Application of Subjective Models in Forecasting of Renewable Energy Technologies Development

Konstancja Poradowska

Abstract

The main reason for the difficulties in forecasting new phenomena is the lack of sufficient empirical data, on which assumptions about the future development can be taken and estimations of the prediction model parameters can be produced. These difficulties are exacerbated when, for example, for the long-term development scenarios, the design of entire sets of forecasts' trajectories is required and they have to reach numerous time horizons. Such a problem occurred during the implementation of the energy foresight for Poland, which required the construction of renewable energy production forecasts for the years 2010-2050. Possible solutions to this problem are the main aspects of this article. The paper presents methods of formal prediction models' construction in the absence of the past data. Subjective opinions of experts on the development of a projected phenomenon were used to evaluate the parameters of such models. Thus, those models are called subjective. There are considered four subjective prediction models: a development trend model, Rogers's diffusion model and Bass's diffusion model, ADBUDG model. On the basis of each of the models, as an illustration of theoretical considerations, were built predictions of energy production from renewable energy sources in Poland in the years 2010-2050. In the conclusions part, the individual models are evaluated from the standpoint of their usefulness as well as their advantages and disadvantages in building long-term forecasts of new technologies' development are discussed
Author Konstancja Poradowska (ES / DFaEA)
Konstancja Poradowska,,
- Department of Forecasting and Economic Analysis
Pages1202-1211
Publication size in sheets0.5
Book Soliman Khalid S. (eds.): Innovation Vision 2020: Sustainable Growth, Entrepreneurship, and Economic Development. Proceedings of The 19th International Business Information Management Association Conference [dokument elektroniczny], 2012, International Business Information Management Association (IBIMA), ISBN 978-0-9821489-8-3, 2270 p.
Keywords in Englishsubjective models, experts' forecasts
Languageen angielski
Score (nominal)10
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