Alternative estimating and testing empirical strategies for fractional regression models

TLDR: In this article, a comprehensive survey of the main alternative models and estimation methods suitable to deal with fractional response variables is presented, and a full testing methodology is proposed to assess the validity of the assumptions required by each alternative estimator.

Abstract: In many economic settings, the variable of interest is often a fraction or a proportion, being defined only on the unit interval. The bounded nature of such variables and, in some cases, the possibility of nontrivial probability mass accumulating at one or both boundaries raise some interesting estimation and inference issues. In this paper we: (i) provide a comprehensive survey of the main alternative models and estimation methods suitable to deal with fractional response variables; (ii) propose a full testing methodology to assess the validity of the assumptions required by each alternative estimator; and (iii) examine the finite sample properties of most of the estimators and tests discussed through an extensive Monte Carlo study. An application concerning corporate capital structure choices is also provided.