TY - JOUR
AU - Mullahy,John
TI - Multivariate Fractional Regression Estimation of Econometric Share Models
JF - National Bureau of Economic Research Working Paper Series
VL - No. 16354
PY - 2010
Y2 - September 2010
DO - 10.3386/w16354
UR - http://www.nber.org/papers/w16354
L1 - http://www.nber.org/papers/w16354.pdf
N1 - Author contact info:
John Mullahy
University of Wisconsin-Madison
Dept. of Population Health Sciences
787 WARF, 610 N. Walnut Street
Madison, WI 53726
Tel: 608/265-5410
Fax: 608/263-2820
E-Mail: jmullahy@facstaff.wisc.edu
AB - 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 Dirichlet-multinomial 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.
ER -