They could've spent some time clearing up their differences. Why exactly does Deaton believe randomizing can't account for I observed heterogeneity?
- macro bro
List vs Deaton
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List is simply a well spoken conartists. If you really want to take an economists side then listen to what Deaton has to say.
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Oh and I should warn you that a lot of these experiments are designed to give you the results you want to see (even if it doesn't show up in the paper).
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OP still to learn difference between random sampling and random allocation.
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No answer? Cmon bros, help out a bodybuilder
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natural field experiments can have full market sample and randomization of variable of interest. Deaton is going after the framed field experiment randomistas
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I agree. He should have been a car sales person.
List is simply a well spoken conartists.
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I think Deaton's main point is that in the real world, RCTs always involve attrition, nonresponse, crossover and other deviations from the ideal. There are ways to adjust for these deviations, but they are not content-free: you are still making assumptions about how the heterogeneity you observe reflects or does not the unobserved heterogeneity of the underlying population.
There's a deeper issue that I think Deaton and his wife Anne Case's paper from last year illustrates well, too, that somewhat relates to his criticism of RCTs. Sometimes, economists in particular but social scientists at large are liable to think that well-identified Local Average Treatment Effects are all that is going on in the world. But that can make you lose the forest for the trees. As their paper points out using simple observational data, there are huge increases in early mortality due to suicide, overdose, and alcoholism among non-hispanic American whites that are sufficient to drive all-cause mortality up. (The 2015 data which is now available shows that this increase has gone up still further.) You really can't get at these overall trends by simply aggregating across all the different LATEs you measure from individual quasiexperimental or experimental studies, but they're clearly important, and reflect some of the overall drivers of collective behavior.
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There will always be a place for good descriptive reg monkey work. Of all the fads that have been and gone, reg monkeying observational data for interesting patterns is still strong.
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I think Deaton's main point is that in the real world, RCTs always involve attrition, nonresponse, crossover and other deviations from the ideal. There are ways to adjust for these deviations, but they are not content-free: you are still making assumptions about how the heterogeneity you observe reflects or does not the unobserved heterogeneity of the underlying population.
There's a deeper issue that I think Deaton and his wife Anne Case's paper from last year illustrates well, too, that somewhat relates to his criticism of RCTs. Sometimes, economists in particular but social scientists at large are liable to think that well-identified Local Average Treatment Effects are all that is going on in the world. But that can make you lose the forest for the trees. As their paper points out using simple observational data, there are huge increases in early mortality due to suicide, overdose, and alcoholism among non-hispanic American whites that are sufficient to drive all-cause mortality up. (The 2015 data which is now available shows that this increase has gone up still further.) You really can't get at these overall trends by simply aggregating across all the different LATEs you measure from individual quasiexperimental or experimental studies, but they're clearly important, and reflect some of the overall drivers of collective behavior.Economist detected!
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^^^ your second point was accepted though by List himself: people often forget about the generality of the situation. Thank you for actually enriching the thread.
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I think Deaton's main point is that in the real world, RCTs always involve attrition, nonresponse, crossover and other deviations from the ideal. There are ways to adjust for these deviations, but they are not content-free: you are still making assumptions about how the heterogeneity you observe reflects or does not the unobserved heterogeneity of the underlying population.
There's a deeper issue that I think Deaton and his wife Anne Case's paper from last year illustrates well, too, that somewhat relates to his criticism of RCTs. Sometimes, economists in particular but social scientists at large are liable to think that well-identified Local Average Treatment Effects are all that is going on in the world. But that can make you lose the forest for the trees. As their paper points out using simple observational data, there are huge increases in early mortality due to suicide, overdose, and alcoholism among non-hispanic American whites that are sufficient to drive all-cause mortality up. (The 2015 data which is now available shows that this increase has gone up still further.) You really can't get at these overall trends by simply aggregating across all the different LATEs you measure from individual quasiexperimental or experimental studies, but they're clearly important, and reflect some of the overall drivers of collective behavior.Economist detected!
You are a gentlelady and a scholar.