Joshua Angrist

Last updated

Joshua Angrist
Angrist, Josh Fall2015.jpg
Angrist in 2015
Born (1960-09-18) September 18, 1960 (age 61)
Institution Massachusetts Institute of Technology
Field Econometrics, labor economics
Alma mater Oberlin College (BA)
Princeton University (MA, PhD)
Orley Ashenfelter
Esther Duflo
Melissa Kearney
Contributions Local average treatment effect
Awards Nobel Memorial Prize in Economic Sciences (2021)
Information at IDEAS / RePEc
Academic background
Thesis Econometric Analysis of the Vietnam Era Draft Lottery (1989)

Joshua David Angrist (born September 18, 1960) [1] is an Israeli American economist and Ford Professor of Economics at the Massachusetts Institute of Technology. [2] In 2021 Angrist was awarded the Nobel Memorial Prize in Economics, together with David Card and Guido Imbens. Angrist and Imbens shared one half of the prize "for their methodological contributions to the analysis of causal relationships." [3]


He ranks among the world's top economists in labor economics, [4] urban economics, [5] and the economics of education, [6] and is known for his use of quasi-experimental research designs (such as instrumental variables) to study the effects of public policies and changes in economic or social circumstances. He is a co-founder and co-director of the MIT's School Effectiveness & Inequality Initiative, [7] which studies the relationship between human capital and income inequality in the U.S.


Born to a Jewish family in Columbus, Ohio, and raised in Pittsburgh, Pennsylvania, Angrist attended Oberlin College, where he received his B.A. in economics in 1982. He lived in Israel from 1982 until 1985 and served as a paratrooper in the Israeli Defence Forces. [8] Angrist received a M.A. and a Ph.D. in economics from Princeton University in 1987 and 1989, respectively. His doctoral dissertation, Econometric Analysis of the Vietnam Era Draft Lottery , was supervised by Orley Ashenfelter and later published in parts in the American Economic Review . [9] After completing his Ph.D., Angrist joined Harvard University as an assistant professor until 1991, when he returned to Israel as a senior lecturer (equivalent to an Assistant Professor in the US system) at the Hebrew University. [10] After being promoted to associate professor at Hebrew University, he joined MIT's Economics Department in 1996 as associate professor, before being raised to full professor in 1998. Since 2008, he has been MIT's Ford Professor of Economics and teaches econometrics and labor economics to its students. He additionally served as the Wesley Clair Mitchell Visiting Professor at Columbia University in 2018. [11] Angrist is affiliated with the National Bureau of Economic Research, [12] the IZA Institute of Labor Economics, the American Economic Association, American Statistical Association, Econometric Society, Population Association of America and the Society of Labor Economists. In terms of professional service, he has performed editorial duties at the journals Econometrica , American Economic Review , American Economic Journal: Applied Economics , Journal of Business and Economic Statistics , Economics Letters , Labour Economics and the Journal of Labor Economics .

Angrist holds dual US-Israeli citizenship [13] and lives in Brookline, Massachusetts.[ citation needed ]


Angrist's research interests include the economics of education and school reform, social programs and the labor market, the effects of immigration, labor market regulation and institutions, and econometric methods for program and policy evaluation. [14] He ranks among the top 50 out of over 56,000 economists registered on IDEAS/RePEc in terms of research output. [15] He is a frequent co-author of Guido Imbens, Alan B. Krueger, Victor Lavy, Parag Pathak and Jörn-Steffen Pischke. [16] Together with Pischke, Angrist published Mostly Harmless Econometrics in 2009, in which they explore econometric tools used by empirical researchers. [17] In 2014, Angrist and Pischke released Mastering 'Metrics': The Path from Cause to Effect, which is targeted at undergraduate econometrics students.

Economics of education

Research on the returns to schooling

The bulk of Angrist's research has concentrated on the economics of education, beginning with the returns to schooling. In one early study, Angrist and Krueger exploited the relationship between children's season of birth and educational attainment that is due to policies and laws setting ages for school start and compulsory schooling, finding that returns to education are close to their OLS estimates [18] and that compulsory attendance laws constrain roughly 10% of students to stay in school who would have otherwise left. [19] Another early attempt at using IV to estimate returns to schooling by Angrist and Krueger was to exploit the Vietnam-era draft lottery. [20] However, while their later research on split-sample IVs confirmed the findings of their compulsory schooling research, it failed to support the returns to schooling estimates derived from the draft-lottery research. [21] Angrist further used variation in U.S. compulsory schooling laws in research with Daron Acemoglu in order to estimate human-capital externalities, which they found to be about 1% and not statistically significant. [22] Angrist has also studied the strong decrease in the economic returns to schooling in the West Bank and Gaza Strip in the 1980s. [23] Together with Lavy, Angrist has also explored the returns to schooling in Morocco, exploiting a change in its language of instruction from French to Arabic to find that policy substantially reduced Moroccan youths' returns to schooling by deteriorating their French writing skills. [24]

