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Trends in Earnings Inequality and Earnings Instability among U.S. Couples: How Important is Assortative Matching?

January 2015

Working Paper Number:

CES-15-04

Abstract

We examine changes in inequality and instability of the combined earnings of married couples over the 1980-2009 period using two U.S. panel data sets: Social Security earnings data matched to Survey of Income and Program Participation panels (SIPP-SSA) and the Panel Study of Income Dynamics. Relative to male earnings inequality, the inequality of couples' earnings is both lower in levels and rises by a smaller amount. We also find that couples' earnings instability is lower in levels compared to male earnings instability and actually declines in the SIPP-SSA data. While wives' earnings played an important role in dampening the rise in inequality and year-to-year variation in resources at the family level, we find that marital sorting and coordination of labor supply decisions at the family level played a minor role. Comparing actual couples to randomly paired simulated couples, we find very similar trends in earnings inequality and instability.

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, recession, retirement, salary, ssa, earn, family, household income, fertility, marriage, divorced, earnings inequality, women earnings, couple

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

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Social Security Administration, National Bureau of Economic Research, Stern School of Business, Survey of Income and Program Participation, Social Security, Research Data Center, PSID, Master Earnings File

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