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Understanding Uncertainty Shocks and the Role of Black Swans. (2014). Veldkamp, Laura ; Orlik, Anna.
In: CEPR Discussion Papers.
RePEc:cpr:ceprdp:10147.

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  5. Does U.S. Monetary Policy Respond to Macroeconomic Uncertainty?. (2023). Piccillo, Giulia ; Gomez, Thomas.
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    In: Papers.
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  11. Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers. (2022). Moramarco, Graziano.
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    In: European Economic Review.
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    In: The Review of Economics and Statistics.
    RePEc:tpr:restat:v:102:y:2020:i:2:p:287-303.

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    In: PIER Discussion Papers.
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    RePEc:pra:mprapa:103516.

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    In: Working Papers.
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    In: Working papers.
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    In: Working Papers.
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    In: 2018 Meeting Papers.
    RePEc:red:sed018:1111.

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    In: NBER Working Papers.
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    In: RBA Research Discussion Papers.
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  64. The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation. (2016). Veldkamp, Laura ; Venkateswaran, Venky ; Kozlowski, Julian.
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  65. The Impact of US Uncertainty on the Euro Area in Good and Bad Times: Evidence from a Quantile Structural Vector Autoregressive Model. (2016). Wohar, Mark ; Lau, Chi Keung ; GUPTA, RANGAN ; Marco, Chi Keung.
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  70. The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation. (2016). Veldkamp, Laura ; Venkateswaran, Venky ; Kozlowski, Julian.
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  71. The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation. (2015). Venkateswaran, Venky ; Kozlowski, Julian ; Veldkamp, Laura.
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  72. The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation. (2015). Veldkamp, Laura ; Venkateswaran, Venky ; Kozlowski, Julian.
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  73. The Tail that Wags the Economy: Beliefs and Persistent Stagnation. (2015). Veldkamp, Laura ; Venkateswaran, Venky ; Kozlowski, Julian.
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  36. Nakamura, E., D. Sergeyev, and J. Steinsson (2012): “Growth-Rate and Uncertainty Shocks in Consumption: Cross-Country Evidence,” Columbia University working paper. Nimark, K. (forthcoming): “Man-Bites-Dog Business Cycles,” American Economic Review.

  37. Pastor, L., and P. Veronesi (2012): “Uncertainty about Government Policy and Stock Prices,” Journal of Finance, forthcoming.

  38. Rietz, T. (1988): “The Equity Risk Premium: A Solution,” Journal of Monetary Economics, 22(1), 117–131.

  39. Roberts, G., A. Gelman, and W. Gilks (1997): “Weak Convergence and Optimal Scaling of Random Walk Metropolis Algorithms,” Annals of Applied Probability, 7(1), 110–120.
    Paper not yet in RePEc: Add citation now

  40. Stock, J., and M. Watson (2012): “Disentangling the Channels of the 2007-2009 Recession, ” Brookings Papers on Economic Activity, pp. 81–135.

  41. Straub, L., and R. Ulbricht (2013): “Credit Crunches, Information Failures, and the Persistence of Pessimism,” Toulouse School of Economics working paper.
    Paper not yet in RePEc: Add citation now

  42. Van Nieuwerburgh, S., and L. Veldkamp (2006): “Learning Asymmetries in Real Business Cycles,” Journal of Monetary Economics, 53(4), 753–772.

  43. Wachter, J. (2013): “Can Time-Varying Risk or Rare Disasters Explain Aggregate Stock Market Volatility?,” Journal of Finance, 68(3), 987–1035. A Proofs Lemma 1: Skewness and the concave change of measure We can write the skewness of y (times the variance, which is always positive) as E[(y − E[y])3 ] = Z (y − E[y])3 φ(g−1 (y))dy (12) where φ(g−1(y)) is the probability density of y, by assumption. Using the change of variable rule, we can replace y with g(x). E[(g(x) − E[g(x)])3 ] = Z (g(x) − E[g(x)])3 ∂g ∂x φ(x)dx (13)

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