Frontmatter -- 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

restricted access online access with authorization star

http://purl.org/coar/access_right/c_16ec

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

Issued also in print.

The accessibility of this resources in unknown or unassessed.

Mode of access: Internet via World Wide Web.

Marno Verbeek, Erasmus University, The Netherlands

In English.

Description based on online resource; title from PDF title page (publisher's Web site, viewed March 03 2026)