Penalized Indirect Inference

Francisco Blasques () and Artem Duplinskiy
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Artem Duplinskiy: VU University Amsterdam, the Netherlands

No 15-009/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying economic theory. Bayesian methods have become increasingly popular as a tool for conducting inference on structural models since priors offer a way to exert control over the estimation results. This paper proposes a penalized indirect inference estimator that allows researchers to obtain economically meaningful parameter estimates in a frequentist setting. The asymptotic properties of the estimator are established for both correctly and incorrectly specified models. A Monte Carlo study reveals the role of the penalty function in shaping the finite sample distribution of the estimator. The advantages of using this estimator are highlighted in the empirical study of a state-of-the-art dynamic stochastic general equilibrium model.

Keywords: Penalized estimation; Indirect Inference; Simulation-based methods; DSGE models (search for similar items in EconPapers)
JEL-codes: C13 C15 D58 E32 (search for similar items in EconPapers)
Date: 2015-01-19
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-mac
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Related works:
Journal Article: Penalized indirect inference (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20150009

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