Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-14T07:29:11.767Z Has data issue: false hasContentIssue false
  • English
  • Français

Exploring the Role of Managerial Ability in Influencing Dairy Farm Efficiency

Published online by Cambridge University Press:  15 September 2016

Justin P. Byma  and
Loren W. Tauer
Justin P. Byma
Affiliation:
Department of Applied Economics and Management at Cornell University in Ithaca, New York
Loren W. Tauer
Affiliation:
Department of Applied Economics and Management at Cornell University in Ithaca, New York
Get access

Abstract

This paper explores the role of managerial ability in determining efficiency in New York dairy farms. Using an unbalanced panel of farm data from 1993 through 2004, we estimate outputoriented technical efficiencies using stochastic distance frontier functions. We find that both lagged net farm income and farmers’ own estimates of the value of their labor and management as proxies for managerial ability impact measured efficiency. Efficiency increases with operator education, farm size, and extended participation in a farm management program, but decreases with operator age.

Keywords

dairy farmsdistance functionmanagement and efficiencystochastic frontier analysis
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 39 , Issue 3 , October 2010 , pp. 505 - 516
Copyright
Copyright © 2010 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aigner, D., Lovell, C.A.K., and Schmidt, P. 1977. “Formulation and Estimation of Stochastic Frontier Production Function Models.” Journal of Econometrics 6(1): 21–37.Google Scholar
Beyers, L. 2001. “Managerial Ability and Its Influence on Size Economies in South African Dairy Production.” Working Paper No. 2001-09, Department of Agricultural Economics, University of Pretoria, South Africa.Google Scholar
Brummer, B., Glauben, T., and Thijssen, G. 2002. “Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries.”CrossRefGoogle Scholar
American Journal of Agricultural Economics 84(3): 628–644.CrossRefGoogle Scholar
Charnes, A., Cooper, W.W., and Rhodes, E. 1978. “Measuring the Efficiency of Decision-Making Units.” European Journal of Operations Research 2(6): 429–444.CrossRefGoogle Scholar
Coelli, T. 2000. “On the Econometric Estimation of the Distance Function Representation of a Production Technology.” CORE Discussion Paper No. 2000042, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.Google Scholar
Dawson, P.J., and Hubbard, L.J. 1987. “Management and Size Economies in the England and Wales Dairy Sector.” Journal of Agricultural Economics 38(1): 27–38.Google Scholar
Debreu, G. 1951. “The Coefficient of Resource Utilization.” Econometrica 19(3): 273–292.CrossRefGoogle Scholar
Farrell, M.J. 1957. “The Measurement of Productive Efficiency.” Journal of the Royal Statistical Society 120(3): 253–290.Google Scholar
Førsund, F., Lovell, C.A.K., and Schmidt, P. 1980. “A Survey of Frontier Production Functions and Their Relationship to Efficiency Measurement.” Journal of Econometrics 13(1): 5–25.Google Scholar
Gallacher, M., Goetz, S.J., and Debertin, D.L. 1994. “Managerial Form, Ownership and Efficiency: A Case Study of Argentine Agriculture.” Agricultural Economics 11(2/3): 289–299.Google Scholar
Hadri, K. 1999. “Estimation of Doubly Heteroscedastic Frontier Cost Function.” Journal of Business and Economic Statistics 17(3): 359–363.Google Scholar
Karagiannis, G., Midmore, P., and Tzouvelekas, V. 2004. “Parametric Decomposition of Output Growth Using a Stochastic Input Distance Function.” American Journal of Agricultural Economics 86(4): 1044–1057.CrossRefGoogle Scholar
Knight, F.H. 1921. Risk, Uncertainty, and Profit. Boston: Houghton Mifflin Company.Google Scholar
Leibenstein, H. 1966. “Allocative vs. X-efficiency.” The American Economic Review 56(3): 392–415.Google Scholar
Nelson, R.R., and Winter, S.G. 1982. An Evolutionary Theory of Economic Change. Boston: Harvard University Press.Google Scholar
Newman, C., and Matthews, A. 2007. “Performance of Agricultural Enterprises in Ireland Using a Multiple Output Distance Function Approach.” Journal of Agricultural Economics 58(1): 128–151.CrossRefGoogle Scholar
Seitz, W.D. 1971. “Productive Efficiency in the Steam-Electric Generating Industry.” Journal of Political Economy 79(4): 878–886.Google Scholar
Shephard, R.W. 1953. Cost and Production Functions. Princeton, NJ: Princeton University Press.Google Scholar
Simon, H.A. 1959. “Theories of Decision Making in Economics.” American Economic Review 49(3): 253–283.Google Scholar
Stefanou, S.E., and Saxena, S. 1988. “Education Experience and Allocative Efficiency: A Dual Approach.” American Journal of Agricultural Economics 70(2): 338–345.Google Scholar
Stigler, G.J. 1976. “The Xistence of X-Efficiency.” The American Economic Review 66(1): 213–216.Google Scholar
Tauer, L.W. 1993. “Short-Run and Long-Run Efficiencies of New York Dairy Farms.” Agricultural and Resource Economics Review 22(1): 1–9.Google Scholar
Tauer, L.W., and Mishra, A.K. 2006. “Can the Small Dairy Farm Remain Competitive in U.S. Agriculture?” Food Policy 31(5): 458–468.Google Scholar
U.S. Department of Agriculture. 2004. Agricultural Prices. National Agricultural Statistics Service (NASS), U.S. Department of Agriculture, Washington, D.C. Google Scholar
von Hayek, F.A. 1945. “The Use of Knowledge in Society.” American Economic Review 35(4): 519–530.Google Scholar
Wang, H. 2002. “Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model.” Journal of Productivity Analysis 18(3) 241–253.Google Scholar