As the old saying goes, “Don’t put all of your eggs in one basket lest you drop the basket and lose all of your eggs.” Suppose the head of a forecasting division of a company has two sources of forecasts for the company’s sales, one source being the forecasts generated by the division’s econometrics group using an econometric time series model and the other source being the aggregated forecasts...

This study investigates the performance of combination forecasts in the context of international tourism demand. Five econometric and two time-series models are employed to generate individual forecasts. Six combination methods are then employed, and their forecasting performance evaluated, using data on UK outbound tourism demand in seven destination countries. The results suggest that combina...

Using quarterly Taiwan economic data, we demonstrate that deeper understanding of relations between variables and substantial gains in forecasting can be obtained by applying econometric and statistical tools to the traditional macroeconometric models. The improvement in forecasting accuracy is illustrated by outof-sample forecasts, and the models employed in the comparison include univariate t...

Modeling of a product or service’s attractiveness as a function of its own attributes (e.g., price and quality) is one of the foundations in econometric forecasts, which have been provided with an assumption that each human rationally has a consistent preference order among his choice decisions. Yet the preference orders by real humans become irrationally reversed, when the choice set of availa...

Judgmental bootstrapping is a type of expert system. It translates an experts' rules into a quantitative model by regressing the experts' forecasts against the information that he used. Bootstrapping models apply an experts' rules consistently, and many studies have shown that decisions and predictions from bootstrapping models are similar to those from the experts. Three studies showed that bo...

We used the take-the-best heuristic to develop a model to forecast the popular twoparty vote shares in U.S. presidential elections. The model draws upon information about how voters expect the candidates to deal with the most important issue facing the country. We used cross-validation to calculate a total of 1,000 out-ofsample forecasts, one for each of the last 100 days of the ten U.S. presid...