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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& #39;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& #39;s Inequality, Chebyshev’s Inequality
4. Linear Projection and Its Properties
5. Weak Law of Large Numbers, Central Limit Theorem
6. Slutksy& #39;s Theorem, Continuous Convergence Theorem, Asymptotic Equivalence Lemma
7. Big Op, Little op, and the algebra of them.
6. Slutksy& #39;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& #39;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& #39;t changed in a year.
