France: Nowcasting French GDP

The business cycle analysis focuses on studying the economic fluctuations in the short term. This was made possible thanks to the development of national accounting and the increasing availability of economic data. At the heart of this approach are the measurement and forecasting of GDP growth . To enhance the accuracy of GDP forecasts, many models have been developed over time, ranging from basic regressions to multiple regressions and dynamic factor models. On the one hand, p enalized multiple regressions, inspired by machine learning techniques, stand out for their ease of implementation. On the other hand, dynamic factor models tend to be more accurate but are more complex to implement. In this report, we provide an overview of the various econometric methods employed (simple regressions, multiple regressions, dynamic factor models, as shown in Chart 1 ) that contribute to enhancing our library of no wcasting models for France. The key findings are as follows: The different n owcasting models we have developed suggest that GDP growth in France is expected to be between 0.1% and 0.2% in the second quarter of 2025 . GDP growth is expected around 0.2% in the third quarter. Among the multiple regression models, the BIC and ElasticNet models demonstrate better performance than the one based on the GETS algorithm. Our Natixis dynamic factor model has shown significant improvement in performance since early 2024 and has the advantage of being easily re plicable to the euro area and other major European economies .