Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based...

D espite a significant decline in the pace of economic growth in the second half of 2000, macroeconomic forecasters underpredicted real GDP growth and overpredicted the unemployment rate by a significant amount, for the fifth consecutive year. On average, real GDP forecasts were about 2 percentage points below the actual data for the 1996-2000 period, and unemployment rate forecasts about 0.5 p...

This paper establishes properties of optimal forecasts under general loss functions, extending existing results obtained under speci…c functional forms and data generating processes. We propose a new method that changes the probability measure under which the well-known properties of optimal forecasts under mean squared error loss can be recovered. We illustrate the proposed methods through an ...

In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...

We investigate the presence and impact of forecast errors in the arrival rate of customers to a service system. Analysis of a large dataset shows that forecast errors can be large relative to the fluctuations naturally expected in a Poisson process. We show that ignoring forecast errors typically leads to overestimates of performance and that forecast errors of the magnitude seen in our dataset...