# Basic OLS and hypothesis testing Flashcards Preview

## Econometrics > Basic OLS and hypothesis testing > Flashcards

Flashcards in Basic OLS and hypothesis testing Deck (10)
1
Q

What are the four OLS assumptions?

A

1) Xi,…Xn are independent and identically distributed draws from an underlying distribution, X
2) E[ui | X] = 0. Error terms have mean zero
3) V[ui] = σ2. Variance of the error terms is constant across observations
4) Corr [ui, uj] = 0 . Error terms are uncorrelated across observations

2
Q

What is the formula for the OLS coefficient estimator?

A
3
Q

What are two key weaknesses of the OLS model?

A

1) Basic OLS is very sensitive to outliers, so you should check you results and data graphically
2) If you have only 1 independent variable, the likelihood of omitted variable bias is very high

4
Q

What is the efficiency of OLS?

A

Under Gauss-Markov assumptions, the OLS estimator beta is the best linear unbiased estimator (BLUE).

5
Q

When do you use weighted least squares?

A

When you want to weight different observations in your sample differently either because of known gheteroskedasticity of use of a complex survey with different sampling problems.

1) Xi…Xn are iid draws from an underlying distribution x
2) E[u | Xi,…Xki] = ??? error terms may vary with x
3) X1i,…Xki and Yi have finite fourth moments. No huge outlier
4) the regression of any Xk on all the other covariates has R2<1. No perfect multicollinearity

6
Q

What is the formula for weighted least squares?

A

Put a weight on the numerator and denominator of Beta one.

7
Q

Hypothesis testing: what is the formula for a one-sample Z-test for the population mean, when σ is known?

A

Z = (xbar-miu)/σ/sqrt(n) where n >30

Population σ is known

8
Q

Hypothesis testing: What is the formula for a one-sample t-test for a population mean when the population is normally distributed and σ is not known?

A

t = (Xbar-miu)/[s/srqt(n)]

9
Q

What is the formula for a two-sample Z-test for difference of population means?

A

– Two samples must be independnent, normally distributed, σx and σy are known

Z = (xbar-ybar)-D/{sqrt(σx2/n + σy2/m)

10
Q

What is the definition of “best” estimator?

A

???