seminars:stat:171207 [Department of Mathematics and Statistics, Binghamton University]

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<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>

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^  **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  |
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<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.
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