摘要:

AbstractThe model presented in this paper integrates two distinct components of the demand for durable goods: adoptions and replacements. The adoption of a new product is modeled as an innovation diffusion process, using price and population as exogenous variables. Adopters are expected to eventually replace their old units of the product, with a probability which depends on the age of the owned unit, and other random factors such as overload, style‐changes etc.It is shovn that the integration of adoption and replacement demand components in our model yields quality sales forecasts, not only under conditions where detailed data on replacement sales is available, but also when the forecaster's access is limited to total sales data and educated guesses on certain elements of the replacement proces

ISSN:0277-6693    

DOI:10.1002/for.3980060102

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractForecasters are generally concerned about the properties of model‐based predictions in the presence of structural change. In this paper, it is argued that forecast errors can under those conditions be greatly reduced through systematic combination of forecasts. We propose various extensions of the standard regression‐based theory of forecast combination. Rolling weighted least squares and time‐varying parameter techniques are shown to be useful generalizations of the basic framework. Numerical examples, based on various types of structural change in the constituent forecasts, indicate that the potential reduction in forecast error variance through these methods is very significant. The adaptive nature of these updating procedures greatly enhances the effect of risk‐spreading embodied in standard combination tec

ISSN:0277-6693    

DOI:10.1002/for.3980060103

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractIn this paper a data analysis tool for analyzing highly correlated time series data is suggested. The main objective is to unify multiple time series into a single series and then apply a univariate method for the purpose of prediction. This method is essentially efficient for analyzing multiple time series with sparse data. Several time series data of relative demand for black and white television receivers in various countries are analyzed and quite accurate predictions are obtained.

ISSN:0277-6693    

DOI:10.1002/for.3980060104

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractProfessional analysts' judgments of the political riskiness of 49 focal countries for the period 1983‐1985 were studied. Data were collected on nine predictor variables; each was significantly correlated at the 0.01 level with ratings of political riskiness. The highest correlation was withinfant mortalityandlife expectancy; either accounted for roughly 50% of the variance in ratings. Different variables were better predictors of political risk within different geographic regions. A factor analysis suggested the presence of three underlying factors. The predictor variable with the highest loading was chosen to represent each of the three factors. These were:exchange rate differential; estimated inflation rate; andinfant mortality rate. Approximately 75% of the variance in ratings could be accounted for on the basis of a linear combination of the three predictor variables. These three variables were capable of good prediction even for various subsets of countries based on geographic region or other criteria. Using all nine variables as predictors resulted in only marginal improvement. A cluster analysis revealed little difference among clusters of judges. Ratings by undergraduate students closely paralled those of professional analysts. As in previous studies of expert predictions and forecasts, claims of expertise in political risk analysis were better supported by command of factual knowledge than by differentially superior predictive abilit

ISSN:0277-6693    

DOI:10.1002/for.3980060105

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060106

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060107

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060101

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY