The 2007-2008 global financial crisis and the subsequent anemic recovery have rekindled academic interest in quantifying the impact of uncertainty on macroeconomic dynamics based on the premise that uncertainty causes economic activity to slow down and contract. In this paper, we study the interrelation between financial markets volatility and economic activity assuming that both variables are driven by the same set of unobserved common factors. We further assume that these common factors affect volatility and economic activity with a time lag of at least a quarter. Under these assumptions, we show analytically that volatility is forward looking and that the output equation of a typical VAR estimated in the literature is mis-specified as least squares estimates of this equation are inconsistent. Empirically, we document a statistically significant and economically sizable impact of future output growth on current volatility, and no effect of volatility shocks on business cycles, over and above those driven by the common factors. We interpret this evidence as suggesting that volatility is a symptom rather than a cause of economic instability.

This paper quantifies the economic impact of uncertainty shocks in the UK using data that span the recent Great Recession. We find that uncertainty shocks have a significant impact on economic activity in the UK, depressing industrial production and GDP. The peak impact is felt fairly quickly at around 6-12 months after the shock, and becomes statistically negligible after 18 months. Interestingly, the impact of uncertainty shocks on industrial production in the UK is strikingly similar to that of the US both in terms of the shape and magnitude of the response. However, unemployment in the UK is less affected by uncertainty shocks. Finally, we find that uncertainty shocks can account for about a quarter of the decline in industrial production during the Great Recession.

Measures of economic uncertainty are countercyclical, but economic theory does not provide definite guidance on the direction of causation between uncertainty and the business cycle. This paper proposes a new multi-country approach to the analysis of the interaction between uncertainty and economic activity, without a priori restricting the direction of causality. We develop a multi-country version of the Lucas tree model with time-varying volatility and show that in addition to common technology shocks that affect output growth, higher-order moments of technology shocks are also required to explain the cross country variations of the realized volatility of equity concerns. Using this theoretical insight, two common factors, a ‘real’ and a ‘financial’ one, are identified in the empirical analysis assuming different patterns of cross-country correlations of country-specific innovations to real GDP growth and realized stock market volatility. We then quantify the absolute and the relative importance of the common factor shocks as well as country-specific volatility and GDP growth shocks. The paper highlights three main empirical findings. First, it is shown that most of the unconditional correlation between volatility and growth can be accounted for by the real common factor, which is proportional to world growth in our empirical model and linked to the risk-free rate. Second, the share of volatility forecast error variance explained by the real common factor and by country-specific growth shocks amounts to less than 5 percent. Third, shocks to the common financial factor explain about 10 percent of the growth forecast error variance, but when such shocks occur, their negative impact on growth is large and persistent. In contrast, country-specific volatility shocks account for less than 1-2 percent of the growth forecast error variance.

Motivated by the literature on the capital asset pricing model, we decompose the uncertainty of a typical forecaster into common and idiosyncratic uncertainty. Using individual survey data from the Consensus Forecasts over the period of 1989-2014, we develop monthly measures of macroeconomic uncertainty covering 45 countries and construct a measure of global uncertainty as the weighted average of country-specific uncertainties. Our measure captures perceived uncertainty of market participants and derives from two components that are shown to exhibit strikingly different behavior. Common uncertainty shocks produce the large and persistent negative response in real economic activity, whereas the contributions of idiosyncratic uncertainty shocks are negligible.

Uncertain Futures considers how economic actors visualize the future and decide how to act in conditions of radical uncertainty. It starts from the premise that dynamic capitalist economies are characterized by relentless innovation and novelty and hence exhibit an indeterminacy that cannot be reduced to measurable risk. The organizing question then becomes how economic actors form expectations and make decisions despite the uncertainty they face. This edited volume lays the foundations for a new model of economic reasoning by showing how, in conditions of uncertainty, economic actors combine calculation with imaginaries and narratives to form fictional expectations that coordinate action and provide the confidence to act. It draws on groundbreaking research in economic sociology, economics, anthropology, and psychology to present theoretically grounded empirical case studies. These demonstrate how grand narratives, central bank forward guidance, economic forecasts, finance models, business plans, visions of technological futures, and new era stories influence behaviour and become instruments of power in markets and societies. The market impact of shared calculative devices, social narratives, and contingent imaginaries underlines the rationale for a new form of narrative economics.