The model forecasts point to three interesting observations. The first is that compared to the IMF forecasts and the consensus of market analysts, the risks are that GDP growth in 2024 could be stronger in the US and weaker in the eurozone. The second is that based on the probability distributions of the models' forecasts, a technical recession in the eurozone in the first half of 2024 may occur with a one in five chance.5 Yet, the third observation is that despite the lingering risk of recession, eurozone GDP growth should improve in Q2 2024 after six quarters of stagnation.
In conclusion, the expectation that the US economy will grow at a much stronger rate than the eurozone in 2024 has firmed in recent months, reflecting, among other factors, a more expansionary US fiscal policy. Growth estimates for the first half of the year based on business surveys point to a significant risk that the growth gap between the two areas will be higher than markets expect. If this forecast materialises, it would be natural to expect that, in the coming months, the eurozone monetary policy stance, measured as the real interest rate deflated by the change in core prices in the previous twelve months, will become relatively more expansionary compared to the US than markets discount (see Chart 1b).
1 Other factors, such as demographics and the lower dependence of the US on China, help to explain the growth differential between the two areas.
2 To measure the fiscal policy stance, reference is made to the primary balance not adjusted for the cycle given the uncertainty of estimates on potential GDP due to the impact of the pandemic on the economic cycle.
3 The Stability and Growth Pact was temporarily suspended from 2020 to 2023 to respond to the emergencies of the pandemic and the war in Ukraine.
4 The quarterly GDP change is forecast using a simple statistical model based on the monthly ISM indices in the US and PMI indices in the eurozone for the manufacturing and services sectors. The model sample spans from 1998Q1 to 2023Q4, excluding the quarters affected by the pandemic. Instead of using quarterly averages of the ISM and PMI indices, different models are separately estimated using the three monthly observations of each quarter. This approach exploits the different information content of the monthly surveys among firms for quarterly GDP growth. Statistical tests have shown that the out-of-sample forecasting power of this approach is superior to using quarterly averages of ISM and PMI data
5 Since the models do not consider lagged observations of the dependent variable, the forecasts of the different models are independent of each other, and it is possible to calculate the joint probability that the quarterly change in GDP is negative in both forecasting periods.