Locus of Control and Prosocial Behavior
We investigate how locus of control beliefs – the extent to which individuals attribute control over events in their life to themselves as opposed to outside factors – affect prosocial behavior and the private provision of public goods. We begin by developing a conceptual framework showing how locus of control beliefs serve as a weight placed on the returns from one’s own contributions (impure altruism) and others contributions (pure altruism). Using multiple data sets from Germany and the U.S., we show that individuals who relate consequences to their own behavior are more likely to contribute to climate change mitigation, to donate money and in-kind gifts to charitable causes, to share money with others, to cast a vote in parliamentary elections, and to donate blood. Our results provide comprehensive evidence that locus of control beliefs affect prosocial behavior.
We are grateful for comments and suggestions by Maja Adena, Deborah Cobb-Clark, Steffen Huck, Katrina Jessoe, Martin Kesternich, John List, Travis Lybbert, and Arne Uhlendorff as well as by participants of the Advances with Field Experiments virtual conference 2020 (AFE), the Chicago Experimental Lunch Seminar, the 25th Annual Conference of the European Association of Environmental and Resource Economists (EAERE), the 2020 Virtual Congress of the European Economic Association (EEA), the 8th Conference for Social and Economic Data (8|KSWD), the 8th Mannheim Energy Conference, the 4th Workshop on Recent Advances in the Economics of Philanthropy, the 1st RWI Empirical Environmental Economics Workshop (RWI EEEW), and the 24th Spring Meeting of Young Economists (SMYE). Furthermore, we thank Sven Hansteen and Johanna Meier for excellent research assistance. We gratefully acknowledge financial support by the German Federal Ministry of Education and Research (BMBF) within the framework program “Economics of Climate Change” under grant 01LA1113A and by the Collaborative Research Center “Statistical Modeling of Nonlinear Dynamic Processes” (SFB 823) of the German Research Foundation (DFG), within the framework of Project A3, “Dynamic Technology Modeling”. We would also like to acknowledge financial support from the National Science Foundation under grant number SES-1658743. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.