Special Issue "Econometrics and Income Inequality"
A special issue of Econometrics (ISSN 2225-1146).
Deadline for manuscript submissions: closed (31 January 2018) | Viewed by 112853
A printed edition of this Special Issue is available here.
Interests: labor economics; income distribution; education economics; microeconometrics
This Special Issue is devoted to the econometric analysis of income inequality and income distributions. Given the recent surge of inequality research, this Special Issue seeks to combine both theoretical and applied contributions which advance the econometric analysis of income inequality and income distributions. Possible topics include, but are not limited to, statistical inference for inequality measurement, inequality measurement with complex survey data, parametric or non-parametric modelling of income distributions, statistical decomposition methodology, methods to investigate the determinants of distributional change, causal inference in inequality measurement, and applications of such methods to substantive research questions in different fields of economics.
Prof. Martin Biewen
Prof. Emmanuel Flachaire
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Inequality measurement
- Complex survey data
- Incomplete data
- Robust inference
- Modelling of top tails
- Decomposition methods
- Wage inequality