The re-election of Donald Trump has led to heightened uncertainty in the global economy (Grzana and Ilzetzki 2025). The whiplash-inducing, erratic tariff announcements on and around ‘Liberation Day’ on 2 April 2025, are a perfect showcase. They triggered major turmoil in global financial markets (Benigno 2025).
Every unhappy country is unhappy in its own way
However, even a global uncertainty shock such as Trump's ‘Liberation Day’ tariff announcement does not affect all countries equally. Countries have varying exposures to international trade, especially with the US. Figure 1 illustrates, from the perspective of selected European countries, the unexpected increase in stock market volatility in April 2025 — a widely used indicator of economic uncertainty. Uncertainty in Germany, Portugal, and Slovenia surged by almost three standard deviations, an event only expected in 0.3% of all months. At the same time, the impact was less pronounced in Cyprus and Lithuania. Given that these countries share a common monetary policy within the euro area, one might be concerned that the absence of a country-specific monetary policy response could amplify the shock's effects. Indeed, it is well established that uncertainty shocks can have particularly adverse effects when monetary policy is not responsive due to the zero lower bound (Basu and Bundick 2017). The same may hold true when the exchange rate arrangement prevents a monetary policy response at the country level.
Figure 1 Increase in stock market volatility in April 2025
Notes: Unexpected realised stock market volatility in April 2025. We estimate an AR(1) for the monthly realised volatility of the Datastream Stock Market Performance Index for each country. What is shown are the residuals in April 2025, expressed as standard deviations of the country’s residuals.
In new research, we show that this conjecture is wrong (Born et al. 2025). We investigate how economic uncertainty affects euro area (EA) countries compared to countries with flexible exchange rates and find that while the impact of common uncertainty shocks is comparable in both country groups, the impact of country-specific uncertainty shocks is weaker in euro area countries, not stronger as the received wisdom would suggest.
Evidence from 30 countries
We analyse quarterly data from 17 euro area members and 13 countries with floating exchange rates over the period 1999–2022. Using a structural Bayesian vector autoregression (BVAR), we estimate the effects of uncertainty shocks based on two measures of economic uncertainty: realised stock market volatility, following Bloom (2009), and the forecast error-based uncertainty indicator developed by Jurado et al. (2015), compiled by Comunale and Nguyen (2023) for euro area countries. Importantly, we identify both common and country-specific uncertainty shocks within the BVAR.
Figure 2 Output response to common (top) vs. country-specific (bottom) uncertainty shocks
Notes: Impulse responses of output to common (top) and country-specific (bottom) uncertainty shocks according to estimated BVAR (left) and structural model (right). Blue dashed and solid red lines indicate VAR responses in euro area countries (monetary union), yellow lines with markers/green lines indicate responses under flexible exchange rates (float). Shaded areas indicate 68% and 90% highest posterior density intervals. Horizontal axis: time after shock in quarters; vertical axis: real GDP response in percent.
The left panels of Figure 2 show the impulse responses: how an uncertainty shock impacts economic activity over time, measured by real GDP. In the top panel, we show the adjustment to a common uncertainty shock for countries with flexible exchange rates and for EA countries. There is no difference. In the bottom panel, we show the result for a country-specific uncertainty shock: it lowers economic activity in countries with flexible exchange rates but hardly affects economic activity in euro area countries. Considering the received wisdom, this is a surprising pattern. After all, monetary policy in the euro area cannot and does not accommodate country-specific shocks.
An explanation: Price level expectations are anchored by union membership
We explain this result in a structural two-country model of a monetary union, extending the closed-economy setup of Basu and Bundick (2017). In the model, the ‘Home’ country is small and has negligible influence on union-wide aggregates, which in turn determine the common monetary policy. ‘Foreign’ represents the larger rest of the union. Uncertainty shocks in the model widen the distribution of supply and demand shocks. The model is estimated on euro area data to match the impulse responses to common uncertainty shocks. We find that the estimated model indeed predicts weaker effects of country-specific uncertainty shocks, both compared to common shocks and to a counterfactual with floating exchange rates. We show these results in the right panels of Figure 2 above. These findings are particularly noteworthy because the impulse responses to country-specific uncertainty shocks were not targeted during the estimation of the model.
Based on counterfactuals, we establish that price level risk is key for this result. Absent a monetary union, when a country’s monetary policy targets inflation, an increase in uncertainty is associated with an increase in price level risk. We illustrate this in the left panel of Figure 3, which shows the simulated long-run distribution of the price level after a demand shock with and without heightened uncertainty. Price level risk, in turn, is detrimental to consumption and investment, as we show in the paper. In contrast, even when country-specific uncertainty goes up in a country operating within the monetary union, the long-run price level remains anchored by the union level. Long-run (relative) purchasing power parity, as in the data (Bergin et al. 2017), implies that a country’s price level must converge to the union level in the absence of a flexible exchange rate.
Figure 3 Union membership eliminates price level risk
Notes: Distribution of long-run price levels 100 quarters after random one-time level demand shock drawn from distribution with average uncertainty (solid line) and after one-standard deviation country-specific uncertainty shock (dotted line) under floating exchange rate (left panel) and in monetary union (right panel). Horizontal axis: price change in percent; vertical axis: density.
Policy implications
Our research highlights a key benefit of monetary union membership: the reduction of price level risk arising from country-specific uncertainty shocks. The nominal anchor provided by the union not only eliminates the inflationary bias, as is often argued (Alesina and Barro 2002), but also shapes business cycle dynamics. This finding has policy implications: heterogeneous exposure to uncertainty may be less problematic than one might think. This reduces the need for targeted policy intervention at the country level — whether by the common central bank or by national fiscal policy. Instead, it may be sufficient to rely on the stabilising effects of a credible nominal anchor, even in troubled waters.
References
Alesina, A and R J Barro (2002), “Currency unions”, Quarterly Journal of Economics 117(2): 409–436.
Basu, S and B. Bundick (2017), “Uncertainty shocks in a model of effective demand”, Econometrica 85(3): 937–958.
Benigno, G (2025), “Why the tariffs caused turmoil in financial markets”, VoxEU.org, 11 April.
Bergin, P R, R Glick and J-L Wu (2017), ““Conditional PPP” and real exchange rate convergence in the euro area”, Journal of International Money and Finance 73: 78–92.
Bloom, N (2009), “The impact of uncertainty shocks”, Econometrica 77(3): 623–685.
Born, B, L Huxel, G Müller and J Pfeifer (2025), “Anchored in troubled waters: Monetary unions and uncertainty”, CEPR Discussion Paper 15579.
Comunale, M and H T Nguyen (2023), “Measuring uncertainty in the Euro Area using a forecast error-based approach”, ECB Working Paper Series, No. 2712.
Grzana, M and E Ilzetzki (2025), “The impact of Trump’s economic policy on the EU economy”, VoxEU.org, 16 March.
Jurado, K, S C Ludvigson and S Ng (2015), “Measuring uncertainty”, American Economic Review 105(3): 1177–1216.
