Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-19T17:51:12.163Z Has data issue: false hasContentIssue false
  • English
  • Français

Per Unit Costs to Own and Operate Farm Machinery

Published online by Cambridge University Press:  28 April 2005

Aaron J. Beaton ,
Kevin C. Dhuyvetter ,
Terry L. Kastens  and
Jeffery R. Williams
Aaron J. Beaton
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, KS
Kevin C. Dhuyvetter
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, KS
Terry L. Kastens
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, KS
Jeffery R. Williams
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, KS
Get access Rights & Permissions [Opens in a new window]

Abstract

With increasingly thin margins and new technologies, it is important that farm managers know their cost of field operations on a per unit basis (e.g., acre, ton, bale). Accurate per unit costs give confidence when constructing enterprise budgets and evaluating new technologies, such as no-till. Custom rates are often used as a proxy for per unit costs; however, this research, using entropy and jackknife estimation procedures, found that custom rates understate total ownership and operating costs by approximately 25% for an average Kansas farm. Estimates from these models are then used to benchmark actual costs against expected cost.

Keywords

benchmarkcustom ratescustom workentropyjackknifemachinery costsQ10Q12C51C60
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 37 , Issue 1 , April 2005 , pp. 131 - 144
Copyright
Copyright © Southern Agricultural Economics Association 2005

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

Albright, M. “Characteristics of Profitable Farms: An Analysis of Kansas Farm Management Association Enterprise Data.” Manhattan: Kansas State University Risk and Profit Conference, 2002.Google Scholar
ASAE Standards 2000. 47th ed. St. Joseph, MI: American Society of Agricultural Engineers, 2000.Google Scholar
Beaton, A.J. “Per Unit Costs to Own and Operate Farm Machinery on Kansas Farms.” M.S. thesis, Kansas State University, 2003.Google Scholar
Bowers, W. Machinery Replacement Strategies. Moline, IL: Deere & Company Service Publications, 1994.Google Scholar
Cross, T.L., and Perry, G.M.. “Depreciation Patterns for Agricultural Machinery.” American Journal of Agricultural Economics 77(1995): 194–204.10.2307/1243901Google Scholar
Excel. Microsoft® Excel 2000. Copyright© 1985–1999 Microsoft Corporation.Google Scholar
Golan, A., Judge, G., and Miller, D.. Maximum Entropy Econometrics: Robust Estimation with Limited Data. New York: John Wiley and Sons, 1996.Google Scholar
Gujarati, D.N. Basic Econometrics. 3rd ed. New York: McGraw-Hill, 1995.Google Scholar
Hunt, D. Farm Power and Machinery Management. 9th ed. Ames: Iowa State University Press, 1995.Google Scholar
Kansas Agricultural Statistics Service. “2001 Kansas Custom Rates.” Topeka: Kansas Agricultural Statistics Service, 2001.Google Scholar
Kansas Farm Management Association. Internet site: www.agecon.ksu.edu/kfma (Accessed February 20, 2002).Google Scholar
Langemeier, L.N., and Taylor, R.K.. “A Look at Machinery Costs.” Manhattan: Kansas State University, Farm Management Guide MF-842, 1998.Google Scholar
Maddala, G.S. Introduction to Econometrics. 3rd ed. New York: John Wiley and Sons, 2001.Google Scholar
Reid, D.W., and Bradford, G.L.. “On Optimal Replacement of Farm Tractors.” American Journal of Agricultural Economics 65(1983):326–31.10.2307/1240883Google Scholar
Schnitkey, G. “Per Acre Machinery Costs on Illinois Grain Farms.” Urbana: University of Illinois, Farm Economics Facts and Opinions, FEFO 01-06, 2001.Google Scholar
Schuster, K. “Benchmarking: How Do You Measure Up?” Food Management 32,8(1997):42-43, 46–49.Google Scholar