The market price of risk and the equity premium: A legacy of the Great Depression?

Cogley, Timothy; Sargent, Thomas J.

doi:10.1016/j.jmoneco.2008.01.006

Cited by 184 publications

(165 citation statements)

References 37 publications

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“…Although we do not focus on survival, one side contribution of this paper is to make Blume and Easley's results more robust because we show that every Bayesian agent with a belief with the lowest dimensional support actually survives with probability one (not just in probability), not only for almost every parameter in the support of her belief but actually for all parameters in the support of her belief. 7 Example 4 also contributes to this literature since it is, to the best of our knowledge, the first of its kind. Since it does not require market incompleteness, it constitutes a robust argument against the market selection hypothesis.…”

Section: Introductionmentioning

confidence: 92%

The dynamics of efficient asset trading with heterogeneous beliefs

Beker

Espino

2011

Journal of Economic Theory

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This paper analyzes the dynamic properties of portfolios that sustain dynamically complete markets equilibria when agents have heterogeneous priors. We argue that the conventional wisdom that belief heterogeneity generates continuous trade and significant fluctuations in individual portfolios may be correct but it needs some qualifications. We consider an infinite horizon stochastic endowment economy populated by many Bayesian agents with heterogeneous priors over the stochastic process of the states of nature. Our approach hinges on studying the portfolios that decentralize Pareto optimal allocations. Since these allocations are typically history dependent, we propose a methodology to provide a complete recursive characterization when agents believe that the process of states of nature is i.i.d. but disagree about the probability of the states. We show that even though heterogeneous priors within that class can indeed generate genuine changes in the portfolios of any dynamically complete markets equilibrium, these changes vanish with probability one if the true process consists of i.i.d. draws from a common distribution and the support of every agent's prior belief contains the true distribution. Finally, we provide examples in which asset trading does not vanish because either (i) no agent learns the true conditional probability of the states or (ii) some agent does not know the true process generating the data is i.i.d.Keywords: heterogeneous beliefs, asset trading, dynamically complete markets. * We thank Rody Manuelli and Juan Dubra for detailed comments. We are also very grateful to one of the referees for very detailed comments that greatly improved the paper and the proof of Proposition 16. All the remaining errors are ours.

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Section: Introductionmentioning

confidence: 92%

The dynamics of efficient asset trading with heterogeneous beliefs

Beker

Espino

2011

Journal of Economic Theory

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“…For GDP, shown in Table A2 (in Appendix III) and summarized in See Cagan (1965, p. 138). Chatterjee and Corbae [2007] and Cogley and Sargent [2008]). One reason for this focus on the Depression is that the United States happened to do well economically during the two world wars, which were major economic disasters for much of the rest of the world, including many OECD countries.…”

Section: Consumption and Gdp Disastersmentioning

confidence: 98%

Macroeconomic Crises since 1870

Barro¹,

Ursúa²

2008

eca

281

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We build on the Maddison GDP data to assemble international time series from before 1914 on real per capita personal consumer expenditure, C. We also improve the GDP data in many cases. The C variable comes closer than GDP to the consumption concept that enters into usual asset-pricing equations. We have essentially full annual data on C for 24 countries and GDP for 36 countries. For samples that start as early as 1870, we apply a peak-to-trough method for each country to isolate economic crises, defined as cumulative declines in C or GDP by at least 10%. The principal world economic crises ranked by importance are World War II, World War I and the Great Depression, the early 1920s (possibly reflecting the influenza epidemic of 1918-20), and post-World War II events such as the Latin-American debt crisis and the Asian financial crisis. We find 95 crises for C and 152 for GDP, implying disaster probabilities around 3-1/2% per year. The disaster size has a mean of 21-22% and an average duration of 3-1/2 years. A comparison of C and GDP declines shows roughly coincident timing. The average fractional decline in C exceeds that in GDP during wartime crises but is similar for non-war crises. We simulate a Lucas-tree model with i.i.d. growth shocks and Epstein-Zin-Weil preferences. This simulation accords with the observed average equity premium of around 7% on levered equity, using a "reasonable" coefficient of relative risk aversion of 3.5. This result is robust to a number of perturbations, except for limiting the sample to non-war crises, a selection that eliminates most of the largest declines in C and GDP.

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“…An apparent drawback of both approaches is, however, their incompatibility with standard learning models with Bayesian features or overtones by which subjective beliefs converge to their objective counterparts in the long-run, cf. Barsky and DeLong (1993), Timmermann (1993), Brav and Heaton (2002), Cogley and Sargent (2008) and Adam, Marcet and Nicolini (2008). As a potential contribution to this …nancial economics literature, the non-converging Bayesian learning model of this paper provides a consistent theoretical foundation for why a subjective estimator may remain biased even in the long-run.…”

Section: Related Literature and Further Motivationmentioning

confidence: 99%

Do Bayesians Learn Their Way Out of Ambiguity?

Zimper

2011

Decision Analysis

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In standard models of Bayesian learning agents reduce their uncertainty about an event's true probability because their consistent estimator concentrates almost surely around this probability's true value as the number of observations becomes large. This paper takes the empirically observed violations of Savage's (1954) sure thing principle seriously and asks whether Bayesian learners with ambiguity attitudes will reduce their ambiguity when sample information becomes large. To address this question, I develop closed-form models of Bayesian learning in which beliefs are described as Choquet estimators with respect to neo-additive capacities (Chateauneuf, Eichberger, and Grant 2007). Under the optimistic, the pessimistic, and the full Bayesian update rule, a Bayesian learner's ambiguity will increase rather than decrease to the e¤ect that these agents will express ambiguity attitudes regardless of whether they have access to large sample information or not. While consistent Bayesian learning occurs under the Sarin-Wakker update rule, this result comes with the descriptive drawback that it does not apply to agents who still express ambiguity attitudes after one round of updating.

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The market price of risk and the equity premium: A legacy of the Great Depression?

Cited by 184 publications

References 37 publications

The dynamics of efficient asset trading with heterogeneous beliefs

The dynamics of efficient asset trading with heterogeneous beliefs

Macroeconomic Crises since 1870

Do Bayesians Learn Their Way Out of Ambiguity?

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