Instrumental Variables Methods in Microeconometrics

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Questions and Answers

What is a key limitation of the Instrumental Variables (IV) method?

IV is only informative for those who respond to the IV, not for Never-takers and Always-takers.

Explain the Two-Stage Least Squares (2SLS) technique in the context of IV.

2SLS is used to estimate causal relationships when there is incomplete compliance, involving first predicting the treatment assignment and then using it to estimate outcomes.

What is the impact of incomplete compliance on treatment estimates?

Incomplete compliance leads to biased estimates if only the intention-to-treat (ITT) approach is used, as not everyone assigned to treatment receives it.

What does the IV method assume regarding the random assignment of treatment?

The IV method assumes that while treatment assignment is random, actual treatment received may not be due to factors like non-compliance. Signup and view all the answers

Compare Average Treatment Effect (ATE) and Average Treatment Effect on the Treated (ATT).

ATE includes effects for all subjects, while ATT focuses only on those who actually received treatment, typically highlighting a higher effect. Signup and view all the answers

What is the relationship between LATE and ATT when there are no Always-takers?

When there are no Always-takers, LATE equals ATT as both only consider Compliers in their estimates. Signup and view all the answers

What is meant by the term 'Complier-Population' in the context of IV?

The Complier-Population includes individuals who change their treatment status in line with the instrument, often being the largest group in such analyses. Signup and view all the answers

In the Minneapolis Domestic Violence Experiment (MDVE), what was a significant issue with treatment compliance?

The issue was that officers did not always adhere to the experimental protocol, leading to non-random treatment delivery. Signup and view all the answers

What is a significant limitation of using instrumental variables (IV) in causal inference?

A significant limitation is the reliance on the exogeneity assumption, which cannot be tested. Signup and view all the answers

Describe the Two-Stage Least Squares (2SLS) method in the context of IV estimation.

The 2SLS method involves first predicting the endogenous variable using the instrument, then using this prediction to estimate the effect on the outcome variable. Signup and view all the answers

What challenges arise from incomplete compliance in IV studies?

Incomplete compliance can lead to biases in estimating the causal effect, as the treatment effect may not apply to those who do not receive the treatment. Signup and view all the answers

Explain how the IV method addresses selection bias in treatment effects.

The IV method helps control for selection bias by using an instrument that influences the treatment assignment but is not directly correlated with the outcome. Signup and view all the answers

What is the significance of the Local Average Treatment Effect (LATE) in evaluating treatment effects?

LATE identifies the average causal effect specifically on compliers who change their treatment status according to the instrument. Signup and view all the answers

How does the independence assumption in IV estimation impact the validity of causal inferences?

The independence assumption requires that the instrument is as good as randomly assigned and does not affect omitted variables relevant to the outcome. Signup and view all the answers

What role does compliance play in the external validity of IV studies?

Compliance determines the external validity as it reveals who is affected by the treatment based on the instrument. Signup and view all the answers

Why is testing the relevance assumption important in IV analysis?

Testing the relevance assumption is important to ensure that the instrument correlates significantly with the endogenous variable. Signup and view all the answers

What is a key limitation of the IV method when dealing with incomplete compliance in experiments?

A key limitation is that it can lead to biased estimates if the instrument does not sufficiently predict treatment assignment. Signup and view all the answers

Explain how the Two-Stage Least Squares (2SLS) estimator enhances the IV method.

2SLS enhances the IV method by allowing the inclusion of multiple instrumental variables and control variables in estimation. Signup and view all the answers

How does incomplete compliance affect the estimation of treatment effects?

Incomplete compliance leads to discrepancies between the actual treatment received and the treatment assigned, complicating impact estimation. Signup and view all the answers

What does the ITT estimate represent in the context of randomized experiments?

ITT (Intention to Treat) estimate represents the effect of assignment to treatment, regardless of whether participants fully complied. Signup and view all the answers

Why must control variables be included in both the first and second stages of the 2SLS estimation process?

Control variables must be included to ensure that they account for confounding effects across both stages of the analysis. Signup and view all the answers

What requirement must be met regarding the number of IVs and endogenous variables in a 2SLS framework?

The number of instrumental variables must be at least as large as the number of endogenous variables to ensure identification. Signup and view all the answers

How do researchers typically correct standard errors in a 2SLS analysis?

Researchers typically correct standard errors to account for the two-step estimation process, ensuring accurate inference. Signup and view all the answers

In comparing treatment effects, what is the significance of LATE within the context of IV estimation?

LATE (Local Average Treatment Effect) estimates the average treatment effect for compliers, providing insights into treatment efficacy. Signup and view all the answers

Study Notes

Instrumental Variables (IV) Methods

Applied microeconometric methods use instrumental variables (IV) to analyze causal relationships.
IV methods are crucial for addressing endogeneity in observational studies where the treatment variable is correlated with the unobserved error term.
A valid instrumental variable (IV) must correlate with the endogenous variable but not directly affect the outcome variable. It should be independent of the omitted variables that impact the outcome.
This method is often used in incomplete experiments where treatment allocation isn't entirely random.

