Working Paper: NBER ID: w17957
Authors: Omar Alubaydli; John A. List
Abstract: Economists are increasingly turning to the experimental method as a means to estimate causal effects. By using randomization to identify key treatment effects, theories previously viewed as untestable are now scrutinized, efficacy of public policies are now more easily verified, and stakeholders can swiftly add empirical evidence to aid their decision-making. This study provides an overview of experimental methods in economics, with a special focus on developing an economic theory of generalizability. Given that field experiments are in their infancy, our secondary focus pertains to a discussion of the various parameters that they identify, and how they add to scientific knowledge. We conclude that until we conduct more field experiments that build a bridge between the lab and the naturally-occurring settings of interest we cannot begin to make strong conclusions empirically on the crucial question of generalizability from the lab to the field.
Keywords: Lab and Field Experiments; Generalizability
JEL Codes: C9; C91; C92; C93; D03
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| propensity score matching (C52) | valid causal inferences (C20) |
| selection bias (C24) | optimistic estimates of program efficacy (C87) |
| laboratory experiments (C91) | qualitative treatment effects (C21) |
| generalizability of experimental results (C90) | contingent on context and experimental design (C90) |
| difference-in-difference regression models (C32) | valid causal inferences (C20) |
| randomization (C90) | causal effects (C22) |
| randomization as instrumental variable (C36) | balance unobservables (D52) |
| field experiments (C93) | bridging laboratory findings and real-world applications (C91) |
| natural field experiments (C93) | elimination of selection biases (C52) |