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Common Errors: How to (and Not to) Control for Unobserved Heterogeneity
by
Gormley, Todd A.
, Matsa, David A.
in
Analytical estimating
/ Asset pricing
/ Computational methods
/ Consistent estimators
/ Corporate finance
/ Covariance
/ Errors
/ Estimating techniques
/ Estimation
/ Estimation bias
/ Estimation methods
/ Estimators
/ Financial analysis
/ Heterogeneity
/ Industrial research
/ Inference
/ Mathematical independent variables
/ Mathematical models
/ Methodology
/ Modeling
/ Research methodology
/ Standard error
/ Statistical inference
/ Studies
2014
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Common Errors: How to (and Not to) Control for Unobserved Heterogeneity
by
Gormley, Todd A.
, Matsa, David A.
in
Analytical estimating
/ Asset pricing
/ Computational methods
/ Consistent estimators
/ Corporate finance
/ Covariance
/ Errors
/ Estimating techniques
/ Estimation
/ Estimation bias
/ Estimation methods
/ Estimators
/ Financial analysis
/ Heterogeneity
/ Industrial research
/ Inference
/ Mathematical independent variables
/ Mathematical models
/ Methodology
/ Modeling
/ Research methodology
/ Standard error
/ Statistical inference
/ Studies
2014
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Do you wish to request the book?
Common Errors: How to (and Not to) Control for Unobserved Heterogeneity
by
Gormley, Todd A.
, Matsa, David A.
in
Analytical estimating
/ Asset pricing
/ Computational methods
/ Consistent estimators
/ Corporate finance
/ Covariance
/ Errors
/ Estimating techniques
/ Estimation
/ Estimation bias
/ Estimation methods
/ Estimators
/ Financial analysis
/ Heterogeneity
/ Industrial research
/ Inference
/ Mathematical independent variables
/ Mathematical models
/ Methodology
/ Modeling
/ Research methodology
/ Standard error
/ Statistical inference
/ Studies
2014
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Common Errors: How to (and Not to) Control for Unobserved Heterogeneity
Journal Article
Common Errors: How to (and Not to) Control for Unobserved Heterogeneity
2014
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Overview
Controlling for unobserved heterogeneity (or \"common errors\"), such as industry-specific shocks, is a fundamental challenge in empirical research. This paper discusses the limitations of two approaches widely used in corporate finance and asset pricing research: demeaning the dependent variable with respect to the group (e.g., \"industry-adjusting\") and adding the mean of the group's dependent variable as a control. We show that these methods produce inconsistent estimates and can distort inference. In contrast, the fixed effects estimator is consistent and should be used instead. We also explain how to estimate the fixed effects model when traditional methods are computationally infeasible.
Publisher
Oxford University Press,Oxford Publishing Limited (England)
Subject
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