Identification-Robust Inference With Simulation-Based Pseudo-Matching

Bertille Antoine, Lynda Khalaf, Maral Kichian and Zhenjiang Lin

Journal of Business & Economic Statistics, 2023, vol. 41, issue 2, 321-338

Abstract: 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.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2021.2019046 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:41:y:2023:i:2:p:321-338

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1080/07350015.2021.2019046

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().