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Estimating a Demand System with Seasonally Differenced Data

Published online by Cambridge University Press:  26 January 2015

Ardian Harri ,
B. Wade Brorsen ,
Andrew Muhammad  and
John D. Anderson
Ardian Harri
Affiliation:
Department of Agricultural Economics, Mississippi State University, Mississippi State, MS
B. Wade Brorsen
Affiliation:
Department of Agricultural Economics, Oklahoma State University, Stillwater, OK
Andrew Muhammad
Affiliation:
Markets and Trade Economics Division, Economic Research Service, U.S. Department of Agriculture, Washington, DC
John D. Anderson
Affiliation:
American Farm Bureau Federation, Washington, DC
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Abstract

Several recent papers have used annual changes and monthly data to estimate demand systems. Such use of overlapping data introduces a moving average error term. This paper shows how to obtain consistent and asymptotically efficient estimates of a demand system using seasonally differenced data. Monte Carlo simulations and an empirical application to the estimation of the U.S. meat demand are used to compare the proposed estimator with alternative estimators. Once the correct estimator is used, there is no advantage to using overlapping data in estimating a demand system.

Keywords

autocorrelationdemand systemMonte Carlooverlapping dataseasonal differencesC13Q11Q13

Information

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 42 , Issue 2 , May 2010 , pp. 321 - 335
Copyright
Copyright © Southern Agricultural Economics Association 2010

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