Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models

Journal of Econometrics, 2020, vol. 218, issue 2, 561-586

Abstract: This paper considers the problem of hypothesis testing in linear Gaussian state space models. We consider two hypotheses of interest: a simple null and a hypothesis of explicit parameter restrictions. We derive the asymptotic distributions of the corresponding likelihood ratio test statistics and compute the Bartlett adjustments. The results are non-trivial because the unrestricted state space model is not (even locally) identified. We apply our analysis to test the validity of the Dynamic Stochastic General Equilibrium (DSGE) models. A Monte Carlo exercise illustrates our findings and confirms the importance of Bartlett corrections at sample sizes typically encountered in macroeconomics.

Keywords: Linear Gaussian state space models; Likelihood ratio test; Bartlett adjustment (search for similar items in EconPapers)
JEL-codes: C12 C32 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:218:y:2020:i:2:p:561-586

DOI: 10.1016/j.jeconom.2020.04.029

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