Identifying Latent Structures in Panel Data

• Main Authors: SU, Liangjun, SHI, Zhentao, PHILLIPS, Peter C. B.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Classification; Cluster analysis; Convergence club; Dynamic panel; Group Lasso; High dimensionality; Oracle property; Panel structure model; Parameter heterogeneity; Penalized least squares; Penalized GMM; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1561; https://ink.library.smu.edu.sg/context/soe_research/article/2560/viewcontent/panel_structure_20131204.pdf
• Institution: Singapore Management University

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is unknown. Tw...