Question 1

In a sharp regression discontinuity design,

Accepted Answer

A) crossing the threshold influences receipt of the treatment but is not the sole determinant. 
B) the population regression line must be linear above and below the threshold. 
C) Xi will in general be correlated with ui. 
D) receipt of treatment is entirely determined by whether W exceeds the threshold. 
A) crossing the threshold influences receipt of the treatment but is not the sole determinant. 
B) the population regression line must be linear above and below the threshold. 
C) Xi will in general be correlated with ui. 
D) receipt of treatment is entirely determined by whether W exceeds the threshold.

Question 2

Small sample sizes in an experiment

Accepted Answer

A) biases the estimators of the causal effect. 
B) may pose a problem because the assumption that errors are normally distributed is dubious for experimental data. 
C) do not raise threats to the validity of confidence intervals as long as heteroskedasticity-robust standard errors are used. 
D) may affect confidence intervals but not hypothesis tests. 
A) biases the estimators of the causal effect. 
B) may pose a problem because the assumption that errors are normally distributed is dubious for experimental data. 
C) do not raise threats to the validity of confidence intervals as long as heteroskedasticity-robust standard errors are used. 
D) may affect confidence intervals but not hypothesis tests.

Question 3

Quasi-experiments

Accepted Answer

A) provide a bridge between the econometric analysis of observational data sets and the statistical ideal of a true randomized controlled experiment. 
B) are not the same as experiments, and lessons learned from the use of the latter can therefore not be applied to them. 
C) most often use difference-in-difference estimators, which are quite different from OLS and instrumental variables methods studied in earlier chapters of the book. 
D) use the same methods as studied in earlier chapters of the book, and hence the interpretation of these methods is the same. 
A) provide a bridge between the econometric analysis of observational data sets and the statistical ideal of a true randomized controlled experiment. 
B) are not the same as experiments, and lessons learned from the use of the latter can therefore not be applied to them. 
C) most often use difference-in-difference estimators, which are quite different from OLS and instrumental variables methods studied in earlier chapters of the book. 
D) use the same methods as studied in earlier chapters of the book, and hence the interpretation of these methods is the same.

Question 4

In the case of heterogeneous causal effects, the following is not true:

Accepted Answer

A) in the circumstances in which OLS would normally be consistent (when E(ui | Xi)= 0), the OLS estimator continues to be consistent. 
B) OLS estimation using heteroskedasticity-robust standard errors is identical to TSLS. 
C) the OLS estimator is properly interpreted as a consistent estimator of the average causal effect in the population being studied. 
D) the TSLS estimator in general is not a consistent estimator of the average causal effect if an individual's decision to receive treatment depends on the effectiveness of the treatment for that individual. 
A) in the circumstances in which OLS would normally be consistent (when E(ui | Xi)= 0), the OLS estimator continues to be consistent. 
B) OLS estimation using heteroskedasticity-robust standard errors is identical to TSLS. 
C) the OLS estimator is properly interpreted as a consistent estimator of the average causal effect in the population being studied. 
D) the TSLS estimator in general is not a consistent estimator of the average causal effect if an individual's decision to receive treatment depends on the effectiveness of the treatment for that individual.

Question 5

Testing for the random receipt of treatment

Accepted Answer

A) is not possible, in general. 
B) entails testing the hypothesis that the coefficients on W1i, …, Wri are non-zero in a regression of Xi on W1i, …, Wr. 
C) is not meaningful since the LHS variable is binary. 
D) entails testing the hypothesis that the coefficients on W1i, …, Wri are zero in a regression of Xi on W1i, …, Wr. 
A) is not possible, in general. 
B) entails testing the hypothesis that the coefficients on W1i, …, Wri are non-zero in a regression of Xi on W1i, …, Wr. 
C) is not meaningful since the LHS variable is binary. 
D) entails testing the hypothesis that the coefficients on W1i, …, Wri are zero in a regression of Xi on W1i, …, Wr.

Question 6

Failure to follow the treatment protocol means that

Accepted Answer

A) the OLS estimator cannot be computed. 
B) instrumental variables estimation of the treatment effect should be used where the initial random assignment is the instrument for the treatment actually received. 
C) you should use the TSLS estimator and regress the outcome variable Y on the initial random assignment in the first stage to get predicted values of the outcome variable. 
D) the Hawthorne effect plays a crucial role. 
A) the OLS estimator cannot be computed. 
B) instrumental variables estimation of the treatment effect should be used where the initial random assignment is the instrument for the treatment actually received. 
C) you should use the TSLS estimator and regress the outcome variable Y on the initial random assignment in the first stage to get predicted values of the outcome variable. 
D) the Hawthorne effect plays a crucial role.

