The DOI matches its Crossref record; 174 of the 174 references it cites were found in a registry or an index.
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
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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]
In the citing paper
“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
In the citing paper
“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]
Citations
Cites
Arellano, M., & Bond, S. (1991) · The Review of Economic Studies · doi:10.2307/2297968 · Cited by 33,272
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Longitudinal data analysis using generalized linear models
LIANG, K.-Y., & ZEGER, S. L. (1986) · Biometrika · doi:10.1093/biomet/73.1.13 · Cited by 18,550
(1963) · Medical Entomology and Zoology · Cited by 15,085
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1995) · Working Paper Series · doi:10.1920/wp.ifs.1995.9517 · Cited by 14,755
Large Sample Properties of Generalized Method of Moments Estimators
Hansen, L. P. (1982) · Econometrica · doi:10.2307/1912775 · Cited by 13,467
(2002) · Cited by 13,211
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
The Colonial Origins of Comparative Development: An Empirical Investigation: Reply
Acemoğlu, D., Johnson, S., & Robinson, J. A. (2012) · American Economic Review · doi:10.1257/aer.102.6.3077 · Cited by 6,050
Cited by
Sorted by citations
Items 1,001–1,052 of 1,052
The Political Economy Consequences of China’s Export Slowdown
Campante, F. R., Chor, D., & Li, B. (2023) · Journal of the European Economic Association · doi:10.1093/jeea/jvad007 · Cited by 58
Jangmo, A., Kuja‐Halkola, R., Pérez-Vigil, A., Almqvist, C., Bulik, C. M., D'Onofrio, B. M., Lichtenstein, P., Ahnemark, E., Werner‐Kiechle, T., & Larsson, H. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247724 · Cited by 69
Wang, Y., Cao, G., Yan, Y., & Wang, J. (2021) · Transport Policy · doi:10.1016/j.tranpol.2021.11.024 · Cited by 60
The Immigrant Wage Gap in Germany: Are East Europeans Worse Off?
Lehmer, F., & Ludsteck, J. (2011) · International Migration Review · doi:10.1111/j.1747-7379.2011.00871.x · Cited by 60
Completing Algebra II in High School: Does It Increase College Access and Success?
Kim, J., Kim, J., DesJardins, S. L., & McCall, B. P. (2015) · The Journal of Higher Education · doi:10.1080/00221546.2015.11777377 · Cited by 60
The Effect of Primary School Size on Academic Achievement
Gershenson, S., & Langbein, L. I. (2015) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373715576075 · Cited by 75
Legal Origins, Corporate Governance, and Environmental Outcomes
Kock, C. J., & Min, B. S. (2015) · Journal of Business Ethics · doi:10.1007/s10551-015-2617-1 · Cited by 60
Detecting Opportunistic Special Items
Cain, C. A., Kolev, K. S., & McVay, S. E. (2019) · Management Science · doi:10.1287/mnsc.2019.3285 · Cited by 60
The regional effects of a place-based policy – Causal evidence from Germany
Brachert, M., Dettmann, E., & Titze, M. (2019) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2019.103483 · Cited by 60
Private Equity Lemons?Evidence on Value Creation in Secondary Buyouts
Achleitner, A., & Figge, C. (2012) · European Financial Management · doi:10.1111/j.1468-036x.2012.00644.x · Cited by 60
State History and Contemporary Conflict: Evidence from Sub-Saharan AfricaPreprint
Depetris-Chauvín, E. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2679594 · Cited by 58
Refining the Evidence: British Columbia’s Carbon Tax and Household Gasoline Consumption
Lawley, C., & Thivierge, V. (2018) · The Energy Journal · doi:10.5547/01956574.39.2.claw · Cited by 59
School Outcomes of Children Raised by Same-Sex Parents: Evidence from Administrative Panel Data
Mazrekaj, D., Witte, K. D., & Cabus, S. J. (2020) · American Sociological Review · doi:10.1177/0003122420957249 · Cited by 62
Urbanization and firm access to credit
Carmignani, A., de Blasio, G., Demma, C., & D’Ignazio, A. (2021) · Journal of Regional Science · doi:10.1111/jors.12525 · Cited by 59
Ibarraran, P., Ripani, L., Taboada, B., Villa, J. M., & Garcia, B. (2014) · IZA Journal of Labor & Development · doi:10.1186/2193-9020-3-10 · Cited by 188
Causal inference on human behaviour
Bailey, D. H., Jung, A. J., Beltz, A. M., Eronen, M. I., Gische, C., Hamaker, E. L., Kording, K. P., Lebel, C., Lindquist, M. A., Moeller, J., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01939-z · Cited by 56
Marginal Effects of Merit Aid for Low-Income Students
Angrist, J., Autor, D., & Pallais, A. (2022) · The Quarterly Journal of Economics · doi:10.1093/qje/qjab050 · Cited by 69
Self-citationWhen Does Intimate Partner Violence Continue After Separation?
