Assessing differences in household needs: A comparison of approaches for the estimation of equivalence scales using German expenditure data
Equivalence scales are routinely applied to adjust the income of households of different size and composition. Because of their practical importance for the measurement of inequality and poverty, a large number of methods for the estimation of equivalence scales have been proposed. Until now, no comprehensive comparison of these methods has been conducted. In this paper, we employ German household expenditure data to estimate exact equivalence scales using several parametric, semiparametric, and nonparametric approaches. Using a single dataset, we find that the resulting equivalence scales do not differ greatly by method; with the exception of some outliers that yield implausible scales. Most of the equivalence scales we estimate are close to the modified OECD scale. Calculating the Gini coefficient, we find that the at-risk-of-poverty rate and the interquartile range based on the more plausible equivalence scales lead to relatively consistent assessments of inequality and poverty. We conclude that differences in estimation methods for equivalence scales might be less important than was previously thought.
Year of publication: |
2017
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Authors: | Dudel, Christian ; Garbuszus, Jan Marvin ; Schmied, Julian |
Publisher: |
Essen : RWI - Leibniz-Institut für Wirtschaftsforschung |
Subject: | Equivalence scales | household demand | inequality measurement | equivalence scale exactness | Engel curves | independence of base |
Saved in:
freely available
Series: | Ruhr Economic Papers ; 723 |
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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
ISBN: | 978-3-86788-843-1 |
Other identifiers: | 10.4419/86788843 [DOI] 1009609033 [GVK] hdl:10419/172475 [Handle] RePEc:zbw:rwirep:723 [RePEc] |
Classification: | D12 - Consumer Economics: Empirical Analysis ; I32 - Measurement and Analysis of Poverty ; C14 - Semiparametric and Nonparametric Methods ; C21 - Cross-Sectional Models; Spatial Models ; C31 - Cross-Sectional Models; Spatial Models |
Source: |
Persistent link: https://www.econbiz.de/10011764717