Robustness of binary choice models to conditional heteroscedasticity

Tim Ginker, Offer Lieberman

Research output: Contribution to journalArticlepeer-review

Abstract

We show that when the true data generating process of a large class of binary choice models contains conditional heteroscedasticity, predictions based on the misspecified MLE in which conditional heteroscedasticity is ignored, are unaffected by the misspecification.

Original languageEnglish
Pages (from-to)130-134
Number of pages5
JournalEconomics Letters
Volume150
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Conditional heteroscedasticity
  • Misspecified models
  • Probit

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics

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