Question 7

Threats to internal validity of quasi-experiments include

Accepted Answer

A) failure of randomization. 
B) failure to follow the treatment protocol. 
C) attrition. 
D) all of the above with some modifications from true randomized controlled experiments. 
A) failure of randomization. 
B) failure to follow the treatment protocol. 
C) attrition. 
D) all of the above with some modifications from true randomized controlled experiments.

Question 8

Earnings functions provide a measure, among other things, of the returns to education. It has been argued these regressions contain a serious omitted variable bias due to differences in abilities. Furthermore, ability is hard to measure and bound to be highly correlated with years of schooling. Hence the standard estimate of about a 10 percent return to every year of schooling is upward biased. Suggest some ways to address this problem. One famous study looked at earnings of identical twins. Explain how this can be viewed as a quasi-experiment, and mention some of the threats to internal and external validity that such a study might encounter.

Accepted Answer

Answers will vary by student. The omitte

Question 9

If the causal effect is different for different people, then the population regression equation for a binary treatment variable Xi, can be written as

Accepted Answer

A) Yi = β0 + β1Xi + ui. 
B) Yi = β0 + β1iXi + ui. 
C) Yi = β0i β1iXi + ui. 
D) Yi = β0 + β1Gi + β2Dt + ui. 
A) Yi = β0 + β1Xi + ui. 
B) Yi = β0 + β1iXi + ui. 
C) Yi = β0i β1iXi + ui. 
D) Yi = β0 + β1Gi + β2Dt + ui.

Question 10

One of the major lessons learned in the chapter on experiments and quasi-experiments

Accepted Answer

A) is that there are almost no true experiments in economics and that quasi-experiments are a poor substitute. 
B) you should always use TSLS when estimating causal effects in quasi-experiments. 
C) populations are always homogeneous. 
D) is that the insights of experimental methods can be applied to quasi-experiments, in which special circumstances make it seem "as if" randomization has occurred. 
A) is that there are almost no true experiments in economics and that quasi-experiments are a poor substitute. 
B) you should always use TSLS when estimating causal effects in quasi-experiments. 
C) populations are always homogeneous. 
D) is that the insights of experimental methods can be applied to quasi-experiments, in which special circumstances make it seem "as if" randomization has occurred.

Question 11

Assume for the moment that the student-teacher ratio effect on test scores was large enough that you would advocate reducing class sizes in elementary schools. In 1996, the State of California reduced class sizes from K-3 to no more than 20 students across all public elementary schools (Class Size Reduction Act)at a cost of approximately $2 billion. In a short essay, discuss why the general equilibrium effects might differ from the results obtained using experiments.

Accepted Answer

The General Equilibrium effects are the

Question 12

Canada and the United States had approximately the same aggregate unemployment rates from the 1920s to 1981. In 1982, a two percentage point gap appears, which has roughly persisted until today, with the Canadian unemployment rate in the third quarter of 2002 being 7.6 percent while the American rate stood at 5.9 percent in the same period. Several authors have investigated this phenomenon. One study, published in 1990, contained the following statement: "It is a clichė that, as compared to analysis in the physical sciences, economic analysis is hampered by the lack of controlled experiments. In this regard, study of the Canadian economy can be much facilitated by comparison with the behavior of the US …" Discuss what the authors may have had in mind. List some potential threats to internal and external validity when comparing aggregate unemployment rate behavior between countries.

Accepted Answer

It should be clear that the authors were

Question 13

A causal effect for a single individual

Accepted Answer

A) can be deduced from the average treatment effect. 
B) cannot be measured. 
C) depends on observable variables only. 
D) is observable since it is used as part of calculating the mean of individual causal effects. 
A) can be deduced from the average treatment effect. 
B) cannot be measured. 
C) depends on observable variables only. 
D) is observable since it is used as part of calculating the mean of individual causal effects.

Question 14

A potential outcome

Accepted Answer

A) is the outcome for an individual under a potential treatment. 
B) cannot be observed because most individuals do not achieve their potential. 
C) is the same as a causal effect. 
D) is none of the above. 
A) is the outcome for an individual under a potential treatment. 
B) cannot be observed because most individuals do not achieve their potential. 
C) is the same as a causal effect. 
D) is none of the above.

Question 15

Roughly ten percent of elementary schools in California have a system whereby 4th to 6th graders share a common classroom and a single teacher (multi-age, multi-grade classroom). Suggest an experimental design that would allow you to assess the effect of learning in this environment. Mention some of the threats to internal and external validity and how you would attempt to circumvent these.

