CREAT: Census Research Exploration and Analysis Tool

The Parental Gender Earnings Gap in the United States

January 2017

Working Paper Number:

CES-17-68

Abstract

This paper examines the parental gender earnings gap, the within-couple differences in earnings over time, before and after the birth of a child. The presence and timing of children are important components of the gender wage gap, but there is selection in both decisions. We estimate the earnings gap between male and female spouses over time, which allows us to control for this timing choice as well as other shared external earnings shifters, such as the local labor market. We use Social Security Administration Detail Earnings Records (SSA-DER) data linked to the Survey of Income and Program Participation (SIPP) to examine a panel of earnings from 1978 to 2011 for the individuals in the SIPP sample. Our main results show that the spousal earnings gap doubles between two years before the birth of the first child and the year after that child is born. After the child's first year of life the gap continues to grow for the next five years, but at a much slower rate, then tapers off and even begins to fall once the child reaches school-age.

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, labor, yearly, retirement, salary, wage gap, socioeconomic, ssa, earn, earner, dependent, parental, fertility, income year, marriage, divorced, earnings age, women earnings

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

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:
Internal Revenue Service, Bureau of Labor Statistics, Social Security Administration, National Science Foundation, Stern School of Business, Current Population Survey, Survey of Income and Program Participation, Cornell University, Detailed Earnings Records

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