1. Assumption required for estimates to be BLUE

2. Hypothesis testing:

a. t- tests (both one-sided and two-sided)

b. Joint hypotheses (F-Tests, Chi-square tests, etc.)i. Exclusion restrictions

ii. Linear combinations of parameters

3. Heteroskedasticity

a. What is heteroskedasticity?

b. How heteroskedasticity occur?

c. The consequences of estimating a heteroskedastic model with OLS

d. Testsi. LaGrange Multiplier Tests (Models 1, 2, and 3)

Model 1:

Model 2:

Model 3:ii. Goldfeld-Quandt test

iii. White's teste. Corrections/Estimation procedures

i. Multiplicative:

ii. Feasible GLSModel 1:

Model 2:

Model 3:iii. White’s correction

8. Autocorrelation

a. What is it and why might it occur?

b. Consequences of ignoring serial correlation and estimating with OLSi. Model including a lagged dependent variable

ii. Model with serially correlated errors

iii. Model with both a lagged dependent variable and serial correlated errors.c. Tests for serial correlation

i. The Durbin-Watson test.

ii. Durbin's h-test.

iii. The Breusch-Godfrey test for higher order serial correlation.d. Corrections

i. Non-linear estimation

ii. The CORC procedure

9. Testing for ARCH errors

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