Results 241 to 250 of about 280,531 (306)

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley   +1 more source

Nowcasting World Trade With Machine Learning: A Three‐Step Approach

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn   +2 more
wiley   +1 more source

The Role of Coincident Information in Real‐Time Business Cycle Forecasting

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Official NBER recession dates are announced with substantial delay. Therefore, real‐time forecasters cannot condition on the most recent business cycle states even though recessions and expansions are highly persistent. I study whether real‐time coincident releases can substitute for this missing information. At each monthly forecast origin, I
Visa Kuntze
wiley   +1 more source

Forecasting Natural Gas Futures Price Volatility of the United States: National Versus State‐Level Climate Concern Indexes

open access: yesJournal of Futures Markets, EarlyView.
ABSTRACT This paper uses GARCH‐MIDAS to predict US natural gas futures volatility using national and state‐level Climate Concern Indexes (CCIs). We find that both national and state‐level CCIs positively affect price volatility. Notably, models using state‐level data—specifically those utilizing least‐squares (LS) weighting combinations—surpass the ...
Afees A. Salisu   +3 more
wiley   +1 more source

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