{"title":"测试推定合法移民身份的有效性。","authors":"Marcelo Castillo, Alexandra Hill, Thomas Hertz","doi":"10.1215/00703370-11189687","DOIUrl":null,"url":null,"abstract":"<p><p>We evaluate the performance of a widely used technique for imputing the legal immigration status of U.S. immigrants in survey data-the logical imputation method. We validate this technique by implementing it in a nationally representative survey of U.S. farmworkers that includes a well-regarded measure of legal status. When using this measure as a benchmark, the imputation algorithm correctly identifies the legal status of 78% of farmworkers. Of all the variables included in the algorithm, we find that Medicaid participation poses the greatest challenge for accuracy. Using the American Community Survey, we show that increased Medicaid enrollments stemming from the implementation of the Affordable Care Act in 2014 led to sizable changes in the share of immigrants imputed as legal over time and across space. We explore the implications of these changes for two previous studies and conclude that including Medicaid criteria in the imputation algorithm can significantly impact research findings. We also provide tools to gauge the sensitivity of results.</p>","PeriodicalId":48394,"journal":{"name":"Demography","volume":" ","pages":"283-306"},"PeriodicalIF":3.6000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Test of the Validity of Imputed Legal Immigration Status.\",\"authors\":\"Marcelo Castillo, Alexandra Hill, Thomas Hertz\",\"doi\":\"10.1215/00703370-11189687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We evaluate the performance of a widely used technique for imputing the legal immigration status of U.S. immigrants in survey data-the logical imputation method. We validate this technique by implementing it in a nationally representative survey of U.S. farmworkers that includes a well-regarded measure of legal status. When using this measure as a benchmark, the imputation algorithm correctly identifies the legal status of 78% of farmworkers. Of all the variables included in the algorithm, we find that Medicaid participation poses the greatest challenge for accuracy. Using the American Community Survey, we show that increased Medicaid enrollments stemming from the implementation of the Affordable Care Act in 2014 led to sizable changes in the share of immigrants imputed as legal over time and across space. We explore the implications of these changes for two previous studies and conclude that including Medicaid criteria in the imputation algorithm can significantly impact research findings. We also provide tools to gauge the sensitivity of results.</p>\",\"PeriodicalId\":48394,\"journal\":{\"name\":\"Demography\",\"volume\":\" \",\"pages\":\"283-306\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Demography\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1215/00703370-11189687\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Demography","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1215/00703370-11189687","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
A Test of the Validity of Imputed Legal Immigration Status.
We evaluate the performance of a widely used technique for imputing the legal immigration status of U.S. immigrants in survey data-the logical imputation method. We validate this technique by implementing it in a nationally representative survey of U.S. farmworkers that includes a well-regarded measure of legal status. When using this measure as a benchmark, the imputation algorithm correctly identifies the legal status of 78% of farmworkers. Of all the variables included in the algorithm, we find that Medicaid participation poses the greatest challenge for accuracy. Using the American Community Survey, we show that increased Medicaid enrollments stemming from the implementation of the Affordable Care Act in 2014 led to sizable changes in the share of immigrants imputed as legal over time and across space. We explore the implications of these changes for two previous studies and conclude that including Medicaid criteria in the imputation algorithm can significantly impact research findings. We also provide tools to gauge the sensitivity of results.
期刊介绍:
Since its founding in 1964, the journal Demography has mirrored the vitality, diversity, high intellectual standard and wide impact of the field on which it reports. Demography presents the highest quality original research of scholars in a broad range of disciplines, including anthropology, biology, economics, geography, history, psychology, public health, sociology, and statistics. The journal encompasses a wide variety of methodological approaches to population research. Its geographic focus is global, with articles addressing demographic matters from around the planet. Its temporal scope is broad, as represented by research that explores demographic phenomena spanning the ages from the past to the present, and reaching toward the future. Authors whose work is published in Demography benefit from the wide audience of population scientists their research will reach. Also in 2011 Demography remains the most cited journal among population studies and demographic periodicals. Published bimonthly, Demography is the flagship journal of the Population Association of America, reaching the membership of one of the largest professional demographic associations in the world.