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dc.contributor.authorJordá, Vanesa 
dc.contributor.authorNiño Zarazúa, Miguel
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2020-02-19T11:01:25Z
dc.date.available2021-11-01T03:45:11Z
dc.date.issued2019-11
dc.identifier.issn1873-5991
dc.identifier.issn0305-750X
dc.identifier.otherECO2016-76203-C2-1-P
dc.identifier.urihttp://hdl.handle.net/10902/18215
dc.description.abstractDespite the growing interest in global inequality, assessing inequality trends is a major challenge becauseindividual data on income or consumption is not often available. Nevertheless, the periodic release of cer-tain summary statistics of the income distribution has become increasingly common. Hence, groupeddata in form of income shares have been conventionally used to construct inequality trends based onlower bound approximations of inequality measures. This approach introduces two potential sourcesof measurement error: first, these estimates are constructed under the assumption of equality of incomeswithin income shares; second, the highest income earners are not included in the household surveysfrom which grouped data is obtained. In this paper, we propose to deploy a flexible parametric model,which addresses these two issues in order to obtain a reliable representation of the income distributionand accurate estimates of inequality measures. This methodology is used to estimate the recent evolutionof global interpersonal inequality from 1990 to 2015 and to examine the effect of survey under-coverageof top incomes on the level and direction of global inequality. Overall, we find that item non-response atthe top of the distribution substantially biases global inequality estimates, but, more importantly, itmight also affect the direction of the trends.es_ES
dc.description.sponsorshipThe authors hereby acknowledge UNU-WIDER and the project World Inequality where an earlier version of this study was published. The authors are grateful to Stephen Jenkins, Branko Milanovic, Nora Lustig, Juan Gabriel Rodriguez, Gustavo Marrero, Roy Van der Weide and participants at the UM Sustainability and Development Conference, Seventh ECINEQ Meeting, the 33th Annual Congress of the European Economic Association, and UNU-WIDER internal seminar series for helpful comments on earlier versions of this paper. Vanesa Jorda wishes to acknowledge financial support from the Ministerio de Economía y Competitividad (Project ECO2016-76203-C2-1-P).es_ES
dc.format.extent15 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceWorld development 123 (2019), 104593es_ES
dc.subject.otherTop incomeses_ES
dc.subject.otherIncome distributiones_ES
dc.subject.otherTruncated Lorenz curveses_ES
dc.titleGlobal inequality: How large is the effect of top incomes?es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.worlddev.2019.06.017es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.worlddev.2019.06.017
dc.type.versionacceptedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International