Estimating Dynamic Panel Models in Corporate Finance

By Mark J. Flannery, Kristine Watson Hankins. 2013

809 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8d6293901d1de17116fdfd3a67081347a9eff85c

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In Economics and Econometrics

Citations in the corpus

Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models (2017, background): “Although an extra regressor is included in the simulation studies in Arellano and Bond [1], Kiviet [13], Bowsher [14], Hsiao et al. [15], Bond and Windmeijer [16], Bun and Carree [17,18], Bun and Kiviet [19], Gouriéroux et al. [20], Hayakawa [21], Dhaene and Jochmans [22], Flannery and Hankins [23],”
Capital Structure Decisions around the World: Which Factors Are Reliably Important? (2015, neutral): “Flannery and Hankins (2013) conclude that Blundell and Bond’s system generalized method of moments (GMM) estimation method provides adequate estimates in the presence of these estimation issues.”
Ownership concentration and corporate performance from a dynamic perspective: Does national governance quality matter? (2015, methodology): “More interestingly, by doing so, our study well-responds to the recent calls from Flannery and Hankins (2013); Wintoki et al.”
Endogeneity - how failure to correct for it can cause wrong inferences and some remedies (2015, neutral): “In addition, Flannery and Hankins (2013) find that Within Groups performs poorly for short panels and is sensitive to high persistence in the data (i.e. coefficient a in equation (1) would be close to 1).”
Bank capital management: International evidence (2015, methodology): “Therefore, following Flannery and Hankins (2013), we estimate equation (3) using Blundell and Bond's (1998) generalized method of moments (GMM) estimator.”