Research on the determinants of student learning

Another strand of Angrist's research in the economics of education concerns the impact of various inputs and rules on learning. For instance, in further work with Lavy, Angrist exploited Maimonides' Rule, which limits class size to 40 students, in order to study the impact of class size on scholastic achievement in Israeli schools, finding that class size reduction substantially increase test scores for 4th and 5th graders, albeit not for 3rd graders. [25] In further research at Israeli schools, they find that teacher training can cost-effectively improve students' test scores (at least in secular schools), [26] that computer-aided instruction doesn't [27] and that cash incentives raised high school achievement among girls (by inducing them to increase time invested into exam preparation) but were ineffective for boys. [28] Similarly, in a study by Angrist, Philip Oreopoulos and Daniel Lang comparing the impact of academic support services, financial incentives and a combination of both on Canadian college first-year students, the combined treatment raised the grades of women throughout their first and second years but had no impact on men. [29] In research on school vouchers for private schools in Colombia with Eric Bettinger, Erik Bloom, Elizabeth King and Michael Kremer, Angrist found voucher recipients 10 pp more likely to finish lower secondary school, 5-7 pp more likely to complete high school, and to score 0.2 standard deviations higher on tests, suggesting that the vouchers' benefits likely exceeded their $24 cost. [30] [31] Another subject of Angrist's research are peer effects in education, [32] which he has e.g. explored with Kevin Lang in the context of METCO's school integrations or with Atila Abdulkadiroglu and Parag Pathak in Boston's and New York City's over-subscribed exam schools, though the effects that they find are brief and modest in both cases. [33] [34] With regard to the effect of teacher testing, which Angrist has studied with Jonathan Guryan in the U.S., he finds that state-mandated teacher testing raises teachers' wages without raising their quality, though it decreases teacher diversity by reducing the fraction of new teachers who are Hispanic. [35] In work with Lavy and Analia Schlosser, Angrist has also explored Becker's hypothesis on a trade-off between child quality and quantity by exploiting variation in twin births and parental preferences for compositions of siblings of mixed sexes, with evidence rejecting the hypothesis. [36]

Research on charter schools

Since the late 2000s, Angrist has conducted extensive research on charter schools in the U.S. with Pathak, Abdulkadiroglu, Susan Dynarski, Thomas Kane, and Christopher Walters. For instance, studying the KIPP Lynn Academy, they estimate that KIPP Lynn attendance increased students' math scores by 0.35 SD and their English scores by 0.12 SD, [37] with most of the gains accruing to students with limited English proficiency or special education needs or those who scored low at baseline. [38] Beyond KIPP Lynn, they find attendance to Boston charter schools to generally increase test scores for middle and high school students, especially for schools with binding assignment lotteries, whereas pilot schools (public schools covered by some collective bargaining provisions and more independence concerning educational policies) generally have at best statistically insignificant or small effects on students' test scores. [39] Further research has attributed the relative efficacy of urban charter schools to these schools' embrace of the No Excuses approach to urban education which emphasizes student discipline and behaviour, traditional reading and math skills, instruction time, and selective teacher hiring. [40]

