Rules for Relevance: An Agenda for Policy-Relevant Behavioral Research

Transcription

1 Rules for Relevance: An Agenda for Policy-Relevant Behavioral Research Proposed Session for the 10 th Triennial Choice Symposium Co-Chairs: Oleg Urminsky University of Chicago Booth School of Business Katherine Milkman Wharton School of Business University of Pennsylvania September 15, 2015

2 Session Summary In recent years, behavioral science approaches, including nudges and choice architecture (Thaler and Sunstein 2008, Johnson et al 2012), have become increasingly prominent as means through which to improve decision-making and achieve policy objectives, often at a relatively low cost. Findings in behavioral economics and psychology have informed effective policy interventions, changing people s retirement savings, energy consumption, vaccination and food choices (Larrick and Soll 2008; Long et al 2015, Milkman et al 2011, Shankar 2015, Thaler and Benartizi 2004). Despite promising developments, the use of behavioral science in policy is often ad hoc, and policy-setting often ignores behavioral science evidence regarding policy effectiveness (Fox and Sitkin 2015). As a result, well-intentioned policies may be introduced untested and without taking into account prior research. Academic research that is valued (and sometimes funded) at least in part for the potential to improve policy outcomes may remain unleveraged. Policy makers who do try to engage with behavioral research can find it difficult to bridge the gap between research findings and practical implications. This stems from multiple structural factors in the way behavioral research is typically conducted and evaluated (Cialdini 2015, Bryan 2015). Primary among these is the common view that questions that arise in implementation are applied and of secondary value, and that can prioritize introducing preliminary evidence for new theories over theory refinement and strong tests of the theory. As a result, behavioral research often focuses primarily on a single theory in isolation and tests policy implications as a secondary goal, with little research taking a cross-theory approach to a single underlying question. Policy makers often need more information than the literature provides about factors such as implementation-relevant moderators, replicability and relative effect sizes. This session will focus on defining solutions and strategies for academic researchers looking to bridge these gaps by doing rigorous theoretical scholarship while remaining policy relevant. The session will review participants research as the basis to explore issues including generalizability and representativeness (Yeager et al 2015), effect magnitude, robustness, implementation-relevant moderators, individual differences, attentional and involvement requirements, net dynamic effects (Goswami and Urminsky 2015), downstream or unanticipated consequences (Allcott & Kessler 2015; Chapman et al 2015), and identifying and prioritizing research questions (Brownwell & Roberto 2015). We will explore when it is that a welldeveloped psychological theory should be able to answer these questions, and the potential for "policy-ready" work in behavioral science to also yield richer theory.

3 Planned Attendees: Hunt Allcott**, New York University, Economics (energy consumption decisions, welfare analysis) Christopher Bryan**, University of Chicago Booth School of Business, Social Psychology (field research on identity and motivation) Heather Caruso**, University of Chicago Booth School of Business, Director of the Center for Decision Research (facilitating and structuring collaboration between academic researchers and practitioners and policy analysts) Gretchen Chapman**, Rutgers University, Cognitive Psychology (field research on behavioral interventions in health settings, unintended consequences of nudges) Indranil Goswami**, University of Chicago Booth School of Business / University of Buffalo, Marketing (financial decision making, communicating financial information) igoswami@chicagobooth.edu Alex Imas**, Carnegie Mellon University Social and Decision Sciences, Economics (pro-social incentives, dynamic decision-making) aimas@andrew.cmu.edu / alex.oleg.imas@gmail.com Minah Jung**, New York University, Stern School of Business, Marketing (pro-social incentives, behavioral field research) minah.h.jung@gmail.com Ariel Kalil**, University of Chicago Harris School of Public Policy, Developmental Psychology (educational interventions, effect of intertemporal preferences on intervention effectiveness) akalil@uchicago.edu Jennifer Kurkoski*, People Innovation Lab, Google (large-scale private-sector field testing and application of behavioral research to corporate policy) kurkoski@google.com Katherine Milkman**, University of Pennsylvania, Management and Health Policy kmilkman@wharton.upenn.edu Christina Roberto**, University of Pennsylvania, Perelman School of Medicine (nutrition and obesity information provision and interventions, practitioner collaboration) croberto@mail.med.upenn.edu Heather Schoefield**, University of Pennsylvania Perelman School of Medicine and Wharton Business School, Economics (effects of malnutrition on cognitive & financial outcomes) heather.schofield@gmail.com Deborah Small**, University of Pennsylvania Wharton School, Marketing and Psychology (factors influencing the effectiveness of pro-social incentives) deborahs@wharton.upenn.edu Jack Soll**, Duke University Fuqua School of Business, Management (accurate information provision, biases in judgment) jsoll@duke.edu William Tucker*, White House Social and Behavioral Sciences Team (large-scale public-sector field testing and application of behavioral research to government policy) william.tucker@gsa.gov

4 Oleg Urminsky**, University of Chicago Booth School of Business, Psychometrics and Marketing (intertemporal preference & motivation, incentives effects over time, psychological effects of information) David Yeager**, University of Texas Austin, Social Psychology (mindsets and self-beliefs, long-term policy effects, large-scale field testing in education) ** - Firm commitment * - Planning to attend but not yet firm commitment

5 References Allcott, H. and J. Kessler (2015), The Welfare Effects of Nudges, Working paper Brownell, KD. & Roberto, C.A. (2015). Strategic science with policy impact. The Lancet. Bryan, Christopher (2015). A Case for a Return to Lewinian Field Research, Working paper Chapman, G.B., Li, M., Leventhal, H., & Leventhal, E.A. (2015). Do defaults promote, or simply displace vaccination? Cialdini, R. B. (2009). We have to break up. Perspectives on Psychological Science, 4(1), 5-6. Fox, C. R., & Sitkin, S. B. (2015). Bridging the divide between behavioral science and policy. Behavioral Science & Policy, 1, Goswami, Indranil and Oleg Urminsky (2015). The Nature and Extent of Post-Reward Crowding-Out: The 'Effort Balancing' Account, Working paper Johnson, E. J., Dellaert, B. G. C., Fox, C., Goldstein, D. G., Haubl, G., Larrick, R. P., et al. (2012). Beyond nudges: Tools of a choice architecture. Marketing Letters, 23(2), Larrick, R. P., & Soll, J. B. (2008). The MPG illusion. Science, 320 (5883),1593. Long, M. W., D. K. Tobias, A. L. Cradock, H. Batchelder, S. L. Gortmaker (2015. Systematic Review and Meta-analysis of the Impact of Restaurant Menu Calorie Labeling, American Journal of Public Health, 105(5), e11-e24. Milkman, K.L., J. Beshears, J.J. Choi, D. Laibson, and B.C. Madrian (2011). Using Implementation Intentions Prompts to Enhance Influenza Vaccination Rates. Proceedings of the National Academy of Sciences, Vol. 108, Shankar, Maya (2015) Using behavioral science insights to make government more effective, simple and more people friendly, WhiteHouse.Gov Thaler, R. H., & Benartzi, S. (2004). Save more tomorrow : Using behavioral economics to increase employee saving. Journal of political Economy, 112(S1), S164-S187. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions about Health, Wealth, and Happiness. Yale University Press. Yeager, David S., Gregory M. Walton and Elizabeth Tipton (2015). A Framework for Generalizable Social-Psychological Intervention, Working paper