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Field Experiments: Here Today Gone Tomorrow?

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  • John List

Abstract

Once believed to be an impossibility, field experiments in economics now occupy a central place in the empiricist's quiver. In the past few decades alone field experiments have taken on much greater import in academe, across organizations, as well as for policymakers. But is this emergence simply a fad that will soon return field experiments to obscurity? I argue in this article that there is something fundamental about the emergence of field experiments, as controlling the assignment mechanism in the field provides unparalleled power to both understand the "effects of causes" and the "causes of effects." This knowledge generation then begins to uncover the generalizability and scalability of knowledge. Quite the opposite of a withering tool that will be gone tomorrow, I urge economists to "double down" on this comparative advantage and in doing so I provide four methodological paths which I hope will cement the promise and growth of field experiments in the social sciences.

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  • John List, 2024. "Field Experiments: Here Today Gone Tomorrow?," Natural Field Experiments 00788, The Field Experiments Website.
  • Handle: RePEc:feb:natura:00788
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    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    2. John A. List, 2004. "The Nature and Extent of Discrimination in the Marketplace: Evidence from the Field," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 49-89.
    3. Levitt, Steven D. & List, John A., 2009. "Field experiments in economics: The past, the present, and the future," European Economic Review, Elsevier, vol. 53(1), pages 1-18, January.
    4. Holz, Justin E. & List, John A. & Zentner, Alejandro & Cardoza, Marvin & Zentner, Joaquin E., 2023. "The $100 million nudge: Increasing tax compliance of firms using a natural field experiment," Journal of Public Economics, Elsevier, vol. 218(C).
    5. repec:feb:artefa:0087 is not listed on IDEAS
    6. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    7. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, September.
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