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Panel Methods for Finance : A Guide to Panel Data Econometrics for Financial Applications / Marno Verbeek.

By: Material type: TextTextSeries: De Gruyter Studies in the Practice of Econometrics ; 1Publisher: Berlin ; Boston : De Gruyter, [2021]Copyright date: ©2021Description: 1 online resource (XVI, 280 p.)Content type:
Media type:
Carrier type:
ISBN:
  • 9783110660135
  • 9783110660814
  • 9783110660739
Subject(s): Other classification:
  • online - DeGruyter
Online resources: Available additional physical forms:
  • Issued also in print.
Contents:
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
Summary: 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
Holdings
Item type Current library Call number URL Status Notes Barcode
eBook eBook Biblioteca "Angelicum" Pont. Univ. S.Tommaso d'Aquino Nuvola online online - DeGruyter (Browse shelf(Opens below)) Online access Not for loan (Accesso limitato) Accesso per gli utenti autorizzati / Access for authorized users (dgr)9783110660739

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

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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.

Mode of access: Internet via World Wide Web.

In English.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 02. Mai 2023)