Ornstein, P., & Rickne, J. (2013) · Violence Against Women · doi:10.1177/1077801213490560 · Cited by 81
Innovation, competition and productivity: Firm‐level evidence for Eastern Europe and Central Asia
Friesenbichler, K., & Peneder, M. (2016) · Economics of Transition · doi:10.1111/ecot.12100 · Cited by 49
Fostering Belonging, Transforming Schools: The Impact of Restorative Practices
Darling-Hammond, S. (2023) · Learning Policy Institute · doi:10.54300/169.703 · Cited by 47
“Put another way, with a “within-school” analysis, the failure to account for stable characteristics mathematically cannot bias the estimate (Angrist & Pischke, 2009).”
MethodInadequacies in the SES–Achievement model: Evidence from PISA and other studies
Marks, G. N., & O'Connell, M. (2021) · Review of Education · doi:10.1002/rev3.3293 · Cited by 47
Human-centered artificial intelligence: a field experiment
Krakowski, S., Haftor, D., Luger, J., Pashkevich, N., & Raisch, S. (2026) · Management Science · doi:10.1287/mnsc.2022.03849 · Cited by 53
DASGUPTA, A. (2018) · American Political Science Review · doi:10.1017/s000305541800031x · Cited by 46
Multi-Method Research in the Social Sciences: A Review of Recent Frameworks and a Way Forward
Beach, D. (2020) · Government and Opposition · doi:10.1017/gov.2018.53 · Cited by 43
Sandoval-Olascoaga, S., Venkataramani, A. S., & Arcaya, M. C. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.29041 · Cited by 41
Impact of New York City’s 2014 increased minimum legal purchase age on youth tobacco use.
Macinko, J., & Silver, D. (2018) · American Journal of Public Health · doi:10.2105/ajph.2018.304340 · Cited by 41
Matthay, E. C., Farkas, K., Rudolph, K. E., Zimmerman, S., Barragan, M., Goin, D. E., & Ahern, J. (2019) · American Journal of Public Health · doi:10.2105/ajph.2019.305288 · Cited by 39
Impact of a Reform Towards Shared Parental Leave on Continued Fertility in Norway and Sweden
Duvander, A.-Z., Lappegard, T., & Johansson, M. (2020) · Population Research and Policy Review · doi:10.1007/s11113-020-09574-y · Cited by 38
Does Participatory Budgeting Change the Share of Public Funding to Low Income Neighborhoods?
