Heteroskedasticity in One-Way Error Component Probit Models

Richard Kouamé Moussa
Additional contact information
Richard Kouamé Moussa: ENSEA, Abidjan 08, Cote D’lvoire

Econometrics, 2019, vol. 7, issue 3, 1-22

Abstract: This paper introduces an estimation procedure for a random effects probit model in presence of heteroskedasticity and a likelihood ratio test for homoskedasticity. The cases where the heteroskedasticity is due to individual effects or idiosyncratic errors or both are analyzed. Monte Carlo simulations show that the test performs well in the case of high degree of heteroskedasticity. Furthermore, the power of the test increases with larger individual and time dimensions. The robustness analysis shows that applying the wrong approach may generate misleading results except for the case where both individual effects and idiosyncratic errors are modelled as heteroskedastic.

Keywords: heteroskedasticity; probit; panel data; Gauss–Hermite quadrature; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2225-1146/7/3/35/pdf (application/pdf)
https://www.mdpi.com/2225-1146/7/3/35/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:7:y:2019:i:3:p:35-:d:256734

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().