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Activity Number: 403 - SPAAC Poster Competition
Type: Topic Contributed
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #301754
Title: Estimation of Semiparametric Functional Coefficients Panel Data Model
Author(s): Shaymal Halder* and Emir Malikov
Companies: Auburn University and Auburn University
Keywords: panel data; functional coefficient; fixed effect; local linear regression; monte carlo simulation; finite sample performance

We consider the problem of estimating a semiparametric varying coefficient panel data model where the unobserved individual effects are correlated with explanatory variables in an unknown arbitrary way using a local linear regression approach. We present a new technique to estimate this model along the lines of Sun & Malikov’s (2015; 2018) whereby, unlike Rodriguez & Soberon’s (2014) alternative approach, we locally approximate the fixed-effects-free transformed equation around two different points. Using Monte Carlo simulations, we study potential gains in the finite sample performance and/or the computational time of the proposed estimation procedure over available alternatives under different scenarios.

Authors who are presenting talks have a * after their name.

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