Equilibrium indeterminacy and sunspot tales

Chetan Dave and Marco Sorge

European Economic Review, 2021, vol. 140, issue C

Abstract: We argue that dynamic indeterminacy in structural models can help rationalize statistical regularities regarding higher-order properties of macroeconomic time series. Without departing from the Gaussian rational expectations paradigm, we formally establish that any indeterminate equilibrium model admits a linear recursion with multiplicative noise representation. This allows self-fulfilling expectations (sunspots) to enhance endogenous propagation forces that trigger high-probability extreme changes in model variables, while also inducing time variation in conditional volatilities. As a result, even modest, short-lived exogenous shocks can produce large and persistent macroeconomic effects. Using a workhorse New Keynesian framework, we investigate the ability of such a general mechanism to account for observed fat-tailed behavior and volatility clusters in the inflation series over the Great Inflation period of US macroeconomic history.

Keywords: Indeterminacy; Sunspots; Fat tails; Conditional heteroskedasticity (search for similar items in EconPapers)
JEL-codes: E3 E4 E7 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0014292121002348
Full text for ScienceDirect subscribers only

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:eee:eecrev:v:140:y:2021:i:c:s0014292121002348

DOI: 10.1016/j.euroecorev.2021.103933

Access Statistics for this article

European Economic Review is currently edited by T.S. Eicher, A. Imrohoroglu, E. Leeper, J. Oechssler and M. Pesendorfer

More articles in European Economic Review from Elsevier
Bibliographic data for series maintained by Catherine Liu ().