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

• Main Authors: BALTAGI, Badi K., PIROTTE, Alain, Yang, Zhenlin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Spatial effects; Adjusted quasi-scores; Fixed effects; Heteroskedasticity; Incidental parameters; Martingale difference; Non-normality; Short dynamic panels; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/2479; https://ink.library.smu.edu.sg/context/soe_research/article/3478/viewcontent/Tests_Homo_BPY_June2018_sv.pdf
• Institution: Singapore Management University

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.