We develop a dynamic panel threshold model of capital structure to test the dynamic trade-off theory, allowing for asymmetries in firms' adjustments toward target leverage. Our novel estimation approach is able to consistently estimate heterogeneous speeds of adjustment in different regimes as well as to properly test for the threshold effect. We consider several proxies for adjustment costs that affect the asymmetries in capital structure adjustments and find evidence that firms with large financing imbalance (or a deficit), large investment or low earnings volatility adjust faster than those with the opposite characteristics. Firms not only adjust at different rates but also seem to adjust toward heterogeneous leverage targets. Moreover, we document a consistent pattern that firms undertaking quick adjustment are over-levered with a financing deficit and rely heavily on equity issues to make such adjustment.

Please cite this article as: Dang, V.A., Kim, M., Shin, Y., In search of robust methods for dynamic panel data models in empirical corporate finance, Journal of Banking & Finance (2014), doi: http://dx. AbstractWe 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. (Viet Anh Dang), Minjoo.Kim@glasgow.ac.uk (Minjoo Kim), yongcheol.shin@york.a.cuk (Yongcheol Shin)

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