Accepted Answer

Students should be selected randomly wit

Question 16

The major distinction between the experiments and quasi-experiments chapter and earlier chapters is the

Accepted Answer

A) frequent use of binary variables. 
B) type of data analyzed and the special opportunities and challenges posed when analyzing experiments and quasi-experiments. 
C) superiority of TSLS over OLS. 
D) use of heteroskedasticity-robust standard errors. 
A) frequent use of binary variables. 
B) type of data analyzed and the special opportunities and challenges posed when analyzing experiments and quasi-experiments. 
C) superiority of TSLS over OLS. 
D) use of heteroskedasticity-robust standard errors.

Question 17

Randomization based on covariates is

Accepted Answer

A) not of practical importance since individuals are hardly ever assigned in this fashion. 
B) dependent on the covariances of the error term (serial correlation). 
C) a randomization in which the probability of assignment to the treatment group depends on one of more observable variables W. 
D) eliminates the omitted variable bias when using the difference estimator based on Yi = β0 + β1Xi + ui, where Y is the outcome variable and X is the treatment indicator. 
A) not of practical importance since individuals are hardly ever assigned in this fashion. 
B) dependent on the covariances of the error term (serial correlation). 
C) a randomization in which the probability of assignment to the treatment group depends on one of more observable variables W. 
D) eliminates the omitted variable bias when using the difference estimator based on Yi = β0 + β1Xi + ui, where Y is the outcome variable and X is the treatment indicator.

Question 18

A repeated cross-sectional data set is

Accepted Answer

A) a collection of cross-sectional data sets, where each cross-sectional data set corresponds to a different time period. 
B) the same as a balanced panel data set. 
C) what Card and Krueger used in their study of the effect of minimum wages on teenage employment. 
D) time series. 
A) a collection of cross-sectional data sets, where each cross-sectional data set corresponds to a different time period. 
B) the same as a balanced panel data set. 
C) what Card and Krueger used in their study of the effect of minimum wages on teenage employment. 
D) time series.

Question 19

You want to study whether or not the use of computers in the classroom for elementary students has an effect on performance. Explain in some detail how you would ideally set up such an experiment and what threats to internal and external validity there might be.

Accepted Answer

Answer will differ by students. Students

Question 20

Describe the major differences between a randomized controlled experiment and a quasi-experiment.

Accepted Answer

Answers will vary by student. Some of th

In a sharp regression discontinuity design,

Small sample sizes in an experiment

Quasi-experiments

In the case of heterogeneous causal effects, the following is not true:

Testing for the random receipt of treatment

Failure to follow the treatment protocol means that

Threats to internal validity of quasi-experiments include

If the causal effect is different for different people, then the population regression equation for a binary treatment variable X_i, can be written as

One of the major lessons learned in the chapter on experiments and quasi-experiments

A causal effect for a single individual

A potential outcome

The major distinction between the experiments and quasi-experiments chapter and earlier chapters is the

Randomization based on covariates is

A repeated cross-sectional data set is

You want to study whether or not the use of computers in the classroom for elementary students has an effect on performance. Explain in some detail how you would ideally set up such an experiment and what threats to internal and external validity there might be.

Describe the major differences between a randomized controlled experiment and a quasi-experiment.

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 Panel Data

Regression With a Binary Dependent Variable

Instrumental Variables Regression

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 13: Experiments and Quasi-Experiments

In a sharp regression discontinuity design,

Small sample sizes in an experiment

Quasi-experiments

In the case of heterogeneous causal effects, the following is not true:

Testing for the random receipt of treatment

Failure to follow the treatment protocol means that

Threats to internal validity of quasi-experiments include

If the causal effect is different for different people, then the population regression equation for a binary treatment variable Xi, can be written as

One of the major lessons learned in the chapter on experiments and quasi-experiments

A causal effect for a single individual

A potential outcome

The major distinction between the experiments and quasi-experiments chapter and earlier chapters is the

Randomization based on covariates is

A repeated cross-sectional data set is

You want to study whether or not the use of computers in the classroom for elementary students has an effect on performance. Explain in some detail how you would ideally set up such an experiment and what threats to internal and external validity there might be.

Describe the major differences between a randomized controlled experiment and a quasi-experiment.

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 Panel Data

Regression With a Binary Dependent Variable

Instrumental Variables Regression

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

If the causal effect is different for different people, then the population regression equation for a binary treatment variable X_i, can be written as