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

Badi H. Baltagi, Alain Pirotte, Zhenlin Yang

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
JournalJournal of Econometrics
DOIs
StateAccepted/In press - 2020

Keywords

  • Adjusted quasi-scores
  • Fixed effects
  • Heteroskedasticity
  • Incidental parameters
  • Martingale difference
  • Non-normality
  • Short dynamic panels
  • Spatial effects

ASJC Scopus subject areas

  • Economics and Econometrics

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