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Use of Markov Processes in Predicting Dairy Farm Size Distribution Changes

Published online by Cambridge University Press:  10 May 2017

John W. Wysong  and
Mahmood Y. Seyala
John W. Wysong
Affiliation:
Department of Agricultural and Resource Economics, University of Maryland
Mahmood Y. Seyala
Affiliation:
Department of Agricultural and Resource Economics, University of Maryland
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Extract

During the past several decades, a number of research publications have used Markov chain processes to predict changes in number of farm firms, the average size of farms and labor resource productivity in farm production (Conneman, Harris and Wilson, Judge and Swanson, Kottke, Seyala, Willett and Saupe, Wysong and Seyala). The Markov method assumes that the pattern of change exhibited in the past will continue into the future. This method provides information on historical changes by frequency distribution categories as well as for the whole cohort, and allows for projection of these changes into the future. Previous studies have used mainly short-run periods of up to 5 years as the primary data base. This study has considered the use of longer-run base periods of 10 to 20 years combined with periodic updating of sample data in projecting long-term trends in numbers and sizes of dairy farms and revising such projections through time.

Type
Contributed Papers
Information
Journal of the Northeastern Agricultural Economics Council , Volume 8 , Issue 2 , October 1979 , pp. 59 - 72
Copyright
Copyright © Northeastern Agricultural and Resource Economics Association 

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References

Conneman, George J. Jr. “A Methodological Study of Representative Farm Groups and Alternative Methods of Analysis and Projecting Changes in Milk Production.” Unpublished Ph.D. dissertation, Department of Agricultural Economics, Pennsylvania State University, 1967.Google Scholar
Crowder, Richard T. “Statistical vs. Judgment and Audience Considerations in the Formulation and Use of Econometric Models.” American Journal of Agricultural Economics. Vol. 54, No. 5, (Dec. 1972): 779–783.Google Scholar
Harris, H. M. Jr. and Wilson, L. E. Size Adjustments of Alabama Grade A Milk Producers. Alabama Agricultural Experiment Station Bull. 371, October 1966.Google Scholar
Judge, G. G. and Swanson, E. R. Markov Chains: Basic Concepts and and Suggested Uses in Agricultural Economics. University of Illinois Agricultural Experiment Station. Research Report AERR-49. December 1961.Google Scholar
Kottke, M. W. Patterns of Dairy Farm Exit and Growth. Connecticut Agricultural Experiment Station, Bull. 382, August 1964. Storrs.Google Scholar
Sevala, Mahmood Y. “An Economic Trend Analysis of Dairy Farms in the Central Piedmont Area of Maryland, 1956–66.” Unpublished Ph.D. dis-sertation. Dept. of Agricultural and Resource Economics, University of Marvland, College Park, 1969.Google Scholar
Willett, G. S. and Saupe, W. E. “Wisconsin Dairy Farming Adjustments Projected to 1980.” University of Wisconsin – Madison, Research Divison, College of Agricultural and Life Sciences Research Report R 2470. (Jan. 1973): 12.Google Scholar
Wvsong, John W. “Changes and Adjustments in the Organization and Operation of Maryland Dairy Farms.” Maryland Agricultural Experiment Station Misc. Publ. 361, June 1959.Google Scholar
Wvsong, John W. Economics of Large Size in the Production of Fluid Milk on Specialized Farms in Maryland. Maryland Agricultural Experiment Station Misc. Publ. 544, March 1965.Google Scholar
Wvsong, John W. “Long-Term Adjustments by a Panel of Mid-Atlantic Dairv Farm Firms to Improve Their Business Efficiency and profitability. Maryland Agricultural Experiment Stateion. Ag. Econ. Mineo Series, No. 29, Apr. 1968, p. 16.Google Scholar
Wvsong, John W. “Man-Machine Interaction Systems for Feeding and Milking on Selected Maryland Dairy Farms.” Marvland Bull. 458, (Oct. 1969) : 14.Google Scholar
Wvsong, John W. “Private and Public Farm Manpower Policy Implications of the Dairy Farm Firm. Labor Resource Adjustment Process.” Maryland Agricultural Experiment Station. Ag. Econ. Mimeo Series No. 23, July 1967, p. 17.Google Scholar
Wvsong, John W. and Seyala, Mahmood Y. “An Evaluation of Dairy Farm Adjustment Potentials Using Cross-Sectional and Time Series Analyses.” Maryland Agricultural Experiment Station, Agricultural and Resourec Economices Scientific Article A 1926, August 1973, p. 21. Article listing in AJAE Dec. 1973, p. 1023.Google Scholar
Wvsong, John W. and Seyala, Mahmood Y. Maryland Dairy Farm Adjustment : Preformances and Potentials. Maryland Agricultural Experiment Station, MP 913, (July 1977): 30.Google Scholar
Wvsong, John W. and Seyala, Mahmood Y. “A Reevaluation of Dairy Farm Adjustment Potentials Using Cross-Sectional and Time-Series Analyses.” Maryland Agricultural Experiment Station, Agricultural and Resourec Economices Scientific Journal – Proceedings, Fall 1977. Paper Printed at 1977 annual meeting of Eastern Economic Assiciation of Hartford, OH on April 14, 1977.Google Scholar
Wvsong, John W. and Seyala, Mahmood Y. Sources of Increased Productivity on Dairy Farms. Maryland Experiment Station, Dept. of Agricultural and Resource Economices APRIL 19, Jan. 1978, p. 16.Google Scholar