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323
2013): “Uncertainty Shocks are Aggregate Demand Shocks,” Federal Reserve Bank of San Francisco, Working Paper
"... Abstract. We present empirical evidence and a theoretical argument that uncertainty shocks act like a negative aggregate demand shock, which raises unemployment and lowers inflation. We measure uncertainty using survey data from the United States and the United Kingdom. We estimate the macroeconomic ..."
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Cited by 28 (4 self)
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Abstract. We present empirical evidence and a theoretical argument that uncertainty shocks act like a negative aggregate demand shock, which raises unemployment and lowers inflation. We measure uncertainty using survey data from the United States and the United Kingdom. We estimate the macroeconomic effects of uncertainty shocks in a vector autoregression (VAR) model, exploiting the relative timing of the surveys and macroeconomic data releases for identification. Our estimation reveals that uncertainty shocks accounted for at least one percentage point increases in unemployment in the Great Recession and recovery, but did not contribute much to the 198182 recession. We present a DSGE model to show that, to understand the observed macroeconomic effects of uncertainty shocks, it is essential to have both labor search frictions and nominal rigidities. I.
A Macroeconomic Framework for Quantifying Systemic Risk. Working
, 2012
"... Systemic risk arises when shocks lead to states where a disruption in financial intermediation adversely affects the economy and feeds back into further disrupting financial intermediation. We present a macroeconomic model with a financial intermediary sector subject to an equity capital constraint. ..."
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Cited by 27 (2 self)
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Systemic risk arises when shocks lead to states where a disruption in financial intermediation adversely affects the economy and feeds back into further disrupting financial intermediation. We present a macroeconomic model with a financial intermediary sector subject to an equity capital constraint. The novel aspect of our analysis is that the model produces a stochastic steady state distribution for the economy, in which only some of the states correspond to systemic risk states. The model allows us to examine the transition from “normal ” states to systemic risk states. We calibrate our model and use it to match the systemic risk apparent during the 2007/2008 financial crisis. We also use the model to compute the conditional probabilities of arriving at a systemic risk state, such as 2007/2008. Finally, we show how the model can be used to conduct a macroeconomic “stress test ” linking a stress scenario to the probability of systemic risk states.
Disaster risk and business cycles
, 2009
"... This paper proposes a tractable business cycle model with large, volatile, and countercyclical risk premia. Risk premia are driven by a small, exogenously timevarying risk of economic disaster, and macroeconomic aggregates respond to this timevarying risk. The model is consistent with the second m ..."
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Cited by 25 (0 self)
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This paper proposes a tractable business cycle model with large, volatile, and countercyclical risk premia. Risk premia are driven by a small, exogenously timevarying risk of economic disaster, and macroeconomic aggregates respond to this timevarying risk. The model is consistent with the second moments of quantities, of asset returns, and matches well the relations between quantities and asset prices. An increase in the probability of disaster leads to a collapse of investment and a recession, with no current or future change in productivity. Demand for precautionary savings increases, leading yields on safe assets to fall, while spreads on risky securities increase. To assess the empirical validity of the model, I infer the probability of disaster from observed asset prices and feed it into the model. The variation over time in this probability appears to account for a signi…cant fraction of business cycle dynamics, especially sharp downturns in investment and output such as the last quarter of 2008. This is consistent with the thenwidespread fear of a repeat of the
Discounting with fattailed economic growth
 Journal of Risk and Uncertainty
, 2008
"... When the growth of aggregate consumption exhibits no serial correlation, the socially efficient discount rate is independent of the time horizon, because the wealth effect and the precautionary effect are proportional to the time horizon. In this paper, we consider alternative growth processes: an A ..."
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Cited by 25 (2 self)
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When the growth of aggregate consumption exhibits no serial correlation, the socially efficient discount rate is independent of the time horizon, because the wealth effect and the precautionary effect are proportional to the time horizon. In this paper, we consider alternative growth processes: an AR(1), a Brownian motion with unknown trend or volatility, a twostate regimeswitching model, and a model with an uncertain return of capital. All these models exhibit some persistence of shocks on the growth rate of the economy and fat tails, which implies that one should discount more distant costs and benefits at a smaller rate.
Disasters implied by equity index options
, 2009
"... We use prices of equity index options to quantify the impact of extreme events on asset returns. We define extreme events as departures from normality of the log of the pricing kernel and summarize their impact with highorder cumulants: skewness, kurtosis, and so on. We show that highorder cumulan ..."
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Cited by 24 (5 self)
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We use prices of equity index options to quantify the impact of extreme events on asset returns. We define extreme events as departures from normality of the log of the pricing kernel and summarize their impact with highorder cumulants: skewness, kurtosis, and so on. We show that highorder cumulants are quantitatively important in both representativeagent models with disasters and in a statistical pricing model estimated from equity index options. Option prices thus provide independent confirmation of the impact of extreme events on asset returns, but they imply a more modest distribution of them.
Uncertainty in environmental economics
, 2006
"... In a world of certainty, the design of environmental policy is relatively straightforward, and boils down to maximizing the present value of the flow of social benefits minus costs. But the real world is one of considerable uncertainty – over the physical and ecological impact of pollution, over t ..."
