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The Fallacy of Differencing to Reduce Multicollinearity

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  • Oscar R. Burt

Abstract

It is shown analytically that differencing time-series data for the purpose of reducing multicollinearity in the data set for the independent variables of a regression equation cannot possibly succeed when its effect on the disturbance term is taken into account. In addition, the intuitive basis used to justify first differencing of multicollinear data is demonstrated to contain a flaw, even when the effects of differencing the disturbance term are ignored.

Suggested Citation

  • Oscar R. Burt, 1987. "The Fallacy of Differencing to Reduce Multicollinearity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(3), pages 697-700.
    • Handle: RePEc:oup:ajagec:v:69:y:1987:i:3:p:697-700.
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    Cited by:

    1. Lippi, Francesco & Secchi, Alessandro, 2006. "Technological change and the demand for currency: An analysis with household data," CEPR Discussion Papers 6023, C.E.P.R. Discussion Papers.
    2. Yaguchi, Yu, 1994. "A panel data approach to the intercountry metaproduction function," ISU General Staff Papers 1994010108000018181, Iowa State University, Department of Economics.
    3. Gvillo, Rejeana & Capps, Oral, Jr. & Dharmasena, Senarath, 2014. "Dynamics of Advertising and Demand for Fluid Milk in the United States: An Incomplete Demand Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170265, Agricultural and Applied Economics Association.

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