Krugman’s modeling flim flam Paul Krugman has a piece up on his blog this week arguing that the ‘discipline of modeling’ is a sine qua non for tackling politically and emotionally charged economic issues: You might say that the way to go about research is to approach issues with a pure heart and mind: seek the truth, and derive any policy conclusions afterwards. But that, I suspect, is rarely how things work. After all, the reason you study an issue at all is usually that you care about it, that there’s something you want to achieve or see happen. Motivation is always there; the trick is to do all you can to avoid motivated reasoning that validates what you want to hear. In my experience, modeling is a helpful tool (among others) in avoiding that trap, in being self-aware when you’re starting to let your desired conclusions dictate your analysis. Why? Because when you try to write down a model, it often seems to lead some place you weren’t expecting or wanting to go. And if you catch yourself fiddling with the model to get something else out of it, that should set off a little alarm in your brain.
Topics:
Lars Pålsson Syll considers the following as important: Economics
This could be interesting, too:
Merijn T. Knibbe writes ´Extra Unordinarily Persistent Large Otput Gaps´ (EU-PLOGs)
Peter Radford writes The Geology of Economics?
Lars Pålsson Syll writes Årets ‘Nobelpris’ i ekonomi — gammal skåpmat!
Lars Pålsson Syll writes Germany’s ‘debt brake’ — a ridiculously bad idea
Krugman’s modeling flim flam
Paul Krugman has a piece up on his blog this week arguing that the ‘discipline of modeling’ is a sine qua non for tackling politically and emotionally charged economic issues:
You might say that the way to go about research is to approach issues with a pure heart and mind: seek the truth, and derive any policy conclusions afterwards. But that, I suspect, is rarely how things work. After all, the reason you study an issue at all is usually that you care about it, that there’s something you want to achieve or see happen. Motivation is always there; the trick is to do all you can to avoid motivated reasoning that validates what you want to hear.
In my experience, modeling is a helpful tool (among others) in avoiding that trap, in being self-aware when you’re starting to let your desired conclusions dictate your analysis. Why? Because when you try to write down a model, it often seems to lead some place you weren’t expecting or wanting to go. And if you catch yourself fiddling with the model to get something else out of it, that should set off a little alarm in your brain.
Hmm …
So when Krugman and other ‘modern’ mainstream economists use their models — standardly assuming rational expectations, Walrasian market clearing, unique equilibria, time invariance, linear separability and homogeneity of both inputs/outputs and technology, infinitely lived intertemporally optimizing representative agents with homothetic and identical preferences, etc. — and standardly ignoring complexity, diversity, uncertainty, coordination problems, non-market clearing prices, real aggregation problems, emergence, expectations formation, etc — we are supposed to believe that this somehow helps them ‘to avoid motivated reasoning that validates what you want to hear.’
Yours truly is, however, far from convinced. The alarm that sets off in my brain is that this, rather than being helpful for understanding real world economic issues, sounds more like an ill-advised plaidoyer for voluntarily taking on a methodological straight-jacket of unsubstantiated and known to be false assumptions.