Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/227330
Authors: 
Baltagi, Badi H.
Pirotte, Alain
Yang, Zhenlin
Year of Publication: 
2020
Series/Report no.: 
IZA Discussion Papers No. 13803
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.
Subjects: 
adjusted quasi-scores
fixed effects
heteroskedasticity
incidental parameters
martingale difference
non-normality
short dynamic panels
spatial effects
JEL: 
C12
C18
C21
C23
Document Type: 
Working Paper

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