Identifying Latent Structures in Panel Data

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dc.contributor.author Su, L en
dc.contributor.author Shi, Z en
dc.contributor.author Phillips, Peter en
dc.date.accessioned 2017-03-22T23:40:59Z en
dc.date.issued 2016-11 en
dc.identifier.citation Econometrica, November 2016, 84 (6), 2215 - 2264 en
dc.identifier.issn 0012-9682 en
dc.identifier.uri http://hdl.handle.net/2292/32288 en
dc.description.abstract This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented. en
dc.description.uri https://www.econometricsociety.org/publications/econometrica/2016/11/01/identifying-latent-structures-panel-data en
dc.language English en
dc.publisher The Econometric Society en
dc.relation.ispartofseries Econometrica en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from http://www.sherpa.ac.uk/romeo/issn/0012-9682/ https://www.econometricsociety.org/publications/econometrica/permissions en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Identifying Latent Structures in Panel Data en
dc.type Journal Article en
dc.identifier.doi 10.3982/ECTA12560 en
pubs.issue 6 en
pubs.begin-page 2215 en
pubs.volume 84 en
dc.description.version VoR - Version of Record en
pubs.author-url http://onlinelibrary.wiley.com/doi/10.3982/ECTA12560/full en
pubs.end-page 2264 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Article en
pubs.elements-id 547918 en
pubs.org-id Business and Economics en
pubs.org-id Economics en
dc.identifier.eissn 1468-0262 en
pubs.record-created-at-source-date 2017-03-23 en
pubs.online-publication-date 2016-11-09 en


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