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Multivariate Fractional Regression Estimation Of Econometric Share Models

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  • John Mullahy

    (Dept. of Population Health Science, University of Wisconsin-Madison)

Abstract

This paper describes and applies econometric strategies for estimating regression models of economic share data outcomes where the shares may take boundary values (zero and one) with nontrivial probability. The main focus of the paper is on the conditional mean structures of such data. The paper proposes an extension of the fractional regression methodology proposed by Papke and Wooldridge, 1996, 2008, in univariate cross-sectional and panel contexts. The paper discusses the stochastic aspects of share definition and measurement, and summarizes important features of the existing literature on econometric strategies for share model estimation. The paper then goes on to discuss the univariate fractional regression estimation strategies proposed by Papke and Wooldridge and to extend the fractional regression approach to estimation of and inference about regression models describing the multivariate share data. Some issues involving outcome aggregation/disaggregation are considered, as is a full likelihood estimation approach based on Dirichletmultinomial models. The paper demonstrates the workings of these various empirical strategies by estimating models of financial asset portfolio shares using data from the 2001, 2004, and 2007 U.S. Surveys of Consumer Finances

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Bibliographic Info

Paper provided by Geary Institute, University College Dublin in its series Working Papers with number 201133.

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Length: 45 pages
Date of creation: 30 Nov 2011
Date of revision:
Handle: RePEc:ucd:wpaper:201133

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Keywords: fractional regression; economic shares; outcome aggregation/disaggregation; Dirichlet-multinomial models;

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References

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Cited by:
  1. Jianhong Mu & Bruce McCarl & Anne Wein, 2013. "Adaptation to climate change: changes in farmland use and stocking rate in the U.S," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 18(6), pages 713-730, August.
  2. Jean-Sauveur Ay & Raja Chakir & Julie Le Gallo, 2014. "The effects of scale, space and time on the predictive accuracy of land use models," Working Papers 2014/02, INRA, Economie Publique.
  3. Girma, Hiywot Menker & Hassan, Rashid M., 2014. "Drivers of land-use change in the Southern Nations, Nationalities and People’s Region of Ethiopia," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 9(2), April.
  4. Harald Oberhofer & Michael Pfaffermayr, 2014. "Two-Part Models for Fractional Responses Defined as Ratios of Integers," WIFO Working Papers 472, WIFO.

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