by What can RCTs tell us? We seek to promote an approach to RCTs that is tentative in its claims and that avoids simplistic generalisations about causality and replaces these with more nuanced and grounded accounts that acknowledge uncertainty, plausibility and statistical probability … Whilst promoting the use of RCTs in education we also need to be acutely aware of their limitations … Whilst the strength of an RCT rests on strong internal validity, the Achilles heel of the RCT is external validity … Within education and the social sciences a range of cultural conditions is likely to influence the external validity of trial results across different contexts. It is precisely for this reason that qualitative components of an evaluation, and particularly the
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What can RCTs tell us?
We seek to promote an approach to RCTs that is tentative in its claims and that avoids simplistic generalisations about causality and replaces these with more nuanced and grounded accounts that acknowledge uncertainty, plausibility and statistical probability …
Whilst promoting the use of RCTs in education we also need to be acutely aware of their limitations … Whilst the strength of an RCT rests on strong internal validity, the Achilles heel of the RCT is external validity … Within education and the social sciences a range of cultural conditions is likely to influence the external validity of trial results across different contexts. It is precisely for this reason that qualitative components of an evaluation, and particularly the development of plausible accounts of generative mechanisms are so important …
Highly recommended reading.
Nowadays it is widely believed among mainstream economists that the scientific value of randomisation — contrary to other methods — is totally uncontroversial and that randomised experiments are free from bias. When looked at carefully, however, there are in fact few real reasons to share this optimism on the alleged ’experimental turn’ in economics. Strictly seen, randomisation does not guarantee anything.
‘Ideally controlled experiments’ tell us with certainty what causes what effects — but only given the right ‘closures.’ Making appropriate extrapolations from (ideal, accidental, natural or quasi) experiments to different settings, populations or target systems, is not easy. Causes deduced in an experimental setting still have to show that they come with an export-warrant to their target populations.
The almost religious belief with which its propagators — like last year’s ‘Nobel prize’ winners Duflo, Banerjee and Kremer — portray it, cannot hide the fact that RCTs cannot be taken for granted to give generalisable results. That something works somewhere is no warranty for us to believe it to work for us here or even that it works generally.
The present RCT idolatry is dangerous. Believing there is only one really good evidence-based method on the market — and that randomisation is the only way to achieve scientific validity — blinds people to searching for and using other methods that in many contexts are better. RCTs are simply not the best method for all questions and in all circumstances. Insisting on using only one tool often means using the wrong tool.
‘Nobel prize’ winners like Duflo et consortes think that economics should be based on evidence from randomised experiments and field studies. They want to give up on ‘big ideas’ like political economy and institutional reform and instead go for solving more manageable problems the way plumbers do. But that modern time ‘marginalist’ approach sure can’t be the right way to move economics forward and make it a relevant and realist science. A plumber can fix minor leaks in your system, but if the whole system is rotten, something more than good old fashion plumbing is needed. The big social and economic problems we face today is not going to be solved by plumbers performing RCTs.