Labor economics

Similar to his research on the economics of education, Angrist's research on labor economics also often seeks to exploit quasi-natural experiments to identify causal relationships. In a publication derived from his dissertation, Angrist e.g. exploits the military draft lottery during the Vietnam War to estimate that fighting in Vietnam reduced veterans' lifetime earnings by about 15% relative to those of nonveterans. [41] Taking into account veterans' benefits that subsidized education and training (e.g. through the G.I. Bill), he finds that these benefits raised schooling in the U.S. by ca. 1.4 years and veterans' earnings by 6%. [42] In further work exploiting the idiosyncrasies of U.S. military recruitment, Angrist studies the labor market impact of voluntary military service in the 1980s, estimating that voluntary soldiers serving in the 1980s earned considerably more than comparable civilians while serving and experienced comparatively higher employment rates thereafter, even though it raised their long-run civilian earnings at best modestly and - for whites - reduced them. [43] Together with Krueger, Angrist also investigated with Krueger whether U.S. World War II veterans earned more than nonveterans, finding instead that they earned at most as much as comparable nonveterans. [44] Angrist and Krueger later on summarized their work on causality in labor economics in a chapter of the Handbook of Labor Economics, with special emphasis on controls for confounding variables, fixed effects models and difference-in-differences, instrumental variables estimation and regression discontinuity designs. [45] In another study related to the U.S. military, Angrist and John H. Johnson IV use the Gulf War to estimate the effects of work-related separations on military families, showing large differences between the impact of male and female soldiers' deployment on divorce rates and spousal labor supply. [46] In work with William Evans, Angrist exploited families' preference for having siblings of mixed sex to estimate children's impact on parental labor supply, observing that family size had no impact on husbands' labor supply and that the impact on women was being overestimated through OLS. [47] In further work with Evans, he also explored the impact of the 1970 state abortion reforms on schooling and labor market outcomes, arguing that they reduced Afro-American teen fertility and thereby raised black women's rates of high school completion, college attendance and employment. [48] In another study with Acemoglu, Angrist has also analysed the consequences of the Americans with Disabilities Act of 1990 (ADA), finding a sharp drop in employment of persons with disabilities (PwDs) shortly after its inception, thus suggesting that ADA has likely hurt PwDs' labor market outcomes. [49] Angrist has also studied the U.S. marriage market, finding - by exploiting endogamy in marriages - that high male-female sex ratios increased the likelihood of female marriage and decreased their labor force participation. [50] Together with Adriana Kugler, Angrist finds that labor market institutions that reduce labor market flexibility exacerbate native job losses from immigration, especially regarding restricted product markets. [51] Angrist and Kugler also investigated the relationship between coca prices and civil conflict in Colombia, observing that financial opportunities offered by coca cultivation fueled the conflict, with cultivated rural areas witnessing pronounced increases in violence. [52]


Besides his empirical research, Angrist has also made major contributions to econometrics, especially concerning the use of instrumental variables estimations. For instance, Angrist developed a two-stage least squares (2SLS) equivalent of the efficient Wald estimator. [53] Together with Guido Imbens, he developed the concept of local average treatment effects and showed how to identify and to estimate them, [54] and how to use 2SLS to estimate the average causal effect of variable treatments. [55] In further work with Imbens and Donald Rubin, Angrist then showed how instrumental variables can be embedded within the Rubin causal model in order to identify causal effects between variables. [56] Angrist also developed with Imbens and Krueger so-called "jackknife instrumental variables estimators" to address the bias in 2SLS estimates in over-identified models [57] and has explored the interpretation of IV estimators in simultaneous equations models along with Imbens and Kathryn Graddy. [58] Again with Imbens, along with Alberto Abadie, he has also studied the effect of subsidized training due to the Job Training Partnership Act of 1982 on the quantiles of trainee earnings, finding large effects of JTPA on low-wage female workers but significant effects on men only for the upper half of the male trainee earnings distribution. [59] With regard to limited dependent variable models with binary endogenous regressors, Angrist argues in favour of using 2SLS, multiplicative models for conditional means, linear approximation of non-linear causal models, models for distribution effects, and quantile regression with an endogenous binary regressor. [60] Angrist has also explored the link between local average treatment effects and population average treatment effects, i.e., the external validity of IV estimates. [61] Finally, along with Victor Chernozhukov and Iván Fernández-Val, Angrist has also explored quantile regressions, showing that they minimize a weighted MSE loss function for specification error. [62]

In articles with Krueger as well as with Jorn-Steffen Pischke in the Journal of Economic Perspectives , Angrist has repeatedly made the case for a focus on the identification of causality in economics, e.g. using instrumental variables; [63] in particular, Angrist has argued in 2010 in response to Edward Leamer's 1983 critique of econometrics that microeconomics had experienced since then a "credibility revolution" thanks to substantial improvements in empirical research designs and renewed attention to causal relationships. [64]

Honors and awards

Angrist is a Research Fellow at the Institute for the Study of Labor (IZA). He is also a fellow of the Econometric Society. He was elected a Fellow of the American Academy of Arts and Sciences in 2006. [65] In 2007 Angrist received an honorary doctorate in Economics from the University of St. Gallen. He is the recipient of the 2011 John von Neumann Award given annually by the Rajk László College for Advanced Studies in Budapest.

