Global effects of US uncertainty: real and financial shocks on real and financial markets
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We estimate the effects of financial, macroeconomic and policy uncertainty from the United States on the dynamics of credit growth, stock prices, economic activity, bond yields and inflation in five of the main receptors of US foreign direct investment from 1950 to 2019: The United Kingdom, The Netherlands, Ireland, Canada and Switzerland. Our multicounty approach allows us to clearly identify the effects of the different sources of uncertainty by imposing natural contemporaneous exogenity restrictions which cannot be used in a single-country perspective, frequently undertaken by the literature. It also considers international common cycle factors that have been previously identified and which are key to adequately measure the dynamics of the effects of uncertainty shocks on financial and real markets, on a global basis. We use an international FAVAR model to carry out our estimations. This approach permits handling a large data set consisting of variables for more than 45 countries at once. Our results point out to financial uncertainty as the main driver (even more than real uncertainty or the US interest rate) of global economic cycles. We show that increases of US financial uncertainty deteriorate economic activity on a global scale, especially by reducing credit and stock prices, and therefore funding opportunities for firms and households (heterogeneously on a country level basis). Our results emphasize the importance of financial markets, and especially financial uncertainty in the United States, as the main origin of global economic fluctuations, which can be said to describe the recent history of the global economy. They also cast doubts on the ability of uncertainty indicators based on the counting of key words in the media as a barometer of traditional economic uncertainty, known to be theoretically associated to negative outcomes in terms of activity and prices. In this sense, uncertainty indicators based on the estimation and aggregation of forecast errors seem more appropriate, hence producing results in line with the understanding of uncertainty as a negative phenomenon on a macro level, especially for investment prospects.