Identifying latent structures in panel data

Identifying latent structures in panel data

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 membershi...

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Bibliographic Details
Main Authors: SU, Liangjun, SHI, Zhentao, Peter C. B. PHILLIPS
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
Classification
cluster analysis
dynamic panel
group Lasso
high dimensionality
nonlinear panel
oracle property
panel structure model
parameter heterogeneity
penalized least squares
penalized GMM
penalized profile likelihood
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/1911
https://ink.library.smu.edu.sg/context/soe_research/article/2910/viewcontent/IdentifyingLatentStructuresPanelData_2014Jul_pp.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/soe_research/1911
https://ink.library.smu.edu.sg/context/soe_research/article/2910/viewcontent/IdentifyingLatentStructuresPanelData_2014Jul_pp.pdf

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