Lecture 4

Question 1

Answer 1

Question 2

Answer 2

The opposite does not exist since strict implies contemporaneous.

Question 3

What are the assumptions for a multiple linear regression for time series data (with strict exogeneity)?

Answer 3

Question 4

Answer 4

Question 5

(do not show)

Answer 5

Question 6

General case of linear regression model for time series data with ‘merely’ contemporaneously exogenous regressors x_t are not unbiased, show this.

Answer 6

Question 7

When a regressor is contemporaneously exogenous, what happens to its asymptotic properties?

Answer 7

Question 8

Answer 8

Question 9

Answer 9

Question 10

Answer 10

Answer 11

Question 12

Answer 12

Question 13

What are examples of time series that are (or are not) stationary and are (or are not) covariance stationary?

Answer 13

Question 14

What is mean reversion?

Answer 14

Question 15

What is a random walk?

Answer 15

Question 16

What is the formula of a random walk?

Answer 16

Question 17

What is a difference-stationary process?

Answer 17

Question 18

Wat is a random walk with drift?

Answer 18

Question 19

Does a random walk with drift return to the trend line?

Answer 19

Not neccessarily

Question 20

What effect does β₁ have on the AR(1) model?

Answer 20

Question 21

Answer 21

Question 22

What is the efficient-market hypothesis?

Answer 22