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Parametric Identification of Multiplicative Exponential Heteroscedasticity

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  • Alyssa Carlson

Abstract

Harvey () first proposed multiplicative exponential heteroscedasticity in the context of linear regression. These days it is more commonly seen in latent variable models such as Probit or Logit where correctly modelling the heteroscedasticity is imperative for consistent parameter estimates (Yatchew and Griliches, ). However, it appears the literature lacks a formal proof of point identification for the parametric model. This paper presents several examples that show the conditions presumed throughout the literature are not sufficient for identification. As a contribution, this paper discusses when identification can and cannot be easily obtained and provides proofs of point identification in common specifications.

Suggested Citation

  • Alyssa Carlson, 2019. "Parametric Identification of Multiplicative Exponential Heteroscedasticity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(3), pages 686-696, June.
    • Handle: RePEc:bla:obuest:v:81:y:2019:i:3:p:686-696
    DOI: 10.1111/obes.12280
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    Cited by:

    1. Alyssa Carlson & Riju Joshi, 2024. "Sample selection in linear panel data models with heterogeneous coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 237-255, March.
    2. Carlson, Alyssa, 2023. "Relaxing conditional independence in an endogenous binary response model," Journal of Econometrics, Elsevier, vol. 232(2), pages 490-500.

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