Full Citation
Title: Pre-Tax Wage and Salary Income Inequalities in Largest Metropolitan Areas in the United States
Citation Type: Journal Article
Publication Year: 2021
ISBN:
ISSN: 2520-6761
DOI: 10.21272/bel.5(2).59-65.2021
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PMID:
Abstract: Hayward, and Washington-Arlington-Alexandria. These ten metropolitan areas employed over 39 million individuals representing well over a quarter of the total employed labour force in the USA. Mean, median, standard error of the mean, 25th percentile, 50th percentile, and the Gini coefficient of pre-tax wages and salaries are presented for each metropolitan area. The metros differ significantly in terms of average pre-tax wages and salaries. They differ significantly in terms of the spread in the distribution of pre-tax wages and salaries measured both in terms of the inter-quartile range (the difference between 75th and 25th percentiles) and the Gini coefficient. San Francisco-Oakland-Hayward is found to have both the highest average pre-tax wages and salaries and widest inequality as measured by the Gini coefficient. The Smallest Gini coefficient is observed in Washington-Arlington-Alexandria metropolitan area. Inequality measured in terms of the Gini coefficient is nearly 15% higher in San Francisco-Oakland-Hayward as compared to Washington-Arlington-Alexandria. The average pre-tax wages and salaries are about 83% higher in San Francisco-Oakland-Hayward than Miami-Fort Lauderdale-West Palm Beach, the lowest in the nation. While aggregate nationwide inequalities attract intense attention, these regional variations point to significant and wide-ranging variations between different regions (metropolitan cities). By focusing on the pre-tax wages and salaries, this study allows us to tie inequalities that are most closely related to the labour market conditions, unlike other sources of income like capital gains, inheritance, government transfers, etc.
Url: http://doi.org/10.21272/bel.5
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Authors: Ray, Achintya
Periodical (Full): Business Ethics and Leadership
Issue: 2
Volume: 5
Pages: 59-65
Data Collections: IPUMS USA
Topics: Labor Force and Occupational Structure, Poverty and Welfare
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