However, there are others as well who have been questioning state of economics who are not as well known. Here is a 2014 paper by Paul Pfleiderer of Stanford (what is it with Profs named Paul!?) who says we have a new problem. There are certain models which are full of assumptions yet are played at a policy/real world level. These models obviously don’s meet the filter of real world once assumptions are done away with. Still they remain the main ideas.
He calls such models as chameleons:
In this essay I discuss how theoretical models in finance and economics are used in ways that make them “chameleons” and how chameleons devalue the intellectual currency and muddy policy debates. A model becomes a chameleon when it is built on assumptions with dubious connections to the real world but nevertheless has conclusions that are uncritically (or not critically enough) applied to understanding our economy. I discuss how chameleons are created and nurtured by the mistaken notion that one should not judge a model by its assumptions, by the unfounded argument that models should have equal standing until definitive empirical tests are conducted, and by misplaced appeals to “as-if” arguments, mathematical elegance, subtlety, references to assumptions that are “standard in the literature,” and the need for tractability.
Just like other Paul, Prof Pfleiderer takes on with specific examples:
In April 2012 Harry DeAngelo and René Stulz circulated a paper entitled “Why High Leverage is Optimal for Banks.” The title of the paper is important here: it strongly suggests that the authors are claiming something about actual banks in the real world. In the introduction to this paper the authors explain what their model is designed to do:
To establish that high bank leverage is the natural (distortion-free) result of intermediation focused on liquid-claim production, the model rules out agency problems, deposit insurance, taxes, and all other distortionary factors. By positing these idealized conditions, the model obviously ignores some important determinants of bank capital structure in the real world. However, in contrast to the MM framework – and generalizations that include only leverage-related distortions – it allows a meaningful role for banks as producers of liquidity and shows clearly that, if one extends the MM model to take that role into account, it is optimal for banks to have high leverage. [emphasis added]
Their model, in other words, is designed to show that if we rule out many important things and just focus on one factor alone, we obtain the particular result that banks should be highly leveraged. This argument is for all intents and purpose analogous to the argument made in another paper entitled “Why High Alcohol Consumption is Optimal for Humans” by Bacardi and Mondavi.5 In the introduction to their paper Bacardi and Mondavi explain what their model does:
To establish that high intake of alcohol is the natural (distortion free) result of human liquid-drink consumption, the model rules out liver disease, DUIs, health benefits, spousal abuse, job loss and all other distortionary factors. By positing these idealized conditions, the model obviously ignores some important determinants of human alcohol consumption in the real world. However, in contrast to the alcohol neutral framework – and generalizations that include only overconsumption related distortions – it allows a meaningful role for humans as producers of that pleasant “buzz” one gets by consuming alcohol, and shows clearly that if one extends the alcohol neutral model to take that role into account, it is optimal for humans to be drinking all of their waking hours. [emphasis added]