SUERF Policy Notes & Briefs offer accessible and concise, high-quality, authoritative and informed analysis on topical issues related to European money and finance. They make research by SUERF Member institutions and academic researchers available to the SUERF network and beyond. SUERF Policy Notes & Briefs are published weekly on the SUERF webpage. The views expressed are those of the author(s) and not necessarily those of the institution(s) the author(s) is/are affiliated with.
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|Nov 2023||Policy Brief||No 723||Analysis of CBDC Narrative by Central Banks using Large Language Models||Andrés Alonso Robisco, José Manuel Carbó|
|Mar 2023||Policy Brief||No 553||Machine Learning Methods in Climate Finance: a Systematic Review||Andrés Alonso-Robisco, José Manuel Carbó, José Manuel Marqués|
|Mar 2023||Policy Brief||No 544||Using machine learning to measure ﬁnancial risk in China||Alexander Al-Haschimi, Apostolos Apostolou, Andres Azqueta-Gavaldon, Martino Ricci|
|Jan 2023||Policy Brief||No 498||Get your bearings: guidelines for newspaper based economic indicators||Erik Andres-Escayola, Corinna Ghirelli, Luis Molina, Javier Perez, Elena Vidal|
|Oct 2022||Policy Brief||No 435||Using household-level data to guide borrower-based macro-prudential policy||Gastón Andrés Giordana, Michael Heinrich Ziegelmeyer|
|Sep 2022||Policy Brief||No 410||Should we trust the credit decisions provided by machine learning models?||Andrés Alonso, José Manuel Carbó|
|Jul 2022||Policy Brief||No 380||Old age takes its toll: long-run projections of health-related public expenditure in Luxembourg||Gastón Andrés Giordana, María Noel Pi Alperin|
|Jun 2022||Policy Brief||No 361||The influence of financial corporations on IMF lending: Has it changed with the global financial crisis?||Lena Lee Andresen|
|Oct 2021||Policy Brief||No 203||The reform of the EU’s fiscal governance framework in a new macroeconomic environment||Mario Alloza, Javier Andrés, Pablo Burriel, Iván Kataryniuk, Javier J. Pérez, Juan Luis Vega|
|Dec 2020||Policy Note||No 210||On the risk-adjusted performance of machine learning models in credit default prediction||Andres Alonso, Jose Manuel Carbo|