Sources of economic policy uncertainty in the euro area: a ready-to-use database

Construimos una base de datos de indicadores de incertidumbre de política económica (economic policy indicators: EPU, por sus siglas en inglés) de acceso público basada en la metodología propuesta por Azqueta-Gavaldón, Hirschbühl, Onorante y Saiz (2023), que utiliza técnicas de topic modelling para identificar los distintos componentes de incertidumbre. Esta base de datos se actualiza periódicamente y es accesible a través de la página web del Banco de España. Actualmente, los indicadores abarcan los cuatro países más grandes de la zona euro: España, Italia, Francia y Alemania. Además, agregando los indicadores nacionales de estos cuatro países, calculamos un indicador EPU para la zona euro. Estamos en el proceso de ampliar la cobertura de datos para construir indicadores EPU para más países de la UEM. Este conjunto de datos y los índices derivados para la zona euro proporcionan valiosas herramientas a investigadores, responsables políticos y analistas para evaluar y supervisar la dinámica de la incertidumbre de la política económica en tiempo real.In this paper, we build a publicly-available database of economic policy uncertainty (EPU) indicators based on the methodology proposed by Azqueta-Gavaldón, Hirschbühl, Onorante and Saiz (2023), which uses topic modelling techniques to identify distinct components of EPU. This database is regularly updated and can be accessed on the Banco de España’s website. Currently, the dataset covers the four largest countries in the euro area, namely Spain, Italy, France, and Germany. Our data coverage is continually expanding to include more euro area countries. Additionally, we compute the aggregated EPU indexes for the euro area. This comprehensive dataset and the resulting euro area indexes provide valuable tools for researchers, policymakers and analysts to assess and monitor the dynamics of economic policy uncertainty in real time

Economic policy uncertainty in the euro area: An unsupervised machine learning approach

We model economic policy uncertainty (EPU) in the four largest euro area countries by applying machine learning techniques to news articles. The unsupervised machine learning algorithm used makes it possible to retrieve the individual components of overall EPU endogenously for a wide range of languages. The uncertainty indices computed from January 2000 to May 2019 capture episodes of regulatory change, trade tensions and financial stress. In an evaluation exercise, we use a structural vector autoregression model to study the relationship between different sources of uncertainty and investment in machinery and equipment as a proxy for business investment. We document strong heterogeneity and asymmetries in the relationship between investment and uncertainty across and within countries. For example, while investment in France, Italy and Spain reacts strongly to political uncertainty shocks, in Germany investment is more sensitive to trade uncertainty shocks