Using Weights in Two-Way Fixed Effects and Event Study Regressions PDF Download
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Author: Jahyeon Koo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Recent papers show that coefficients in two-way fixed effect (TWFE) and event study (ES) regressions can hardly be interpreted as the average treatment effect, depending on heterogeneity in the treatment effects. This paper proposes to contrast estimates with and without weighting to detect heterogeneity in treatment effects. If estimates with and without weighting are similar to each other, TWFE and ES regressions are enough to identify average treatment effect. However, if they are different, it is necessary to use alternative estimators robust to heterogeneous effects to identify the average treatment effect (e.g., de Chaisemartin and D'Haultfuille, 2020). For an empirical application, I revisit literature estimating the impact of unilateral divorce law on the divorce rate with US panel data. The discrepancy between estimates with and without weighting implies that the divorce law affected divorce rates differently across groups and time. After using the alternative estimators, the effect of this law on the divorce rate is smaller than previous papers found.
Author: Jahyeon Koo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Recent papers show that coefficients in two-way fixed effect (TWFE) and event study (ES) regressions can hardly be interpreted as the average treatment effect, depending on heterogeneity in the treatment effects. This paper proposes to contrast estimates with and without weighting to detect heterogeneity in treatment effects. If estimates with and without weighting are similar to each other, TWFE and ES regressions are enough to identify average treatment effect. However, if they are different, it is necessary to use alternative estimators robust to heterogeneous effects to identify the average treatment effect (e.g., de Chaisemartin and D'Haultfuille, 2020). For an empirical application, I revisit literature estimating the impact of unilateral divorce law on the divorce rate with US panel data. The discrepancy between estimates with and without weighting implies that the divorce law affected divorce rates differently across groups and time. After using the alternative estimators, the effect of this law on the divorce rate is smaller than previous papers found.
Author: Clement de Chaisemartin
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
We study regressions with period and group fixed effects and several treatment variables. Under a parallel trends assumption, the coefficient on each treatment identifies the sum of two terms. The first term is a weighted sum of the effect of that treatment in each group and period, with weights that may be negative and sum to one. The second term is a sum of the effects of the other treatments, with weights summing to zero. Accordingly, coefficients in those regressions are not robust to heterogeneous effects, and may be contaminated by the effect of other treatments. We propose alternative differences-in-differences estimators. To estimate, say, the effect of the first treatment, our estimators compare the outcome evolution of a group whose first treatment changes while its other treatments remain unchanged, to control groups whose treatments all remain unchanged, and with the same baseline treatments or treatments' history as the switching group. Those carefully selected comparisons are robust to heterogeneous effects, and do not suffer from the contamination problem.
Author: Jeffrey M. Wooldridge
Publisher: MIT Press
ISBN: 0262232588
Category : Business & Economics
Languages : en
Pages : 1095
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Book Description
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Author: Henning Best
Publisher: SAGE
ISBN: 1473908353
Category : Social Science
Languages : en
Pages : 425
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Book Description
′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.
Author: Paul D. Allison
Publisher:
ISBN: 9781642953237
Category :
Languages : en
Pages : 160
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Book Description
Fixed Effects Regression Methods for Longitudinal Data Using SAS, written by Paul Allison, is an invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques. First introduced by economists, fixed effects methods are gaining widespread use throughout the social sciences. Designed to eliminate major biases from regression models with multiple observations (usually longitudinal) for each subject (usually a person), fixed effects methods essentially offer control for all stable characteristics of the subjects, even characteristics that are difficult or impossible to measure. This straightforward and thorough text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are then illustrated with detailed examples using real data. The book contains thorough discussions of the following uses of SAS procedures: PROC GLM for estimating fixed effects linear models for quantitative outcomes, PROC LOGISTIC for estimating fixed effects logistic regression models, PROC PHREG for estimating fixed effects Cox regression models for repeated event data, PROC GENMOD for estimating fixed effects Poisson regression models for count data, and PROC CALIS for estimating fixed effects structural equation models. To gain the most benefit from this book, readers should be familiar with multiple linear regression, have practical experience using multiple regression on real data, and be comfortable interpreting the output from a regression analysis. An understanding of logistic regression and Poisson regression is a plus. Some experience with SAS is helpful, but not required.
Author: Joshua D. Angrist
Publisher: Princeton University Press
ISBN: 0691120358
Category : Business & Economics
Languages : en
Pages : 392
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Book Description
In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.
Author: Mathias Harrer
Publisher: CRC Press
ISBN: 1000435636
Category : Mathematics
Languages : en
Pages : 500
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Book Description
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Author: Bjørn Espen Eckbo
Publisher: Elsevier
ISBN: 0080488919
Category : Business & Economics
Languages : en
Pages : 559
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Book Description
Judging by the sheer number of papers reviewed in this Handbook, the empirical analysis of firms' financing and investment decisions—empirical corporate finance—has become a dominant field in financial economics. The growing interest in everything "corporate is fueled by a healthy combination of fundamental theoretical developments and recent widespread access to large transactional data bases. A less scientific—but nevertheless important—source of inspiration is a growing awareness of the important social implications of corporate behavior and governance. This Handbook takes stock of the main empirical findings to date across an unprecedented spectrum of corporate finance issues, ranging from econometric methodology, to raising capital and capital structure choice, and to managerial incentives and corporate investment behavior. The surveys are written by leading empirical researchers that remain active in their respective areas of interest. With few exceptions, the writing style makes the chapters accessible to industry practitioners. For doctoral students and seasoned academics, the surveys offer dense roadmaps into the empirical research landscape and provide suggestions for future work.*The Handbooks in Finance series offers a broad group of outstanding volumes in various areas of finance*Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance*The series is international in scope with contributions from field leaders the world over
Author: Walter Leite
Publisher: SAGE Publications
ISBN: 1483313395
Category : Social Science
Languages : en
Pages : 225
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Book Description
Practical Propensity Score Methods Using R by Walter Leite is a practical book that uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Author: A. W. van der Vaart
Publisher: Cambridge University Press
ISBN: 9780521784504
Category : Mathematics
Languages : en
Pages : 470
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Book Description
This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master s level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.
