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Risks For the Long Run: Estimation with Time Aggregation

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  • Ravi Bansal
  • Dana Kiku
  • Amir Yaron

Abstract

The long-run risks (LRR) asset pricing model emphasizes the role of low-frequency movements in expected growth and economic uncertainty, along with investor preferences for early resolution of uncertainty, as an important economic-channel that determines asset prices. In this paper, we estimate the LRR model. To accomplish this we develop a method that allows us to estimate models with recursive preferences, latent state variables, and time-aggregated data. Time-aggregation makes the decision interval of the agent an important parameter to estimate. We find that time-aggregation can significantly affect parameter estimates and statistical inference. Imposing the pricing restrictions and explicitly accounting for time-aggregation, we show that the estimated LRR model can account for the joint dynamics of aggregate consumption, asset cash flows and prices, including the equity premia, risk-free rate and volatility puzzles.

Suggested Citation

  • Ravi Bansal & Dana Kiku & Amir Yaron, 2012. "Risks For the Long Run: Estimation with Time Aggregation," NBER Working Papers 18305, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18305
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    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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