The IV Method

Instrumental variable methods estimate the causal effect of a treatment on an outcome when observations aren't randomly assigned to treatment.
The idea is to find a variable (instrument) that affects the treatment but not directly the outcome.

IV for Incomplete Experiments

IV methods are crucial in cases where treatment assignment is not fully randomized.
This allows for the estimation of causal effects even when treatment assignment is not random.

Two-Stage Least Squares (2SLS)

The 2SLS estimator extends the IV method to handle multiple instrumental variables, control variables, multiple endogenous variables, and continuous instrumental and endogenous variables.
For more than one endogenous variable or control variables, the two-step procedure becomes necessary.

Limitations of Instrumental Variables (IV)

A valid instrumental variable must meet specific assumptions (relevance, exogeneity, independence).
These assumptions are difficult to verify in practice, and violation can lead to inaccurate estimates.
The IV method is not suitable for all research questions or datasets and may not identify the average treatment effect (ATE).

Compliance and External Validity

External validity depends on the group that complies with treatment.
This can be compliers, always-takers, or never-takers, or defiers.
One typically assumes that the defiers group don't exist. (monotonicity or no-defier assumption.)
The IV method is often used in observational studies with incomplete compliance, a key aspect of its use is identifying the group of compliers.

Local Average Treatment Effect (LATE)

LATE helps estimate the average effect on compliers, these are individuals whose participation in the treatment is determined by the instrumental variable (IV).
LATE is not always representative of the average treatment effect on all participants.
If the group of compliers is a sizable proportion of the overall population, a valid LATE is able to reflect the causal effect of the treatment.

Comparison of Average Treatment Effects (ATE), Average Treatment Effect on the Treated (ATT) , and Average Treatment Effect on the Untreated (ATC)

These methods differ in their scope and application.
ATE involves the effects across never-takers, always-takers, and compliers.
ATT involves effects on always-takers and compliers.
ATC involves effects on never-takers and compliers.

Example: Knowledge Is Power Programme (KIPP)

KIPP is a knowledge-is-power program.
Key question: Does the KIPP concept improve learning outcomes of non-white students? Or do better non-white students select into KIPP schools?
The program's popularity leads to a lottery system for admission, which serves as the instrumental variable for a causal study.

Example: Minneapolis Domestic Violence Experiment (MDVE)

Aims to deal with batterers.
Randomizes treatment.
Experiment was not completely effective, thus the use of IV is necessary to ensure valid estimations.

How to Find a Valid Instrumental Variable

Finding a good IV often relies on statistical theory, reasoning, and empirical evidence.
Natural experiments (e.g., policy changes, unexpected events, or institutional reforms) offer good candidates for IVs.
Identifying a good IV is challenging and requires careful scrutiny to satisfy relevance, exogeneity, and independence assumptions.
The method for testing the instrument's quality, including the appropriateness of the chosen instrument, should not be overlooked.

Bartik Instrumental Variables

A method used in labor economics to analyze the impact of local employment changes on certain outcomes.
It involves using national industry growth rates as instrumental variables for local employment growth.
This approach can uncover causal effects by addressing potential endogeneity issues.

Validity Assumptions for IVs

Relevance: An instrumental variable should be correlated with the endogenous variable.
Exogeneity: The instrument should not directly affect the outcome variable and should be independent of the error term.
Independence: The instrumental variable should be independent of omitted variables affecting both treatment and outcome.

Weak Instruments

If an instrument is weak, its effect on the treatment is small.
Weak instruments can generate inaccurate causal estimates, including potentially large biases.
The F-test is a commonly used tool for determining whether instruments are weak or strong.

Bad Controls

Including irrelevant variables as controls in causal analyses can introduce bias and limit the accurate identification of causal effects.
It is important to carefully consider all variables that might affect the treatment or the outcome when implementing the analysis.

Tests for Endogeneity and Overidentifying Restrictions

These help identify whether the assumptions for an IV setup are satisfied, specifically, whether any variables are correlated or endogenous in nature.
The Sargan-Hansen test (J-Test) helps if there are too many instruments, while the Durbin-Wu-Hausman Test assesses if an explanatory variable is indeed endogenous.
Important to note that you need auxiliary instrumental variables for these tests.

Can We Test for Endogeneity?

Endogeneity tests can be used, but often have limitations, as most of these methods require good assumptions and strong instrumental variables.

How to Read an IV-Study

When reviewing an IV-study, pay close attention to the research question, the identification problem, and the plausibility of the exclusion restriction.
Evaluate the reduced form, first stage results, tests for weak instruments, and the differences between the OLS and IV estimates.
A crucial aspect of assessing the study's validity is evaluating the external validity, including the magnitude of the group of compliers compared to always-takers.

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Description

This quiz covers instrumental variable (IV) methods used in applied microeconometrics to analyze causal relationships. It focuses on how IV methods address endogeneity in observational studies and the importance of selecting valid instruments. Participants will explore the applications of IV in incomplete experiments.