Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

Functionalist accounts of hierarchy, longstanding in the social sciences, have gained recent
prominence in studies of leadership, power, and status. This chapter takes a critical look at a …

To improve forecasting accuracy, combine forecasts derived from methods that differ
substantially and draw from different sources of information. When feasible, use five or more …

We study the inflation uncertainty reported by individual forecasters in the Survey of
Professional Forecasters 1969–2001. Three popular measures of uncertainty built from …

Using a standard decomposition of forecast errors into common and idiosyncratic shocks,
we show that aggregate forecast uncertainty can be expressed as the disagreement among …

Purchase intentions are routinely used to forecast sales of existing products and services.
While past studies have shown that intentions are predictive of sales, they have only …

The economics of climate change involves a vast array of uncertainties, complicating our
understanding of climate change. This study explores uncertainty in baseline trajectories …

The application of Internet–based virtual stock markets (VSMs) is an additional approach
that can be used to predict short–and medium–term market developments. The basic …

In this study, we propose a novel nonlinear ensemble forecasting model integrating
generalized linear auto-regression (GLAR) with artificial neural networks (ANN) in order to …

Abstract Research Summary Strategic decisions are uncertain and often irreversible. Hence,
predicting the value of alternatives is important for strategic decision making. We investigate …