Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 463

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The Disturbing "Rise" of Global Income Inequality

Open access
Sala-i-Martin, Xavier·2002·National Bureau of Economic Research

Abstract

We use aggregate GDP data and within-country income shares for the period 1970-1998 to assign a level of income to each person in the world.We then estimate the gaussian kernel density function for the worldwide distribution of income.We compute world poverty rates by integrating the density function below the poverty lines.The $1/day poverty rate has fallen from 20% to 5% over the last twenty five years.The $2/day rate has fallen from 44% to 18%.There are between 300 and 500 million less poor people in 1998 than there were in the 70s.We estimate global income inequality using seven different popular indexes: the Gini coefficient, the variance of log-income, two of Atkinson's indexes, the Mean Logarithmic Deviation, the Theil index and the coefficient of variation.All indexes show a reduction in global income inequality between 1980 and 1998.We also find that most global disparities can be accounted for by across-country, not withincountry, inequalities.Within-country disparities have increased slightly during the sample period, but not nearly enough to offset the substantial reduction in across-country disparities.The across-country reductions in inequality are driven mainly, but not fully, by the large growth rate of the incomes of the 1.2 billion Chinese citizens.Unless Africa starts growing in the near future, we project that income inequalities will start rising again.If Africa does not start growing, then China, India, the OECD and the rest of middle-income and rich countries diverge away from it, and global inequality will rise.Thus, the aggregate GDP growth of the African continent should be the priority of anyone concerned with increasing global income inequality.

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/w8904

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Cited by

See all 463

Metadata

Authors
Sala-i-Martin, X.
Venue
National Bureau of Economic Research
Published
2002-04
OpenAlex
W2100634324
Cited by
463
References
1
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

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.