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Identification-Robust Inference With Simulation-Based Pseudo-Matching

We develop a general simulation-based inference procedure for partially specified models. Our procedure is based on matching auxiliary statistics to simulated counterparts where nuisance parameters are calibrated neither assuming identification of parameters of interest nor a one-to-one binding function. The conditions underlying the asymptotic validity of our (pseudo-)simulators in conjunction with appropriate bootstraps are characterized beyond the strict and exact calibration of the parameters of the simulator. Our procedure is illustrated through impulse-response (IR) matching in a simulation study of a stylized dynamic stochastic equilibrium model, and two empirical applications on the New Keynesian Phillips curve and on the Industrial Production index. In addition to usual Wald-type statistics that combine structural or reduced form IRs, we analyze local projections IRs through a factor-analytic measure of distance which eschews the need to define a weighting matrix.

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Informasi Detail

Judul Seri

JOURNAL OF BUSINESS & ECONIMIC STATISTICS; Vol. 41, No. 2, April 2023

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p 321-338

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

BOOTSTRAP
WEAK IDENTIFICATION
APPROXIMATE CALIBRATION
IR-MATCHING

Info Detail Spesifik

https://doi.org/10.1080/07350015.2021.2019046

Pernyataan Tanggungjawab

Bertille Antoine, Lynda Khalaf, Maral Kichian, Zhenjiang Lin

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