Angrist won the 2021 Nobel Memorial Prize in Economics, along with Guido Imbens. The Royal Swedish Academy of Sciences wrote that:

Data from a natural experiment are difficult to interpret . . . . For example, extending compulsory education by a year for one group of students (but not another) will not affect everyone in that group in the same way. Some students would have kept studying anyway and, for them, the value of education is often not representative of the entire group. So, is it even possible to draw any conclusions about the effect of an extra year in school? In the mid-1990s, Joshua Angrist and Guido Imbens solved this methodological problem, demonstrating how precise conclusions about cause and effect can be drawn from natural experiments. [3]

See also

Related Research Articles

Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships". Jan Tinbergen is one of the two founding fathers of econometrics. The other, Ragnar Frisch, also coined the term in the sense in which it is used today.

A natural experiment is an empirical study in which individuals are exposed to the experimental and control conditions that are determined by nature or by other factors outside the control of the investigators. The process governing the exposures arguably resembles random assignment. Thus, natural experiments are observational studies and are not controlled in the traditional sense of a randomized experiment. Natural experiments are most useful when there has been a clearly defined exposure involving a well defined subpopulation such that changes in outcomes may be plausibly attributed to the exposure. In this sense, the difference between a natural experiment and a non-experimental observational study is that the former includes a comparison of conditions that pave the way for causal inference, but the latter does not.

Field experiment

Field experiments are experiments carried out outside of laboratory settings.

In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment. Intuitively, IVs are used when an explanatory variable of interest is correlated with the error term, in which case ordinary least squares and ANOVA give biased results. A valid instrument induces changes in the explanatory variable but has no independent effect on the dependent variable, allowing a researcher to uncover the causal effect of the explanatory variable on the dependent variable.

David Card Canadian economist (b. 1956)

David Edward Card is a Canadian American labour economist and professor of economics at the University of California, Berkeley. He was awarded half of the 2021 Nobel Memorial Prize in Economic Sciences "for his empirical contributions to labour economics", with Joshua Angrist and Guido Imbens jointly awarded the other half.

Susan Athey American economist

Susan Carleton Athey is an American microeconomist. She is the Economics of Technology Professor in the School of Humanities and Sciences at the Stanford Graduate School of Business. Prior to joining Stanford, she has been a professor at Harvard University and the Massachusetts Institute of Technology. She is the first female winner of the John Bates Clark Medal. She served as the consulting chief economist for Microsoft for six years and was a consulting researcher to Microsoft Research. She is currently on the boards of Expedia, Lending Club, Rover, Turo, Ripple, and non-profit Innovations for Poverty Action. She also serves as the senior fellow at Stanford Institute for Economic Policy Research. She is an associate director for the Stanford Institute for Human-Centered Artificial Intelligence and the director of Golub Capital Social Impact Lab.

In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest-posttest design that aims to determine the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. By comparing observations lying closely on either side of the threshold, it is possible to estimate the average treatment effect in environments in which randomisation is unfeasible. However, it remains impossible to make true causal inference with this method alone, as it does not automatically reject causal effects by any potential confounding variable. First applied by Donald Thistlethwaite and Donald Campbell to the evaluation of scholarship programs, the RDD has become increasingly popular in recent years. Recent study comparisons of randomised controlled trials (RCTs) and RDDs have empirically demonstrated the internal validity of the design.

Matching is a statistical technique which is used to evaluate the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment. The goal of matching is to reduce bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one non-treated unit(s) with similar observable characteristics against who the covariates are balanced out. By matching treated units to similar non-treated units, matching enables a comparison of outcomes among treated and non-treated units to estimate the effect of the treatment reducing bias due to confounding. Propensity score matching, an early matching technique, was developed as part of the Rubin causal model, but has been shown to increase model dependence, bias, inefficiency, and power and is no longer recommended compared to other matching methods.

The methodology of econometrics is the study of the range of differing approaches to undertaking econometric analysis.

Parag A. Pathak is Professor of Economics at the Massachusetts Institute of Technology and is affiliated with the National Bureau of Economic Research where he co-founded and directs the working group on market design.

Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The science of why things occur is called etiology. Causal inference is said to provide the evidence of causality theorized by causal reasoning.

Causation in economics has a long history with Adam Smith explicitly acknowledging its importance via his (1776) An Inquiry into the Nature and Causes of the Wealth of Nations and David Hume and John Stuart Mill (1848) both offering important contributions with more philosophical discussions. Hoover (2006) suggests that a useful way of classifying approaches to causation in economics might be to distinguish between approaches that emphasize structure and those that emphasise process and to add to this a distinction between approaches that adopt a priori reasoning and those that seek to infer causation from the evidence provided by data. He represented by this little table which useful identifies key works in each of the four categories.

