Two flexible functional form approaches for approximating the Lorenz curve.
This paper introduces two flexible form approaches to approximate Lorenz curves. The first approach expands the inverse function of an income distribution in an exponential polynomial series and derives the Lorenz curve from it. The required convexity condition can be imposed using a Bayesian meth...
| Published in: | Journal of Econometrics Vol. 72; pp. 251 - 275 |
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| Main Authors: | , |
| Format: | Article |
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Elsevier Science
May/June 1996
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=512786574&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 512786574 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03044076 ECM jtl: Journal of Econometrics issn: 03044076 maglogo: N pubinfo: dt: May/June 1996 vid: 72 pid: 1004 pub: Elsevier Science artinfo: ui: 512786574 10.1016/0304-4076(94)01722-0 ppf: 251 ppct: 24 formats: tig: atl: Two flexible functional form approaches for approximating the Lorenz curve. aug: au: Ryu, Hang K. Slottje, Daniel Jonathan su: Lorenz curve Bayesian analysis Statistical hypothesis testing Polynomials Income inequality United States South Korea sug: subj: United States South Korea Lorenz curve Bayesian analysis Statistical hypothesis testing Polynomials Income inequality ab: This paper introduces two flexible form approaches to approximate Lorenz curves. The first approach expands the inverse function of an income distribution in an exponential polynomial series and derives the Lorenz curve from it. The required convexity condition can be imposed using a Bayesian method. The second approach approximates the Lorenz curve with a sequence of Berstein polynomial functions. The required convexity condition is automatically established in this approach. We compare these approaches with other well-known fixed functional form approaches. We evaluate the performance of these functional forms by comparing approximation errors, maximum error, and the estimates of the Gini coefficient produced by various approaches. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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