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This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a …
Persistent link: https://www.econbiz.de/10011450047
This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...
Persistent link: https://www.econbiz.de/10012154665
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tests of forecasting accuracy by comparing the imputed monthly series to the original monthly series. Finally, we take a …
Persistent link: https://www.econbiz.de/10013482570
We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...
Persistent link: https://www.econbiz.de/10012668293
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exhibit fractional integration with one or two poles in the spectrum. A forecasting comparison shows that a model with a non …
Persistent link: https://www.econbiz.de/10003720605
This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both … factor-augmented vector autoregression approach, improves forecasting performance for many variables, particularly at short …
Persistent link: https://www.econbiz.de/10003807908
For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis this … beneficial for forecasting. Forecasts based on the original series are compared to forecasts based on logs. It is found that it … substantial forecasting improvements from taking logs are found if the log transformation actually stabilizes the variance of the …
Persistent link: https://www.econbiz.de/10003820020