In this paper we discuss sensitivity of forecasts with respect to the information set considered in prediction; a sensitivity measure called impact factor, IF, is defined. This notion is specialized to the case of VAR processes integrated of order 0, 1 and 2. For stationary VARs this measure corresponds to the sum of the impulse response coefficients. For integrated VAR systems, the IF has a di...

This paper develops methods for Bayesian VAR forecasting when the researcher is uncertain about which variables enter the VAR and the dimension of the VAR may be changing over time. It considers the case where there are N variables which might potentially enter a VAR and the researcher is interested in forecasting N∗ of them. Thus, the researcher is faced with 2N−N ∗ potential VARs. If N is lar...

This paper argues that inferring long-horizon asset-return predictability from the properties of vector autoregressive (VAR) models on relatively short spans of data is potentially unreliable. We illustrate the problems that can arise by re-examining the findings of Bekaert and Hodrick (1992), who detected evidence of in-sample predictability in international equity and foreign exchange markets...

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are base...

In a truly smart grid, system load would be known in advance with a high degree of confidence. Currently, this goal of “smart forecasting” is far from being realized. In the Pacific Gas and Electric (PG&E) aggregation area managed by the California Independent System Operator (ISO), the root mean squared day-ahead forecast error was about 3.8 percent of mean actual load over the period 1 April ...

This paper presents an analysis of how day-ahead electricity spot prices are affected by day-ahead wind power forecasts. Demonstration of this relationship is given as a test case for the Western Danish price area of the Nord Pool’s Elspot market. Impact on the average price behaviour is investigated as well as that on the distributional properties of the price. By using a non-parametric regres...

Cointegration has different theoretical implications for forecasting. Several empirical studies have compared the out of sample forecasting performance of cointegrted VECMs against unrestricted VARs in levels and in differences. The results of these studies have been generally mixed and inconclusive. This paper provides a comprehensive review over the subject, and also examines the effects...

This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micr...

Day-ahead half-hourly demand forecasts are required for scheduling and for calculating the daily electricity pool price. One approach predicts turning points on the demand curve and then produces half-hourly forecasts by a heuristic procedure, called profiling, which is based on a past demand curve. This paper investigates possible profiling improvements. Using a cubic smoothing spline in the h...

• Up to 3 quarters ahead, our mean forecast errors for GDPP growth have been relatively small. However, 4 to 8 quarters ahead we have tended to over-predict quarterly GDPP growth by at least 0.25 per cent (on average). • In terms of accuracy and bias our GDPP growth forecasting performance has been similar to that of the NZIER. • We do not find a significant difference between the accuracy of t...