EconPapers    
Economics at your fingertips  
 

Identifying Latent Structures in Panel Data

Liangjun Su, Zhentao Shi and Peter Phillips ()

Econometrica, 2016, vol. 84, 2215-2264

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.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (31) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/

Related works:
Working Paper: Identifying Latent Structures in Panel Data (2014) Downloads
Working Paper: Identifying Latent Structures in Panel Data (2014) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:emetrp:v:84:y:2016:i::p:2215-2264

Ordering information: This journal article can be ordered from
https://www.economet ... ordering-back-issues

Access Statistics for this article

Econometrica is currently edited by Guido W. Imbens

More articles in Econometrica from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2020-07-29
Handle: RePEc:wly:emetrp:v:84:y:2016:i::p:2215-2264