A regularization approach to the minimum distance estimation: application to structural macroeconomic estimation using IRFs

Senay Sokullu

Oxford Economic Papers, 2020, vol. 72, issue 2, 546-565

Abstract: This article considers the invertibility problem of the optimal weighting matrix encountered during Impulse Response Function Matching Estimation (IRFME) of Dynamic Stochastic General Equilibrium (DSGE) Models. We propose to use a regularized inverse and derive the asymptotic properties of the estimator. We show that the asymptotic distribution of our estimator converges to that of the optimal estimator which has important implications for testing the fit of the model. We demonstrate the small sample properties of the estimator by Monte Carlo simulation exercises. Finally, we use our estimator to estimate the model in Altig et al.

JEL-codes: C10 E30 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/oep/gpz045 (application/pdf)
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:oup:oxecpp:v:72:y:2020:i:2:p:546-565.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

Oxford Economic Papers is currently edited by James Forder and Francis J. Teal

More articles in Oxford Economic Papers from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().