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Rajnish Mehra

Researcher at National Bureau of Economic Research

Publications -  86
Citations -  10858

Rajnish Mehra is an academic researcher from National Bureau of Economic Research. The author has contributed to research in topics: Equity premium puzzle & Equity risk. The author has an hindex of 32, co-authored 83 publications receiving 10572 citations. Previous affiliations of Rajnish Mehra include University of California, Santa Barbara & Arizona State University.

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THE EQUITY PREMIUM A Puzzle

TL;DR: This paper showed that an equilibrium model which is not an Arrow-Debreu economy will be the one that simultaneously rationalizes both historically observed large average equity return and the small average risk-free return.
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The Equity Premium: It's Still a Puzzle

TL;DR: In this paper, the authors discuss and assess various theoretical attempts to explain these two different empirical phenomena: the large "equity premium" and the low "risk free rate" and show that while there are several plausible explanations for the low level of Treasury returns, the large equity premium is still largely a mystery to economists.
Posted Content

The equity premium: a puzzle

TL;DR: The authors showed that an equilibrium model which is not an Arrow-Debreu economy will be the one that simultaneously rationalizes both historically observed large average equity return and the small average risk-free return.
Journal ArticleDOI

Junior Can't Borrow: A New Perspective on the Equity Premium Puzzle

TL;DR: In this paper, the authors studied the historical mean and standard deviation of the return on equities and bonds and on the equilibrium demand for these securities in a stationary, overlapping-generations economy in which consumers are subject to a borrowing constraint.
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The equity premium in retrospect

TL;DR: A critical review of the literature on the "equity premium puzzle" can be found in this paper, where the authors summarize the historical experience for the USA and other industrialized countries and details the intuition behind the discrepancy between model prediction and empirical data.