Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models

Badi Baltagi, Alain Pirotte and Zhenlin Yang

Journal of Econometrics, 2021, vol. 224, issue 2, 245-270

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: Adjusted quasi-scores; Fixed effects; Heteroskedasticity; Incidental parameters; Martingale difference; Non-normality; Short dynamic panels; Spatial effects (search for similar items in EconPapers)
JEL-codes: C12 C18 C21 C23 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models (2021)
Working Paper: Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models (2020)
Working Paper: Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:224:y:2021:i:2:p:245-270

DOI: 10.1016/j.jeconom.2020.10.002

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