Guido Wilhelmus Imbens is a Dutch American economist. In 2021 Imbens was awarded half of the Nobel Memorial Prize in Economic Sciences jointly with Joshua Angrist "for their methodological contributions to the analysis of causal relationships", with David Card awarded the other half. He has been Professor of Economics at the Stanford Graduate School of Business at Stanford University since 2012.

The experimentalist approach to econometrics is a way of doing econometrics that, according to Angrist and Krueger (1999): … puts front and center the problem of identifying causal effects from specific events or situations. These events or situations are thought of as natural experiments that generate exogenous variations in variables that would otherwise be endogenous in the behavioral relationship of interest. An example from the economic study of education can be used to illustrate the approach. Here we might be interested in the effect of effect of an additional year of education on earnings. Those working with an experimentalist approach to econometrics would argue that such a question is problematic to answer because, and this is using their terminology, education is not randomly assigned. That is those with different education levels would tend to also have different levels of other variables. And these other variable, many of which would be unobserved, also affect earnings. This renders the causal effect of extra years of schooling difficult to identify. The experimentalist approach looks for an instrumental variable that is correlated with X but uncorrelated with the unobservables.

Andrew Donald Roy, shortened A. D. Roy, was a British economist who is known for the Roy model of self-selection and income distribution and Roy's safety-first criterion.

The Roy model is one of the earliest works in economics on self-selection due to A. D. Roy. The basic model considers two types of workers that choose occupation in one of two sectors.

Bridget Terry Long is the 12th Dean of the Harvard Graduate School of Education, and the Saris Professor of Education and Economics. She is an economist whose research focuses on college access and success. Long is a Faculty Research Associate at the National Bureau of Economic Research and a member of the National Academy of Education.

Victor Chaim Lavy is an Israeli economist and professor at the University of Warwick and the Hebrew University of Jerusalem. His research interests include labour economics, the economics of education, and development economics. Lavy belongs to the most prominent education economists in the world.

The local average treatment effect (LATE), also known as the complier average causal effect (CACE), was first introduced into the econometrics literature by Guido W. Imbens and Joshua D. Angrist in 1994. It is the treatment effect for the subset of the sample that takes the treatment if and only if they were assigned to the treatment, otherwise known as the compliers. It is not to be confused with the average treatment effect (ATE), which is the average subject-level treatment effect; the LATE is only the ATE among the compliers. The LATE can be estimated by a ratio of the estimated intent-to-treat effect and the estimated proportion of compliers, or alternatively through an instrumental variable estimator.

Dirk Krüger is a German economist and currently Walter H. and Leonore C. Annenberg Professor in the Social Sciences and Professor of Economics at the University of Pennsylvania. He holds a secondary appointment at the Wharton School. His research focuses on macroeconomic risk, public finance and labor economics.


