Abstract

This study uses modeled Small Area Estimates data to analyze the labor market influences on child poverty rates in local areas. These data support analysis of small geographic areas as well as at different points of the business cycle. Statistical tests appropriate for data with geographic and intertemporal correlations are adapted for use with modeled data. The results reveal that child poverty rates in local areas vary with the diversity of the local economy, specifically with dependence on a particular industry and with the diversity of firm size. These influences have varying impact at different points of the business cycle.

Highlights

  • The spatial variation in child poverty rates is influenced by a number of labor supply and labor demand factors

  • This study demonstrates that modeled small area estimates (SAE) data can be used to analyze the spatial distribution of child poverty

  • Small area estimates data can be used to analyze the influences on local child poverty rates

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Summary

Introduction

The spatial variation in child poverty rates is influenced by a number of labor supply and labor demand factors. Friedman and Lichter (1998) have used the local demographic composition, educational attainment, and the proportion of female-headed households as measures of labor supply. Friedman and Lichter (1998) have used the local demographic composition, educational attainment, and the proportion of female-headed households as measures of labor supply. They measure labor demand with the local unemployment rate, the “underemployment” rate, and the mix of employment across industries. This and similar studies of the spatial variation in child poverty rates have, by coincidence, been focused on time periods around business cycle peaks. The Current Population Survey (CPS), for example, can be used to analyze variation in poverty in Metropolitan Statistical Areas (MSAs) but not in rural areas

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