Model Validation and DSGE Modeling
نویسندگان
چکیده
The primary objective of this paper is to revisit DSGE models with a view to appraise their statistical adequacy and propose ways to ameliorate their empirical pertinence. This paper brings out several weaknesses of the traditional DSGE modeling, including statistical misspecification, non-identification of deep parameters, substantive inadequacy, weak forecasting performance and potentially misleading policy analysis. It is argued that most of these weaknesses stem from failing to distinguish between statistical and substantive adequacy and secure the former before assessing the latter. The paper untangles the statistical from the substantive premises of inference with a view to delineate the above mentioned problems and suggest solutions. The critical appraisal is based on the Smets and Wouters (2007) DSGE model using US quarterly data. It is shown that this model is statistically misspecified, and when respecified with a view to achieve statistical adequacy, gives rise to the Student’s t VAR model. The latter model is shown to provide a sound basis for testing the overidentifying restrictions, forecasting and policy simulations.
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