INFERENCE ON TWO-COMPONENT MIXTURES UNDER TAIL RESTRICTIONS

B-Tier
Journal: Econometric Theory
Year: 2017
Volume: 33
Issue: 3
Pages: 610-635

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:cup:etheor:v:33:y:2017:i:03:p:610-635_00
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-25