Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models

Badi Baltagi, Alain Pirotte () and Zhenlin Yang
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Alain Pirotte: University of Paris 2

No 13803, IZA Discussion Papers from Institute of Labor Economics (IZA)

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 or dynamic panel models. Monte Carlo results show that the proposed AQS tests have good finite sample properties.

Keywords: non-normality; martingale difference; incidental parameters; heteroskedasticity; fixed effects; adjusted quasi-scores; short dynamic panels; spatial effects (search for similar items in EconPapers)
JEL-codes: C12 C18 C21 C23 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2020-10
New Economics Papers: this item is included in nep-ore and nep-sea
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Published - published in: Journal of Econometrics, 2021, 224 (2), 245-270.

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Related works:
Journal Article: 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 (2021)
Working Paper: Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models (2018)
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