ECONOMETRICS
These slides were originally for posts in the facebook group Quick concepts for econometrics which is still somewhat active. The creation of each post required at best a two step process and consequently the “postcards” could not be produced directly on the facebook page. I may still from time to time produce such cards for the facebook wall an may even produce similar cards for other subjects (which I have not done yet). The consequence of this is that posts (down the left hand menu) and pages (across the top menu) for econometrics are mirrored and largely the same. Comments and contributions are welcome on the posts but the pages are frozen so to speak.
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GLS Sampling Properties
Beta hat distribution without error normality assumption
OLS Consistency: Asymptotic Stochastic X
OLS Consistency: Asymptotic Stochastic X
Stochastic Convergence
Convergence Theorems
Convergence: Law of Large Numbers & Central Limit Theorems.
OLS Distributional Assumptions
This is key to finding sigma hat the estimated variance.
Gauss Markov Theorem Proof part3-1
Gauss Markov Theorem Proof part3-2
OLS estimators are of minimum variance “Best” amongst linear unbiased estimators
How well does the data fit?
OLS Sampling Properties
OLS Assumptions
Least Squares Coefficient Vector
The orthogonal method of finding Beta hat the coefficient vector of regression coefficients
Finding Beta hat the coefficient vector of regression coefficients
Some vector basics
Linear Regression Equation
Law of Large Numbers
Biased Estimators
Idempotent Projection Matrix.
Idempotent Matrices