We analyze the behavior of experts who quote forecasts for monthly SKU-level sales data where we compare data before and after the moment that experts received different kinds of feedback on their behavior. We have data for 21 experts located in as many countries who make SKUlevel forecasts for...

This paper reports on simulation results for the Wald test for ∝1=∝2=0 in the regression model [Please open the additional file (8526_math.png) to see the regression model] for the case ĸ is known and for the case where ĸ has to be estimated using nonlinear least squares (NLS). This last...

Experts frequently adjust statistical model-based forecasts. Sometimes this leads to higher forecast accuracy, but expert forecasts can also be dramatically worse. We explore the potential drivers of the relevance and quality of experts' added knowledge. For that purpose, we examine a very large...

We propose a new and simple methodology to estimate the loss function associated with experts' forecasts. Under the assumption of conditional normality of the data and the forecast distribution, the asymmetry parameter of the lin-lin and linex loss function can easily be estimated using a linear...

Experts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and...

Macroeconomic forecasts are frequently produced, published, discussed and used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyse some recent developments from that...

The primary purpose of the paper is to answer the following two questions regarding the performance of the influential Federal Open Market Committee (FOMC) of the Federal Reserve System, in comparison with the forecasts contained in the “Greenbooks” of the professional staff of the Board of...

It frequently occurs that experts adjust forecasts from statistical models. There is some evidence that such adjusted forecasts can lead to substantially better performance. Little is known about competence and confidence effects in what these experts do. Theoretical and experimental results in...

Experts can rely on statistical model forecasts when creating their own forecasts. Usually it is not known what experts actually do. In this paper we focus on three questions, which we try to answer given the availability of expert forecasts and model forecasts. First, is the expert forecast...

Experts may have domain-specific knowledge that is not included in a statistical model and that can improve forecasts. While one-step-ahead forecasts address the conditional mean of the variable, model-based forecasts for longer horizons have a tendency to convert to the unconditional mean of a...