Identify latent group structures in panel data: The classifylasso command

Yiru Wang

Canadian Stata Conference 2023 from Stata Users Group

Abstract: This presentation introduces a new command, classifylasso, that implements the classifier-lasso method to simultaneously identify and estimate unobserved parameter heterogeneity in panel-data models using penalized techniques. I document the functionality of this command, including penalized least-squares estimation of group-specific coefficients and classification of unknown group membership under a certain number of groups; two lasso-type estimators with robust standard errors, namely classifier-lasso and postlasso; and determination of the number of groups based on a BIC-type information criterion. I further introduce postestimation commands to display and visualize the estimation results.

Date: 2023-08-20
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Persistent link: https://EconPapers.repec.org/RePEc:boc:csug23:02

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