Machine learning: Optimising forecasting for better decision-making

Karin Klieber is a research economist in the Monetary Policy Section at the Austrian National Bank (Oesterreichische Nationalbank, OeNB). She specializes in the intersection of applied econometrics and central banking, bridging academic research and policy needs. Her work focuses on inflation, monetary policy, and machine learning in applied econometrics, and has been published in top field journals such as the Journal of Econometrics and the Journal of Applied Econometrics. She has recently been a visiting researcher at the Federal Reserve Bank of New York and has worked at the European Central Bank. She holds a PhD from the University of Salzburg.

Elvira Prades is a Research Economist in the Economic Analysis Division at the Bank of Spain (Banco de España, BdE) and an Adviser at the BIS Innovation Hub. Her research lies at the intersection of international trade, global value chains, and inflation and price setting dynamics, with a particular focus on the integration of machine learning methods into empirical economic analysis. She has held visiting research positions at the Banque de France and the Central Bank of Chile. She holds a PhD from the European University Institute (EUI).