Probability distortion, asset prices, and economic growth

Maik Dierkes, Stephan Germer and Vulnet Sejdiu

Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), 2020, vol. 84, issue C

Abstract: In this paper, we link stock market investors’ probability distortion to future economic growth. The empirical challenge is to quantify the optimality of today’s decision making to test for its impact on future economic growth. Fortunately, risk preferences can be estimated from stock markets. Using monthly aggregate stock prices from 1926 to 2015, we estimate risk preferences via an asset pricing model with Cumulative Prospect Theory (CPT) agents and distill a recently proposed probability distortion index. This index negatively predicts GDP growth in-sample and out-of-sample. Predictability is stronger and more reliable over longer horizons. Our results suggest that distorted asset prices may lead to significant welfare losses.

Keywords: Economic growth; Probability distortion; Suboptimal decision making (search for similar items in EconPapers)
JEL-codes: G02 G12 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2214804318304774
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:soceco:v:84:y:2020:i:c:s2214804318304774

DOI: 10.1016/j.socec.2019.101476

Access Statistics for this article

Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics) is currently edited by Pablo Brañas Garza

More articles in Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().