The DOI matches its Crossref record.
Regional Variation in Earnings Inequality in Reform-Era Urban China
Abstract
This article studies the regional variation in earnings inequality in contemporary urban China, focusing on the relationship between the pace of economic reforms and earning determination. Through a multilevel analysis, it shows that economic growth depresses the retunrs to education and work experience and does not affect the net differences between party members and nonmembers and between men and women. Overall earning inequality remains low and only slightly correlated with economic growth because, in faster-growing cities, the tendency toward higher levels of inequality is somewhat offset by the lower returns to human capital. A plausible interpretation is that these results are largely due to the lack of a true labor market in urban China.
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
Cited by
Economic Transformation and Income Inequality in Urban China: Evidence from Panel Data
Zhou, X. (2000) · American Journal of Sociology · doi:10.1086/210401 · Cited by 477
The Chinese General Social Survey (2003-8): Sample Designs and Data Evaluation
Bian, Y., & Li, L. (2012) · Chinese Sociological Review · doi:10.2753/csa2162-0555450104 · Cited by 275
Do Sons or Daughters Give More Money to Parents in Urban China?
Xie, Y., & Zhu, H. (2009) · Journal of Marriage and Family · doi:10.1111/j.1741-3737.2008.00588.x · Cited by 233
Self-citationSons, Daughters, and Intergenerational Support in China
Lei, L. (2013) · Chinese Sociological Review · doi:10.2753/csa2162-0555450302 · Cited by 115
Gerber, T. P. (2000) · Social Science Research · doi:10.1006/ssre.1999.0651 · Cited by 104
Metadata
- Authors
- Xie, Y., & Hannum, E.
- Venue
- American Journal of Sociology
- Publisher
- University of Chicago Press
- Published
- 1996-01
- Volume
- 101
- Issue
- 4
- Pages
- 950-992
- ISSN
- 0002-9602 (ISSN-L)
- 1537-5390
- OpenAlex
- W1989748059
- Cited by
- 369
- References
- 0
- FWCI
- 37.87
- 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: Regional Variation in Earnings Inequality in Reform-Era Urban China. https://app.cochat.ai/papers/10.1086/230785
- The paper
- Xie, Y., & Hannum, E. (1996). Regional Variation in Earnings Inequality in Reform-Era Urban China. American Journal of Sociology. https://doi.org/10.1086/230785
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.