Article ID Journal Published Year Pages File Type
5088714 Journal of Banking & Finance 2015 47 Pages PDF
Abstract
We examine which methods are appropriate for estimating dynamic panel data models in empirical corporate finance. Our simulations show that the instrumental variable and GMM estimators are unreliable, and sensitive to the presence of unobserved heterogeneity, residual serial correlation, and changes in control parameters. The bias-corrected fixed-effects estimators, based on an analytical, bootstrap, or indirect inference approach, are found to be the most appropriate and robust methods. These estimators perform reasonably well even in models with fractional dependent variables censored at [0, 1]. We verify these results in two empirical applications, on dynamic capital structure and cash holdings.
Related Topics
Social Sciences and Humanities Economics, Econometrics and Finance Economics and Econometrics
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