Toward an Understanding of Corporate Social Responsibility: Theory and Field Experimental Evidence

Daniel Hedblom, Brent R. Hickman, John A. List

NBER Working Paper No. 26222
Issued in September 2019

---- Acknowledgments ----

We thank Stephane Bonhomme, Aaron Bodoh-Creed, Steven Levitt, Emir Kamenica, James McKinnon, Ivan Canay, Vadim Marmer, and Christopher Cotton for helpful comments. Special thanks to Joseph Seidel for excellent research assistance. The authors also wish to thank seminar participants at The U. of Chicago, U. of Wisconsin-Madison, UCL, CREST, Queen’s U., the Economic Science Association North American meeting, Econometric Society North American Summer Meetings, the U. of Chicago Advances with Field Experiments conference, Penn State, Carnegie Mellon, and the Olin Business School at Washington U in St. Louis. We also acknowledge Danielle Hickman, Leah Vanevenhoven, and Bloom Bakeshop for insightful conversations on the interpretation of our results. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

DISCLOSURE STATEMENT: As per NBER's submission requirements, we wish to disclose the following information:

1) This research was executed entirely with internal funding provided by the University if Chicago and did not use outside sources of monetary support.

2) Neither Hedblom, nor Hickman, nor List received financial support from any interested parties in the execution of this research.

3) List held a position as Chief Economist at Uber Technologies during the data collection phase of this research. As explained in Section 2 of the current manuscript, Hedblom, Hickman, and List incorporated a firm, HHL Solutions, LLC, a non-profit consultancy, as part of the experimental research design. The two clients served by HHL Solutions, LLC included Uber Technologies, and the Becker-Friedman Institute for Research in Economics at the University of Chicago. Specifically, these two entities were the intended recipients of the data products resulting from test subjects' real-effort work producing data entry services. List did not receive any financial compensation specific to this research from Uber Technologies.

4) No outside parties had rights to review this manuscript prior to its circulation.

5) This research was conducted under Institutional Review Board Approval IRB15-1094 at the University of Chicago.

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