The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments
Abstract
Labor supply theory predicts systematic heterogeneity in the impact of recent welfare reforms on earnings, transfers, and income. Yet most welfare reform research focuses on mean impacts. We investigate the importance of heterogeneity using random-assignment data from Connecticut's Jobs First waiver, which features key elements of post-1996 welfare programs. Estimated quantile treatment effects exhibit the substantial heterogeneity predicted by labor supply theory. Thus mean impacts miss a great deal. Looking separately at samples of dropouts and other women does not improve the performance of mean impacts. We conclude that welfare reform's effects are likely both more varied and more extensive than has been recognized.
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.
Integrity signals
Registry
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.
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
Cites
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
(2012) · American Economic Review · doi:10.1257/aer.102.7.i · Cited by 6,810
Identification and estimation of local average treatment effects
Imbens, G. W., & Angrist, J. D. (1994) · Econometrica · doi:10.2307/2951620 · Cited by 4,101
Journal of Economic Literature
(2017) · Journal of Economic Literature · doi:10.1257/jel · Cited by 4,052
On the measurement of inequality
Atkinson, A. B. (1970) · Journal of Economic Theory · doi:10.1016/0022-0531(70)90039-6 · Cited by 3,945
Matching As An Econometric Evaluation Estimator
Heckman, J. J., Ichimura, H., & Todd, P. (1998) · Review of Economic Studies · doi:10.1111/1467-937x.00044 · Cited by 3,807
Identification and Estimation of Local Average Treatment Effects
Angrist, J., & Imbens, G. (1995) · National Bureau of Economic Research · doi:10.3386/t0118 · Cited by 2,808
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
Hirano, K., Imbens, G. W., & Ridder, G. (2003) · Econometrica · doi:10.1111/1468-0262.00442 · Cited by 2,355
Incentive Effects of the U.S. Welfare System: A Review
Moffitt, R. (1992) · Cited by 1,110
Do Taxpayers Bunch at Kink Points?
Saez, E. (2010) · American Economic Journal: Economic Policy · doi:10.1257/pol.2.3.180 · Cited by 950
Cited by
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
Social norms and energy conservation
Allcott, H. (2011) · Journal of Public Economics · doi:10.1016/j.jpubeco.2011.03.003 · Cited by 2,802
Understanding and misunderstanding randomized controlled trials
Deaton, A., & Cartwright, N. (2018) · Social Science & Medicine · doi:10.1016/j.socscimed.2017.12.005 · Cited by 1,841
(2015) · Handbook of Regional and Urban Economics · doi:10.1016/b978-0-444-59531-7.00018-1 · Cited by 597
Causal Inference in Sociological Research
Gangl, M. (2010) · Annual Review of Sociology · doi:10.1146/annurev.soc.012809.102702 · Cited by 401
Metadata
- Authors
- Bitler, M. P., Gelbach, J. B., & Hoynes, H. W.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2006-09-01
- Volume
- 96
- Issue
- 4
- Pages
- 988-1012
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3122297245
- Cited by
- 426
- References
- 45
- FWCI
- 47.56
- Type
- journal article
- Language
- en
- Open access
- closed
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: What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments. https://app.cochat.ai/papers/10.1257/aer.96.4.988
- The paper
- Bitler, M. P., Gelbach, J. B., & Hoynes, H. W. (2006). What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments. American Economic Review. https://doi.org/10.1257/aer.96.4.988
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.
