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The purpose of this project was to measure and estimate the distribution of personal income and related economic factors in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components. Data were collected through a series of questionnaire-based interviews conducted in rural and urban areas at the end of 2002. There are ten separate datasets. The first four datasets were derived from the urban questionnaire. The first contains data about individuals living in urban areas. The second contains data about urban households. The third contains individual-level economic variables copied from the initial urban interview form. The fourth contains household-level economic variables copied from the initial urban interview form. The fifth dataset contains village-level data, which was obtained by interviewing village leaders. The sixth contains data about individuals living in rural areas. The seventh contains data about rural households, as well as most of the data from a social network questionnaire which was presented to rural households. The eighth contains the rest of the data from the social network questionnaire and is specifically about the activities of rural school-age children. The ninth dataset contains data about individuals who have migrated from rural to urban areas, and the tenth dataset contains data about rural-urban migrant households. Dataset 1 contains 151 variables and 20,632 cases (individual urban household members). Dataset 2 contains 88 variables and 6,835 cases (urban households). Dataset 3 contains 44 variables and 27,818 cases, at least 6,835 of which are empty cases used to separate households in the file. The remaining cases from dataset 3 match those in dataset 1. Dataset 4 contains 212 variables and 6,835 cases, which match those in dataset 2. Dataset 5 contains 259 variables and 961 cases (villages). Dataset 6 contains 84 variables and 37,969 cases (individual rural household members). Dataset 7 contains 449 variables and 9,200 cases (rural households). Dataset 8 contains 38 variables and 8,121 cases (individual school-age children). Dataset 9 contains 76 variables and 5,327 cases (individual rural-urban migrant household members). Dataset 10 contains 129 variables and 2,000 cases (rural-urban migrant households).

The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

The IPUMS Contextual Determinants of Health (CDOH) data series includes measures of disparities, policies, and counts by state or county for historically marginalized populations in the United States including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons as well as women.

The IPUMS CDOH data are made available through ICPSR/DSDR for merging with the National Couples' Health and Time Study (NCHAT), United States, 2020-2021 (ICPSR 38417) by approved restricted data researchers. All other researchers can access the IPUMS CDOH data via the IPUMS CDOH website.

Unlike other IPUMS products, the CDOH data are organized into multiple categories related to Race and Ethnicity, Sexual and Gender Minority, Gender, and Politics. The CDOH measures were created from a wide variety of data sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and Myers Abortion Facility Database). Measures are currently available for states or counties from approximately 2015 to 2020.

The Gender measures in this release include the state-level earnings ratio, which compares the median earnings of full-time wage and salary workers identifying as male to the median earnings of full-time wage and salary workers identifying as female in a given state in a given year. To work with the IPUMS CDOH data, researchers will need to first merge the NCHAT data to DS1 (MATCH ID and State FIPS Data). This merged file can then be linked to the IPUMS CDOH datafile (DS2) using the STATEFIPS variable.