Global Income Distributions and Inequality, 1993 and 2000: Incorporating Country-Level Inequality Modeled with Beta Distributions

Chotikapanich, Duangkamon; Griffiths, William E.; Rao, D. S. Prasada; Valencia, Vicar

doi:10.1162/rest_a_00145

Cited by 87 publications

(53 citation statements)

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“…Quintano and D'Agostino (2006) use the Dagum distribution and the Biewen-Jenkins methodology to examine the dependence of inequality and poverty on personal characteristics. In an extensive study examining global inequality, Chotikapanich et al (2012) estimate special case beta2 distributions for 91 countries in 1993 and 2000. In an application involving 10 regions, Hajargasht and Griffiths (2013) find that the GB2 distribution compares favorably with the four-parameter double Pareto-lognormal distribution in terms of goodness-of-fit.…”

Section: Introductionmentioning

confidence: 99%

Using the GB2 Income Distribution

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Abstract:To use the generalized beta distribution of the second kind (GB2) for the analysis of income and other positively skewed distributions, knowledge of estimation methods and the ability to compute quantities of interest from the estimated parameters are required. We review estimation methodology that has appeared in the literature, and summarize expressions for inequality, poverty, and pro-poor growth that can be used to compute these measures from GB2 parameter estimates. An application to data from China and Indonesia is provided.

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Section: Introductionmentioning

confidence: 99%

Using the GB2 Income Distribution

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“… Beta distribution : Chotikapanich, Griffiths, Rao and Valencia (2012) estimate the three parameters of the beta distribution (for each country) using a method-ofmoments estimator based on data of income shares.…”

Section: Earlier Methods For Estimating the World Distribution Of Incomementioning

confidence: 99%

“… GDP per capita at purchasing power parity (PPP) (eg Chotikapanich, Valenzuela and Rao, 1997;Bourguignon and Morrisson, 2002;Bhalla, 2002;and Sala-i-Martin, 2006;Chotikapanich, Griffiths, Rao and Valencia, 2012);…”

Section: Earlier Methods For Estimating the World Distribution Of Incomementioning

confidence: 99%

“…We test this hypothesis in section 5. Chotikapanich, Valenzuela and Rao (1997), Table 8 of Chotikapanich, Griffiths, Rao and Valencia (2012), Figure 11.1 of Bhalla (2002), Table 1 of Bourguignon and Morrisson (2002), Table 16 of Milanovic (2002) and Table III of Sala-i-Martin (2006). Note: the country coverage in each of these works was different.…”

Section: Earlier Methods For Estimating the World Distribution Of Incomementioning

confidence: 99%

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Some are more equal than others

Alexander¹

2016

Human Resource Management International Digest

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Some are more equal than others: new estimates of global and regional inequality Zsolt DarvasHighlights: We compare four methodologies to estimate the global distribution of income and find that many methods work well, but the method based on two-parameter distributions is more accurate than other methods. This method is simpler, easier to implement and relies on a more internationally-comparable dataset of national income distributions than other approaches used in the literature to calculate the global distribution of income. We suggest a simulation-based technique to estimate the standard error of the global Gini coefficient.

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“…Milanovic, 2012) or by 'fitting' the national profile to an idealised mathematical functional form (e.g. Chotikapanich et al, 2007;Pinkovskiy and Sala-i-Martin, 2009). Unlike the GrIP model, these sorts of approaches can involve degrading the source (quintile and decile) data on distributions so that the reproductions of the national distributions in the model become inherently different from those indicated by the data input to the model.…”

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The Future of Global Poverty in a Multi-Speed World: New Estimates of Scale, Location and Cost

Edward

Sumner

2013

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 Rights and PermissionsAll rights reserved.The text and data in this publication may be reproduced as long as the source is cited. Reproductions for commercial purposes are forbidden. International Policy Centre for Inclusive Growth (IPC -IG)Poverty Practice, Bureau for Development Policy, UNDP SBS, Quadra 1, Bloco J, Ed. BNDES, 13º andar 70076-900 Brasilia, DF -Brazil Telephone: +55 61 21055000 E-mail: ipc@ipc-undp.org URL: www.ipc-undp.orgThe International Policy Centre for Inclusive Growth disseminates the findings of its work in progress to encourage the exchange of ideas about development issues. The papers are signed by the authors and should be cited accordingly. The findings, interpretations, and conclusions that they express are those of the authors and not necessarily those of the United Nations Development Programme or the Government of Brazil.Working Papers are available online at www.ipc-undp.org and subscriptions can be requested by email to ipc@ipc-undp.orgPrint ISSN: 1812-108X THE FUTURE OF GLOBAL POVERTY IN A MULTI-SPEED WORLD: NEW ESTIMATES OF SCALE, LOCATION AND COSTPeter Edward and Andy Sumner* Various recent papers have sought to make projections about the scale and locations of global poverty in the next 20 to 30 years. Such forecasts have significant policy implications because they are used to inform debates on the scale and objectives of future aid. However, these papers have produced some very different projections for global poverty so that a complex and rather inconsistent picture has emerged. Estimating even current global poverty levels is problematic for a range of reasons arising largely from the limitations of available data and the various alternative modelling approaches used to compensate for them. Forecasts for future poverty become further complicated by the range of scenarios for future economic growth and changes in inequality. Largely as a result of these differences, not only do different analysts arrive at very different understandings of the extent and prospects for global poverty but it is also extremely difficult to make meaningful comparisons between different analyses.In response to this, we introduce here a new model of growth, inequality and poverty that has been developed to allow comparative analyses under a wide range of different input assumptions. After validating the model against World Bank estimates of historical poverty, we then use it to explore and expose how, and by h...

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Global Income Distributions and Inequality, 1993 and 2000: Incorporating Country-Level Inequality Modeled with Beta Distributions

Cited by 87 publications

References 20 publications

Using the GB2 Income Distribution

Using the GB2 Income Distribution

Some are more equal than others

The Future of Global Poverty in a Multi-Speed World: New Estimates of Scale, Location and Cost

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