Targeting predictors in random forest regression
D Borup, BJ Christensen, NS Mühlbach… - International Journal of …, 2023 - Elsevier
Random forest (RF) regression is an extremely popular tool for analyzing high-dimensional
data. Nonetheless, its benefits may be lessened in sparse settings due to weak predictors …
data. Nonetheless, its benefits may be lessened in sparse settings due to weak predictors …
Nowcasting with payments system data
JW Galbraith, G Tkacz - International Journal of Forecasting, 2018 - Elsevier
We consider the potential usefulness of a large set of electronic payments data, comprising
the values and numbers of both debit card transactions and cheques that clear through the …
the values and numbers of both debit card transactions and cheques that clear through the …
Credit rating migration risk and business cycles
F Fei, AM Fuertes, E Kalotychou - Journal of Business Finance …, 2012 - Wiley Online Library
Basel III seeks to improve the financial sector's resilience to stress scenarios which calls for
a reassessment of banks' credit risk models and, particularly, of their dependence on …
a reassessment of banks' credit risk models and, particularly, of their dependence on …
The accuracy and informativeness of agricultural baselines
SS Bora, AL Katchova… - American Journal of …, 2023 - Wiley Online Library
Agricultural baselines facilitate policy and investment decisions by governments and market
participants by providing long‐term projections about the farm sector. Despite their …
participants by providing long‐term projections about the farm sector. Despite their …
Changes in predictive ability with mixed frequency data
AB Galvão - International Journal of Forecasting, 2013 - Elsevier
When assessing the predictive power of financial variables for economic activity,
researchers usually aggregate higher-frequency data before estimating a forecasting model …
researchers usually aggregate higher-frequency data before estimating a forecasting model …
Learning and heterogeneity in GDP and inflation forecasts
Using a Bayesian learning model with heterogeneity across agents, our study aims to
identify the relative importance of alternative pathways through which professional …
identify the relative importance of alternative pathways through which professional …
How far can we forecast? Statistical tests of the predictive content
J Breitung, M Knüppel - Journal of Applied Econometrics, 2021 - Wiley Online Library
We develop tests for the null hypothesis that forecasts become uninformative beyond some
maximum forecast horizon h∗. The forecast may result from a survey of forecasters or from …
maximum forecast horizon h∗. The forecast may result from a survey of forecasters or from …
Nowcasting GDP with electronic payments data
JW Galbraith, G Tkacz - 2015 - econstor.eu
We assess the usefulness of a large set of electronic payments data comprising debit and
credit card transactions, as well as cheques that clear through the banking system, as …
credit card transactions, as well as cheques that clear through the banking system, as …
The Murphy decomposition and the calibration-resolution principle: A new perspective on forecast evaluation
MO Pohle - arXiv preprint arXiv:2005.01835, 2020 - arxiv.org
I provide a unifying perspective on forecast evaluation, characterizing accurate forecasts of
all types, from simple point to complete probabilistic forecasts, in terms of two fundamental …
all types, from simple point to complete probabilistic forecasts, in terms of two fundamental …
Assessing gross domestic product and inflation probability forecasts derived from Bank of England fan charts
JW Galbraith, S van Norden - Journal of the Royal Statistical …, 2012 - academic.oup.com
Density forecasts, including the pioneering Bank of England 'fan charts', are often used to
produce forecast probabilities of a particular event. We use the Bank of England's forecast …
produce forecast probabilities of a particular event. We use the Bank of England's forecast …