The Fiscal Multiplier Morass: A Bayesian Perspective

Todd Walker, Nora Traum and Eric Leeper

No 583, 2011 Meeting Papers from Society for Economic Dynamics

Abstract: A Bayesian prior predictive analysis is conducted on a suite of models to assess the probability that a model and corresponding prior distributions bias results toward a specific range of fiscal multipliers. We examine a wide range of DSGE models commonly used to estimate fiscal multipliers, including a real business cycle model, a New Keynesian model with nominal and real rigidities, and open economy models. We decompose changes in multipliers across models into wealth and substitution effects, allowing for a more uniform comparison across models. Through the prior predictive analysis, we show that many of the models and prior distributions impose a very tight range for the multiplier before the models are taken to data. We argue that constraining the multiplier to such a tight range prior to conditioning on data is tantamount to biasing results. A broader message of the paper calls for employing prior predictive analysis when estimating DSGE models.

Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
https://red-files-public.s3.amazonaws.com/meetpapers/2011/paper_583.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:red:sed011:583

Access Statistics for this paper

More papers in 2011 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().