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Forecasting quantitatively using micro/meso/macro-economics with scenarios for qualitative balance

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PurposeThe purpose of the paper is to report on a novel approach to assessing long-term policy and technology impacts. This approach combines a qualitative forecast with a tri-level quantitative projection to provide a broadly socio-economic analysis. It is aimed at forecasting problems, such as impact assessment for future policy formulation in the light of socio-economic, technological and market developments. Design/methodology/approachThe paper is based on a variety of research methods including scenario planning, and techniques taken from analysis of stochastic processes to identify and correlate behaviour, combined with the concepts meso-economics, in order to produce more robust tri-level quantitative estimations, driven by qualitative analysis. FindingsThe paper finds that it is possible to join micro-economic behaviour to macro-economic, using meso-economics to attack what was previously seen as a difficult gap between the two. It also finds that quantitative forecasting, based on socio-economic behaviour using the qualitative assessment from a scenario ‐ i.e. from stories about the future ‐ can form a basis for quantitative forecasting. Different scenarios may be linked to corresponding quantitative economic estimations using key indicator parameters at each economic level, those which are the most relevant to the scenarios, and so exploit statistical techniques across the three levels in a balanced fashion. Originality/valueThis paper summarises a novel approach, taking a fresh look at forecasting economic impacts assessments by shaping the quantitative form with a qualitative tool, while introducing the linking powers of meso-economics. General economic theories in widespread use today seem to be weak when dealing with the non-deterministic nature of real markets and economies and especially in linking micro-economic parameters to macro-economic. The approach attempts to resolve this dilemma. An example is presented of its use in a recent study.

Keywords: Economics; Forecasting; Qualitative methods; Quantitative methods

Document Type: Research Article


Publication date: 2009-02-20

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