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Found 6 papers, 1 papers with code
Maximally Forward-Looking Core Inflation
Timely monetary policy decision-making requires timely core inflation measures.
From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks
We reinvigorate maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres.
Integration or fragmentation? A closer look at euro area financial markets
This paper examines the degree of integration at euro area financial markets.
Non-linear dimension reduction in factor-augmented vector autoregressions
This paper introduces non-linear dimension reduction in factor-augmented vector autoregressions to analyze the effects of different economic shocks.
Bayesian Neural Networks for Macroeconomic Analysis
Neural networks, by contrast, are designed for datasets with millions of observations and covariates.
Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques
Among the techniques considered, the Autoencoder and squared principal components yield factors that have high predictive power for one-month- and one-quarter-ahead inflation.
