In this paper we investigate whether and how far density forecasts sensibly can be combined to produce a “better” pooled density forecast. In so doing we bring together two important but hitherto largely unrelated areas of the forecasting literature in economics, density forecasting and forecast combination. We provide simple Bayesian methods of pooling information across alternative density fo...

BACKGROUND Any improvement in the forecast accuracy of life expectancy would be beneficial for policy decision regarding the allocation of current and future resources. In this paper, I revisit some methods for forecasting age-specific life expectancies. OBJECTIVE This paper proposes a model averaging approach to produce accurate point forecasts of age-specific life expectancies. METHODS Illust...

This paper presents an artificial neural network(ANN) approach to electric load forecasting. The ANN is used to learn the relationship among past, current and future temperatures and loads. In order to provide the forecasted load, the ANN interpolates among the load and temperature data in a training data set. The average absolute errors of the one-hour and 24-hour ahead forecasts in our test o...

We propose a global smoothing method based on polynomial splines for the estimation of functional coefficient regression models for nonlinear time series. Consistency and rate of convergence results are given to support the proposed estimation method. Methods for automatic selection of the threshold variable and significant variables (or lags) are discussed. The estimated model is used to produ...

This paper presents an initial validation of a solar radiation service that provides historical, as well as up-to-the-moment solar resource data from satellites, short-term forecasts from cloud motion analysis, and medium term forecasts (up to seven days ahead) from numerical weather prediction models [1]. Forecasts are validated for several, climatically distinct regions of the US, investigati...

This paper uses minute-by-minute British electricity demand observations to evaluate methods for prediction from 10 to 30 minutes ahead. Such very short lead times are important for the real-time scheduling of electricity generation. We consider methods designed to capture both the intraday and the intraweek seasonal cycles in the data, including ARIMA modelling, an adaptation of Holt-Winters e...

A call center is a centralized hub where customer and other telephone calls are dealt with by an organization. In today’s economy, they have become the primary point of contact between customers and businesses. Accurate prediction of the call arrival rate is therefore indispensable for call center practitioners to staff their call center efficiently and cost effectively. This article proposes a...

In this paper we propose a relatively simple procedure to predict Euro-zone industrial production using mostly data derived from the business surveys of the three major economies within the European Monetary Union (France, Germany, and Italy). The basic idea is that of estimating business cyclical indicators to be used as predictors for the industrial production in France and Germany; as far as...

This paper investigates the extent to which investors are rational with respect to two well-known empirical properties of analyst consensus forecasts: optimism and autocorrelated revisions. Consistent with previous research, I find that investors are aware of the optimistic bias in analyst forecasts, but do not adjust for it completely. Using Mishkin’s test, I find that the market’s expectation...

This paper re-examines the empirical content of the expectations theory of the term structure by employing the Campbell-Shiller (1987) methodology to study the behaviour of 10-year/three-month US government yield spreads. The methodology is implemented in two ways. First, theoretical spreads satisfying the expectations theory are constructed from in-sample forecasts of future changes in short r...