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Nowcasting World Trade with Machine Learning : A Three-Step Approach

Chinn, Menzie David; Meunier, Baptiste; Stumpner, Sebastian - 2023

We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, linear gradient boosting). While much less used in the literature, the latter are found to outperform...

Persistent link: https://www.econbiz.de/10014352801

Credit Growth, the Yield Curve and Financial Crisis Prediction : Evidence from a Machine Learning Approach

Bluwstein, Kristina; Buckmann, Marcus; Joseph, Andreas; … - 2021

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870–2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...

Persistent link: https://www.econbiz.de/10013313452

DSGE Model Forecasting : Rational Expectations vs. Adaptive Learning

Warne, Anders - 2023

This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1–2019Q4. The adaptive learning...

Persistent link: https://www.econbiz.de/10014258211

New technologies and jobs in Europe

Albanesi, Stefania; da Silva, António Dias; Jimeno, Juan F. - 2023

We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and … that on average employment shares have increased in occupations more exposed to AI. This is particularly the case for … shares of occupations more exposed to AI-enabled automation. Country heterogeneity for this result seems to be linked to the …

Persistent link: https://www.econbiz.de/10014374775

New Technologies and Jobs in Europe

Albanesi, Stefania; Dias da Silva, Antonio; Jimeno, Juan F. - 2023

Persistent link: https://www.econbiz.de/10014346583

Economic Policy Uncertainty in the Euro Area : An Unsupervised Machine Learning Approach

Azqueta-Gavaldon, Andres - 2020

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...

Persistent link: https://www.econbiz.de/10012844456

Are Emerging Market Currency Crises Predictable? - a Test

Peltonen, Tuomas A. - 2021

This paper analyzes the predictability of emerging market currency crises by comparing the often used probit model to a new method, namely a multi-layer perceptron artificial neural network (ANN) model. According to the results, both models were able to signal currency crises reasonably well...

Persistent link: https://www.econbiz.de/10013318114

Using Machine Learning to Measure Financial Risk in China

Al-Haschimi, Alexander; Apostolou, Apostolos; … - 2023

We develop a measure of overall financial risk in China by applying machine learning techniques to textual data. A pre-defined set of relevant newspaper articles is first selected using a specific constellation of risk-related keywords. Then, we employ topical modelling based on an unsupervised...

Persistent link: https://www.econbiz.de/10014258212

Nowcasting Business Cycle Turning Points with Stock Networks and Machine Learning

Azqueta-Gavaldon, Andres; Hirschbühl, Dominik; … - 2021

We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through...

Persistent link: https://www.econbiz.de/10013314911

Mitigating the Forward Guidance Puzzle : Inattention, Credibility, Finite Planning Horizons and Learning

Groot, Oliver - 2020

This paper develops a simple, consistent methodology for generating empirically realistic forward guidance simulations using existing macroeconomic models by modifying expectations about policy announcements. The main advantage of our method lies in the exact preservation of all other shock...

Persistent link: https://www.econbiz.de/10012830239

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