A Tale of Fat Tails

Dave & Malik (2017) (European Economic Review, Forthcoming)

41 Pages Posted: 26 Sep 2017

See all articles by Chetan Dave

Chetan Dave

New York University

Samreen Malik

New York University (NYU) - New York University Abu Dhabi

Date Written: September 4, 2017


We document the extent to which major macroeconomic series, used to inform linear DSGE models, can be characterized by power laws whose indices we estimate via maximum likelihood. Assuming data follow a linear recursion with multiplicative noise, low estimated indices suggest fat tails. We then ask whether standard DSGE models under constant gain learning can replicate those fat tails by an appropriate increase in the estimated gain and without much change in the transmission mechanism of shocks. We find that is largely the case via implementation of a minimum distance estimation method that eschews any allegiance to distributional assumptions.

Suggested Citation

Dave, Chetan and Malik, Samreen, A Tale of Fat Tails (September 4, 2017). Dave & Malik (2017) (European Economic Review, Forthcoming). Available at SSRN: https://ssrn.com/abstract=3042101

Chetan Dave

New York University ( email )

Department of Economics
19 W. 4th Street, 6FL
New York, NY 10012
United States

Samreen Malik (Contact Author)

New York University (NYU) - New York University Abu Dhabi ( email )

PO Box 129188
Abu Dhabi
United Arab Emirates

HOME PAGE: http://samreenmalik.net

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