A Two-Stage Estimator of Instrumental Variable Quantile Regression for Panel Data with Time-Invariant Effects

Tao Li

Title:
A Two-Stage Estimator of Instrumental Variable Quantile Regression for Panel Data with Time-Invariant Effects

Authors:
Tao Li

Cite This Article :

Tao Li "A Two-Stage Estimator of Instrumental Variable Quantile Regression for Panel Data with Time-Invariant Effects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-6, October 2021, pp.1757-1762, URL: https://www.ijtsrd.com/papers/ijtsrd47716.pdf

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Abstract :
This paper proposes a two-stage instrumental variable quantile regression (2S-IVQR) estimation to estimate the time-invariant effects in panel data model. In the first stage, we introduce the dummy variables to represent the time-invariant effects, and use quantile regression to estimate effects of individual covariates. The advantage of the first stage is that it can reduce calculations and the number of estimation parameters. Then in the second stage, we adapt instrument variables approach and 2SLS method. In addition, we present a proof of 2S-IVQR estimator's large sample properties. Monte Carlo simulation study shows that with increasing sample size, the Bias and RMSE of our estimator are decreased. Besides, our estimator has lower Bias and RMSE than those of the other two estimators.

Keywords :
Time-invariant effects; Panel data; Quantile regression; Instrument variables

Publication Details:

Unique Identification Number : IJTSRD47716

Published In : Volume-5 | Issue-6, October 2021

Page Number(s) : 1757-1762

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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