western Australia, in Crawley, Australia
Michael R. Langemeier
Affiliation:
Center for Commercial Agriculture at Purdue University, in West Lafayette, Indiana
Allen M. Featherstone
Affiliation:
Master of Agribusiness Program in the Department of Agricultural Economics at Kansas State University, in Manhattan, Kansas
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Abstract

We use nonparametric production function methods to decompose farm-level labor productivity growth into components attributable to efficiency change, technical change, and factor intensity. The estimation is accomplished using balanced panel data drawn from the Kansas Farm Management Association for the period 1993 to 2007. We find that labor productivity growth is primarily driven by factor intensity and technical change. Efficiency change is declining with increasing productivity growth, and technical change is not Hicks-neutral and occurs at high levels of factor intensity, suggesting that innovation is embodied in factor intensity.

Keywords

labor productivity growthefficiency changetechnical changefactor intensity
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 41 , Issue 3 , December 2012 , pp. 298 - 312
Copyright
Copyright © 2012 Northeastern Agricultural and Resource Economics Association 

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References

Acquaye, A.K.A., Alston, J.M., and Pardey, P.G. 2003. “Post-War Productivity Patterns in U.S. Agriculture: Influences of Aggregation Procedures in a State-Level Analysis.” American Journal of Agricultural Economics 85(1): 59–80.CrossRefGoogle Scholar
Acs, Z.J., Morck, R., and Yeung, B. 1999. “Productivity Growth and Firm Size Distribution.” In Acs, Z.J., Carlsson, B., and Karlsson, C., eds., Entrepreneurship, Small and Medium-Sized Enterprises and the Macroeconomy. Cambridge, UK: Cambridge University Press.Google Scholar
Alston, J.L., Craig, B.J., and Pardey, P.G. 1998. “Dynamics in the Creation and Depreciation of Knowledge, and the Returns to Research.” EPTD Discussion Paper No. 35, International Food Policy Research Institute, Washington, D.C. Available at http://ageconsearch.umn.edu/bitstream/16102/1/ept-dp35.pdf (accessed January 15, 2011).Google Scholar
Ball, V.E., Bureau, J.C., Butault, J.P., and Nehring, R. 2001. “Levels of Farm Sector Productivity: An International Comparison.” Journal of Productivity Analysis 15(1): 5–29.CrossRefGoogle Scholar
Ball, V.E., Hallhan, C., and Nehring, R. 2004. “Convergence of Productivity: An Analysis of the Catch-Up Hypothesis within a Panel of States.” American Journal of Agricultural Economics 86(5): 1315–1321.Google Scholar
Ball, V.E., and Norton, G.W. 2002. Agricultural Productivity: Measurement and Sources of Growth. Boston: Kluwer Academic Publishers.Google Scholar
Bravo-Ureta, B., Solís, D., López, V.M., Maripani, J., Thiam, A., and Rivas, T. 2007. “Technical Efficiency in Farming: A Meta-Regression Analysis.” Journal of Productivity Analysis 27(1): 57–72.CrossRefGoogle Scholar
Caves, D.W., Christensen, L.R., and Diewert, W.E. 1982. “The Economic Theory of Index Numbers and the Measurement of Input, Output and Productivity.” Econometrica 50(5): 1393–1414.CrossRefGoogle Scholar
Coelli, T., Rao, D.S.P., O’Donnell, C.J., and Battese, G.E. 2005. An Introduction to Efficiency and Productivity Analysis (2nd edition). New York: Springer.Google Scholar
Delgado-Rodriguez, M.J., and Álvarez-Ayuso, I. 2008. “Economic Growth and Convergence of EU Member States: An Empirical Investigation.” Review of Development Economics 12(3): 1–12.Google Scholar
Färe, R., Grosskopf, S., Norris, M., and Zhang, Z. 1994. “Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries.” American Economic Review 84(1): 66–83.Google Scholar
Fuglie, K.O., MacDonald, J.M., and Ball, E. 2007. “Productivity Growth in U.S. Agriculture.” Economic Brief No. 9, Economic Research Service, U.S. Department of Agriculture, Washington, D.C. Available at http://www.ers.usda.gov/media/201254/eb9_l_.pdf (accessed December 12, 2011).Google Scholar
Hakkio, C.S. 2008. “PCE and CPI Inflation Differentials: Converting Inflation Forecasts.” Economic Review (first quarter): 51–68.Google Scholar