Shybalkina, I., & Bifulco, R. (2019) · Public Budgeting & Finance · doi:10.1111/pbaf.12212 · Cited by 87
Ban Targeted Advertising? An Empirical Investigation of the Consequences for App Development
Kircher, T., & Foerderer, J. (2024) · Management Science · doi:10.1287/mnsc.2023.4726 · Cited by 36
Exploring the diffusion of low-energy houses: An empirical study in the European Union
Olsthoorn, M., Schleich, J., & Faure, C. (2019) · Energy Policy · doi:10.1016/j.enpol.2019.03.043 · Cited by 32
A Good Start?: The Impact of Texas’ Developmental Summer Bridge Program on Student Success
Wathington, H., Pretlow, J., & Barnett, E. (2016) · The Journal of Higher Education · doi:10.1353/jhe.2016.0010 · Cited by 31
Haber, N. A., Clarke-Deelder, E., Feller, A., Smith, E. R., Salomon, J. A., MacCormack-Gelles, B., Stone, E. M., Bolster-Foucault, C., Daw, J. R., Hatfield, L. A., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053820 · Cited by 36
Kikuta, K. (2019) · Journal of Conflict Resolution · doi:10.1177/0022002717753919 · Cited by 28
On factors that moderate the effect of buyer-supplier experience on e-procurement platforms
Hong, Y., & Shao, B. B. M. (2021) · Production and Operations Management · doi:10.1111/poms.13291 · Cited by 28
Xu, F., Medappa, P. K., Tunc, M. M., Vroegindeweij, M., & Fransoo, J. C. (2025) · arXiv · doi:10.48550/arxiv.2510.10165 · Cited by 27
A Quasi-Experimental Evaluation of the Impact of Public Assistance on Prisoner Recidivism
Luallen, J., Edgerton, J., & Rabideau, D. (2018) · Journal of Quantitative Criminology · doi:10.1007/s10940-017-9353-x · Cited by 26
Annual Levels of Immigration and Immigrant Entry Earnings in Canada
Hou, F., & Picot, G. (2014) · Canadian Public Policy · doi:10.3138/cpp.2013-017 · Cited by 22
The relationship between price and retail concentration: evidence from the US food industry
Hovhannisyan, V., Cho, C., & Bozic, M. (2019) · European Review of Agricultural Economics · doi:10.1093/erae/jby026 · Cited by 19
Kikuta, K., & Uesugi, M. (2023) · International Organization · doi:10.1017/s0020818322000261 · Cited by 17
Song, F., Agarwal, A., & Wen, W. (2024) · SSRN Electronic Journal (preprint) · doi:10.2139/ssrn.4856935 · Cited by 30
HIV/AIDS, life expectancy, and the opportunity cost model of civil war
Kustra, T. (2017) · Journal of Conflict Resolution · doi:10.1177/0022002716628281 · Cited by 16
Roads to Development: Experimental Evidence from Urban Road Pavement
Gonzalez-Navarro, M., & Quintana-Domeque, C. (2010) · doi:10.2139/ssrn.1558631 · Cited by 11
Universal Transfers, Tax Breaks and Fertility: Evidence from a Regional Reform in Norway
Hart, R. K., & Galloway, T. A. (2023) · Population Research and Policy Review · doi:10.1007/s11113-023-09793-z · Cited by 8
“Standard errors are robust with clustering on municipality (Angrist & Pischke, 2009).”
BackgroundBraga, A. A., MacDonald, J. M., & McCabe, J. E. (2024) · Criminology & Public Policy · doi:10.1111/1745-9133.12679 · Cited by 6
Nordbrandt, M. (2022) · Frontiers in Political Science · doi:10.3389/fpos.2022.921188 · Cited by 5
“One of the major benefits of panel data vis-à-vis crosssectional data is the possibility of retrieving within-unit estimates (Angrist and Pischke, 2008; Bell et al., 2018).”
BackgroundIzquierdo LLanes, G., García-López, M. J., Cabezas Ares, A., & Pinto Hernández, F. (2026) · International Journal of Housing Markets and Analysis · doi:10.1108/ijhma-03-2026-0073 · Cited by 3
The Moltbook Illusion: Separating Human Influence from Emergent Behavior in AI Agent Societies
Li, N. (2026) · arXiv · doi:10.48550/arxiv.2602.07432 · Cited by 22
“This quasi-experimental approach leverages the platform’s natural disruption as an exogenous shock 40 .”
Fertility Transitions in Developing Countries: Convergence, Timing, and Causes
Papagni, E. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3522996 · Cited by 1
Quantifying the prevalence and impact of overreaching causal claims in social science
Isch, C., Dörr, T., Fasching, N., Jennings, G., & Watts, D. J. (2026) · Nature Human Behaviour · doi:10.1038/s41562-026-02553-x
Rong, W., & Swink, M. (2026) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2026.101177
Making AI Visible, Not Vanished: How AI Policies Reshape Developer Experience on GitHub
Chen, Y., Zimmermann, T., & Trinkenreich, B. (2026) · arXiv · doi:10.48550/arxiv.2608.03329
Metadata
- 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
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