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Cited by 23 (1 self)
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In a world of certainty, the design of environmental policy is relatively straightforward, and boils down to maximizing the present value of the flow of social benefits minus costs. But the real world is one of considerable uncertainty – over the physical and ecological impact of pollution, over the economic costs and benefits of reducing it, and over the discount rates that should be used to compute present values. The implications of uncertainty are complicated by the fact that most environmental policy problems involve highly nonlinear damage functions, important irreversibilities, and long time horizons. Correctly incorporating uncertainty in policy design is therefore one of the more interesting and important research areas in environmental economics. This paper offers no easy formulas or solutions for treating uncertainty – to my knowledge, none exist. Instead, I try to clarify the ways in which various kinds of uncertainties will affect optimal policy design, and summarize what we know and don’t know about the problem.
Ambiguity Aversion: Implications for the Uncovered Interest Rate Parity Puzzle.” Working Paper
, 2010
"... Highinterestrate currencies tend to appreciate in the future relative to lowinterestrate currencies instead of depreciating as uncoveredinterestparity (UIP) predicts. I construct a model of exchangerate determination in which ambiguityaverse agents face a dynamic filtering problem featuring ..."
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Cited by 23 (4 self)
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Highinterestrate currencies tend to appreciate in the future relative to lowinterestrate currencies instead of depreciating as uncoveredinterestparity (UIP) predicts. I construct a model of exchangerate determination in which ambiguityaverse agents face a dynamic filtering problem featuring signals of uncertain precision. Solving a maxmin problem, agents act upon a worstcase signal precision and systematically underestimate the hidden state that controls payoffs. Thus, on average, agents next periods perceive positive innovations, which generates an upward reevaluation of the strategy’s profitability and implies expost departures from UIP. The model also produces predictable expectational errors, negative skewness and timeseries momentum for currency speculation payoffs.
Common Risk Factors in Currency Markets
, 2008
"... Currency excess returns are highly predictable and strongly countercyclical. The average excess returns on low interest rate currencies are 4.8 percent per annum smaller than those on high interest rate currencies after accounting for transaction costs. A single returnbased factor, the return on t ..."
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Cited by 23 (0 self)
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Currency excess returns are highly predictable and strongly countercyclical. The average excess returns on low interest rate currencies are 4.8 percent per annum smaller than those on high interest rate currencies after accounting for transaction costs. A single returnbased factor, the return on the highest minus the return on the lowest interest rate currency portfolios, explains the crosssectional variation in average currency excess returns from low to high interest rate currencies. In a simple affine pricing model, we show that the highminuslow currency return measures that component of the stochastic discount factor innovations that is common across countries. To match the carry trade returns in the data, low interest rate currencies need to load more on this common innovation when the market price of global risk is high.
2009, “What Ties Return Volatilities to Price Valuations and Fundamentals?,” Working paper
"... The relation between the volatility of stocks and bonds and their price valuations is strongly timevarying, both in magnitude and direction, defying traditional asset pricing models and conventional wisdom. We construct and estimate a model in which investors ’ learning about regular and unusual fu ..."
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Cited by 22 (2 self)
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The relation between the volatility of stocks and bonds and their price valuations is strongly timevarying, both in magnitude and direction, defying traditional asset pricing models and conventional wisdom. We construct and estimate a model in which investors ’ learning about regular and unusual fundamental states leads to a nonmonotonic V −shaped relation between volatilities and prices. Structural forecasts from our model predict future return volatility and covariances with R2 ranging between 40 % and 60 % at the 1year horizon. The model’s success stems largely from backing out the endogenous and timevarying pro (counter) cyclical weights that investors assign to earnings (inflation) news. While it is intuitive that the volatilities and comovements of stocks and bonds are strongly related to the state of economic fundamentals, it is surprising that the financial literature has been unable to empirically demonstrate such a strong link between them, as evidenced in the following quote from a recent paper by Nobel prize laureate Robert Engle.
On the Size Distribution of Macroeconomic Disasters
 Ursua (2008a): “Macroeconomic Crises since 1870,” Brookings Papers on Economic Activity
"... In the raredisasters setting, a key determinant of the equity premium is the size distribution of macroeconomic disasters, gauged by proportionate declines in per capita consumption or GDP. The longterm nationalaccounts data for up to 36 countries provide a large sample of disaster events of magn ..."
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Cited by 20 (3 self)
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In the raredisasters setting, a key determinant of the equity premium is the size distribution of macroeconomic disasters, gauged by proportionate declines in per capita consumption or GDP. The longterm nationalaccounts data for up to 36 countries provide a large sample of disaster events of magnitude 10 % or more. For this sample, a powerlaw density provides a good fit to the distribution of the ratio of normal to disaster consumption or GDP. The key parameter of the size distribution is the uppertail exponent, α, estimated to be near 5, with a 95 % confidence interval between 31/2 and 7. The equity premium involves a race between α and the coefficient of relative risk aversion, γ. A higher α signifies a thinner tail and, therefore, a lower equity premium, whereas a higher γ implies a higher equity premium. The equity premium is finite if α1>γ. To accord with the observed average unlevered equity premium of around 5%, we get a point estimate for γ close to 3, with a 95 % confidence interval of roughly 2 to 4. * This research has been supported by the National Science Foundation. We appreciate helpful comments from Xavier Gabaix, Rustam Ibragimov, Chris Sims, Jose Ursua, and Marty Weitzman. Recent research builds on the raredisasters idea of Rietz (1988) to explain the longterm