New forecasting methods for an old problem: Predicting 147 years of systemic financial crises
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More about this item
Keywords
machine learning; systemic financial crises; leading indicators; forecasting; early warning signal;All these keywords.
JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BAN-2022-10-10 (Banking)
- NEP-BIG-2022-10-10 (Big Data)
- NEP-CMP-2022-10-10 (Computational Economics)
- NEP-FDG-2022-10-10 (Financial Development and Growth)
- NEP-FOR-2022-10-10 (Forecasting)
- NEP-MON-2022-10-10 (Monetary Economics)
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