MCQ (Panel data)
1. What are panel data?
a.
b.
c.
d.
Data containing units measured at different time points
Data where each unit is measured at more than one time point
Data containing skewed variable distributions
Data measured at one point in time
2. What does it mean when we say that our panel is balanced?
a.
b.
c.
d.
When we have more time periods than units
When we have a large sample of units
When we have an equal number of time periods per unit
When we have an unequal number of time periods per unit
3. The main advantage of using panel data over cross sectional data is that it
a. gives you more observations.
b. allows you to analyze behavior across time but not across entities.
c. allows you to control for some types of omitted variables without actually observing
them.
d. implies that inference based on the standard normal distribution is more appropriate.
4. What does lagging variables mean?
a.
b.
c.
d.
That we use previous values of a variable
That we use future values of a variable
That we set all values at its mean across time
That we log transform the variable
5. Which model takes into account both the time-varying independent variables, the timeinvariant independent variables and the unmeasured time-invariant variables?
a.
b.
c.
d.
Pooled OLS
Between effects
Fixed effects
Random effects
6. Working with short panels (𝑁 ≫ 𝑇) is similar to
a.
b.
c.
d.
Cross section data analysis
Time series analysis
Pooled regression analysis
Fixed effect analysis
7. Working with short panels (𝑇 ≫ 𝑁) is similar to
e.
f.
g.
h.
Cross section data analysis
Time series analysis
Pooled regression analysis
Fixed effect analysis
8. How is the heteroscedastic assumption captured in a pooled regression model?
a. By running an ordinary least squares regression.
b. By running an ordinary least squares regression with robust standard errors.
c. By taking the mean of each variable for each unit across time, and running a regression
on the collapsed dataset of means.
d. By way of including unit dummy variables.
9. How is the fixed effect model estimated?
e. By running an ordinary least squares regression.
f. By running an ordinary least squares regression with robust standard errors.
g. By taking the mean of each variable for each unit across time, and running a regression
on the collapsed dataset of means.
h. By way of including unit dummy variables.
10. If 𝑋𝑖𝑡 is correlated with 𝑋𝑖𝑠 for different values of 𝑠 and 𝑡, then
a. 𝑋𝑖𝑡 is said to be autocorrelated
b. the OLS estimator cannot be computed
c. statistical inference cannot proceed in a standard way even if clustered standard errors
are used
d. this is not of practical importance since these correlations are typically weak in
applications