Use this URL to cite or link to this record in EThOS:
Title: The usefulness of aggregate and disaggregate models in market forecasting
Author: Papaioannou, Anna
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 1993
Availability of Full Text:
Access from EThOS:
This study aims to contribute to an improved understanding of the aggregation/disaggregation issue in market forecasting. It has developed a theoretical framework to explain the relative efficiency of various methods for forecasting aggregates and disaggregates and the effectiveness of combinations of forecasts including combinations across different levels of aggregation. The theoretical results not only explain and unify many previous research findings but they also predict the success of some new methods of forecasting e.g. using aggregate data to improve forecasts of the disaggregates and using data from many disaggregates to improve the individual forecasts. The empirical results confirmed most of the previous research findings and the theoretical suggestions. Because of the limitations in the data set most of the results have the status of hypotheses for general purposes e.g it is better to forecast an aggregate by direct extrapolation than by summing lower level forecasts. In addition the empirical results covered a range of areas which are not directly addressed by the theory developed e.g. forecasts at longer lead times etc.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available