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We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against...
Persistent link: https://www.econbiz.de/10012143752
We study the real-time predictive content of crude oil prices for US real GDP growth through a pseudo out-of-sample (OOS) forecasting exercise. Comparing our benchmark model ?withoutoil? against alternatives ?with oil,? we strongly reject the null hypothesis of no OOS population-level...
Persistent link: https://www.econbiz.de/10010553113
We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark "model\without oil against...
Persistent link: https://www.econbiz.de/10013136099
We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against...
Persistent link: https://www.econbiz.de/10013137990
Persistent link: https://www.econbiz.de/10008656224
Persistent link: https://www.econbiz.de/10011387979
Persistent link: https://www.econbiz.de/10010440419
This paper examines the predictive power of weather for electricity prices in day-ahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of day-ahead electricity prices substantially, suggesting that weather forecasts can price the weather premium....
Persistent link: https://www.econbiz.de/10005481438
We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary...
Persistent link: https://www.econbiz.de/10004976646
We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combination through a utility-based objective function. We use this approach in the context of stock return predictability and...
Persistent link: https://www.econbiz.de/10011162487