Randomized Controlled Trials Overview

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Questions and Answers

What is the primary purpose of a Randomized Controlled Trial (RCT) in evaluating policy effects?

To compare different groups based on observed characteristics.

To predict future outcomes based on historical data.

To establish a direct link between an action and its outcome, demonstrating causation. (correct)

To identify patterns and trends in data, regardless of causal relationships.

What does the abbreviation 'ACE' stand for in the context of evaluating policy impacts?

Average Causal Effect

Correlation implies causation.

False (B)

What is the primary concern addressed by Randomized Controlled Trials (RCTs) in policy evaluation?

Selection bias Signup and view all the answers

What is the key principle behind the 'ceteris paribus' condition in RCTs?

All other things being equal Signup and view all the answers

Which of the following is NOT a threat to internal validity in an RCT?

Generalizability of findings to other populations. (D) Signup and view all the answers

What is the primary goal of the 'Fixed Effects' regression model?

To control for unobserved, constant factors that vary across entities but do not change over time. Signup and view all the answers

Name one of the methods used to control for unobserved factors in analyzing policy impact when RCTs are not feasible.

Regression analysis Signup and view all the answers

The 'Hawthorne effect' refers to participants' improved performance simply because they are aware of being observed.

True (A) Signup and view all the answers

What is the primary purpose of the 'Difference-in-Differences' (DID) method in policy evaluation?

To compare changes over time between treatment and control groups, controlling for common trends affecting both groups. Signup and view all the answers

What is the main assumption underlying the 'Difference-in-Differences' (DID) method?

The treatment and control groups would have experienced the same change in outcomes over time in the absence of the intervention. Signup and view all the answers

What is the key difference between a 'sharp' and a 'fuzzy' Regression Discontinuity Design (RDD)?

In a sharp RDD, treatment assignment is strictly determined by whether the running variable crosses the threshold. In a fuzzy RDD, crossing the threshold only increases the probability of treatment, but does not guarantee it. Signup and view all the answers

What is the primary goal of the 'Instrumental Variables' (IV) method in policy evaluation?

To address endogeneity bias when the treatment is not randomly assigned. Signup and view all the answers

What is the key characteristic of an 'instrument' used in the IV method?

It must be exogenous, meaning it is uncorrelated with the error term in the outcome equation. Signup and view all the answers

Which of the following is NOT a limitation of the 'Instrumental Variables' (IV) method?

The method assumes random assignment of treatment. (D) Signup and view all the answers

The 'Regression Discontinuity' (RDD) method is particularly useful when researchers have access to large datasets with multiple time periods.

False (B) Signup and view all the answers

The 'Regression Discontinuity' (RDD) method requires a sharp cutoff point in the running variable for treatment assignment.

False (B) Signup and view all the answers

Study Notes

Randomized Controlled Trials (RCTs)

RCTs are the gold standard for establishing causality.
Random assignment ensures treatment and control groups are similar.
Any difference in outcomes is attributed to the treatment.
RCTs are essential for understanding how policies and interventions affect outcomes.
They distinguish between correlation and causation.
Correlation does not imply causation.
Causation establishes a direct link between a cause and its effect.
Average Causal Effect (ACE) measures the average impact of an intervention across a population.
ACE accounts for variations in individual responses to the intervention.
Selection bias is a key challenge in causal inference.
Selection bias occurs when groups differ systematically due to factors unrelated to the treatment.
Randomized Controlled Trials (RCTs) effectively eliminate selection bias.
RCTs randomly assign participants to treatment or control groups.
This ensures that the only difference between the groups is the treatment.
RCTs must be well-designed to avoid biases and threats to internal and external validity.

Fixed Effects (FE)

Controls for unchanging differences within entities (e.g., schools, people).
Eliminates bias from time-invariant factors like school culture or teacher quality.
FE regression isolates the effect of a treatment over time for specific groups.
Powerful in scenarios with unobservable or unmeasurable factors that vary across entities but remain constant over time.
Comparing outcomes before and after treatment between similar groups, helps in isolating the effect of the treatment on an outcome.

Instrumental Variables (IV)

Fixes endogeneity when the treatment isn't randomly assigned.
Uses an external “instrument” (e.g., random selection for laptops) to assess the treatment's impact, not confounding factors.
IV method isolates the treatment effect, even if treatment assignment is not random.

Difference-in-Differences (DID)

DID compares changes over time across a treatment and control group to determine the effect of intervention.
The method identifies differences across the two groups after implementing a treatment that wasn't present in the previous time period.
DID relies on the assumption that both groups would follow parallel trends without the intervention.
DID regression isolates treatment effect by capturing changes in the experimental group compared to the control group over time.

Regression Discontinuity (RD)

RD estimates causal effects by comparing people just above and below a threshold (e.g., GPA).
Assumes that people just above and below the threshold are comparable except for the treatment.
Helpful when there is a 'cutoff' for an intervention (e.g., students with 3.0 GPA receive laptops.)
Can use either simple or multiple regression.

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Description

Explore the principles and importance of Randomized Controlled Trials (RCTs) in establishing causality. This quiz covers topics such as random assignment, the Average Causal Effect (ACE), and challenges like selection bias. Understand how RCTs differentiate between correlation and causation, and their role in policy evaluation.