CREAT: Census Research Exploration and Analysis Tool

From Marcy to Madison Square? The Effects of Growing Up in Public Housing on Early Adulthood Outcomes

November 2024

Working Paper Number:

CES-24-67

Abstract

This paper studies the effects of growing up in public housing in New York City on children's long-run outcomes. Using linked administrative data, we exploit variation in the age children move into public housing to estimate the effects of spending an additional year of childhood in public housing on a range of economic and social outcomes in early adulthood. We find that childhood exposure to public housing improves labor market outcomes and reduces participation in federal safety net programs, particularly for children from the most disadvantaged families. Additionally, we find there is some heterogeneity in impacts across public housing developments. Developments located in neighborhoods with relatively fewer renters and higher household incomes are better for children overall. Our estimate of the marginal value of public funds suggests that for every $1 the government spends per child on public housing, children receive $1.40 in benefits, including $2.30 for children from the most disadvantaged families.

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.
:
expenditure, spending, budget, disadvantaged, welfare, housing, residential, poverty, socioeconomic, neighborhood, saving, intergenerational, rent, homeowner, apartment, child

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, Housing and Urban Development, Department of Housing and Urban Development, American Community Survey, Social Security Number, Protected Identification Key, Earned Income Tax Credit, W-2, UC Berkeley, Temporary Assistance for Needy Families, National Academy of Sciences, Census Bureau Disclosure Review Board, Personally Identifiable Information, Census Household Composition Key

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