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Causal Inference and Impact Evaluation Methods

Description: This quiz covers the fundamental concepts, methods, and applications of causal inference and impact evaluation in economic data analysis.
Number of Questions: 15
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Tags: causal inference impact evaluation econometrics research methods
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What is the primary objective of causal inference?

  1. To establish a causal relationship between two variables.

  2. To predict the value of one variable based on another.

  3. To describe the distribution of a variable.

  4. To test the significance of a statistical relationship.

Show answer
Correct Option: A
Explanation:

Causal inference aims to determine whether a change in one variable causes a change in another, rather than merely observing a correlation between them.

Which of the following is NOT a common method for causal inference?

  1. Randomized controlled trials (RCTs)

  2. Observational studies

  3. Instrumental variables (IVs)

  4. Regression discontinuity design (RDD)

Show answer
Correct Option: B
Explanation:

Observational studies are not a method for causal inference, as they cannot establish a causal relationship between variables due to the potential for confounding factors.

In an RCT, participants are randomly assigned to either a treatment group or a control group. What is the purpose of the control group?

  1. To provide a comparison group for the treatment group.

  2. To increase the sample size of the study.

  3. To reduce the cost of the study.

  4. To ensure that the results are generalizable to the population.

Show answer
Correct Option: A
Explanation:

The control group in an RCT serves as a comparison group to the treatment group, allowing researchers to assess the causal effect of the treatment by comparing the outcomes of the two groups.

What is the main challenge in conducting observational studies for causal inference?

  1. The presence of confounding factors.

  2. The lack of random assignment.

  3. The small sample size.

  4. The high cost of data collection.

Show answer
Correct Option: A
Explanation:

Confounding factors are variables that are correlated with both the treatment variable and the outcome variable, potentially biasing the results of the study.

Which of the following is an example of an instrumental variable (IV)?

  1. Age

  2. Gender

  3. Education

  4. Lottery winning

Show answer
Correct Option: D
Explanation:

Lottery winning is an example of an IV because it is randomly assigned and affects the treatment variable (e.g., participation in a program) but is not directly related to the outcome variable (e.g., earnings).

What is the key assumption of the regression discontinuity design (RDD)?

  1. The treatment variable is randomly assigned.

  2. The outcome variable is continuous.

  3. The treatment variable has a sharp discontinuity at a specific threshold.

  4. The confounding factors are evenly distributed across the treatment and control groups.

Show answer
Correct Option: C
Explanation:

The RDD assumes that the treatment variable changes abruptly at a specific threshold, allowing researchers to compare outcomes for individuals just above and below the threshold.

Which of the following is a common measure of the causal effect in impact evaluation?

  1. Average treatment effect (ATE)

  2. Average treatment effect on the treated (ATT)

  3. Instrumental variable (IV) estimate

  4. Regression discontinuity design (RDD) estimate

Show answer
Correct Option: A
Explanation:

The ATE is a measure of the overall causal effect of a treatment, calculated as the difference in the average outcome between the treatment and control groups.

What is the difference between the ATE and the ATT?

  1. The ATE includes the effect of the treatment on both treated and untreated individuals, while the ATT only includes the effect on treated individuals.

  2. The ATE is calculated using an RCT, while the ATT is calculated using an observational study.

  3. The ATE is a measure of the average effect of the treatment, while the ATT is a measure of the average effect of the treatment on the treated.

  4. The ATE is always positive, while the ATT can be negative.

Show answer
Correct Option: A
Explanation:

The ATE captures the overall impact of the treatment, including the effect on individuals who were not actually treated, while the ATT focuses specifically on the effect on those who received the treatment.

Which of the following is NOT a potential threat to the validity of an impact evaluation?

  1. Selection bias

  2. Confounding factors

  3. Measurement error

  4. Random assignment

Show answer
Correct Option: D
Explanation:

Random assignment is a method used to eliminate selection bias and ensure that the treatment and control groups are comparable, thus reducing the threat to validity.

What is the purpose of a sensitivity analysis in impact evaluation?

  1. To assess the robustness of the results to different assumptions and specifications.

  2. To increase the sample size of the study.

  3. To reduce the cost of the study.

  4. To ensure that the results are generalizable to the population.

Show answer
Correct Option: A
Explanation:

Sensitivity analysis is used to evaluate how sensitive the results of an impact evaluation are to changes in the assumptions and specifications of the analysis, helping to determine the reliability of the findings.

Which of the following is an example of a non-experimental method for impact evaluation?

  1. Randomized controlled trial (RCT)

  2. Regression discontinuity design (RDD)

  3. Matching methods

  4. Instrumental variables (IVs)

Show answer
Correct Option: C
Explanation:

Matching methods are a non-experimental approach to impact evaluation that aims to create a comparison group that is similar to the treatment group in terms of observable characteristics.

What is the main challenge in using matching methods for impact evaluation?

  1. The lack of a random assignment.

  2. The presence of confounding factors.

  3. The small sample size.

  4. The high cost of data collection.

Show answer
Correct Option: B
Explanation:

The main challenge in using matching methods is the potential for confounding factors, as it is difficult to ensure that the treatment and comparison groups are perfectly matched on all relevant characteristics.

Which of the following is a common type of matching method used in impact evaluation?

  1. Propensity score matching

  2. Exact matching

  3. Coarsened exact matching

  4. Multivariate adaptive regression splines (MARS)

Show answer
Correct Option: A
Explanation:

Propensity score matching is a widely used matching method that aims to balance the distribution of observable characteristics between the treatment and comparison groups by matching individuals with similar propensity scores.

What is the role of a counterfactual in causal inference?

  1. To represent the outcome that would have occurred in the absence of the treatment.

  2. To estimate the average treatment effect.

  3. To select the appropriate control group.

  4. To assess the robustness of the results.

Show answer
Correct Option: A
Explanation:

The counterfactual represents the hypothetical outcome for an individual or group if they had not received the treatment, allowing researchers to estimate the causal effect of the treatment.

Which of the following is NOT a common type of impact evaluation study design?

  1. Before-and-after study

  2. Cross-sectional study

  3. Panel study

  4. Randomized controlled trial (RCT)

Show answer
Correct Option: B
Explanation:

Cross-sectional studies are not typically used for impact evaluation as they cannot establish a causal relationship between the treatment and the outcome due to the lack of temporal variation.

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