by ‘Rigorous’ evidence — often worse than useless So far we have shown that for two prominent questions in the economics of education, experimental and non-experimental estimates appear to be in tension. Furthermore, experimental results across different contexts are often in tension with each other. The first tension presents policymakers with a trade-off between the internal validity of estimates from the “wrong” context, and the greater external validity of observational data analysis from the “right” context. The second tension, between equally well-identifed results across contexts, suggests that the resolution of this trade-off is not trivial. There appears to be genuine heterogeneity in the true causal parameter across contexts. These findings imply that the common practice of ranking evidence by its level of “rigor”, without respect to context, may produce misleading policy recommendations … Despite the fact that we have chosen to focus on extremely well-researched literatures, it is plausible that a development practitioner confronting questions related to class size, private schooling, or the labor-market returns to education would confront a dearth of well-identified, experimental or quasi-experimental evidence from the country or context in which they are working.
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Lars Pålsson Syll considers the following as important: Economics
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‘Rigorous’ evidence — often worse than useless
So far we have shown that for two prominent questions in the economics of education, experimental and non-experimental estimates appear to be in tension. Furthermore, experimental results across different contexts are often in tension with each other. The first tension presents policymakers with a trade-off between the internal validity of estimates from the “wrong” context, and the greater external validity of observational data analysis from the “right” context. The second tension, between equally well-identifed results across contexts, suggests that the resolution of this trade-off is not trivial. There appears to be genuine heterogeneity in the true causal parameter across contexts.
These findings imply that the common practice of ranking evidence by its level of “rigor”,
without respect to context, may produce misleading policy recommendations …Despite the fact that we have chosen to focus on extremely well-researched literatures,
it is plausible that a development practitioner confronting questions related to class size, private schooling, or the labor-market returns to education would confront a dearth of well-identified, experimental or quasi-experimental evidence from the country or context in which they are working. They would instead be forced to choose between less internally valid OLS estimates, and more internally valid experimental estimates produced in a very different setting. For all five of the examples explored here, the literature provides a compelling case that policymakers interested in minimizing the error of their parameter estimates would do well to prioritize careful thinking about local evidence over rigorously-estimated causal effects from the wrong context.
