TY  - THES
AB  - Economic experiments are prized for their high internal validity due to the randomization tech- niques they employ. However, especially in recent years, they have been criticized for their lack of external validity—the ability of their results to apply to different populations, settings, and con- texts. Despite these critiques and concerns, an economist seeking to optimally design an experiment for external validity lacks quantitative guidance, even though there is a wealth of literature on op- timal design for maximizing internal validity. This paper bridges that gap by outlining and solving a series of novel optimal design problems, providing experimental economists with the quantitative tools necessary to maximize the generalizability of their results.
AD  - University of Chicago
AU  - Heron, Connor
DA  - 2024-08
DO  - 10.6082/uchicago.13112
DO  - doi
ED  - John A. List
ED  - Kotaro Yoshida
ID  - 13112
KW  - Experimental Economics
KW  - Optimal Design
KW  - External Validity
L1  - https://knowledge.uchicago.edu/record/13112/files/Thesis_final.pdf
L2  - https://knowledge.uchicago.edu/record/13112/files/Thesis_final.pdf
L4  - https://knowledge.uchicago.edu/record/13112/files/Thesis_final.pdf
LA  - eng
LK  - https://knowledge.uchicago.edu/record/13112/files/Thesis_final.pdf
N2  - Economic experiments are prized for their high internal validity due to the randomization tech- niques they employ. However, especially in recent years, they have been criticized for their lack of external validity—the ability of their results to apply to different populations, settings, and con- texts. Despite these critiques and concerns, an economist seeking to optimally design an experiment for external validity lacks quantitative guidance, even though there is a wealth of literature on op- timal design for maximizing internal validity. This paper bridges that gap by outlining and solving a series of novel optimal design problems, providing experimental economists with the quantitative tools necessary to maximize the generalizability of their results.
PB  - University of Chicago
PY  - 2024-08
T1  - Optimal Generalization: An Optimal Experimental Design Approach to the External Validity Crisis
TI  - Optimal Generalization: An Optimal Experimental Design Approach to the External Validity Crisis
UR  - https://knowledge.uchicago.edu/record/13112/files/Thesis_final.pdf
Y1  - 2024-08
ER  -