We investigate the link between leadership, beliefs and pro-social behavior in social dilemmas. This link is interesting because field evidence suggests that people's behavior in domains like charitable giving, tax evasion, corporate culture and corruption is influenced by leaders (CEOs, politicians) and beliefs about others’ behavior. Our framework is a repeated experimental public goods game with and without a leader who makes a contribution to the public good before others (the followers). We find that leaders strongly shape their followers’ initial beliefs and contributions. In later rounds, followers put more weight on other followers’ past behavior than on the leader's current action. This creates a path dependency the leader can hardly correct. We discuss the implications for understanding belief effects in naturally occurring situations.This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.

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