Toward a Uniform Definition of Household Income

Smeeding, Timothy M.; Weinberg, Daniel H.

doi:10.1111/1475-4991.00001

Cited by 123 publications

(76 citation statements)

References 3 publications

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“…Atkinson, Rainwater and Smeeding, 1995;Sheridan and Macedrie, 1999;and Smeeding and Weinberg, 2001;Congressional Budget Office, 2016). The household is also the traditional sharing unit that is recommended by the Canberra Group for measuring income (United Nations Economic…”

Section: Householdsmentioning

confidence: 99%

Household Incomes in Tax Data: Using Addresses to Move from Tax Unit to Household Income Distributions

Larrimore

Mortenson²,

Splinter³

2017

FEDS

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Tax return data are increasingly the standard for tracking income statistics in the United States. However, these data have traditionally been limited by their inability to capture non-filers and to identify members of separate tax units living in the same household. We overcome these obstacles and create household records directly in the tax data using mailing address information included on tax forms. We then present the first set of tax-based household income and inequality measures for the entire income distribution. When comparing household income inequality results in the tax data to those using the March CPS, we confirm previous findings that the March CPS understates the inequality of household income. However, we also find that the previous approach of using tax units in the IRS data to proxy for households leads to an overstatement of household income inequality. Finally, using households in the IRS tax records, we illustrate how focusing on tax units rather than households alters the observed distribution of tax programs such as the Earned Income Tax Credit.JEL Codes: D31, H24

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Section: Householdsmentioning

confidence: 99%

Household Incomes in Tax Data: Using Addresses to Move from Tax Unit to Household Income Distributions

Larrimore

Mortenson²,

Splinter³

2017

FEDS

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“…Like other types of private in-kind income, such as imputed rent for owner-occupied housing and fringe benefits, home production improves household welfare without being reflected in the household's cash flow, either in disposable household income or in labor income (see Smeeding and Weinberg 2001). In distributional analyses, the omission of private in-kind incomes may lead to substantially biased results on economic inequality and poverty.…”

Section: Introductionmentioning

confidence: 99%

The impact of home production on economic inequality in Germany

2011

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in SOEPpapers on Multidisciplinary Panel Data Research at DIW BerlinThis series presents research findings based either directly on data from the German SocioEconomic Panel Study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and behavioral sciences: economics, sociology, psychology, survey methodology, econometrics and applied statistics, educational science, political science, public health, behavioral genetics, demography, geography, and sport science.The decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly. AbstractUsing representative income and time use-data from the German Socio-Economic Panel (SOEP), we estimate non-monetary income advantages arising from home production and analyse their impact on economic inequality. As an alternative to existing measures, we propose a predicted wage approach based on a bias-adjusted measure of hours spent on home production. Sensitivity analyses comparing results obtained from different approaches provide indications of methodological effects arising from the choice of method. Although the substantive notion of reduced inequality is stable, the degree of variation in our findings underscores the need for a harmonized approach in cross-nationally comparative research.

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“…The use of income as a measure of a household's spending power is, however, not without problems (Rossiter, 1995). Not only is there no agreement on what exactly constitutes a household's income (Smeeding & Weinberg, 2001), but there are also different ways of computing income resulting in different meanings (Rossiter, 1995). Per capita income is a measure of the amount of money a person can spend, while gross household income reflects lifestyle opportunities and is strongly correlated with educational background and age cohort effects (Loudon & Della Bitta, 1993).…”

Section: Introductionmentioning

confidence: 99%

Income differences in food consumption in the 1995 Australian National Nutrition Survey

et al. 2003

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Objective: To assess the relationships between an index of per capita income and the intake of a variety of individual foods as well as groups of food for men and women in different age groups. Design: Cross-sectional national survey of free-living men and women. Subjects: A sample of 5053 males and 5701 females aged 18 y and over who completed the Australian National Nutrition Survey 1995. Methods: Information about the frequency of consumption of 88 food items was obtained. On the basis of scores on the Food Frequency Questionnaire, regular and irregular consumers of single foods were identified. The relationships between regularity of consumption of individual foods and per capita income were analysed via contingency tables. Food variety scores were derived by assigning individual foods to conventional food group taxonomies, and then summing up the dichotomised intake scores for individual foods within each food group. Two-way ANOVA (income Â age group) were performed on the food variety scores for males and females, respectively. Results: Per capita income was extensively related to the reported consumption of individual foods and to total and food group variety indices. Generally, both men and women in low income households had less varied diets than those in higher-income households. However, several traditional foods were consumed less often by young high-income respondents, especially young women. Conclusions: Major income differentials in food variety occur in Australia but they are moderated by age and gender. Younger high-income women, in particular, appear to have rejected a number of traditional foods, possibly on the basis of health beliefs. The findings also suggest that data aggregation has marked effects on income and food consumption relationships.

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Toward a Uniform Definition of Household Income

Cited by 123 publications

References 3 publications

Household Incomes in Tax Data: Using Addresses to Move from Tax Unit to Household Income Distributions

Household Incomes in Tax Data: Using Addresses to Move from Tax Unit to Household Income Distributions

The impact of home production on economic inequality in Germany

Income differences in food consumption in the 1995 Australian National Nutrition Survey

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