Question 1

Causal effects that depend on the value of an observable variable,say Wi,

Accepted Answer

A) cannot be estimated. 
B) can be estimate by interacting the treatment variable with Wi. 
C) result in the OLS estimator being inefficient. 
D) requires use of homoskedasticity-only standard errors. 
A) cannot be estimated. 
B) can be estimate by interacting the treatment variable with Wi. 
C) result in the OLS estimator being inefficient. 
D) requires use of homoskedasticity-only standard errors. B

Question 2

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. B

Question 3

For quasi-experiments,

Accepted Answer

A) there is a particularly important potential threat to internal validity,namely whether the "as if" randomization in fact can be treated reliably as true randomization. 
B) there are the same threats to internal validity as for true randomized controlled experiments,without modifications. 
C) there is little threat to external validity,since the populations are typically already different. 
D) OLS estimation should not be used. 
A) there is a particularly important potential threat to internal validity,namely whether the "as if" randomization in fact can be treated reliably as true randomization. 
B) there are the same threats to internal validity as for true randomized controlled experiments,without modifications. 
C) there is little threat to external validity,since the populations are typically already different. 
D) OLS estimation should not be used. A

Question 4

The following does not represent a threat to internal validity of randomized controlled experiments:

Accepted Answer

A) attrition. 
B) failure to follow the treatment protocol. 
C) experimental effects. 
D) a large sample size. 
A) attrition. 
B) failure to follow the treatment protocol. 
C) experimental effects. 
D) a large sample size.

Question 5

Experimental effects,such as the Hawthorne effect,

Accepted Answer

A) generally are not germane in quasi-experiments. 
B) typically require instrumental variable estimation in quasi-experiments. 
C) can be dealt with using binary variables in quasi-experiments. 
D) are the most important threat to internal validity in quasi-experiments. 
A) generally are not germane in quasi-experiments. 
B) typically require instrumental variable estimation in quasi-experiments. 
C) can be dealt with using binary variables in quasi-experiments. 
D) are the most important threat to internal validity in quasi-experiments.

Question 6

The following are reasons for studying randomized controlled experiment in an econometrics course,with the exception of

Accepted Answer

A) at a conceptual level,the notion of an ideal randomized controlled experiment provides a benchmark against which to judge estimates of causal effects in practice. 
B) when experiments are actually conducted,their results can be very influential,so it is important to understand the limitations and threats to validity of actual experiments as well as their strength. 
C) randomized controlled experiments in economics are common. 
D) external circumstances sometimes produce what appears to be randomization. 
A) at a conceptual level,the notion of an ideal randomized controlled experiment provides a benchmark against which to judge estimates of causal effects in practice. 
B) when experiments are actually conducted,their results can be very influential,so it is important to understand the limitations and threats to validity of actual experiments as well as their strength. 
C) randomized controlled experiments in economics are common. 
D) external circumstances sometimes produce what appears to be randomization.

Question 7

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 8

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 9

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 10

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 11

Program evaluation

Accepted Answer

A) is conducted for most departments in your university/college about every seven years. 
B) is the field of study that concerns estimating the effect of a program,policy,or some other intervention or "treatment." 
C) tries to establish whether EViews,SAS or Stata work best for your econometrics course. 
D) establishes rating systems for television programs in a controlled experiment framework. 
A) is conducted for most departments in your university/college about every seven years. 
B) is the field of study that concerns estimating the effect of a program,policy,or some other intervention or "treatment." 
C) tries to establish whether EViews,SAS or Stata work best for your econometrics course. 
D) establishes rating systems for television programs in a controlled experiment framework.

Question 12

(Requires Appendix material)Discuss how the differences-in-differences estimator can be extended to multiple time periods.In particular,assume that there are n individuals and T time periods.What do the individual and time effects control for?

Accepted Answer

The extension of the differences-in-diff

Question 13

Your textbook gives a graphical example of   ,where outcome is plotted on the vertical axis,and time period appears on the horizontal axis.There are two time periods entered: "t = 1"
and "t = 2." The former corresponds to the "before" time period,while the latter represents the "after" period.The assumption is that the policy occurred sometime between the time periods (call this "t = p").Keeping in mind the graphical example of   ,carefully read what a reviewer of the Card and Krueger (CK)study of the minimum wage effect on employment in the New Jersey-Pennsylvania study had to say:
"Two assumptions are implicit throughout the evaluation of the 'natural experiment:' (1)[   ] would be zero if the treatment had not occurred,so a nonzero [   ] indicates the effect of the treatment (that is,nothing else could have caused the difference in the outcomes to change),and (2)… the intervention occurs after we measure the initial outcomes in the two groups.… Three conditions are particularly relevant in interpreting CK's work: (1)[t = 1] must be sufficiently before [t = p] that [the treatment group] did not adjust to the treatment before [t=1] - otherwise [   -   ] will reflect the effect of the treatment; (2)[t = 2] must be sufficiently after [t = p] to allow the treatment's effect to be fully felt;and (3)we must be sure that the same difference [   -   ] would have been observed at [t = 2] if the treatment had not been imposed,that is,[the control group must be good enough] that there is no need to adjust the differences for factors other than the treatment that might have caused them to change."
Use a figure similar to the textbook to explain what this reviewer meant.

