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Predicting downside risks to house prices and macro-financial stability

Deghi, Andrea; Katagiri, Mitsuru; Shahid, Sohaib; … - 2020

This paper predicts downside risks to future real house price growth (house-prices-at-risk or HaR) in 32 advanced and … overvaluation, excessive credit growth, and tighter financial conditions jointly forecast higher house-prices-at-risk up to three … years ahead. House-prices-at-risk help predict future growth at-risk and financial crises. We also investigate and propose …

Persistent link: https://www.econbiz.de/10012252738

Predicting fiscal crises : a machine learning approach

Hellwig, Klaus-Peter - 2021

In this paper I assess the ability of econometric and machine learning techniques to predict fiscal crises out of sample. I show that the econometric approaches used in many policy applications cannot outperform a simple heuristic rule of thumb. Machine learning techniques (elastic net, random...

Persistent link: https://www.econbiz.de/10012612343

Predicting macroeconomic and macrofinancial stress in low-income countries

Carvalho Filho, Irineu de; Comelli, Fabio; Giri, Rahul; … - 2020

-income countries, focusing on the risk of sharp declines in economic growth and of debt distress. We discuss routes to broadening this …

Persistent link: https://www.econbiz.de/10012486148

Deus ex machina? : a framework for macro forecasting with machine learning

Bolhuis, Marijn A.; Rayner, Brett - 2020

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast...

Persistent link: https://www.econbiz.de/10012251288

Machine learning and causality : the impact of financial crises on growth

Tiffin, Andrew - 2019

Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal …

Persistent link: https://www.econbiz.de/10012154563

Natural disaster insurance for sovereigns : issues, challenges and optimality

Cebotari, Aliona; Youssef, Karim - 2020

simulations of natural disasters and various insurance options, we find that sovereign decisions on optimal risk transfer involve … ex-ante preparedness is needed to manage the risks. The paper discusses sovereign experience with disaster insurance as a … key instrument to mitigate the risks; proposes ways to judge the adequacy of insurance; and considers ways to enhance its …

Persistent link: https://www.econbiz.de/10012170086

Improving the short-term forecast of world trade during the Covid-19 pandemic using SWIFT data on letters of credit

Carton, Benjamin; Hu, Nan; Mongardini, Joannes; Moriya, Kei - 2020

An essential element of the work of the Fund is to monitor and forecast international trade. This paper uses SWIFT messages on letters of credit, together with crude oil prices and new export orders of manufacturing Purchasing Managers' Index (PMI), to improve the short-term forecast of...

Persistent link: https://www.econbiz.de/10012392595

unFEAR : unsupervised feature extraction clustering with an application to crisis regimes classification

Chan-Lau, Jorge A.; Wang, Ran - 2020

cluster crisis frequency. Moreover, unFEAR could serve as a first step towards developing cluster-specific crisis prediction …

Persistent link: https://www.econbiz.de/10012392653

The more the merrier? : a machine learning algorithm for optimal pooling of panel data

Bolhuis, Marijn A.; Rayner, Brett - 2020

structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model …

Persistent link: https://www.econbiz.de/10012251287

Another piece of the puzzle : adding SWIFT data on documentary collections to the short-term forecast of world trade

Ghazaryan, Narek; Goumilevski, Alexei; Mongardini, Joannes - 2021

This paper extends earlier research by adding SWIFT data on documentary collections to the short-term forecast of international trade. While SWIFT documentary collections accounted for just over one percent of world trade financing in 2020, they have strong explanatory power to forecast world...

Persistent link: https://www.econbiz.de/10012794915