Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs
Open accessAbstract
Orley Ashenfelter, David Card, Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs, The Review of Economics and Statistics, Vol. 67, No. 4 (Nov., 1985), pp. 648-660
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
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?
Omitting the 12 months on either side of treatment to avoid the Ashenfelter dip would assume the pre-treatment changes are caused by transitory shocks rather than a trend break.
“While one could omit the 12 months on either side of treatment in an attempt to avoid the Ashenfelter dip, this would assume the pre-treatment changes are caused by transitory shocks rather than a trend break (see the discussion in Ashenfelter and Card, 1985).”
From Incarceration, Recidivism, and Employment (2020) · cites this paper as Ashenfelter and Card, 1985
The paper’s Section C models pre-training earnings differences as both transitory and trend-related, and its discussion of symmetric difference-in-differences estimators says their choice requires maintained assumptions. It does not discuss omitting exactly 12 months on either side of treatment; it also finds that transitory earnings shocks can persist for years. The citation supports the concern about assuming a transitory dip rather than a trend change, but not the specific 12-month rule. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe first papers that mention difference-in-differences estimators in the data are Ashenfelter and Card (1985) and Card and Sullivan (1988), which appeared as NBER working papers in 1984 and 1987, respectively.
“The first papers that mention difference-in-differences estimators in our data are Ashenfelter and Card (1985) and Card and Sullivan (1988), which appeared as NBER working papers in 1984 and 1987, respectively.”
From Technology and Big Data Are Changing Economics: Mining Text to Track Methods (2020) · cites this paper as Ashenfelter and Card (1985)
The paper discusses and estimates difference-in-differences effects (passages labeled Abstract; page unavailable), supporting its identification as a paper that mentions the estimator. Our copy does not establish that these were the first papers in the citing authors’ data, identify Card and Sullivan (1988), or verify the stated NBER working-paper dates. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 6
- Ashenfelter, Orley. "The Effect of Manpower Training on Earnings: Preliminary Results," in Proceedings of the Twenty-Seventh Annual Winter Meeting of the Industrial Relations Research Association, 1975, pp. 252-260.
- Ashenfelter, Orley. "Estimating the Effects of Training Programs on Earnings," Review of Economics and Statistics, February 1978, pp. 47-57.
- Bassi, Laurie J. "The Effect of CETA on the Postprogram Earnings of Participants," Journal of Human Resources, Fall 1983, pp. 539-556.
- Bassi, Laurie J. "Estimating the Effect of Training Programs with Non-Random Selection," Review of Economics and Statistics, February 1984, pp. 36-43.
- Heckman, James J. "The Longitudinal Analysis of Earnings." Unpublished manuscript presented at SSRC Conference on Longitudinal Studies of the Labor Market, October 1978.
- Kiefer, Nicholas M. 'The Economic Benefits from Four Government Training Programs," in Farrell E, Bloch (ed.), atm Manpower friin Greenwich,Connecticut: JAI Press, 1979, pp. 159-187.
Cited by
Sorted by citations
Recent Developments in the Econometrics of Program Evaluation
Imbens, G. W., & Wooldridge, J. M. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.1.5 · Cited by 4,926 · see citing works
Does matching overcome lalonde’s critique of nonexperimental estimators?