  1. "Angrist, Joshua David - Full record view - Libraries Australia Search".
  2. "MIT Economics: Joshua Angrist" . Retrieved May 11, 2011.
  3. 1 2 "The Prize in Economic Sciences 2021" (PDF) (Press release). Royal Swedish Academy of Sciences. October 11, 2021.
  4. Joshua Angrist ranked 15th among 3037 authors registered in the field of labor economics on IDEAS/RePEc. Retrieved July 20th, 2019.
  5. Joshua Angrist ranked 4th among 3323 authors registered in the field of urban and real estate economics on IDEAS/RePEc. Retrieved July 20th, 2019.
  6. Joshua Angrist ranked 3rd among 1427 authors registered in the field of education on IDEAS/RePEc. Retrieved July 20th, 2019.
  7. "School Effectiveness & Inequality Initiative: Joshua Angrist". May 11, 2012.
  8. "Maimonides in the classroom: The research that led Angrist to the Nobel". Times of Israel. October 11, 2021. Retrieved October 11, 2021.
  9. Angrist, Joshua D. (1990). "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records". American Economic Review. 80 (3): 313–336. JSTOR   2006669.
  10. "Curriculum Vitae: Joshua D.Angrist" . Retrieved June 10, 2011.
  11. "Joshhua D. Angrist (01/2021)". MIT Department of Economics.
  12. "NBER: Joshua Angrist" . Retrieved May 11, 2012.
  13. or empty |title= (help)
  14. Short biography of Joshua Angrist on the website of MIT. Retrieved July 20th, 2019.
  15. Joshua Angrist ranks 47th out of 56344 authors registered on IDEAS/RePEc. Retrieved July 20th, 2019.
  16. Google Scholar page of Joshua Angrist. Retrieved July 20th, 2019.
  17. "Mostly Harmless Econometrics". Princeton University Press. Retrieved May 11, 2012.
  18. Angrist, Joshua D.; Krueger, Alan B. (1991). "Does Compulsory School Attendance Affect Schooling and Earnings?". The Quarterly Journal of Economics. 106 (4): 979–1014. doi:10.2307/2937954. JSTOR   2937954. S2CID   153718259 via JSTOR.
  19. Angrist, Joshua D.; Krueger, Alan B. (1992). "The Effect of Age at School Entry on Educational Attainment: An Application of Instrumental Variables with Moments from Two Samples". Journal of the American Statistical Association. 87 (418): 328–336. doi:10.2307/2290263. JSTOR   2290263 via JSTOR.
  20. "Angrist, J.D., Krueger, A.B. (1992). Estimating the payoff to schooling using the Vietnam-era draft lottery. NBER Working Paper Series, No. 4067" (PDF).
  21. Angrist, Joshua D.; Krueger, Alan B. (April 1, 1995). "Split-Sample Instrumental Variables Estimates of the Return to Schooling". Journal of Business & Economic Statistics. 13 (2): 225–235. doi:10.1080/07350015.1995.10524597 via Taylor and Francis+NEJM.
  22. Acemoglu, Daron; Angrist, Joshua (January 1, 2000). "How Large Are Human-Capital Externalities? Evidence from Compulsory Schooling Laws". NBER Macroeconomics Annual. 15: 9–59. doi:10.1086/654403 via (Atypon).
  23. Angrist, Joshua D. (1995). "The Economic Returns to Schooling in the West Bank and Gaza Strip". The American Economic Review. 85 (5): 1065–1087. JSTOR   2950975 via JSTOR.
  24. Angrist, J.D., Lavy, V. (1997). The Effect of a Change in Language of Instruction on the Returns to Schooling in Morocco. Journal of Labor Economics, 15(1), pp. S48-S76.
  25. Angrist, Joshua D.; Lavy, Victor (1999). "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement". The Quarterly Journal of Economics. 114 (2): 533–575. doi:10.1162/003355399556061. JSTOR   2587016. S2CID   149871459 via JSTOR.
  26. Angrist, Joshua D.; Lavy, Victor (April 1, 2001). "Does Teacher Training Affect Pupil Learning? Evidence from Matched Comparisons in Jerusalem Public Schools". Journal of Labor Economics. 19 (2): 343–369. doi:10.1086/319564. S2CID   55037721 via (Atypon).
  27. Angrist, Joshua; Lavy, Victor (October 11, 2002). "New Evidence on Classroom Computers and Pupil Learning*". The Economic Journal. 112 (482): 735–765. doi:10.1111/1468-0297.00068. S2CID   17699996 via Wiley Online Library.
  28. Angrist, Joshua; Lavy, Victor (September 11, 2009). "The Effects of High Stakes High School Achievement Awards: Evidence from a Randomized Trial". American Economic Review. 99 (4): 1384–1414. doi:10.1257/aer.99.4.1384. hdl:1721.1/51829 via
