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--- seminars:stat:171207 [2017/11/17 00:22] – created qyu
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+<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>
+<WRAP 70% center>
+^  **DATE:**|Thursday, December 7, 2017 |
+^  **TIME:**|1:15pm -- 2:15pm |
+^  **LOCATION:**|WH 100E |
+^  **SPEAKER:**|Ruiqi Liu, Binghamton University |
+^  **TITLE:**|Identification and estimation of panel data models with group structures  |
+</WRAP>
+\\
+<WRAP center box 80%>
+<WRAP centeralign>**Abstract**</WRAP>
+In this paper, we provide a simple approach to identify and estimate group structure in panel
+models using the M-estimation. We consider both linear and nonlinear panel models where the
+regression coefficients are heterogeneous across groups but homogeneous within a group and the
+group membership is unknown to researchers. The main result of the paper is that under certain
+assumptions, our estimation and classification method is consistent even if one uses an incorrect
+number of groups as long as this number is not underestimated. Conditions under which estimation
+of groups and regression coefficients are consistent and asymptotically normal are also provided
+in the paper. Monte Carlo simulations are conducted to examine the finite sample properties of
+the M-estimation. Findings in the simulation confirm our theoretical results in the paper. Application to labor force participation also highlights the necessity to take into account of individual
+heterogeneity and group heterogeneity.
+</WRAP>