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 sizes and compositions. 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, however, no comprehensive comparison of current methods has been conducted. In this paper, we employ German household expenditure data to estimate equivalence scales using several parametric, semiparametric, and nonparametric approaches. Using a single dataset, we find that some approaches yield more plausible results than others while implausible scales are mostly based on linear Engel curves. The results we consider plausible are close to the modified OECD scale, and to the square root scale for larger households

Income Dependent Equivalence Scales, Inequality, and Poverty

Most equivalence scales which are applied in research on poverty and inequality do not depend on income, although there is strong empirical evidence that equivalence scales in fact are income dependent. This paper explores the consistency of results derived from income independent and income dependent scales. It is shown that scales of both types inevitably lead to differing assessments of poverty and inequality under quite general conditions. German microdata will be used to demonstrate and illustrate our findings. Our results provide evidence that income independent scales should be replaced with income dependent equivalence scales

Non-Parametric Preprocessing for the Estimation of Equivalence Scales

Empirically analyzing household behavior usually relies on informal data preprocessing. That is, before an econometric model is estimated, observations are selected in such a way that the resulting subset of data can be assumed to be sufficiently homogeneous with respect to the specific research question pursued. For example, households with members above retirement age may be excluded where it seems important that they differ from other households with respect to time use and home production. We propose the use of matching techniques and balance checking at this initial stage. This can be interpreted as a non-parametric approach to preprocessing data and as a way to formalize informal procedures. To illustrate this, we use German micro-data on household expenditure to estimate equivalence scales as a specific example. Our results show that matching leads to results which are more stable with respect to model specification and that this type of formal preprocessing is especially useful if one is mainly interested in results for specific subgroups, such as low-income households

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 sizes and compositions. 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, however, no comprehensive comparison of current methods has been conducted. In this paper, we employ German household expenditure data to estimate equivalence scales using several parametric, semiparametric, and nonparametric approaches. Using a single dataset, we find that some approaches yield more plausible results than others while implausible scales are mostly based on linear Engel curves. The results we consider plausible are close to the modified OECD scale, and to the square root scale for larger households

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.Äquivalenzskalen werden routinemäßig angewandt, um Einkommen von Haushalten unterschiedlicher Größe und Zusammensetzung vergleichbar zu machen. Aufgrund ihrer praktischen Relevanz für die Messung von Ungleichheit und Armut wurden etliche Methoden für die Schätzung von Äquivalenzskalen vorgeschlagen. Bis jetzt wurde jedoch noch kein umfassender Vergleich dieser Methoden vorgenommen. In dieser Arbeit werden deutsche Haushaltsausgabedaten verwendet, um exakte Äquivalenzskalen mittels parametrischer, semi- und nichtparametrischer Verfahren zu ermitteln. Auf Basis eines einheitlichen Datensatzes kann gezeigt werden, dass sich die aus den unterschiedlichen Verfahren resultierenden Äquivalenzskalen nur wenig voneinander unterscheiden, mit der Ausnahme von wenigen Ausreißern. Die meisten der geschätzten Äquivalenzskalen sind nahe an der modifizierten OECD-Skala. Sie führen zudem zu relativ konsistenten Ergebnissen bei diversen Armuts- und Ungleichheitsmaßen. Insgesamt zeigt sich, dass die verschiedenen Schätzmethoden für Äquivalenzskalen zu einheitlicheren Ergebnissen führen als bisher gedacht

Development of family income since the 1990s: A fresh look at German microdata using income-dependent equivalence scales

Income inequality and poverty risks receive a lot of attention in public debates and current research. However, the situation of families that di?er in size and composition is rarely considered more closely in this context. Relevant research typically relies on equivalence scales to make income comparable across di?erent types of households. The standard approach for doing so is based on the so-called "(modi?ed) OECD scale". Instead, we apply income-dependent equivalence scales in this paper to assess how the ?nancial situation of families living in Germany has developed since the early 1990s. Among other things, our results indicate that poverty risks for households with children - especially for single parents - are considerably higher than was previously found. We conclude that the application of income-dependent equivalence scales is required for applied research in income inequality, especially if one is concerned with the composition, not just the size of the population at poverty risk

Assessing differences in household needs

Equivalence scales are routinely applied to adjust the income of households of different sizes and compositions. 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, however, no comprehensive comparison of current methods has been conducted. In this paper, we employ German household expenditure data to estimate equivalence scales using several parametric, semiparametric, and nonparametric approaches. Using a single dataset, we find that some approaches yield more plausible results than others while implausible scales are mostly based on linear Engel curves. The results we consider plausible are close to the modified OECD scale, and to the square root scale for larger households

Regelbedarfsermittlung für die Grundsicherung: Perspektiven für die Weiterentwicklung

In der Debatte über die Anfang 2017 vorgenommene Neufestsetzung der Sozialleistungen nach dem SGB II und XII kehren viele Themen aus den öffent-lichen Diskussionen vor Einführung des Regelbedarfs-Ermittlungsgesetzes (RBEG) im Jahr 2011 wieder. Entscheidungen über die Höhe dieser Leistungen sind grundsätzlich normativ geprägt. Viele Aspekte des Verfahrens sind aber methodischen Überlegungen zugänglich. Vor diesem Hintergrund diskutiert der Beitrag Möglichkeiten und Grenzen der Regelbedarfsermittlung nach einem “Statistikmodell“ und macht konkrete Vorschläge für wünschenswerte Aktualisierungen und mögliche Weiterentwicklungen. Ziel ist, ein sachgerechtes und konsistenteres System der Regelbedarfe für verschiedene Haushaltsmitglieder zu entwickeln als bisher.   Assessing Social Assistance Benefits: Perspectives for Refining the Current Approach In debates about the recent re-assessment of welfare benefits for job-seekers and other needy individuals, many issues reappear that have been publicly discussed in 2011, when the current legal framework was defined. Basically, decisions regarding the level of these benefits are normative in their nature. But many aspects of the procedures involved can be subjected to methodological considerations. Against this background, the paper discusses options and limitations of assessing welfare benefits relying on a “statistics approach” and suggests a number of up-dates and refinements. The task is to develop a scheme of subsistence-level benefits for households of differing size that is adequate and more consistent than the existing one. JEL–Klassifizierung: C18, D10, D12, H5

Income-dependent equivalence scales: A fresh look at German micro-data

Income inequality and poverty risks receive a lot of attention in public debates and current research. To make income comparable across different types of households, applying the "(modified) OECD scale" – an equivalence scale with fixed weights for each household type – has become a quasi-standard in research. Instead, we derive a base-dependent equivalence scale allowing for scale weights that vary with income, building on micro-data from Germany. Our results suggest that appropriate equivalence scales are much steeper at the lower end of the income distribution than they are for higher income levels. We illustrate our findings by applying them to data on family income differentiated by household types. It turns out that using income-dependent equivalence scales matters for applied research on income inequality, especially if one is concerned with the composition, not just the size of the population at poverty risk

Income-dependent equivalence scales

Income inequality and poverty risks receive a lot of attention in public debates and current research. To make income comparable across different types of households, applying the "(modified) OECD scale" – an equivalence scale with fixed weights for each household type – has become a quasi-standard in research. Instead, we derive a base-dependent equivalence scale allowing for scale weights that vary with income, building on micro-data from Germany. Our results suggest that appropriate equivalence scales are much steeper at the lower end of the income distribution than they are for higher income levels. We illustrate our findings by applying them to data on family income differentiated by household types. It turns out that using income-dependent equivalence scales matters for applied research on income inequality, especially if one is concerned with the composition, not just the size of the population at poverty risk