Estimation of Fractional Dependent Variables in Dynamic Panel Data Models With an Application to Firm Dividend Policy
提出一种易于实施的分数因变量估计方法，用于动态面板数据模型，并应用于企业股利政策分析，发现忽略动态性、异质性或双重截断会导致误导性结论。
AbstractFractional 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 article 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.KEY WORDS: Doubly censoredDual-corner solutionNonlinear modelTobit