Identifying latent grouped patterns in panel data models with interactive fixed effects

• المؤلفون الرئيسيون: SU, Liangjun, JU, Gaosheng
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2018
• الموضوعات: Classifier Lasso; Cross section dependence; Dynamic panel; High dimensionality; Latent structure; Parameter heterogeneity; Penalized method; Econometrics
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/soe_research/2192; https://ink.library.smu.edu.sg/context/soe_research/article/3191/viewcontent/Panel_structure_interactive_fixed_effects_20160808_pp.pdf

We consider the estimation of latent grouped patterns in dynamic panel data models with interactive fixed effects. We assume that the individual slope coefficients are homogeneous within a group and heterogeneous across groups but each individual’s group membership is unknown to the researcher. We c...