伟易博

行为科学和政策干预交织立异团队分享会——第十四期

2023年9月26日,伟易博应用经济学系与行为科学与政策干预交织立异团队团结举行2023秋季学期应用经济学术分享会暨第二期(总第十四次)行为科学分享会。本次讲座约请到新加坡国立大学(NUS)经济学教授Lorenz G?tte,围绕“How Feedback Creates Habits: Theory and Evidence from a Field Experiment”主题睁开分享。


分享人 The Speaker

Lorenz G?tte is a professor of economics at the National University of Singapore. He completed undergraduate and graduate studies at the University of Zurich, and a post-doc at the University of California, Berkeley. Previously, G?tte was a senior economist at the Federal Reserve Bank of Boston and a professor at the University of Geneva, the University of Lausanne, and the University of Bonn. His research interests are in the field of "economics and psychology", a field that examines systematic departures from the assumptions of the standard economic model. Professor G?tte's research focuses on applications in labor economics. Current projects examine the extent and consequences of downward nominal wage rigidity, and how departures from full intertemporal maximization can impact labor supply in surprising ways. He is also interested how social identity shapes organisations, and incentives within organisations. Lorenz G?tte has published in the American Economic Review, the Review of Economic Studies, the Proceedings of the National Academy of Sciences, and Science.


分享会 The Seminar

In this project, Professor G?tte and coauthors conduct a field experiment to examine behavioral responses to real-time feedback during and after treatment, varying the duration of treatment cycles. They document a distinct asymmetry: treatment effects appear immediately upon feedback, remain stable with continued exposure, and gradually decay once feedback ends—with the decay taking longer for longer treatment durations. To investigate the behavioral mechanisms driving these dynamics, the authors extend a traditional consumption-based model of habit formation by incorporating salience and state-dependent attention. Structural estimation of the model reveals that a dynamic, attention-based mechanism most accurately predicts consumption responses to nudges, both in and out of sample. Counterfactual simulations underscore the importance of correctly identifying the underlying mechanism, highlighting significant differences in the design of effective nudge interventions depending on whether habits form through consumption or attention-based processes.





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