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A year ago on Facebook, at the request of a former MSU student, I made this post. I used to say in class that econometrics is not so hard if you just master about 10 tools and apply them again and again. I decided I should put up or shut up.
#metricstotheface
#metricstotheface
I cheated by combining tools that are connected, so there are actually more than 10 ....
1. Law of Iterated Expectations, Law of Total Variance
2. Linearity of Expectations, Variance of a Sum
3. Jensen's Inequality, Chebyshev’s Inequality
4. Linear Projection and Its Properties
1. Law of Iterated Expectations, Law of Total Variance
2. Linearity of Expectations, Variance of a Sum
3. Jensen's Inequality, Chebyshev’s Inequality
4. Linear Projection and Its Properties
5. Weak Law of Large Numbers, Central Limit Theorem
6. Slutksy's Theorem, Continuous Convergence Theorem, Asymptotic Equivalence Lemma
7. Big Op, Little op, and the algebra of them.
6. Slutksy's Theorem, Continuous Convergence Theorem, Asymptotic Equivalence Lemma
7. Big Op, Little op, and the algebra of them.
8. Delta Method
9. Frisch-Waugh Partialling Out
10. For PD matrices A and B, A - B is PSD if and only if B^(-1) - A^(-1) is PSD.
The list hasn't changed in a year.
9. Frisch-Waugh Partialling Out
10. For PD matrices A and B, A - B is PSD if and only if B^(-1) - A^(-1) is PSD.
The list hasn't changed in a year.