A. Smith, J., & E. Todd, P. (2005) · Journal of Econometrics · doi:10.1016/j.jeconom.2004.04.011 · Cited by 3,176 · see citing works
Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs
Dehejia, R. H., & Wahba, S. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10473858 · Cited by 2,395 · see citing works
Semiparametric Difference-in-Differences Estimators
Abadie, A. (2005) · The Review of Economic Studies · doi:10.1111/0034-6527.00321 · Cited by 2,286 · see citing works
Synthetic Difference-in-Differences
Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., & Wager, S. (2021) · American Economic Review · doi:10.1257/aer.20190159 · Cited by 1,518 · see citing works
Active Labour Market Policy Evaluations: A Meta‐Analysis
Card, D., Kluve, J., & Weber, A. (2010) · The Economic Journal · doi:10.1111/j.1468-0297.2010.02387.x · Cited by 1,298 · see citing works
Self-citationNatural and Quasi-Experiments in Economics
Meyer, B. D. (1995) · Journal of Business & Economic Statistics · doi:10.1080/07350015.1995.10524589 · Cited by 1,100 · see citing works
Identification and Inference in Nonlinear Difference-in-Differences Models
Athey, S., & Imbens, G. W. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00668.x · Cited by 1,084 · see citing works
The Estimation of Causal Effects by Difference-in-Difference Methods
Lechner, M. (2011) · Foundations and Trends® in Econometrics · doi:10.1561/0800000014 · Cited by 935 · see citing works
THE ESTIMATION OF CAUSAL EFFECTS FROM OBSERVATIONAL DATA
Winship, C., & Morgan, S. L. (1999) · Annual Review of Sociology · doi:10.1146/annurev.soc.25.1.659 · Cited by 890 · see citing works
Beyond baseline and follow-up: The case for more T in experiments
McKenzie, D. (2012) · Journal of Development Economics · doi:10.1016/j.jdeveco.2012.01.002 · Cited by 871 · see citing works
Pre-Event Trends in the Panel Event-Study Design
Freyaldenhoven, S., Hansen, C., & Shapiro, J. M. (2019) · American Economic Review · doi:10.1257/aer.20180609 · Cited by 427 · see citing works
Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis
Doudchenko, N., & Imbens, G. (2016) · doi:10.3386/w22791 · Cited by 410 · see citing works
Incarceration, Recidivism, and Employment
Bhuller, M., Dahl, G. B., Løken, K. V., & Mogstad, M. (2020) · Journal of Political Economy · doi:10.1086/705330 · Cited by 335 · see citing works
A multidisciplinary survey on discrimination analysis
Romei, A., & Ruggieri, S. (2014) · The Knowledge Engineering Review · doi:10.1017/s0269888913000039 · Cited by 288 · see citing works
The Effects of Local Police Surges on Crime and Arrests in New York City
MacDonald, J., Fagan, J., & Geller, A. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157223 · Cited by 145 · see citing works
What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations
Card, D., Kluve, J., & Weber, A. (2015) · doi:10.3386/w21431 · Cited by 136 · see citing works
Self-citationTechnology and Big Data Are Changing Economics: Mining Text to Track Methods
Currie, J., Kleven, H., & Zwiers, E. (2020) · AEA Papers and Proceedings · doi:10.1257/pandp.20201058 · Cited by 86 · see citing works
Causal models for longitudinal and panel data: a survey
Arkhangelsky, D., & Imbens, G. (2024) · The Econometrics Journal · doi:10.1093/ectj/utae014 · Cited by 50 · see citing works
Francisco, K. A., & Tanaka, M. (2019) · Economics of Education Review · doi:10.1016/j.econedurev.2019.101927 · Cited by 21 · see citing works
Rong, W., & Swink, M. (2026) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2026.101177
- Authors
- Ashenfelter, O., & Card, D.
- Affiliations
- National Bureau of Economic Research (US)
- ORCID
- Card, David
- Venue
- The Review of Economics and Statistics
- Publisher
- JSTOR
- Published
- 1985-11
- Volume
- 67
- Issue
- 4
- Pages
- 648
- ISSN
- 0034-6535 (ISSN-L)
- OpenAlex
- W2171040166
- Cited by
- 1,023
- References
- 0
- Citations by year
- 2026: 29 · 2025: 51 · 2024: 44 · 2023: 49 · 2022: 56 · 2021: 67 · 2020: 90 · 2019: 60 · 2018: 66 · 2017: 54 · 2016: 45 · 2015: 42 · 2014: 33 · 2013: 45 · 2012: 28
- FWCI
- 14.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.nber.org
- Locations
- The Review of Economics and Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Psychology › Applied Psychology › Human Resource Development and Performance Evaluation
- Keywords
- training program, earnings, returns to training, program evaluation
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