Evaluating the Rationality of Managers' Sales Forecasts

This paper deals with the analysis and evaluation of sales forecasts of managers, given that it is unknown how they constructed their forecasts. Our goal is to find out whether these forecasts are rational. To examine deviations from rationality, we argue that one has to approximate how the managers could have generated the forecasts. We describe several ways to construct these approximate expressions. The analysis of a large set of a single manager's forecasts for sales of pharmaceutical products illustrates the practical usefulness of our methodology

Forecasting Earnings Forecasts

We analyze earnings forecasts retrieved from the I/B/E/S database concerning 596 firms for the sample 1995 to 2011, with a specific focus on whether these earnings forecasts can be predicted from available data. Our main result is that earnings forecasts can be predicted quite accurately using publicly available information. Second, we show that earnings forecasts that are less predictable are also less accurate. We also show that earnings forecasters who quote forecasts that are too extreme need to correct these as the earnings announcement approaches. Finally, we show that the unpredictable component of earnings forecasts can contain information which we can use to improve the forecasts

Benchmarking judgmentally adjusted forecasts

Many publicly available macroeconomic forecasts are judgmentally-adjusted model-based forecasts. In practice usually only a single final forecast is available, and not the underlying econometric model, nor are the size and reason for adjustment known. Hence, the relative weights given to the model forecasts and to the judgment are usually unknown to the analyst. This paper proposes a methodology to evaluate the quality of such final forecasts, also to allow learning fro

Stochastic levels and duration dependence in US unemployment

We introduce a new time series model that can capture the properties of data as is typically exemplified by monthly US unemployment data. These data show the familiar nonlinear features, with steeper increases in unem- ployment during economic downswings than the decreases during economic prosperity. At the same time, the levels of unemployment in each of the two states do not seem fixed, nor are the transition periods abrupt. Finally, our model should generate out-of-sample forecast

Managing Sales Forecasters

A Forecast Support System (FSS), which generates sales forecasts, is a sophisticated business analytical tool that can help to improve targeted business decisions. Many companies use such a tool, although at the same time they may allow managers to quote their own forecasts. These sales forecasters (managers) can take the FSS output as their input, but they can also fully ignore the FSS out- comes. We propose a methodology that allows to evaluate the forecast accuracy of these managers, relative to the FSS, while taking aboard latent variation across managers' behavior. We show that the results, here for a large Germany-based pharmaceutical company, can in fact be used to manage the sales forecasters by giving clear-cut recommendations for improvement

How Informative are the Unpredictable Components of Earnings Forecasts?

__Abstract__ An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the unpredictable components, which may be viewed as the personal expertise of the earnings forecasters, we see that small adjustments to the model forecasts lead to more forecast accuracy. Based on past track records, it is possible to predict the future track record of individual forecasters

A Novel Approach to Measuring Consumer Confidence

This paper puts forward a new data collection method to measure daily consumer confidence at the individual level. The data thus obtained allow to statistically analyze the dynamic correlation of such a consumer confidence indicator and to draw inference on transition rates. The latter is not possible for currently available monthly data collected by statistical agencies on the basis of repeated cross-sections. In an application to measuring Dutch consumer confidence, we show that the incremental information content in the novel indicator helps to better forecast consumption

Analyzing Fixed-Event Forecast Revisions

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current forecast revisions on one-period lagged forecast revisions. Under weak-form (forecast) efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that this null hypothesis of zero correlation is rejected frequently, where the correlation can be either positive (which is widely interpreted in the literature as “smoothing”) or negative (which is widely interpreted as “over-reacting”). We propose a methodology to i