Financial data are typically characterised by a time-series and cross-sectional dimension. Accordingly, econometric modelling in finance requires appropriate attention to these two – or occasionally more than two – dimensions of the data. Panel data techniques are developed to do exactly this. This book provides an overview of commonly applied panel methods for financial applications, including popular techniques such as Fama-MacBeth estimation, one-way, two-way and interactive fixed effects, clustered standard errors, instrumental variables, and difference-in-differences.
Panel Methods for Finance: A Guide to Panel Data Econometrics for Financial Applications by Marno Verbeek offers the reader:
• Focus on panel methods where the time dimension is relatively small
• A clear and intuitive exposition, with a focus on implementation and practical relevance
• Concise presentation, with many references to financial applications and other sources
• Focus on techniques that are relevant for and popular in empirical work in finance and accounting
• Critical discussion of key assumptions, robustness, and other issues related to practical implementation
Author(s): Marno Verbeek
Series: De Gruyter Studies in the Practice of Econometrics, 1
Publisher: De Gruyter
Year: 2021
Language: English
Pages: 250
City: Berlin
Preface
Acknowledgments
Contents
Acronyms
1 Introduction
2 Linear static models
3 Dealing with heterogeneity and endogeneity: fixed effects, IV and GMM
4 Outliers, missing values and other data issues
5 Linear dynamic models
6 Models with limited dependent variables
7 Estimating average treatment effects
Bibliography
Index