Arbeitspapier
Polarization measurement and inference in many dimensions when subgroups cannot be identified
The most popular general univariate polarization indices for discrete (Esteban and Ray 1994), and continuous (Duclos, Esteban and Ray 2004) variables are combined and extended to describe the extent of polarization between agents in a distribution defined over a collection of many discrete and continuous agent characteristics. A formula for the asymptotic variance of the index is also provided. The implementation of the index is illustrated with an application to Chinese urban household data drawn from six provinces in the years 1987 and 2001 (years spanning the growth and urbanization period subsequent to the economic reforms). The data relates to household adult equivalent log income, adult equivalent living space, which are both continuous variables and the education of the head of household which is a discrete variable. For this data set combining the characteristics changes the view of polarization that would be inferred from considering the indices individually.
- Language
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Englisch
- Bibliographic citation
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Series: Economics Discussion Papers ; No. 2011-20
- Classification
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Wirtschaft
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models; Multiple Variables: General
Measurement and Analysis of Poverty
- Subject
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Multivariate polarization measurement
Soziale Ungleichheit
Disparitätsmaß
Multivariate Analyse
Messung
Theorie
Stadtsoziologie
China
- Event
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Geistige Schöpfung
- (who)
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Anderson, Gordon
- Event
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Veröffentlichung
- (who)
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Kiel Institute for the World Economy (IfW)
- (where)
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Kiel
- (when)
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2011
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Anderson, Gordon
- Kiel Institute for the World Economy (IfW)
Time of origin
- 2011
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Polarization measurement and inference in many dimensions when subgroups cannot be identified
Polarization measurement and inference in many dimensions when subgroups can not be identified
Inference about non-identified SVARs
Robust inference in models identified via heteroskedasticity
Inference for VARs identified with sign restrictions
Robust Bayesian inference for set-identified models
Robust Bayesian inference for set-identified models
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Inference in partially identified heteroskedastic simultaneous equations models
Simple misspecification adaptive inference for interval identified parameters
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Polarization measurement and inference in many dimensions when subgroups cannot be identified
Polarization measurement and inference in many dimensions when subgroups can not be identified
Inference about non-identified SVARs
Robust inference in models identified via heteroskedasticity
Inference for VARs identified with sign restrictions
Robust Bayesian inference for set-identified models
Robust Bayesian inference for set-identified models
The centre cannot hold: Patterns of polarization in Nigeria
Inference in partially identified heteroskedastic simultaneous equations models
Simple misspecification adaptive inference for interval identified parameters
Inference in partially identified heteroskedastic simultaneous equations models