GROUPED PATTERNS OF HETEROGENEITY IN PANEL DATA

This paper introduces time-varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a "grouped fixed-effects" estimator that minimizes a least sq...

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Published in:Econometrica Vol. 83; no. 3; pp. 1147 - 1184
Main Authors: Bonhomme, Stéphane, Manresa, Elena
Format: Journal Article
Language:English
Published: Oxford, UK Econometric Society 01.05.2015
Blackwell Publishing Ltd
Subjects:
Cluster analysis
Clustering
Computation
Consistent estimators
Democracy
Discrete heterogeneity
Distinctive features
Econometrics
Economic analysis
Economic models
Estimators
fixed‐effects
Good faith estimates
Heterogeneity
Income
Inference
Infinity
Least squares
Least squares method
Membership
Modeling
NOTES AND COMMENTS
Panel data
Parameter estimation
Population estimates
Statistical inference
Studies
ISSN:0012-9682, 1468-0262
Online Access:Get full text
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Abstract This paper introduces time-varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a "grouped fixed-effects" estimator that minimizes a least squares criterion with respect to all possible groupings of the cross-sectional units. Recent advances in the clustering literature allow for fast and efficient computation. We provide conditions under which our estimator is consistent as both dimensions of the panel tend to infinity, and we develop inference methods. Finally, we allow for grouped patterns of unobserved heterogeneity in the study of the link between income and democracy across countries.
AbstractList This paper introduces time-varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a "grouped fixed-effects" estimator that minimizes a least squares criterion with respect to all possible groupings of the cross-sectional units. Recent advances in the clustering literature allow for fast and efficient computation. We provide conditions under which our estimator is consistent as both dimensions of the panel tend to infinity, and we develop inference methods. Finally, we allow for grouped patterns of unobserved heterogeneity in the study of the link between income and democracy across countries.
This paper introduces time-varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a 'grouped fixed-effects' estimator that minimizes a least squares criterion with respect to all possible groupings of the cross-sectional units. Recent advances in the clustering literature allow for fast and efficient computation. We provide conditions under which our estimator is consistent as both dimensions of the panel tend to infinity, and we develop inference methods. Finally, we allow for grouped patterns of unobserved heterogeneity in the study of the link between income and democracy across countries. Reprinted by permission of the Econometric Society
Author Bonhomme, Stéphane
Manresa, Elena
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SubjectTerms Cluster analysis
Clustering
Computation
Consistent estimators
Democracy
Discrete heterogeneity
Distinctive features
Econometrics
Economic analysis
Economic models
Estimators
fixed‐effects
Good faith estimates
Heterogeneity
Income
Inference
Infinity
Least squares
Least squares method
Membership
Modeling
NOTES AND COMMENTS
Panel data
Parameter estimation
Population estimates
Statistical inference
Studies
Title GROUPED PATTERNS OF HETEROGENEITY IN PANEL DATA
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