Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility
Background Income is one of the most important measures of well-being, but it is notoriously difficult to measure accurately. In the United States, income data are available from surveys, tax records, and government programs, but each of these sources has important strengths and major limitations wh...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Swansea University
2019-01-01
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| Series: | International Journal of Population Data Science |
| Subjects: | |
| Online Access: | https://ijpds.org/article/view/939 |
| _version_ | 1797428408826724352 |
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| author | Carla Medalia Bruce D Meyer Amy B O'Hara Derek Wu |
| author_facet | Carla Medalia Bruce D Meyer Amy B O'Hara Derek Wu |
| author_sort | Carla Medalia |
| collection | DOAJ |
| description | Background
Income is one of the most important measures of well-being, but it is notoriously difficult to measure accurately. In the United States, income data are available from surveys, tax records, and government programs, but each of these sources has important strengths and major limitations when used alone.
Objectives
We link multiple data sources to develop the Comprehensive Income Dataset (CID), a prototype for a restricted micro-level dataset that combines the demographic detail of survey data with the accuracy of administrative measures.
Methods
By incorporating information on nearly all taxable income, tax credits, and cash and in-kind government transfers, the CID surpasses previous efforts to provide an accurate and comprehensive measure of income for the population of United States individuals, families, and households. We also evaluate the accuracy of different income sources and imputation methods.
Conclusions
While still in development, we envision the CID enhancing Census Bureau surveys and statistics by investigating measurement error, improving imputation methods, and augmenting surveys with the best possible estimates of income. It can also be used for policy related research, such as forecasting and simulating changes in programs and taxes. Finally, the CID has substantial advantages over other sources to analyze numerous research topics, including poverty, inequality, mobility, and the distributional consequences of government transfers and taxes. |
| first_indexed | 2024-03-09T08:57:30Z |
| format | Article |
| id | doaj.art-bbb35ed10a4f483e92a5a7f64f033e34 |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T08:57:30Z |
| publishDate | 2019-01-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-bbb35ed10a4f483e92a5a7f64f033e342023-12-02T12:46:02ZengSwansea UniversityInternational Journal of Population Data Science2399-49082019-01-014110.23889/ijpds.v4i1.939Linking Survey and Administrative Data to Measure Income, Inequality, and MobilityCarla Medalia0Bruce D Meyer1Amy B O'Hara2Derek Wu3U.S. Census BureauUniversity of Chicago, NBER, AEI and U.S. Census BureauGeorgetown University. Massive Data Institute, McCourt School of Public Policy, Old North, 37th and O Streets, N.W. Washington D.C. 20057The University of Chicago, Harris Public Policy, 1307 East 60th Street, Chicago, IL 60637Background Income is one of the most important measures of well-being, but it is notoriously difficult to measure accurately. In the United States, income data are available from surveys, tax records, and government programs, but each of these sources has important strengths and major limitations when used alone. Objectives We link multiple data sources to develop the Comprehensive Income Dataset (CID), a prototype for a restricted micro-level dataset that combines the demographic detail of survey data with the accuracy of administrative measures. Methods By incorporating information on nearly all taxable income, tax credits, and cash and in-kind government transfers, the CID surpasses previous efforts to provide an accurate and comprehensive measure of income for the population of United States individuals, families, and households. We also evaluate the accuracy of different income sources and imputation methods. Conclusions While still in development, we envision the CID enhancing Census Bureau surveys and statistics by investigating measurement error, improving imputation methods, and augmenting surveys with the best possible estimates of income. It can also be used for policy related research, such as forecasting and simulating changes in programs and taxes. Finally, the CID has substantial advantages over other sources to analyze numerous research topics, including poverty, inequality, mobility, and the distributional consequences of government transfers and taxes.https://ijpds.org/article/view/939incomeadministrative recordshousehold surveys |
| spellingShingle | Carla Medalia Bruce D Meyer Amy B O'Hara Derek Wu Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility International Journal of Population Data Science income administrative records household surveys |
| title | Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility |
| title_full | Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility |
| title_fullStr | Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility |
| title_full_unstemmed | Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility |
| title_short | Linking Survey and Administrative Data to Measure Income, Inequality, and Mobility |
| title_sort | linking survey and administrative data to measure income inequality and mobility |
| topic | income administrative records household surveys |
| url | https://ijpds.org/article/view/939 |
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