Does macroeconomic uncertainty increase or decrease aggregate growth and asset prices? To address this question, we decompose aggregate uncertainty into ‘good’ and ‘bad’ volatility components, associated with positive and negative innovations to macroeconomic growth. We document that in line with our theoretical framework, these two uncertainties have opposite impact on aggregate growth and asset prices. Good uncertainty predicts an increase in future economic activity, such as consumption, output, and investment, and is positively related to valuation ratios, while bad uncertainty forecasts a decline in economic growth and depresses asset prices. Further, the market price of risk and equity beta of good uncertainty are positive, while negative for bad uncertainty. Hence, both uncertainty risks contribute positively to risk premia, and help explain the cross-section of expected returns beyond cash flow risk.


How do changes in economic uncertainty affect macroeconomic quantities and asset prices? We show that the answer to this question hinges on the type of uncertainty one considers. ‘Bad’ uncertainty is the volatility that is associated with negative innovations to macroeconomic quantities (e.g., output, consumption, earnings), and with lower prices and investment, while ‘good’ uncertainty is the volatility that is associated with positive shocks to these variables, and with higher asset prices and investment.

To illustrate these two types of uncertainties, it is instructive to consider two episodes: (i) the high-tech revolution of early-mid 1990’s, and (ii) the recent collapse of Lehman Brothers in the fall of 2008. In the first case, and with the introduction of the world-wide-web, a common view was that this technology would provide many positive growth opportunities that would enhance the economy, yet it was unknown by how much? We refer to such a situation as `good’ uncertainty. Alternatively, the second case marked the beginning of the global financial crisis, and with many of the ensuing bankruptcy cases one knew that the state of economy was deteriorating – yet, again, it was not clear by how much? We consider this situation as a rise in `bad’ uncertainty. In both cases, uncertainty level rises relative to its long-run steady-state level, yet, the first case coincides with an optimistic view, and the second with a pessimistic one.

In this paper, we demonstrate that variations in good and bad uncertainty have separate and significant opposing impacts on the real economy and asset prices. We use an extended version of the long-run risks model of Bansal and Yaron (2004) to theoretically show conditions under which good and bad uncertainty have different impact on prices. To make a meaningful distinction between good and bad uncertainty, we decompose, within the model, the overall shocks to consumption into two separate zero-mean components (e.g., jumps) which capture positive and negative growth innovations. The volatilities of these two shocks are time varying, and capture uncertainty fluctuations associated with the positive and negative parts of the distribution of consumption growth. Thus, in the model, valuation ratios are driven by three state variables: predictable consumption growth, good uncertainty, and bad uncertainty. Consequently, the stochastic discount factor, and therefore risk premia, are determined by three sources of risk: cash ow, good uncertainty, and bad uncertainty risks.

We show that with a preference for early resolution of uncertainty, the direct impact of both types of uncertainty shocks is to reduce prices, though, prices respond more to bad than to good uncertainty. For prices to rise in response to a good uncertainty shock there has to be an explicit positive link between good uncertainty and future growth prospects { a feature that we impose in our benchmark model. We further show that the market price of good uncertainty risk and its equity beta have the same (positive) sign. Thus, even though prices can rise in response to good uncertainty, it commands a positive risk premium.

Overall the model’s key empirical implications include: (i) good uncertainty positively predicts future measures of economic activity, while bad uncertainty negatively forecasts future economic growth; (ii) good uncertainty fluctuations are positively related to asset valuations and to the real risk-free rate, while an increase in bad uncertainty depresses asset prices and the riskless yield; and (iii) the shocks to good and bad uncertainty carry positive and negative market prices of risk, respectively, yet both contribute positively to the risk premium.

We evaluate our model’s empirical implications by utilizing a novel econometric approach to identify good and bad uncertainty from higher-frequency realized variation in the variables of interest (see Barndor -Nielsen, Kinnebrock, and Shephard (2010)). Empirically, we use the ex-ante predictable components of the positive and negative realized semivariances of industrial production growth rate as the respective proxies for good and bad uncertainty.3 In its limiting behavior, positive (negative) semivariance captures one-half of the variation in any Gaussian symmetric movements in the growth rate of the variable of interest, as well as the variation of any non-Gaussian positive (negative) component in it. Thus, in our empirical work the positive (negative) semivariance captures the volatility component that is associated with the positive (negative) part of the total variation of industrial production growth, and its predictive component corresponds to the model concept for good (bad) uncertainty.


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