TheDeadFlagBlues
Junior Chimp
Posts: 5,987
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« Reply #1 on: July 31, 2016, 02:10:56 AM » |
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« Edited: July 31, 2016, 02:18:59 AM by TheDeadFlagBlues »
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To my knowledge, it's nearly impossible to be a proficient statistician/econometrician without understanding the theoretical basis of statistics (probability theory and mathematical statistics) and this requires calculus. Even one was to advance the critique of economics, a critique that I'm sympathetic towards, that it's insufficiently empirical and overly obsessed with the perfect forms of mathematical models that rarely approximate reality, there could be no claim that calculus isn't...integral to economic science.
I still basically agree with ag though. Most economic practices and outcomes are quantifiable/measurable. As such, they can be modeled easily using math and, for this reason, models have value because they give us a depiction of a hypothetical reality that's easy to understand and reason with. The problems of modeling occur when economists become overly infatuated with particular models, mistaking them for reality, or attempt to apply models to situations that do not call for those models. As an example, a simple model of the labor market might be not be an appropriate tool for understanding the employment effects of a minimum wage increase if one believes that firms have some degree of monopsony power. Do this mean that the simple model of the labor market is wrong? No, it simply means that it isn't an explanatory model in particular situations where its assumptions do not apply. The arguments that underlie this post are detailed quite nicely in a book written by Dani Rodrik (Economics Rules) that I'd recommend. Because I'm an undergraduate, I wouldn't take my post that seriously though...
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