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As a direct criticism, the choice of the Normal distribution adds nothing to the model other than acting as a cover for the author's choice of point estimates. I believe you would get the same results independent of the distribution. Choosing a Normal distribution serves only to create an apparent range of results that are weighted towards the author's preferred choices of values.

Peer-reviewed economic models would have to justify their model assumptions in a more robust way, including empirical data where appropriate. I'm not an expert but I expect this is a good place to start: http://www.journals.elsevier.com/economic-modelling/

All models use simplified assumptions and questionably appropriate techniques, I agree - that is practically the definition of 'model'. However, a useful model should justify those assumptions and techniques using current research-level knowledge, and/or show how the model applies successfully to reality.

I see this model to be as useful to economic discussion as saying "the world is flat, plus or minus 5 degrees". It ignores all current work in the field.



If you're expecting research-level detail in a blog post from someone who is admittedly not an economist, your expectations are too high. The post was meant to present a simple Monte Carlo simulation in Python using a current topic as its subject. He isn't writing a NYT Op-Ed citing his results as evidence that BJ > BI based on sophisticated modeling techniques.




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