Mostly Harmless Econometrics: An Empiricist's Companion
Abstract
The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science. An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications
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Variance-based approaches build on a counterfactual understanding of causation, often developed as the potential outcomes framework.
“Variance-based approaches build on a counterfactual understanding of causation - often developed as the potential outcomes framework (Woodward, 2003; Rubin, 2005; Angrist and Pischke, 2009).”
From Multi-Method Research in the Social Sciences: A Review of Recent Frameworks and a Way Forward (2020) · cites this paper as Angrist and Pischke, 2009
With a within-school analysis, the failure to account for stable characteristics mathematically cannot bias the estimate.
“Put another way, with a 'within-school' analysis, the failure to account for stable characteristics mathematically cannot bias the estimate (Angrist & Pischke, 2009).”
From Fostering Belonging, Transforming Schools: The Impact of Restorative Practices (2023) · cites this paper as Angrist & Pischke, 2009
A within-school approach accounts for all time-invariant endogeneity.
“The benefit of a within-school approach is that it accounts for all time-invariant endogeneity.”
From Fostering Belonging, Transforming Schools: The Impact of Restorative Practices (2023) · cites this paper as Angrist & Pischke, 2009
The coefficients for pre-treatment periods are statistically insignificant, indicating that the parallel trends assumption holds.
“The coefficients for the pre-treatment periods are statistically insignificant, indicating that the parallel trends assumption holds (Angrist and Pischke 2009).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Angrist and Pischke 2009
The inclusion of PSA-specific monthly time trends enables an assessment of whether the findings hold after taking into account that each PSA is implementing cameras at different time points and may have diverging trends.
“The inclusion of PSA-specific monthly time trends enables an assessment of whether the findings hold after taking into account that each PSA is implementing cameras at different time points and may have diverging trends (Angrist & Pischke, 2009).”
From Police reform in public housing contexts: Body‐worn cameras, surveillance, and harm reduction in New York City Housing Authority Developments (2024) · cites this paper as Angrist & Pischke, 2009
Quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy.
“We recognize, of course, that quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions to be drawn from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy 27-30 .”
From Quantifying the prevalence and impact of overreaching causal claims in social science (2026) · cites this paper as [28]
Strictly speaking, observational data in the form of statistical covariation of causes and outcomes across many cases does not enable causal inferences to be made unless we assume that the data have the character of a natural experiment that enables us to claim that our population is split into a treatment and control group in which everything else is constant.
“Strictly speaking, observational data in the form of statistical covariation of causes and outcomes across many cases does not enable causal inferences to be made unless we assume that the data have the character of a natural experiment that enables us to claim that our population is split (either temporally or spatially) into a treatment and control group in which everything else is constant (Ang”
From Multi-Method Research in the Social Sciences: A Review of Recent Frameworks and a Way Forward (2020) · cites this paper as Angrist and Pischke, 2009
A differences-in-differences approach was tested as a sensitivity analysis.
“we tested a differences-in-differences approach26”
From Firearm and Nonfirearm Violence After Operation Peacemaker Fellowship in Richmond, California, 1996–2016 (2019) · cites this paper as [26]
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MOSTLY POINTLESS SPATIAL ECONOMETRICS?*
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“Our result is also related to that of Arkhangelsky et al. (2018) who shows that the weighted two-way fixed effects estimator can improve the synthetic control method of Abadie et al.”
MethodResultRising food prices, food price volatility, and social unrest
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National Institutions and Subnational Development in Africa *
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A large-scale analysis of racial disparities in police stops across the United States
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- Authors
- Angrist, J. D., & Pischke, J.-S.
- Venue
- Princeton University Press eBooks
- Publisher
- Princeton University Press
- Published
- 2009-12-31
- OpenAlex
- W2577227262
- Semantic Scholar
- a432377e8c4e782ff764701f50f84dca3c10663b
- Cited by
- 9,467
- References
- 173
- Citations by year
- 2026: 1243 · 2025: 1060 · 2024: 736 · 2023: 670 · 2022: 615 · 2021: 607 · 2020: 577 · 2019: 542 · 2018: 553 · 2017: 457 · 2016: 455 · 2015: 459 · 2014: 432 · 2013: 363 · 2012: 277
- FWCI
- 38.43
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Princeton University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- applied econometrics, linear regression, instrumental variables, natural experiment, difference-in-differences, regression discontinuity design, quantile regression, standard errors, causal inference, econometric methodology
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