LIKELIHOOD INFERENCE on SEMIPARAMETRIC MODELS with GENERATED REGRESSORS

Yukitoshi Matsushita, Taisuke Otsu

研究成果: Article査読

1 被引用数 (Scopus)

抄録

Hahn and Ridder (2013, Econometrica 81, 315-340) formulated influence functions of semiparametric three-step estimators where generated regressors are computed in the first step. This class of estimators covers several important examples for empirical analysis, such as production function estimators by Olley and Pakes (1996, Econometrica 64, 1263-1297) and propensity score matching estimators for treatment effects by Heckman, Ichimura, and Todd (1998, Review of Economic Studies 65, 261-294). The present article studies a nonparametric likelihood-based inference method for the parameters in such three-step estimation problems. In particular, we apply the general empirical likelihood theory of Bravo, Escanciano, and van Keilegom (2018, Annals of Statistics, forthcoming) to modify semiparametric moment functions to account for influences from plug-in estimates into the above important setup, and show that the resulting likelihood ratio statistic becomes asymptotically pivotal without undersmoothing in the first and second step nonparametric estimates.

本文言語English
ページ(範囲)626-657
ページ数32
ジャーナルEconometric Theory
36
4
DOI
出版ステータスPublished - 2020 8 1
外部発表はい

ASJC Scopus subject areas

  • 社会科学(その他)
  • 経済学、計量経済学

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