Publication Type
Journal Article
Version
submittedVersion
Publication Date
12-2020
Abstract
We propose an Adjusted Quasi-Score (AQS) method for constructing tests for homoskedasticity in spatial econometric models. We first obtain an AQS function by adjusting the score-type function from the given model to achieve unbiasedness, and then develop an Outer-Product-of-Martingale-Difference (OPMD) estimate of its variance. In standard problems where a genuine (quasi) score vector is available, the AQS-OPMD method leads to finite sample improved tests over the usual methods. More importantly in non-standard problems where a genuine (quasi) score is not available and the usual methods fail, the proposed AQS-OPMD method provides feasible solutions. The AQS tests are formally derived and asymptotic properties examined for three representative models: spatial cross-sectional, static and dynamic panel models. Monte Carlo results show that the proposed AQS tests have good finite sample properties.
Keywords
Spatial effects, Adjusted quasi-scores, Fixed effects, Heteroskedasticity, Incidental parameters, Martingale difference, Non-normality, Short dynamic panels
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
First Page
1
Last Page
26
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2020.10.002
Publisher
Elsevier
Embargo Period
7-7-2021
Citation
BALTAGI, Badi K.; PIROTTE, Alain; and Yang, Zhenlin.
Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models. (2020). Journal of Econometrics. 1-26.
Available at: https://ink.library.smu.edu.sg/soe_research/2479
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2020.10.002
