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This paper proposes a uncertainty composite indicator (UCI) based on three distinct sources of uncertainty (namely financial, political, and macroeconomic) for the US economy on the period 1985-2015. For that, we use the dynamic factor model proposed by Doz et al. (2012), summarizing efficiently six individual uncertainty proxies, namely two macroeconomic and financial uncertainty factors based on the unpredictability, a measure of (micro)economic uncertainty, the implied volatility index, the corporate bond spreads, and an index of economic policy uncertainty. We then compare the effects of uncertainty on economic activity when the UCI is used instead of individual uncertainty proxies in structural VAR models.The interest of our UCI is to synthesize theses effects within one measure of uncertainty. Overall, the UCI was able to account for the most important dynamics of uncertainty which play an important role in business cycles.

This article explores the role of trend shocks in explaining the specificities of business cycles in developing countries using the methodology introduced by Aguiar and Gopinath (2007) ["Emerging Market Business Cycles: The Cycle Is the Trend" Journal of Political Economy 115(1)]. We specify a small open economy model with transitory and trend shocks on productivity to replicate the differences in the business cycle behavior observed between developed, emerging, and Sub-Saharan Africa countries. Our results suggest a strong relationship between the weight of trend shocks in the source of fluctuations and the level of economic development. The weight of trend shocks is (i) higher in Sub-Saharan Africa countries than in emerging and developed countries, (ii) negatively correlated with the level of income, the quality of institutions, and the size of the credit market, and (iii) uncorrelated with the volatility of aid received by countries, the inflation rate, and the trend in trade-openness.