Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 876

The DOI matches its Crossref record.

Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs

Open access
Ashenfelter, Orley, Card, David·1984·National Bureau of Economic Research

Abstract

In this paper we set out some methods that utilize the longitudinal structure of earnings of trainees and a comparison group to estimate the effectiveness of training for the 1976 cohort of CETA trainees.By fitting a components-of-variance model of earnings to the control group, and posing a simple model of program participation, we are able to predict the entire earnings histories of the trainees.The fit of these predictions to the pre-training earnings of the CETA participants provides a test of the model of earnings generation and program participation and simple check on the corresponding estimate of the effectiveness of training.Two factors appear to have a critical influence on the size of the estimated training effects: the time of the decision to participate in training and the presence or absence of individual-specific trends in earnings.We find considerable evidence that trainee earnings contain permanent, transitory,and trend-like components of selection bias.We are less successful in distinguishing empirically between alternative assumptions on the timing of the participation decision.If earnings in the year prior to training are the appropriate selection criterion, however, our estimate of the training effect for adult male CETA participants is about 300 dollars per year.Our estimates for female CETA participants are larger, and less sensitive to alternative models of program participation.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3386/w1489

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 876

Metadata

Authors
Ashenfelter, O., & Card, D.
Venue
National Bureau of Economic Research
Published
1984-11
OpenAlex
W3123092502
Cited by
876
References
0
Type
report
Language
en
Open access
green

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs. https://app.cochat.ai/papers/10.3386/w1489
The paper
Ashenfelter, O., & Card, D. (1984). Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs. National Bureau of Economic Research. https://doi.org/10.3386/w1489

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.