Deck 15: Advanced Panel Data

Question 1

Autocorrelation causes bias in a model with fixed effects.

Answer 1

True

Question 2

Autocorrelation causes bias in a model without fixed effects.

Answer 2

False

Question 3

A biased coefficient is always worse than an unbiased coefficient.

Answer 3

False

Question 4

Random effects models are biased if the random effects error term is correlated with X.

Question 5

Random effects models are appropriate only when their coefficients are similar to coefficients produced by fixed effects models.

Question 6

Which of the following is a proper procedure for testing for autocorrelation in a panel data model without a lagged dependent variable?

A) Run a model that does not address autocorrelation and test for autocorrelated errors based on the residuals from that model.
B) Run a $\rho$ -transformed model and test for autocorrelated errors based on the residuals from that model.
C) Assess whether there is a different intercept for each unit.
D) Run a probit or logit model and test for autocorrelated errors based on the residuals from that model.

Question 7

Under what conditions is the bias caused by autocorrelaed errors in a fixed effect model the most severe?

A) We have many observations for each unit.
B) We have few observations for each unit.
C) We have many observations for each time period.
D) We have few observations for each time period.

Question 8

Suppose that we have the following results from a model with lagged dependent variable
Y_it = 0.9Y_i,1t-1+ 2X_1it
Which of the following is most accurate?

A) The short-term effect of a one unit change in X will be a 2.9 unit change in Y.
B) The long-term effect of a one unit change in X will be a 20 unit change in Y.
C) The long-term effect of a one unit change in X will be a 4 unit change in Y.
D) Y will keep getting smaller and smaller over time.

Question 9

Suppose that we are comparing results in the following two models
Model A: Y_it = 0.9Y_i,t-1 + 2X_1it
Model A: Y_it = 0.8Y_i,t-1 + 2X_1it
Which of the following is true?

A) The long-term effect of a one unit change in X will be 10 times bigger in Model A than in Model
B) The long-term effect of a one unit change in X will be 10 percent bigger in Model A than in Model
C) The short-term effect of a one unit change in X will be bigger in Model A than in Model
D) The short-term effect of a one unit change in X will be smaller in Model A than in Model

Question 10

What usually happens to autocorrelation when we add a lagged dependent variable to the model?

A) Autocorrelation gets bigger.
B) Autocorrelation gets smaller.
C) Autocorrelation stays the same.
D) We cannot test for autocorrelation when a lagged dependent variable is included in the model.

Question 11

What usually happens to autocorrelation when we add a lagged dependent variable to the model?

A) Autocorrelation gets bigger.
B) Autocorrelation gets smaller.
C) Autocorrelation stays the same.
D) We cannot test for autocorrelation when a lagged dependent variable is included in the model.

Question 12

OLS coefficients are biased when there is a lagged dependent variable and fixed effects in the same model. Which of the following statements is most accurate about using OLS when there is a lagged dependent variable and fixed effects in the same model?

A) We should never use OLS in this situation.
B) Instrumental variables are easier to use OLS in this situation.
C) OLS can produce coefficient estimates that are biased, but still on average closer to the true values in this situation.
D) OLS performs worse in this situation when we have many observations for each unit.

Question 13

What factor is associated with lower bias in a model with a lagged dependent variable and fixed effects?

A) Large number of observations for each period.
B) Large number of time periods.
C) A large coefficient on the lagged dependent variable.
D) Using multiple lags (e.g., the dependent variable from the previous period and the period before that).

Question 14

Describe the potential trade-off between bias and accuracy using an example of an estimator that is biased, but accurate and one that is unbiased, but inaccurate.

Question 15

Describe when it is appropriate to use random effects models.

Question 16

Explain why a model with a lagged dependent variable and fixed effects will be biased.

Question 17

Explain why it is important to test for autocorrelation when using a model with a lagged dependent variable and no fixed effects.