  29. Angrist, Joshua; Lang, Daniel; Oreopoulos, Philip (January 11, 2009). "Incentives and Services for College Achievement: Evidence from a Randomized Trial". American Economic Journal: Applied Economics. 1 (1): 136–163. doi:10.1257/app.1.1.136. hdl:1721.1/51999. S2CID   73723906 via
  30. Angrist, Joshua; Bettinger, Eric; Bloom, Erik; King, Elizabeth; Kremer, Michael (December 11, 2002). "Vouchers for Private Schooling in Colombia: Evidence from a Randomized Natural Experiment". American Economic Review. 92 (5): 1535–1558. doi:10.1257/000282802762024629 via
  31. Angrist, Joshua; Bettinger, Eric; Kremer, Michael (2006). "Long-Term Educational Consequences of Secondary School Vouchers: Evidence from Administrative Records in Colombia". The American Economic Review. 96 (3): 847–862. doi:10.1257/aer.96.3.847. JSTOR   30034075 via JSTOR.
  32. Angrist, Joshua D. (October 1, 2014). "The perils of peer effects". Labour Economics. 30: 98–108. doi:10.1016/j.labeco.2014.05.008. hdl:1721.1/113693. S2CID   85463136 via ScienceDirect.
  33. Angrist, Joshua D.; Lang, Kevin (December 11, 2004). "Does School Integration Generate Peer Effects? Evidence from Boston's Metco Program". American Economic Review. 94 (5): 1613–1634. doi:10.1257/0002828043052169. hdl:10419/20212. S2CID   53573110 via
  34. Abdulkadiroğlu, Atila; Angrist, Joshua; Pathak, Parag (October 11, 2014). "The Elite Illusion: Achievement Effects at Boston and New York Exam Schools". Econometrica. 82 (1): 137–196. doi:10.3982/ECTA10266. hdl:10419/62423. S2CID   45092956 via Wiley Online Library.
  35. Angrist, Joshua D.; Guryan, Jonathan (October 1, 2008). "Does teacher testing raise teacher quality? Evidence from state certification requirements". Economics of Education Review. 27 (5): 483–503. doi:10.1016/j.econedurev.2007.03.002 via ScienceDirect.
  36. Angrist, Joshua; Lavy, Victor; Schlosser, Analia (2010). "Multiple Experiments for the Causal Link between the Quantity and Quality of Children". Journal of Labor Economics. 28 (4): 773–824. doi:10.1086/653830. hdl:1721.1/61947. JSTOR   10.1086/653830. S2CID   8448649.
  37. Angrist, Joshua D.; Dynarski, Susan M.; Kane, Thomas J.; Pathak, Parag A.; Walters, Christopher R. (May 11, 2010). "Inputs and Impacts in Charter Schools: KIPP Lynn". American Economic Review. 100 (2): 239–243. doi:10.1257/aer.100.2.239. hdl:1721.1/61732 via
  38. Angrist, Joshua D.; Dynarski, Susan M.; Kane, Thomas J.; Pathak, Parag A.; Walters, Christopher R. (October 11, 2012). "Who Benefits from KIPP?". Journal of Policy Analysis and Management. 31 (4): 837–860. doi:10.1002/pam.21647. hdl:1721.1/73139. S2CID   376193 via Wiley Online Library.
  39. "Abdulkadiroglu, A. et al. (2011). Accountability and flexibility in public schools: Evidence from Boston's charters and pilots. Quarterly Journal of Economics, 126(2), pp. 699-748".
  40. Angrist, Joshua D.; Pathak, Parag A.; Walters, Christopher R. (2013). "Explaining Charter School Effectiveness". American Economic Journal: Applied Economics. 5 (4): 1–27. doi:10.1257/app.5.4.1. hdl:1721.1/96157. JSTOR   43189451 via JSTOR.
  41. Angrist, Joshua D. (1990). "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records". The American Economic Review. 80 (3): 313–336. JSTOR   2006669 via JSTOR.
  42. Angrist, Joshua D. (1993). "The Effect of Veterans Benefits on Education and Earnings". Industrial and Labor Relations Review. 46 (4): 637–652. doi:10.2307/2524309. JSTOR   2524309 via JSTOR.
  43. Angrist, Joshua D. (1998). "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants". Econometrica. 66 (2): 249–288. doi:10.2307/2998558. JSTOR   2998558 via JSTOR.
  44. Angrist, Joshua; Krueger, Alan B. (January 1, 1994). "Why Do World War II Veterans Earn More than Nonveterans?". Journal of Labor Economics. 12 (1): 74–97. doi:10.1086/298344. S2CID   153981157 via (Atypon).
  45. Angrist, Joshua D.; Krueger, Alan B. (January 1, 1999). Ashenfelter, Orley C.; Card, David (eds.). Handbook of Labor Economics. 3. Elsevier. pp. 1277–1366. doi:10.1016/S1573-4463(99)03004-7. ISBN   9780444501875 via ScienceDirect.
  46. Angrist, Joshua D.; Johnson, John H. (October 1, 2000). "Effects of Work-Related Absences on Families: Evidence from the Gulf War". ILR Review. 54 (1): 41–58. doi:10.1177/001979390005400103. S2CID   154988740 via SAGE Journals.