Henderson, D.J., and Zelenyuk, V. 2007. “Testing for (Efficiency) Catching-Up.” Southern Economic Journal 73(4): 1003–1019.Google Scholar
Huffman, W.E., and Evenson, R.E. 1992. “Contribution of Public and Private Science and Technology to U.S. Agricultural Productivity.” American Journal of Agricultural Economics 74(3): 745–750.Google Scholar
Huffman, W.E., and Evenson, R.E. 1993. Science for Agriculture: A Long Term Perspective. Ames, IA: Iowa State University Press.Google Scholar
Key, N., and McBride, W.D. 2003. “Production Contracts and Productivity in the U.S. Hog Sector.” American Journal of Agricultural Economics 85(1): 121–133.Google Scholar
Kumar, S., and Russell, R.R. 2002. “Technological Change, Technological Catch-Up, and Capital Deepening: Relative Contributions to Growth and Convergence.” American Economic Review 92(3): 527–548.Google Scholar
Langemeier, M. 2010. “Kansas Farm Management SAS Data Bank Documentation.” Staff Paper No. 11-01, Department of Agricultural Economics, Kansas State University, Manhattan, KS.Google Scholar
Liu, Y., Shumway, C.R., Rosenman, R., and Ball, V. 2011. “Productivity Growth and Convergence in U.S. Agriculture: New Cointegration Panel Data Results.” Applied Economics Letters 43(1): 91–102.Google Scholar
Managi, S., and Karemera, D. 2004. “Input and Output Biased Technological Change in U.S. Agriculture.” Applied Economics Letters 11(5): 283–286.Google Scholar
Martell, G. 2003. “Monitoring El Niño in Real Time: The 2002-2003 Warm Episode.” No. 33192, Agricultural Outlook Forum 2003, U.S. Department of Agriculture, Washington, D.C. Available at http://ideas.repec.org/p/ags/usaoth/33192.html (accessed February 20, 2012).Google Scholar
McCunn, A., and Huffman, W.E. 2000. “Convergence in U.S. Productivity Growth for Agriculture: Implications of Interstate Research Spillovers for Funding Agricultural Research.” American Journal of Agricultural Economics 82(2): 370–388.CrossRefGoogle Scholar
Mugera, A.M., and Langemeier, M.R. 2011. Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas. Journal of Agricultural and Applied Economics 43(4): 515–528.Google Scholar
Mundlak, Y. 2005. “Economic Growth: Lessons from Two Centuries of American Agriculture.” Journal of Economic Literature 43(4): 989–1024.Google Scholar
Seaver, B.L., and Triantis, K.P. 1989. “The Implications of Using Messy Data to Estimate Production-Frontier Based Technical Efficiency Measures.” Journal of Business and Economic Statistics 7(1): 49–59.Google Scholar
Serra, T., Goodwin, B.K., and Featherstone, A.M. 2005. “Agricultural Policy Reform and Off-Farm Labour Decisions.” Journal of Agricultural Economics 56(2): 271–285.Google Scholar
Serra, T., Zilberman, D., and Gil, J.M. 2008. “Farms’ Technical Inefficiencies in the Presence of Government Programs.” Australian Journal of Agricultural and Resource Economics 52(1): 57–76.Google Scholar
Serra, T., Zilberman, D., Goodwin, B.K., and Featherstone, A.M. 2006. “Effects of Decoupling on the Mean and Variability of Output.” European Review of Agricultural Economics 33(3): 269–288.Google Scholar
Simar, L., and Wilson, P. 1998. “Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Non-Parametric Frontier Models.” Management Science 44(1): 49–61.Google Scholar
Simar, L., and Wilson, P. 2000. “A General Methodology for Bootstrapping in Nonparametric Frontier Models.” Journal of Applied Statistics 27(6): 779–802.Google Scholar
Thirtle, C.G., Schimmelpfennig, D.E., and Townsend, R.F. 2002. “Induced Innovation in United States Agriculture, 1880-1990: Time Series Tests and an Error Correction Model.” American Journal of Agricultural Economics 84(3): 598–614.Google Scholar
Weber, W.L., and Domazlicky, B.R. 2006. “Capital Deepening and Manufacturing's Contribution to Regional Economic Convergence.” Journal of Regional Analysis and Policy 36(1): 31–44.Google Scholar
Weersink, A., and Tauer, L.W. 1991. “Causality between Dairy Farm Size and Productivity,” American Journal of Agricultural Economics 74(4): 1138–1145.Google Scholar
Yee, J., Huffman, W., Ahearn, M., and Newton, D. 2002. “Sources of Agricultural Productivity Growth at the State Level, 1960-1993.” In Ball, V.E. and Norton, G.W., eds., Agricultural Productivity: Measurement and Sources of Growth. Norwell, MA: Kluwer.Google Scholar