Trading-Day Variation: Theory and Implications for Monthly Meat Demand

M. McNulty and Wallace Huffman

Staff General Research Papers Archive from Iowa State University, Department of Economics

Abstract: The authors consider the problem of fitting regression models with data containing trading-day variation. Multiplicative and additive expressions for trading-day variation are presented. Multiplicative adjustment is more reasonable than the additive but is also more complex. Expressions are derived for biases that trading-day variation introduces into least squares estimators. Estimated retail demands for beef, pork, and chicken show the biases are large and in the directions predicted when monthly data are used, but are small when quarterly data are used. Multiplicative adjustment is statistically superior to additive adjustment, although practical differences are small.

Date: 1992-01-01
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Published in American Journal of Agricultural Economics 1992, vol. 74, pp. 1003-1009

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Journal Article: Trading-Day Variation: Theory and Implications for Monthly Meat Demand (1992)
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