This OpenICPSR repository contains all replication materials for the journal article "U.S. Trends in Job Stability by Sex, Race, and Ethnicity from 1996 to 2020", published in RSF: The Russell Sage Foundation Journal of the Social Sciences. The key datasets are QWI hiring records and Current Population Survey Job Tenure Supplements.The latter dataset is a subsample of the IPUMS CPS data available from cps.ipums.org. The attached data files are intended only for replication purposes. Individuals are not to redistribute the data without permission. Contact ipums@umn.edu for redistribution requests. For all other uses of these data, please access data directly via cps.ipums.org.Any use of such data should be cited as follows: Sarah Flood, Miriam King, Renae Rodgers, Steven Ruggles, J. Robert Warren, Daniel Backman, Annie Chen, Grace Cooper, Stephanie Richards, Megan Schouweiler, and Michael Westberry. IPUMS CPS: Version 11.0 [dataset]. Minneapolis, MN: IPUMS, 2023. https://doi.org/10.18128/D030.V11.0All versions of this repository starting from V7 contain an errata documenting typos in the published article and minor numerical errors caused by the inclusion of a small number of non-response case erroneously included in the analytic sample. These changes do not substantively affect the published article's findings. Article URL: https://www.rsfjournal.org/content/11/1/224

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Occupied dwellings

UNITS IDENTIFIED: - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Mortality at household level available as unharmonized variables.

UNIT DESCRIPTIONS: - Group quarters: Households living in tent/camp/inn/hotel: or collective house, barrack, campus, etc. or no living house.

Universe

Residents in Vietnam, including those usually resident in Vietnam, but who were overseas at the time of the census; special groups were enumerated, including the police force, army and foreign affairs.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Constructed by census agency. Microdata files from CD dated November, 2010

SAMPLE DESIGN: Stratified systematic sample of enumeration areas. Strata correspond to 3 groups of districts. All dwellings/households within an enumeration area are included in the sample.

SAMPLE FRACTION: 15%

SAMPLE SIZE (person records): 14,177,590

Mode of data collection

Face-to-face [f2f]

Research instrument

Two forms: long (15% sample survey) and short (remaining 85% of the population). The long form contained both the core and sample questions.

Analysis unit

Women, Birth, Child, Man, Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-59, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Cellule de Planification et de Statistiques (CPS/SSDSPF), Institut National de la Statistique (INSTAT), Centre d’Études et d’Information Statistiques (INFO-STAT) [Mali] and ICF International.

SAMPLE UNIT: Women SAMPLE SIZE: 10424

SAMPLE UNIT: Birth SAMPLE SIZE: 33803

SAMPLE UNIT: Child SAMPLE SIZE: 10326

SAMPLE UNIT: Man SAMPLE SIZE: 4399

SAMPLE UNIT: Member SAMPLE SIZE: 58330

Mode of data collection

Face-to-face [f2f]

Analysis unit

Woman, Birth, Child, Man, Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-59, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Cellule de Planification et de Statistique du Ministere de la Sante' (CPS/MS) [Mali], Direction Nationale de la Statistique et de l'Informatique (DNSI) [Mali], and ORC Macro.

SAMPLE UNIT: Woman SAMPLE SIZE: 12849

SAMPLE UNIT: Birth SAMPLE SIZE: 48407

SAMPLE UNIT: Child SAMPLE SIZE: 13097

SAMPLE UNIT: Man SAMPLE SIZE: 3405

SAMPLE UNIT: Member SAMPLE SIZE: 66505

Mode of data collection

Face-to-face [f2f]

This paper calculates the distribution of an adjusted measure of income that deducts damages due to exposure to air pollution from reported market income in the United States from 2011 to 2014. The Gini coefficient for this measure of adjusted income is 0.682 in 2011, as compared to 0.482 for market income. By 2014, we estimate that the Gini for adjusted income fell to 0.646, while the market income Gini did not appreciably change. The inclusion of air pollution damage acts like a regressive tax: with air pollution, the bottom 20% of households lose roughly 10% of the share of income, while the top 20% of households gain 10%. We find that, unlike the case for market income, New England is not the most unequal division with respect to adjusted income. Further, the difference between adjusted income for white and Hispanics is smaller than expected. However, the gap in augmented income between whites and African-Americans is widening. Data_MMWG_PLOS_One_2018This directory contains income data, pollution levels, and vital statistics necessary to replicate the paper's findings. Data used in the paper for household income are publicly available at IPUMS-CPS , and are made available here with permission from IPUMS. Any subsequent use of these data should please cite IPUMS. For full citation, please see the attached README file.Scripts_MMWG_PLOS_One_2018This directory contains the Stata scripts necessary to replicate the results in the paper. It also contains a README file to instruct users on how to replicate. Data for household income used in the paper are publicly available at IPUMS-CPS and are made available here with permission from IPUMS. Any subsequent use of these data should please cite IPUMS. For full citation, please see the attached README file.

Current policies to reduce greenhouse gas (GHG) emissions and increase adaptation and mitigation funding are insufficient to limit global temperature rise to 1.5°C. It is clear that further action is needed to avoid the worst impacts of climate change and achieve a just climate future. Here, we offer a new perspective on emissions responsibility and climate finance by conducting an environmentally extended input output analysis that links 30 years (1990–2019) of United States (U.S.) household-level income data to the emissions generated in creating that income. To do this we draw on over 2.8 billion inter-sectoral transfers from the Eora MRIO database to calculate both supplier- and producer-based GHG emissions intensities and connect these with detailed income and demographic data for over 5 million U.S. individuals in the IPUMS Current Population Survey. We find significant and growing emissions inequality that cuts across economic and racial lines. In 2019, fully 40% of total U.S. emissions were associated with income flows to the highest earning 10% of households. Among the highest earning 1% of households (whose income is linked to 15–17% of national emissions) investment holdings account for 38–43% of their emissions. Even when allowing for a considerable range of investment strategies, passive income accruing to this group is a major factor shaping the U.S. emissions distribution. Results suggest an alternative income or shareholder-based carbon tax, focused on investments, may have equity advantages over traditional consumer-facing cap-and-trade or carbon tax options and be a useful policy tool to encourage decarbonization while raising revenue for climate finance.