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The households supply labor inelastically and its a tax on labor income
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If a continuum of identical households shares the profits of a price-taking representative firm does it really matter who bears the burden of a tax change?
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I was reading a finance book a couple weeks ago and they spent like a chapter and a half talking about martingales and subsequently dedicated 40ish pages to basic probability (like defining expectations)
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Like if you’ve already introduced Blackwell contraction mapping thm you prolly don’t need to define metrics
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It’s always funny to me when lecture notes/textbooks define something that should be instant recall to the reader
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I am cracking Sargent/Ljungqvist for the first time in 8 months so actually I might be
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There are two kinds of people who study for a macro comp with SLP and I am neither of them
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Readers with prior knowledge can skip this section if they want to double their reading time by trying to figure out my notation
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Or like for Spotify with my morning commute -- like play the quick NPR news update, a few songs, go into a podcast. . I think that'd be an easier one cause you're only dealing with the Spotify API
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Has anyone built a scheduler for OTT streaming services? I'd like to download an app, name some shows I like and give it access to my accounts and get a TV schedule for the evening
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anyway, I love it when professors assign problem sets that require implementing something. Lots of that here, with a focus on simulation which seems superior from a pedagogical perspective to me
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people in other disciplines actively contribute to both of these fields! its not just econometricians or machine learning researchers. if the results are good and the methods fill gaps then they should be accepted, and sometimes it seems like we just wanna criticize what's trendy
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Other disciplines have found the techniques developed by econometricians useful, and others view the success of econometrics as yet another example of economic imperialism. . . I think that the criticisms of ML tend to be rooted in folks viewing it as imperialism
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That or 'it's just statistics.' Both seem assessments seem unfair to me. ML is to computer science and electrical engineering as econometrics is to economics. Its a set of methods developed in the domain and by statisticians generally thinking about domain-specific problems
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I only mention the coverage of neural networks because I think that that's sort of the caricature of machine learning that a lot of people have in their heads when they talk about the subject
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