  47. Angrist, Joshua D.; Evans, William N. (1998). "Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size". The American Economic Review. 88 (3): 450–477. JSTOR   116844 via JSTOR.
  48. Angrist, Joshua D.; Evans, William N. (January 1, 2000). Research in Labor Economics. 18. Emerald Group Publishing Limited. pp. 75–113. doi:10.1016/S0147-9121(99)18020-8. ISBN   0-7623-0584-3 via Emerald Insight.
  49. Acemoglu, Daron; Angrist, Joshua D. (October 1, 2001). "Consequences of Employment Protection? The Case of the Americans with Disabilities Act". Journal of Political Economy. 109 (5): 915–957. doi:10.1086/322836. S2CID   15460395 via (Atypon).
  50. "Angrist, J. (2002). How do sex ratios affect marriage and labor markets? Evidence from America's second generation. Quarterly Journal of Economics, 117(3), pp. 997-1038".
  51. Angrist, Joshua D.; Kugler, Adriana D. (October 11, 2003). "Protective or counter-productive? labour market institutions and the effect of immigration on eu natives*". The Economic Journal. 113 (488): F302–F331. doi:10.1111/1468-0297.00136. S2CID   16002161 via Wiley Online Library.
  52. Angrist, Joshua D.; Kugler, Adriana D. (May 1, 2008). "Rural Windfall or a New Resource Curse? Coca, Income, and Civil Conflict in Colombia". The Review of Economics and Statistics. 90 (2): 191–215. doi:10.1162/rest.90.2.191. S2CID   18641300 via Silverchair.
  53. Angrist, Joshua D. (February 3, 1991). "Grouped-data estimation and testing in simple labor-supply models". Journal of Econometrics. 47 (2): 243–266. doi:10.1016/0304-4076(91)90101-I via ScienceDirect.
  54. Imbens, Guido W.; Angrist, Joshua D. (1994). "Identification and Estimation of Local Average Treatment Effects". Econometrica. 62 (2): 467–475. doi:10.2307/2951620. JSTOR   2951620. S2CID   153123153 via JSTOR.
  55. Angrist, Joshua D.; Imbens, Guido W. (June 1, 1995). "Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity". Journal of the American Statistical Association. 90 (430): 431–442. doi:10.1080/01621459.1995.10476535 via Taylor and Francis+NEJM.
  56. Angrist, Joshua D.; Imbens, Guido W.; Rubin, Donald B. (1996). "Identification of Causal Effects Using Instrumental Variables". Journal of the American Statistical Association. 91 (434): 444–455. doi:10.2307/2291629. JSTOR   2291629. S2CID   8705497 via JSTOR.
  57. Angrist, J. D.; Imbens, G. W.; Krueger, A. B. (October 11, 1999). "Jackknife instrumental variables estimation". Journal of Applied Econometrics. 14 (1): 57–67. doi:10.1002/(SICI)1099-1255(199901/02)14:1<57::AID-JAE501>3.0.CO;2-G via Wiley Online Library.
  58. Angrist, Joshua D.; Graddy, Kathryn; Imbens, Guido W. (2000). "The Interpretation of Instrumental Variables Estimators in Simultaneous Equations Models with an Application to the Demand for Fish". The Review of Economic Studies. 67 (3): 499–527. doi:10.1111/1467-937X.00141. JSTOR   2566964 via JSTOR.
  59. Abadie, Alberto; Angrist, Joshua; Imbens, Guido (2002). "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings". Econometrica. 70 (1): 91–117. doi:10.1111/1468-0262.00270. hdl:1721.1/63745. JSTOR   2692164 via JSTOR.
  60. Angrist, Joshua D (January 1, 2001). "Estimation of Limited Dependent Variable Models With Dummy Endogenous Regressors". Journal of Business & Economic Statistics. 19 (1): 2–28. doi:10.1198/07350010152472571. S2CID   156494015 via Taylor and Francis+NEJM.
  61. Angrist, J.D. (2004). Treatment effect heterogeneity in theory and practice. Economic Journal, 114(494), pp. C52-C83.
  62. Angrist, Joshua; Chernozhukov, Victor; Fernández-Val, Iván (2006). "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure". Econometrica. 74 (2): 539–563. doi:10.1111/j.1468-0262.2006.00671.x. JSTOR   3598810 via JSTOR.
  63. Angrist, Joshua D.; Krueger, Alan B. (December 11, 2001). "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments". Journal of Economic Perspectives. 15 (4): 69–85. doi:10.1257/jep.15.4.69 via
  64. Angrist, Joshua D.; Pischke, Jörn-Steffen (June 11, 2010). "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics". Journal of Economic Perspectives. 24 (2): 3–30. doi:10.1257/jep.24.2.3 via
  65. "Book of Members, 1780–2010: Chapter A" (PDF). American Academy of Arts and Sciences. Retrieved April 18, 2011.