The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Why Have Some Indian States Done Better than Others at Reducing Rural Poverty?
Abstract
Rural poverty rankings of Indian states in 1990 were very different from those of 1960. This unevenness in progress allows us to study the causes of poverty in a developing rural economy. We model the evolution of various poverty measures using pooled state‐level data for the period 1957–91. Differences in trend rates of poverty reduction are attributed to differing growth rates of farm yield per acre and differing initial conditions; states starting with better infrastructure and human resources saw significantly higher long‐term rates of poverty reduction. Deviations from trend are attributed to inflation (which hurt the poor in the short term) and shocks to farm and non‐farm output.
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
Metadata
- Authors
- Datt, G., & Ravallion, M.
- Venue
- Economica
- Publisher
- Wiley
- Published
- 1998-02
- Volume
- 65
- Issue
- 257
- Pages
- 17-38
- ISSN
- 0013-0427 (ISSN-L)
- 1468-0335
- OpenAlex
- W2137955781
- Cited by
- 401
- References
- 1
- FWCI
- 99.09
- 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
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.
