IV

Instrumental Variables MOC

Instrumental variables (IV) identify causal effects by isolating variation in a treatment that is driven by an external instrument — variation that is plausibly as-good-as-randomly assigned and affects the outcome only through the treatment. The framework’s defining insight is interpretive: with heterogeneous effects, IV does not recover an overall average but the LATE — the effect for compliers, the units the instrument actually moves. The identifying triad is instrument independence (Randomization), the Exclusion-Restriction, and Monotonicity, plus a first stage.

Papers

• Angrist2022-EmpiricalStrategiesIlluminatingPath — Angrist’s Nobel lecture: the LATE framework, separating cheap independence from the substantive exclusion restriction, illustrated with school-admission instruments.
• AngristKrueger1999-EmpiricalStrategiesLaborEconomics — the handbook chapter that systematized IV (and other empirical strategies) in labor economics.
• AngristKrueger2001-SearchForIdentification — JEP history of IV from supply–demand systems to natural experiments; the exclusion restriction as the binding assumption.
• Imbens2014-IVEconometriciansPerspective — potential-outcomes synthesis bridging the econometric and statistical accounts; IV as a complier-specific LATE.
• Murray2006-WeakAndInvalidInstruments — practitioner’s guide to the two central threats: invalid instruments (exclusion) and weak instruments (first stage).
• RosenzweigWolpin2000-NaturalNaturalExperiments — structuralist critique: natural experiments still need an economic model to interpret what is identified.
• DeChaisemartinDHaultfoeuille2018-FuzzyDiD — fuzzy DiD as an IV/LATE problem in a panel setting; bridges DiD and IV.
• FreyaldenhovenEtAl2019-PreEventTrendsPanelEventStudy — IV inside the event study: policy leads as excluded instruments, an unaffected covariate as the endogenous proxy for the confound; bridges DiD’s pre-trends problem and IV.
• AngristPischke2010-CredibilityRevolution — situates IV within the broader design-based credibility revolution.

Key Concepts

LATE · Exclusion-Restriction · Monotonicity · Randomization (instrument independence) · Weak-Instruments (relevance / first stage) · Causal-Estimand · SUTVA

Debates & Contradictions

• What does IV estimate? The LATE revolution (Imbens–Angrist, here via Angrist 2022) reframed IV as recovering a complier-specific effect, not a universal ATE — a shift from the older “IV estimates the structural parameter” view that some structural econometricians still contest.
• Independence vs exclusion. Angrist stresses that random assignment buys independence cheaply, but the exclusion restriction is a separate, untestable, substantive commitment — the assumption most IV critiques actually target.
• External validity. A complier-defined estimand is internally credible but may not generalize to always-takers or never-takers — the recurring price of design- based identification.
• Design vs. structure. RosenzweigWolpin2000-NaturalNaturalExperiments argues natural-experiment IV still needs an economic model to interpret the estimated parameter — a structuralist pushback on atheoretical “as-if random” identification.
• Weak and invalid instruments. Beyond exclusion, a weak first stage biases 2SLS toward OLS and breaks inference (Weak-Instruments, Murray2006-WeakAndInvalidInstruments); relevance is testable, validity is not.

Next

IV shares its potential-outcomes foundation with Foundations and its fuzzy-design and changes-in-changes machinery with DiD. Fuzzy RD is an IV problem at the cutoff — see RDD and CattaneoEtAl2020-RDDHandbook.