Unimodal intertemporal decisions involve comparing options of the same type (e.g., apples now versus apples later), and cross-modal decisions involve comparing options of different types (e.g., a car now versus a vacation later). As we show, existing models of intertemporal choice do not allow time preference to depend on whether the comparisons to be made are unimodal or cross-modal. We test this restriction in an experiment using the delayed compensation method, a new extension of the standard method of eliciting intertemporal preferences that allows for assessment of time preference for nonmonetary and discrete outcomes, as well as for both cross-modal and unimodal comparisons. Participants were much more averse to delay for unimodal than cross-modal decisions. We provide two potential explanations for this effect: one drawing on multiattribute choice, the other drawing on construal-level theory.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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