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Estimating the Potential Impact of Combined Race and Ethnicity Reporting on Long-Term Earnings Statistics

September 2024

Working Paper Number:

CES-24-48

Abstract

We use place of birth information from the Social Security Administration linked to earnings data from the Longitudinal Employer-Household Dynamics Program and detailed race and ethnicity data from the 2010 Census to study how long-term earnings differentials vary by place of birth for different self-identified race and ethnicity categories. We focus on foreign-born persons from countries that are heavily Hispanic and from countries in the Middle East and North Africa (MENA). We find substantial heterogeneity of long-term earnings differentials within country of birth, some of which will be difficult to detect when the reporting format changes from the current two-question version to the new single-question version because they depend on self-identifications that place the individual in two distinct categories within the single-question format, specifically, Hispanic and White or Black, and MENA and White or Black. We also study the USA-born children of these same immigrants. Long-term earnings differences for the 2nd generation also vary as a function of self-identified ethnicity and race in ways that changing to the single-question format could affect.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
earnings, minority, ethnicity, ethnic, hispanic, heterogeneity, mexican, immigrant, immigrated, discriminatory, latino, racial, race, generation, ssa, intergenerational, census responses, race census

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

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:
Social Security Administration, Decennial Census, Cornell University, Unemployment Insurance, American Community Survey, Social Security Number, Longitudinal Employer Household Dynamics, Protected Identification Key, Sloan Foundation, Office of Personnel Management, Census Bureau Disclosure Review Board, 2010 Census, Disclosure Review Board, Census Numident, Some Other Race

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