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USING REGRESSION ANALYSIS TO REDUCE AGGREGATION BIAS IN LINEAR PROGRAMMING SUPPLY MODELS*

USING REGRESSION ANALYSIS TO REDUCE AGGREGATION BIAS IN LINEAR PROGRAMMING SUPPLY MODELS* Because methods of eliminating aggregation bias are impracticable, an alternative method is suggested for reducing aggregation bias which uses regression estimates of farm resonrce availabilities as functions of farm size. The estimates are incorporated in a parametric run of the LP problem in which size is parameterized. The method is applied to a case study problem, and the results compared with other methods of demarcating representative farms. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Australian Journal of Agricultural Resource Economics Wiley

USING REGRESSION ANALYSIS TO REDUCE AGGREGATION BIAS IN LINEAR PROGRAMMING SUPPLY MODELS*

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Publisher
Wiley
Copyright
Copyright © 1975 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1364-985X
eISSN
1467-8489
DOI
10.1111/j.1467-8489.1975.tb00141.x
Publisher site
See Article on Publisher Site

Abstract

Because methods of eliminating aggregation bias are impracticable, an alternative method is suggested for reducing aggregation bias which uses regression estimates of farm resonrce availabilities as functions of farm size. The estimates are incorporated in a parametric run of the LP problem in which size is parameterized. The method is applied to a case study problem, and the results compared with other methods of demarcating representative farms.

Journal

The Australian Journal of Agricultural Resource EconomicsWiley

Published: Apr 1, 1975

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