Simulation-based tests of forward-looking models under VAR learning dynamics
✍ Scribed by Luca Fanelli; Giulio Palomba
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 230 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0883-7252
- DOI
- 10.1002/jae.1138
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✦ Synopsis
In this paper we propose a simulation-based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider 'one-shot' tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p-values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non-stationary cointegrated processes. Application to the 'hybrid' New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward-looking component of inflation dynamics is much larger than the backward-looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984-2005.