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File name: SSRN-id1030061. ; Size: 235K
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Estimation of Fractional Dependent Variables in Dynamic Panel Data Models with an Application to Firm Dividend Policy
Margaret S. Loudermilk
University of Chicago; Argonne National Laboratory; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP)
Journal of Business and Economic Statistics, 2007, 25, 462-472.
Abstract:
Fractional dependent variables and models with state dependence arise in many economic applications. However, estimating models with fractional dependent variables is complicated by the presence of two corner solution outcomes. When coupled with a dynamic panel data setting, estimating quantities of interest can be quite complex or computationally difficult. This paper demonstrates a method for estimating fractional response variables, which is easy to implement, and presents an application of the technique to the determination of firm dividend policy. The estimation demonstrates that neglecting dynamics, unobserved heterogeneity, or the doubly-censored nature of the dependent variable can generate misleading conclusions.
Number of Pages in PDF File: 11
Keywords: Tobit, nonlinear model, dual corner solution, doubly-censored
JEL Classification: C1, C2, C5
Accepted Paper Series
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Date posted: October 6, 2007
; Last revised: November 16, 2007
Suggested CitationLoudermilk, Margaret S., Estimation of Fractional Dependent Variables in Dynamic Panel Data Models with an Application to Firm Dividend Policy. Journal of Business and Economic Statistics, 2007, 25, 462-472.. Available at SSRN: http://ssrn.com/abstract=1019347
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