Ch. 10 - econometrics

The notation for panel data is (Xit, Yit), i = 1, ..., n and t = 1, ..., T because

A) we take into account that the entities included in the panel change over time and are replaced by others.

B) the X's represent the observed effects and the Y the omitted fixed effects.

C) there are n entities and T time periods.

D) n has to be larger than T for the OLS estimator to exist.

C

The difference between an unbalanced and a balanced panel is that

A) you cannot have both fixed time effects and fixed entity effects regressions.

B) an unbalanced panel contains missing observations for at least one time period or one entity.

C) the impact of different regressors are roughly the same for balanced but not for unbalanced panels.

D) in the former you may not include drivers who have been drinking in the fatality rate/beer tax study.

B

The Fixed Effects regression model

A) has n different intercepts.

B) the slope coefficients are allowed to differ across entities, but the intercept is "fixed" (remains unchanged).

C) has "fixed" (repaired) the effect of heteroskedasticity.

D) in a log-log model may include logs of the binary variables, which control for the fixed effects.

A

In the Fixed Effects regression model, you should exclude one of the binary variables for the entities when an intercept is present in the equation

A) because one of the entities is always excluded.

B) because there are already too many coefficients to estimate.

C) to allow for some changes between entities to take place.

D) to avoid perfect multicollinearity.

D

In the Fixed Effects regression model, using (n - 1) binary variables for the entities, the coefficient of the binary variable indicates

A) the level of the fixed effect of the ith entity.

B) will be either 0 or 1.

C) the difference in fixed effects between the ith and the first entity.

D) the response in the dependent variable to a percentage change in the binary variable.

C

cov (uit, uis Xit, Xis = 0 for t ≠ s means that

A) there is no perfect multicollinearity in the errors.

B) division of errors by regressors in different time periods is always zero.

C) there is no correlation over time in the residuals.

D) conditional on the regressors, the errors are uncorrelated over time.

D

In the Fixed Time Effects regression model, you should exclude one of the binary variables for the time periods when an intercept is present in the equation

A) because the first time period must always excluded from your data set.

B) because there are already too many coefficients to estimate.

C) to avoid perfect multicollinearity.

D) to allow for some changes between time periods to take place.

C

If you included both time and entity fixed effects in the regression model which includes a constant, then

A) one of the explanatory variables needs to be excluded to avoid perfect multicollinearity.

B) you can use the "before and after" specification even for T > 2.

C) you must exclude one of the entity binary variables and one of the time binary variables for the OLS estimator to exist.

D) the OLS estimator no longer exists.

C

Consider estimating the effect of the beer tax on the fatality rate, using time and state fixed effect for the Northeast Region of the United States (Maine, Vermont, New Hampshire, Massachusetts, Connecticut and Rhode Island) for the period 1991-2001. If Beer Tax was the only explanatory variable, how many coefficients would you need to estimate, excluding the constant?

A) 18

B) 17

C) 7

D) 11

B

In the panel regression analysis of beer taxes on traffic deaths, the estimation period is 1982-1988 for the 48 contiguous U.S. states. To test for the significance of time fixed effects, you should calculate the F-statistic and compare it to the critical value from your Fq,∞ distribution, where q equals

A) 6.

B) 7.

C) 48.

D) 53.

A

When you add state fixed effects to a simple regression model for U.S. states over a certain time period, and the regression R2 increases significantly, then it is safe to assume that

A) the included explanatory variables, other than the state fixed effects, are unimportant.

B) state fixed effects account for a large amount of the variation in the data.

C) the coefficients on the other included explanatory variables will not change.

D) time fixed effects are unimportant.

B

Time Fixed Effects regression are useful in dealing with omitted variables

A) even if you only have a cross-section of data available.

B) if these omitted variables are constant across entities but vary over time.

C) when there are more than 100 observations.

D) if these omitted variables are constant across entities but not over time.

B

Indicate for which of the following examples you cannot use Entity and Time Fixed Effects: a regression of

A) OECD unemployment rates on unemployment insurance generosity for the period 1980-2006 (annual data).

B) the (log of) earnings on the number of years of education, using the Current Population Survey of 60,000 households for March 2006.

C) the per capita income level in Canadian Provinces on provincial population growth rates, using decade averages for 1960, 1970, and 1980.

D) the risk premium of 75 stocks on the market premium for the years 1998-2006.

B

Panel data is also called

A) longitudinal data.

B) cross-sectional data.

C) time series data.

D) experimental data.

A

In the panel regression analysis of beer taxes on traffic deaths, the estimation period is 1982-1988 for the 48 contiguous U.S. states. To test for the significance of entity fixed effects, you should calculate the F-statistic and compare it to the critical value from your Fq,∞ distribution, where q equals

A) 48.

B) 54.

C) 7.

D) 47.

D

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) allows you to look up critical values in the standard normal distribution.

C

One of the following is a regression example for which Entity and Time Fixed Effects could be used: a study of the effect of

A) minimum wages on teenage employment using annual data from the 48 contiguous states in 2006 .

B) various performance statistics on the (log of) salaries of baseball pitchers in the American League and the National League in 2005 and 2006.

C) inflation and inflationary expectations on unemployment rates in the United States, using quarterly data from 1960-2006.

D) drinking alcohol on the GPA of 150 students at your university, controlling for incoming SAT scores.

B

Consider a panel regression of unemployment rates for the G7 countries (United States, Canada, France, Germany, Italy, United Kingdom, Japan) on a set of explanatory variables for the time period 1980-2000 (annual data). If you included entity and time fixed effects, you would need to specify the following number of binary variables:

A) 21.

B) 6.

C) 28.

D) 26.

D

A pattern in the coefficients of the time fixed effects binary variables may reveal the following in a study of the determinants of state unemployment rates using panel data:

A) macroeconomic effects, which affect all states equally in a given year.

B) attitude differences towards unemployment between states.

C) there is no economic information that can be retrieved from these coefficients.

D) regional effects, which affect all states equally, as long as they are a member of that region.

A

In panel data, the regression error

A) is likely to be correlated over time within an entity

B) should be calculated taking into account heteroskedasticity but not autocorrelation

C) only exists for the case of T > 2

D) fits all of the three descriptions above

A

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

A