In the field of economics, individual decision making is the basic building block for studying complex environments such as markets, political systems, and social dynamics. Individual decision making is embodied in the neoclassical economically rational agent, whose only concern is the maximization of utility from his own material consumption. Two qualities of this agent are especially important for the research we will undertake: He has perfect understanding of the problems he faces - today and in the future - and unbounded computational ability to solve them. He also has no regard for the consumption of other members of the society or for their feelings about his actions. Huge empirical and experimental evidence shows that departure from these qualities is robust and significant. The failure of the existing models to incorporate bounded rationality and social concerns has proven critical in socially relevant and complex situations such as lifetime consumption and saving, taxation and expenditure policy, labour search and wage determination. The objective of this project is to bring these phenomena into the framework of neoclassical economics, to test their implications, and to tackle important applications. A novel and central feature of our approach is the attempt to retain the parsimonious methodological approach of economic modelling, which has scored groundbreaking successes in matters such as the design of auctions, markets, contracts, and voting mechanisms. Our project envisions the development of theory on individual decision making, the use of experiments to illuminate and test the theory, and the concrete application of theory - mainly to financial markets. The project will push the frontiers of the understanding of the above mentioned socially relevant situations. The explanatory power of our approach will be guaranteed by the continuous feed-back between theory and evidence- experimental and neuroexperimental, and by a departure from ad hoc modelling.
Fields of science
Call for proposal
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Funding SchemeERC-AG - ERC Advanced Grant