Working Paper: CEPR ID: DP13492
Authors: Jesper Lind; Stefan Lasen; Marco Ratto
Abstract: In this paper, we study identification and misspecification problems in standard closed and open-economy empirical New-Keynesian DSGE models used in monetary policy analysis. We find that problems with model misspecification still appear to be a first-order issue in monetary DSGE models, and argue that it is problems with model misspecification that may benefit the most from moving from a classical to a Bayesian framework. We also argue that lack of identification should neither be ignored nor be assumed to affect all DSGE models. Fortunately, identification problems can be readily assessed on a case-by-case basis, by applying recently developed pre-tests of identification.
Keywords: Bayesian estimation; Monte Carlo methods; Maximum likelihood estimation; DSGE model; Closed economy; Open economy
JEL Codes: C13; C51; E30
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| problems with model misspecification (C50) | identification issues (F55) |
| Bayesian methods (C11) | handling of misspecification issues (C50) |
| identification can be assessed effectively (C52) | identification problems are limited to a few parameters (C30) |
| correctly specified models (C52) | informative estimates about structural parameters (C51) |
| ML estimates (C51) | significant increase in log likelihood (C52) |
| Calvo parameters yield implausibly high values (C51) | potential misspecification in the model (C50) |
| formal tests of misspecification (C52) | show that closed and open economy models are misspecified (F41) |
| incorrectly specified Phillips curve (E31) | evidence of issues in the price-setting block (P22) |
| analysis highlights challenges related to identification and misspecification (C50) | implications for monetary policy analysis (E19) |
| sample size increases (C83) | small sample biases diminish (C83) |