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Inference on two component mixtures under tail restrictions

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  • Marc Henry
  • Koen Jochmans
  • Bernard Salani'e

Abstract

Many econometric models can be analyzed as finite mixtures. We focus on two-component mixtures and we show that they are nonparametrically point identified by a combination of an exclusion restriction and tail restrictions. Our identification analysis suggests simple closed-form estimators of the component distributions and mixing proportions, as well as a specification test. We derive their asymptotic properties using results on tail empirical processes and we present a simulation study that documents their finite-sample performance.

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  • Marc Henry & Koen Jochmans & Bernard Salani'e, 2021. "Inference on two component mixtures under tail restrictions," Papers 2102.06232, arXiv.org.
    • Handle: RePEc:arx:papers:2102.06232
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    2. Yuichi Kitamura & Louise Laage, 2018. "Nonparametric Analysis of Finite Mixtures," Papers 1811.02727, arXiv.org.

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