Showing 1 - 10 of 1,642
; (iv) newer generation Phillips curve models with several timevarying features are a promising avenue for forecasting …
Persistent link: https://www.econbiz.de/10012299084
the beginning of 2018. They also have performed well in forecasting the direction of inflation. In terms of the …
Persistent link: https://www.econbiz.de/10011901421
depends strongly on the time period. Global factors provide only limited additional information for forecasting. In addition …
Persistent link: https://www.econbiz.de/10012926349
; (iv) newer generation Phillips curve models with several time-varying features are a promising avenue for forecasting …
Persistent link: https://www.econbiz.de/10012822484
This paper uses a panel VAR (PVAR) approach to estimating, analysing and forecasting price dynamics in four different …
Persistent link: https://www.econbiz.de/10010411883
This paper investigates the trade-off between timeliness and quality in nowcasting practices. This trade-off arises when the frequency of the variable to be nowcast, such as GDP, is quarterly, while that of the underlying panel data is monthly; and the latter contains both survey and...
Persistent link: https://www.econbiz.de/10011846875
indicators help improve upon the simple Autoregressive (AR) model for forecasting HICP core inflation as well total inflation, if …
Persistent link: https://www.econbiz.de/10013134965
- and hard-threshold algorithms improves the forecasting performance, especially during periods of economic crisis. While a … effect on forecasting performance, all the more, if the set of indicators becomes unbalanced. …
Persistent link: https://www.econbiz.de/10010532088
Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...
Persistent link: https://www.econbiz.de/10010257225
Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....
Persistent link: https://www.econbiz.de/10010342246