The DOI matches its Crossref record; 96 of the 233 references it cites were found in a registry or an index.
Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments
Open accessAbstract
Instrumental variables was first used in the 1920s to estimate supply and demand elasticities and later to correct for measurement error in single equation models. Recently, instrumental variables have been widely used to reduce bias from omitted variables in estimates of causal relationships. Intuitively, instrumental variables methods use only a portion of the variability in key variables to estimate the relationships of interest; if the instruments are valid, that portion is unrelated to the omitted variables. We discuss the mechanics of instrumental variables and the qualities that make for a good instrument, devoting particular attention to instruments derived from “natural experiments.”
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Observational studies using carefully chosen IVs are sometimes regarded as being equivalent to quasi experiments regarding their power to support causal claims (Angrist and Krueger 2001).”
From Financial literacy, financial advice, and financial behavior (2017) · cites this paper as Angrist and Krueger 2001
In the citing paper
“IV analyses can be applied to any potential source of randomization, including intentionally designed RCTs or quasi-randomization in natural experiments.15,16”
From Mendelian randomization (2022) · cites this paper as [15]
In the citing paper
“IV analyses are an alternative estimation method that can be used to derive an estimate of the causal effect of the treatment (here, CRP) on the outcome (SBP) by accounting for the size of the association between randomization and CRP.3,4,12–15”
From Mendelian randomization (2022) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Filders, R. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90130-2 · Cited by 16,765
Introductory Econometrics: A Modern Approach
Wooldridge, J. M. (1999) · Cited by 14,354
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Journal of Economic Literature
Durlauf, S. N. (2019) · AEA Papers and Proceedings · doi:10.1257/pandp.109.633 · Cited by 7,666
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. H. (1997) · Econometrica · doi:10.2307/2171753 · Cited by 7,081
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302
Statistics and Causal Inference
Holland, P. W. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478354 · Cited by 5,293
Moffitt, R. (2009) · American Economic Review · doi:10.1257/aer.99.2.660 · Cited by 4,888
Identification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230
Self-citationIdentification and estimation of local average treatment effects
Imbens, G. W., & Angrist, J. D. (1994) · Econometrica · doi:10.2307/2951620 · Cited by 4,101
Self-citation
Flagged first, then by citations
Research works printed but not linked: 6
- Angrist Joshua D, 1990, American Economic Review, 80, 313
- Bronars Stephen G, 1994, American Economic Review., 84, 1141
- Haavelmo Trygve, 1944, Econometrica, 1
- Levitt Steven D, 1997, American Economic Review, 87, 270
- Meyer Bruce D., W., 1995, American Economic Review, 85, 322
- Reiersøl Olav, 1945, Arkiv för Matematik, Astronomi och Fysik. 32a, 4, 1
Cited by
Sorted by citations
Do free trade agreements actually increase members' international trade?
Baier, S. L., & Bergstrand, J. H. (2007) · Journal of International Economics · doi:10.1016/j.jinteco.2006.02.005 · Cited by 2,692
Economic Shocks and Civil Conflict: An Instrumental Variables Approach
Miguel, E., Satyanath, S., & Sergenti, E. (2004) · Journal of Political Economy · doi:10.1086/421174 · Cited by 2,460
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441
Harrison, G. W., & List, J. A. (2004) · Journal of Economic Literature · doi:10.1257/0022051043004577 · Cited by 2,282
Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229
Metadata
- Authors
- Angrist, J. D., & Krueger, A. B.
- Affiliations
- Massachusetts Institute of Technology (US)
- Princeton University (US)
- ORCID
- Angrist, Joshua D
- Venue
- Journal of Economic Perspectives
- Publisher
- American Economic Association
- Published
- 2001-11-01
- Volume
- 15
- Issue
- 4
- Pages
- 69-85
- ISSN
- 0895-3309 (ISSN-L)
- OpenAlex
- W3123059484
- Cited by
- 2,355
- References
- 98
- Citations by year
- 2026: 58 · 2025: 115 · 2024: 105 · 2023: 124 · 2022: 107 · 2021: 119 · 2020: 144 · 2019: 116 · 2018: 92 · 2017: 103 · 2016: 115 · 2015: 124 · 2014: 121 · 2013: 113 · 2012: 131
- FWCI
- 28.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- The Journal of Economic Perspectives (publishedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Monetary Policy and Economic Impact
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Keywords
- instrumental variables, identification, natural experiment, omitted variable bias, causal inference, supply and demand elasticities, measurement error, assessment validity, econometrics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review