Improved Inference of Heteroscedastic Fixed Effects Models | Saeed | Pakistan Journal of Statistics and Operation Research

Download this PDF file

Refbacks

There are currently no refbacks.

Copyright (c) 2016 Pakistan Journal of Statistics and Operation Research

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Title

Improved Inference of Heteroscedastic Fixed Effects Models

Keywords

Bootstrap; HCCME; Kernel smoothing; Leverage points; Size distortion

Description

Heteroscedasticity is a stern problem that distorts estimation and testing of panel data model (PDM). Arellano (1987) proposed the White (1980) estimator for PDM with heteroscedastic errors but it provides erroneous inference for the data sets including high leverage points. In this paper, our attempt is to improve heteroscedastic consistent covariance matrix estimator (HCCME) for panel dataset with high leverage points. To draw robust inference for the PDM, our focus is to improve kernel bootstrap estimators, proposed by Racine and MacKinnon (2007). The Monte Carlo scheme is used for assertion of the results.

Date

2016-12-01

Identifier

http://pjsor.com/index.php/pjsor/article/view/1441

Source

Pakistan Journal of Statistics and Operation Research; Vol. 12 No. 4, 2016

Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810