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Identifying long-run risks: a bayesian mixed-frequency approach

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  • Frank Schorfheide
  • Dongho Song
  • Amir Yaron
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    Abstract

    We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Building on Bansal and Yaron (2004), our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly consumption data after 1959, and monthly asset return data throughout. We maximize the span of the sample to recover the predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our Bayesian estimation provides strong evidence for a small predictable component in consumption growth (even if asset return data are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our measurement error specification implies that consumption is measured much more precisely at an annual than monthly frequency; and the estimated model is able to capture key asset-pricing facts of the data.

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    Bibliographic Info

    Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 13-39.

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    Date of creation: 2013
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    Handle: RePEc:fip:fedpwp:13-39

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    Related research

    Keywords: Nonlinear theories ; Dividends ; Consumption (Economics) ; Bayesian statistical decision theory;

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    References

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    1. Chiara Scotti & S.Boragan Aruoba & Francis X. Diebold & University of Maryland, 2006. "Real-Time Measurement of Business Conditions," Computing in Economics and Finance 2006 387, Society for Computational Economics.
    2. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, 08.
    3. Robert J. Barro, 2007. "Rare Disasters, Asset Prices, and Welfare Costs," NBER Working Papers 13690, National Bureau of Economic Research, Inc.
    4. Rui Albuquerque & Martin S. Eichenbaum & Sergio Rebelo, 2012. "Valuation Risk and Asset Pricing," NBER Working Papers 18617, National Bureau of Economic Research, Inc.
    5. Robert E. Hall, 1988. "Intertemporal Substitution in Consumption," NBER Working Papers 0720, National Bureau of Economic Research, Inc.
    6. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-86.
    7. Wilcox, David W, 1992. "The Construction of U.S. Consumption Data: Some Facts and Their Implications for Empirical Work," American Economic Review, American Economic Association, vol. 82(4), pages 922-41, September.
    8. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc.
    9. Epstein, Larry G & Zin, Stanley E, 1989. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: A Theoretical Framework," Econometrica, Econometric Society, vol. 57(4), pages 937-69, July.
    10. Beeler, Jason & Campbell, John Y., 2012. "The Long-Run Risks Model and Aggregate Asset Prices: An Empirical Assessment," Critical Finance Review, now publishers, vol. 1(1), pages 141-182, January.
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