Modelling and complexity in social sciences: what impact on decision-making?

Abstract

The issues raised by modelling (in social sciences) are by definition repetitive, and this characteristic reinforces their seriousness/interest for researchers. A model will be all the more accurate and theoretically useful if it allows us to make predictions that can be observed to see if they actually come true in practice. However, economic reality is extremely diverse and complex. In addition to theoretical and practical questions, there are also more political and ethical questions. The economy is rarely repetitive. Time disrupts the economy and hinders its tendency to reconcile "economic efficiency" and scientific rigour. Furthermore, economic logic is that of an uncertain universe, characterised by economic instability, insecurity and precariousness. In such a universe, agents favour the short term... Creativity, emotion, behaviour and subjectivity play a fundamental role. Under these conditions, could modelling be a tool for forecasting and optimisation? Economic theories are only approximate, and models cannot be confused with reality. How, then, should we position ourselves – scientifically and philosophically speaking – in relation to historical experience and experience in terms of modelling? A review of theoretical analyses/modelling is needed. We therefore propose a review of the literature (epistemological, etc.) on modelling.