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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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18305.

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Date of creation: Aug 2012
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Handle: RePEc:nbr:nberwo:18305

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Cited by:
  1. Lundtofte, Frederik & Wilhelmsson, Anders, 2013. "Risk premia: Exact solutions vs. log-linear approximations," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4256-4264.

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