This chapter aims to discuss certain limitations of the dominant equilibrium thinking in policy and explore more complexity-friendly alternatives. If societies and markets are viewed as complex,non-equilibrium systems, understanding nonlinear, adaptive and evolving patterns emerging from agent behaviour in network structures is fundamental for policy purposes.This requires improved realism of the behavioural and social foundations on which policiesare based.We must also reconsider the mantra of incentivisation, institutional design and the top-down regulation that typically dominates conventional policy. Recent cases of financial market regulation and health policies can help us to understand the importance of looking at the subtle ways in which people or organisations behave when exposed to social influence, and pre-existing social norms and network externalities. Changing the current policy narrative and exploring complexity-friendly concepts, instruments and methods requires a shift of focus of policy-making from forecast and prediction of system equilibrium in order to understand and manage complex social systems better.
Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy / F. Squazzoni (UNDERSTANDING COMPLEX SYSTEMS). - In: Non-Equilibrium Social Science and Policy : Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking / [a cura di] J. Johnson, A. Nowak, P. Ormerod, B. Rosewell, Y.-C. Zhang. - Prima edizione. - [s.l] : Springer, 2017. - ISBN 9783319424248. - pp. 135-148 [10.1007/978-3-319-42424-8_9]
Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy
F. Squazzoni
2017
Abstract
This chapter aims to discuss certain limitations of the dominant equilibrium thinking in policy and explore more complexity-friendly alternatives. If societies and markets are viewed as complex,non-equilibrium systems, understanding nonlinear, adaptive and evolving patterns emerging from agent behaviour in network structures is fundamental for policy purposes.This requires improved realism of the behavioural and social foundations on which policiesare based.We must also reconsider the mantra of incentivisation, institutional design and the top-down regulation that typically dominates conventional policy. Recent cases of financial market regulation and health policies can help us to understand the importance of looking at the subtle ways in which people or organisations behave when exposed to social influence, and pre-existing social norms and network externalities. Changing the current policy narrative and exploring complexity-friendly concepts, instruments and methods requires a shift of focus of policy-making from forecast and prediction of system equilibrium in order to understand and manage complex social systems better.File | Dimensione | Formato | |
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