Explaining International and Intertemporal Variations in Income Inequality

Li, Hongyi; Squire, Lyn; Zou, Heng-Fu

doi:10.1111/1468-0297.00271

Cited by 715 publications

(459 citation statements)

References 14 publications

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“…The results are homogeneous and for each series between-country variation represents between 80% and 90% of total variation. This suggests that inequality levels are more important than inequality trends, a conclusion also reached by Li, et al (1998). However, in our case the within-country variation is also significant and thus, we find evidence for the weaker hypothesis they test, i.e., that intertemporal shifts in inequality are modest compared with international differences.…”

Section: Descriptive Informationsupporting

confidence: 54%

“…However, we also find that within-country inequality is still important and there are significant time trends in our series. Therefore, we reject the "glacial change" hypothesis (Li, et al, 1998) that inequality does not vary significantly over time. For the specific case of OECD countries, we clearly detect a U-shape pattern that confirms the "U-turn" hypothesis of Atkinson (2003).…”

Section: Discussionmentioning

confidence: 70%

“…36 Li, et al (1998) fail to find any significant time trend. However, they only use the linear approach.…”

Section: International Patternsmentioning

confidence: 92%

“…This also provides confidence in the values of the Atkinson indexes that also use the constructed Lorenz curves. Li et al (1998) state that the estimation methods vary across different sources and therefore, the use of one standard technique can minimize this problem. Consequently, our main series include our own estimations when there is income share information, and the source data when there is no way to estimate the Gini coefficient and the Atkinson indexes.…”

Section: Compatibility Of the Source And Our Estimated Gini Coefficientsmentioning

confidence: 99%

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The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets

François

Rojas‐Romagosa

2005

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes.You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. licence. www.econstor.eu Please send questions and/or remarks of nonscientific nature to driessen@tinbergen.nl. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicatedMost TI discussion papers can be downloaded at http://www.tinbergen.nl. The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets Joseph F. Francois Tinbergen Institute (Erasmus University Rotterdam) and CEPR Hugo Rojas-Romagosa Tinbergen Institute (Erasmus University Rotterdam) August 2005Abstract: The inequality dataset compiled in the 1990s by the World Bank and extended by the UN has been both widely used and strongly criticized. The criticisms raise questions about conclusions drawn from secondary inequality datasets in general. We develop techniques to deal with national and international comparability problems intrinsic to such datasets. The result is a new dataset of consistent inequality series, allowing us to explore problems of measurement error. In addition, the new data allow us to perform parametric non-linear estimation of Lorenz curves from grouped data. This in turn allows us to estimate the entire income distribution, computing alternative inequality indexes and poverty estimates. Finally, we have used our broadly comparable dataset to examine international patterns of inequality and poverty.Keywords: Income distribution datasets, inequality trends, Lorenz curve estimation, poverty estimation JEL codes: D31, C80, O15We acknowledge support from the EU research and training network (RTN) "Trade, Industrialization, and Development," as well as research support from DFID and the World Bank. All errors are of course our own.Address correspondence to: J. Francois, Tinbergen Institute, Erasmus University Rotterdam, Burg Oudlaan 50-H8-18, 3000DR Rotterdam, NETHERLANDS. Email: francois@few.eur.nl. Data are available at www.intereconomics.com/francois/data.html. OverviewThere is a sizeable literature regarding the interaction between income inequality and other economic variables, such as growth, poverty, trade and ...

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Section: Descriptive Informationsupporting

confidence: 54%

Section: Discussionmentioning

confidence: 70%

“…36 Li, et al (1998) fail to find any significant time trend. However, they only use the linear approach.…”

Section: International Patternsmentioning

confidence: 92%

Section: Compatibility Of the Source And Our Estimated Gini Coefficientsmentioning

confidence: 99%

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The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets

François

Rojas‐Romagosa

2005

SSRN Journal

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“…The expenditure-based NSS Gini is only 36. 24 So-(1) are expenditures significantly more equally distributed, compared to income, than we would expect (a conventional adjustment, suggested by Li, Squire and Zou (1998), is 5 to 6 Gini points while here the difference is 9 Gini points), 25 or (2) Income distribution data. The source is Malanima (2006: p. 31), who uses the tax census data from 1811.…”

Section: India (Moghul) Around 1750 and India (British) 1947mentioning

confidence: 77%

Measuring Ancient Inequality

Milanović¹,

Lindert²,

Williamson³

2007

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Globalization and Inequality

Albrecht¹,

Korzeniewicz²

2012

The Wiley‐Blackwell Encyclopedia of Globalization

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The United Nations' 2005 Report on the World Social Situation: The Inequality Predicament opens with the claim that “globalization has helped to accentuate trends that show the wealthiest 20 per cent of the planet accounting for 86 per cent of all private consumption and the poorest accounting for just above 1 per cent”; the first area demanding “urgent attention” in the report is “worldwide asymmetries deriving from globalization” (United Nations 2005: 6, 9). On the other hand, albeit writing about a previous wave of globalization in the late nineteenth and early twentieth centuries, Williamson (1997: 405) concluded that “globalization was the critical factor promoting economic convergence” not only between nations, but within nations as well. These two examples illustrate deep disagreements about the impact of globalization on inequality.

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Explaining International and Intertemporal Variations in Income Inequality

Cited by 715 publications

References 14 publications

The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets

The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets

Measuring Ancient Inequality

Globalization and Inequality

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