Accepted Answer

See accompanying figures. @#IMG-DLM& (1) @#IMG-DLM& would be

Question 14

All of the following are reasons for using the differences estimator with additional regressors,with the exception of

Accepted Answer

A) efficiency. 
B) providing a check for randomization. 
C) providing an adjustment for "conditional" randomization. 
D) making the difference estimator easier to calculate than in the case of the differences estimator without the additional regressors. 
A) efficiency. 
B) providing a check for randomization. 
C) providing an adjustment for "conditional" randomization. 
D) making the difference estimator easier to calculate than in the case of the differences estimator without the additional regressors.

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

In a quasi-experiment

Accepted Answer

A) quasi differences are used,i.e. ,instead of △Y you need to use (   - λ ×
  ),where 0 < λ < 1. 
B) randomness is introduced by variations in individual circumstances that make it appear as if the treatment is randomly assigned. 
C) the causal effect has to be estimated through quasi maximum likelihood estimation. 
D) the t-statistic is no longer normally distributed in large samples. 
A) quasi differences are used,i.e. ,instead of △Y you need to use (   - λ ×
  ),where 0 < λ < 1. 
B) randomness is introduced by variations in individual circumstances that make it appear as if the treatment is randomly assigned. 
C) the causal effect has to be estimated through quasi maximum likelihood estimation. 
D) the t-statistic is no longer normally distributed in large samples.

Question 17

Consider the simple population regression model where the treatment is the same for the members of the treatment group,and hence X is a binary variable.Explain why the coefficient on X represents the difference between two means.How is the test for the statistical significance of the coefficient on X related to the test for differences in means between two populations,when their variances are different? Write down the null and alternative hypothesis in each case.

Accepted Answer

The answer should proceed along the line

Question 18

Assume that data are available on other characteristics of the subjects that are relevant to determining the experimental outcome.Then including these determinants explicitly results in

Accepted Answer

A) the limited dependent variable model. 
B) the differences in means test. 
C) the multiple regression model. 
D) large scale equilibrium effects. 
A) the limited dependent variable model. 
B) the differences in means test. 
C) the multiple regression model. 
D) large scale equilibrium effects.

Question 19

Present alternative estimators for causal effects using experimental data when data is available for a single period or for two periods.Discuss their advantages and disadvantages.

Accepted Answer

There are essentially four estimators di

Question 20

Specify the multiple regression model that contains the difference-in-difference estimator (with additional regressors).Explain the circumstances under which this model is preferable to the simple difference-in-difference estimator.Explain how the W's can be used to test for randomization.How does the interpretation of the W variables change compared to the differences estimator with additional regressors?

Accepted Answer

The differences-in-differences estimator

Causal effects that depend on the value of an observable variable,say Wi,

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

For quasi-experiments,

The following does not represent a threat to internal validity of randomized controlled experiments:

Experimental effects,such as the Hawthorne effect,

The following are reasons for studying randomized controlled experiment in an econometrics course,with the exception of

In a sharp regression discontinuity design,

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

Threats to internal validity of quasi-experiments include

Program evaluation

(Requires Appendix material)Discuss how the differences-in-differences estimator can be extended to multiple time periods.In particular,assume that there are n individuals and T time periods.What do the individual and time effects control for?

All of the following are reasons for using the differences estimator with additional regressors,with the exception of

In a quasi-experiment

Assume that data are available on other characteristics of the subjects that are relevant to determining the experimental outcome.Then including these determinants explicitly results in

Present alternative estimators for causal effects using experimental data when data is available for a single period or for two periods.Discuss their advantages and disadvantages.

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

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Exam 13: Experiments and Quasi-Experiments

Causal effects that depend on the value of an observable variable,say Wi,

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

For quasi-experiments,

The following does not represent a threat to internal validity of randomized controlled experiments:

Experimental effects,such as the Hawthorne effect,

The following are reasons for studying randomized controlled experiment in an econometrics course,with the exception of

In a sharp regression discontinuity design,

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

Threats to internal validity of quasi-experiments include

Program evaluation

(Requires Appendix material)Discuss how the differences-in-differences estimator can be extended to multiple time periods.In particular,assume that there are n individuals and T time periods.What do the individual and time effects control for?

All of the following are reasons for using the differences estimator with additional regressors,with the exception of

In a quasi-experiment

Assume that data are available on other characteristics of the subjects that are relevant to determining the experimental outcome.Then including these determinants explicitly results in

Present alternative estimators for causal effects using experimental data when data is available for a single period or for two periods.Discuss their advantages and disadvantages.

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