Hostname: page-component-77c89778f8-cnmwb Total loading time: 0 Render date: 2024-07-17T02:11:07.709Z Has data issue: false hasContentIssue false
  • English
  • Français

Measuring Productivity Change in U.S. Agriculture*

Published online by Cambridge University Press:  05 September 2016

Yao-Chi Lu
Yao-Chi Lu*
Affiliation:
National Economic Analysis Division, ERS, USDA, Oklahoma State University
Get access Rights & Permissions [Opens in a new window]

Extract

To understand the sources of change in productivity, that appropriate public policy and programs can be developed to increase productivity growth, a reliable and updated measure is needed. The term “productivity” discussed here refers to total factor productivity, or the ratio of value of total agricultural output to that of all inputs used in agricultural production.

The first comprehensive work on the measurement of productivity change in U.S. agriculture was done by Loomis and Barton in 1961. Since then, this index has been updated annually as an offical USDA agricultural productivity index. The weakness of using index numbers lies in the arithmetic formula used. It implies a specific functional form of the production function that may not accurately describe the data. Thus, a need arises to consider an alternative estimate of productivity.

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 7 , Issue 2 , December 1975 , pp. 69 - 75
Copyright
Copyright © Southern Agricultural Economics Association 1975

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.)

Footnotes

*

The author wishes to express his appreciation to Drs. Richard Just and Evan Drummond for helpful comments. Thanks are also due to Mr. Don Durost for his assistance in collecting data used in this study. Alternative measurements of agricultural productivity presented in this paper were made by the author as a part of an ERS — Oklahoma State University cooperative research project to project technological change in U.S. agriculture and are not offical USDA measures. The USDA is testing alternative methods including those reported in this paper in its ongoing program of measuring productivity in U.S. agriculture.

References

[1] Balestra, Pietro, and Marc, Nerlove. “Pooling Cross Section and Time Series Data in the Estimation of a Dynamic Model: The Demand for Natural Gas,” Econometrica, 34 (3):585–612, 1966.Google Scholar
[2] Binswanger, Hans P. “A Cost Function Approach to the Measurement of Elasticity of Factor Demand and Elasticity of Substitution,” Paper presented at the joint AAEA-ES session of the Winter meetings, December 1973.Google Scholar
[3] de Janvry, Alain .“Optimal Levels of Fertilizer Under Risk: The Potential for Com and Wheat Fertilization Under Alternative Price Policies in Argentina,” American Journal of Agricultural Economics, 54 (1):1–10, Feb. 1972.Google Scholar
[4] de Janvry, Alain. “The Class of Generalized Power Production Functions,” American Journal of Agricultural Economics, 54 (2):234–237, May 1972.Google Scholar
[5] Griliches, Zvi. “The Sources of Measured Productivity Growth: United States Agriculture, 1940-60,” Journal of Political Economy, 71:331–346, August 1963.CrossRefGoogle Scholar
[6] Hoch, Irving. “Estimation of Production Function Parameters Combining Timed-Series and Cross-Section Data,” Econometrica, 30 (1):34–53, 1962.Google Scholar
[7] Holmes, R.A. “Combining Cross-Section and Time Series Information on Demand Relationships for Substitute Goods,” American Journal of Agricultural Economics, 50 (1):56–65, 1968.Google Scholar
[8] Lave, L. Technological Change: Its Conception and Measurement, Englewood Cliffs: Prentice-Hall, New Jersey, 1966.Google Scholar
[9] Loomis, Ralph A. and Barton, Glen T.. Productivity of Agriculture, USDA Technical Bulletin No. 1238, April 1961.Google Scholar
[10] Lu, Yao-chi, and Fletcher, L.B.. “A Generalization of the CES Production Function,” Review of Economics and Statistics, 50 (4):449–452, November 1968.CrossRefGoogle Scholar
[11] Mundlak, Yair. “Estimation of Production and Behavioral Function from a Combination of Cross-Secion and Time Series Data,” in Measurement in Economics, Christ, Carl F., et. al., eds., Stanford: University Press, 1963.Google Scholar
[12] Nevel, Robert O. “Technological Change in Agriculture,” Agricultural Economics Research, 21 (1):13–18, January 1969.Google Scholar
[13] Paris, Q., and Hoch, I.. “Combination of Time-Series and Cross-Section Data in Dairy Production Analysis,” Proceedings of Western Farm Economic Association, pp. 247-58, 1966.Google Scholar
[14] Revankar, N. “A Class of Variable Elasticity of Substitution Production Functions,” Econometrica, 39(1):61–71, January 1971.Google Scholar
[15] Sahota, G. “The Sources of Measured Productivity Growth: United States Fertilizer Mineral Industries, 1936-1960,” Review of Economics and Statistics, 48 (2): 193–204, May 1966.CrossRefGoogle Scholar
[16] Sato, R. “Linear Elasticity of Substitution Production Functions,” Metroeconomica, 19:33–41, January-April 1967.Google Scholar
[17] Solow, Robert M. “Technical Change and the Aggregate Production Function,” Review of Economics and Statistics, 39 (3):312-20, August 1957.Google Scholar
[18] Sudit, E.F. “Additive Nonhomogeneous Production Functions in Telecommunications,” The Bell Journal of Economics and Management Science, 4(2):499–514, Autumn 1973.Google Scholar
[19] U.S. Department of Agriculture. Changes in Farm Production and Efficiency, Statistical Bulletin No. 232, Economic Research Service, Annual Issues.Google Scholar
[20] Vinod, H.D. “Nonhomogeneous Production Functions and Applications to Telecommunications,” The Bell Journal of Economics and Management Science, 3(2):531–543, Autumn 1972.Google Scholar
[21] Wallace, T.D. and Ashiq, Hassain. “The Use of Error Components Models in Combining Cross Section with Time Series Data,” Econometrica, 37(1):55–72, January, 1969.Google Scholar