Question 1

It is advisable to use clustered standard errors in panel regressions because

Accepted Answer

A) without clustered standard errors,the OLS estimator is biased 
B) hypothesis testing can proceed in a standard way even if there are few entities (n is small) 
C) they are easier to calculate than homoskedasticity-only standard errors 
D) the fixed effects estimator is asymptotically normally distributed when n is large 
A) without clustered standard errors,the OLS estimator is biased 
B) hypothesis testing can proceed in a standard way even if there are few entities (n is small) 
C) they are easier to calculate than homoskedasticity-only standard errors 
D) the fixed effects estimator is asymptotically normally distributed when n is large

Question 2

Panel data is also called

Accepted Answer

A) longitudinal data. 
B) cross-sectional data. 
C) time series data. 
D) experimental data. 
A) longitudinal data. 
B) cross-sectional data. 
C) time series data. 
D) experimental data.

Question 3

The Fixed Effects regression model

Accepted Answer

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) 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.

Question 4

A study attempts to investigate the role of the various determinants of regional Canadian unemployment rates in order to get a better picture of Canadian aggregate unemployment rate behavior.The annual data (1967-1991)is for five regions (Atlantic region,Quebec,Ontario,Prairies,and British Columbia),and four age-gender groups (female and male,adult and young).Focusing on young females,the authors find significant effects for the following variables: the regional relative minimum wage rate (minimum wages divided by average hourly earnings),the regional share of youth in the labor force,the regional share of adult females in the labor force,United States activity shocks (deviations of United States GDP from trend),an indicator of the degree of monetary tightness in Canada,regional union density,and a regional index of unemployment insurance generosity.Explain why the authors only used region fixed effects.How would their specification have to change if they also employed time fixed effects?

Accepted Answer

Since the study used Canada-wide effects

Question 5

A researcher investigating the determinants of crime in the United Kingdom has data for 42 police regions over 22 years.She estimates by OLS the following regression
ln(cmrt)it = αi + φt + β1unrtmit + β2proythit + β3 ln(pp)it + uit;i = 1,... ,t = 1,... ,22
where cmrt is the crime rate per head of population,unrtm is the unemployment rate of males,proyth is the proportion of youths,pp is the probability of punishment measured as (number of convictions)/(number of crimes reported).α and φ are area and year fixed effects,where αi equals one for area i and is zero otherwise for all i,and φt is one in year t and zero for all other years for t = 2,…,22.φ1 is not included.
(a)What is the purpose of excluding φ1? What are the terms α and φ likely to pick up? Discuss the advantages of using panel data for this type of investigation.
(b)Estimation by OLS using heteroskedasticity and autocorrelation-consistent standard errors results in the following output,where the coefficients of the fixed effects are not reported:   = 0.063 × unrtmit + 3.739 × proythit - 0.588 × ln(pp)it ;R2 = 0.904
(0.109)(0.179)(0.024)
Comment on the results.In particular,what is the effect of a ten percent increase in the probability of punishment?
(c)To test for the relevance of the area fixed effects,your restrict the regression by dropping all entity fixed effects and add single constant is added.The relevant F-statistic is 135.28.What are the degrees of freedom? What is the critical value from your F table?
(d)Although the test rejects the hypothesis of eliminating the fixed effects from the regression,you want to analyze what happens to the coefficients and their standard errors when the equation is re-estimated without fixed effects.In the resulting regression,   and   do not change by much,although their standard errors roughly double.However,   is now 1.340 with a standard error of 0.234.Why do you think that is?

Accepted Answer

(a)Since there is no constant in additio

Question 6

Your textbook suggests an "entity-demeaned" procedure to avoid having to specify a potentially large number of binary variables.While it is somewhat tedious to specify a binary variable for each entity,this can still be handled relatively easily in the case of the 48 contiguous states.Give a few examples where it might be close to impossible to implement specifying such large number of entity binary variables.The idea of the "entity-demeaned" procedure was introduced as a computationally convenient and simplifying procedure.Since there are also time fixed effects,why is there no discussion of using a "time-demeaned" procedure? Using the following equation
Yit = β0 + β1Xit + β3St + uit,
Show how β1 can be estimated by the OLS regression using "time-demeaned" variables.

Accepted Answer

Answers will vary by student with regard

Question 7

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

Accepted Answer

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. 
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.

Question 8

The main advantage of using panel data over cross sectional data is that it

Accepted Answer

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. 
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.

Question 9

Your textbook reports the following result from an two-way fixed effects (entity and time fixed effects)regression model:   = -0.66 BeerTax + StateFixedEffects + TimeFixedEffects
(0.36)
Where the number in parenthesis is the heteroskedasticity- and autocorrelation-consistent (HAC)standard error.
a.Calculate the t-statistic.Can you reject the null hypothesis that the slope coefficient is zero in the population,using a two-sided test and a 5% significance level?
b.Given that economic theory suggests that the population slope is negative under the alternative hypothesis,is it possible to use a one-sided test here? In that case,does your conclusion change?
c.Using only heteroskedasticity-robust standard errors,but not HAC standard errors,the value in parenthesis becomes 0.25.Repeat the calculations in (a)and report your decision based on a two-sided test.
d.Since the coefficient becomes more statistically significant in (d),should this influence your choice of standard errors? Why or why not?

Accepted Answer

a.t = @#IMG-DLM& = -1.78 < -1.96.Hence you cannot

Question 10

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

Accepted Answer

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. 
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.

It is advisable to use clustered standard errors in panel regressions because

Panel data is also called

The Fixed Effects regression model

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

The main advantage of using panel data over cross sectional data is that it

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

Economic Questions and Data

Review of Probability

Review of Statistics

Linear Regression With One Regressor

Regression With a Single Regressor: Hypothesis Tests and Confidence Intervals

Linear Regression With Multiple Regressors

Hypothesis Tests and Confidence Intervals in Multiple Regression

Nonlinear Regression Functions

Assessing Studies Based on Multiple Regression

Regression With a Binary Dependent Variable

Instrumental Variables Regression

Experiments and Quasi-Experiments

Introduction to Time Series Regression and Forecasting

Estimation of Dynamic Causal Effects

Additional Topics in Time Series Regression

The Theory of Linear Regression With One Regressor

The Theory of Multiple Regression

Filters

Exam 10: Regression With Panel Data

It is advisable to use clustered standard errors in panel regressions because

Panel data is also called

The Fixed Effects regression model

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

The main advantage of using panel data over cross sectional data is that it

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

Economic Questions and Data

Review of Probability

Review of Statistics

Linear Regression With One Regressor

Regression With a Single Regressor: Hypothesis Tests and Confidence Intervals

Linear Regression With Multiple Regressors

Hypothesis Tests and Confidence Intervals in Multiple Regression

Nonlinear Regression Functions

Assessing Studies Based on Multiple Regression

Regression With a Binary Dependent Variable

Instrumental Variables Regression

Experiments and Quasi-Experiments

Introduction to Time Series Regression and Forecasting

Estimation of Dynamic Causal Effects

Additional Topics in Time Series Regression

The Theory of Linear Regression With One Regressor

The Theory of Multiple Regression

Filters