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Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United States over the last four decades. Employing a price index that appears appropriate for low income households, we show that poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our results are threefold. First, we identify the poor as more likely to be minorities, without a college education, never married, and living in the Midwest. Second, the importance of some factors, such as race and ethnicity, for determining poverty has declined over the last decades but they remain significant. Third, we find that social and economic factors can only partially capture the likelihood of being poor, pointing to the possibility that random factors (“bad luck”) could play a significant role.
Macroeconomics --- Economics: General --- Poverty and Homelessness --- Intelligence (AI) & Semantics --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Measurement and Analysis of Poverty --- Government Policy --- Provision and Effects of Welfare Program --- Welfare, Well-Being, and Poverty: General --- Macroeconomics: Consumption --- Saving --- Wealth --- Aggregate Factor Income Distribution --- Technological Change: Choices and Consequences --- Diffusion Processes --- Economic & financial crises & disasters --- Economics of specific sectors --- Poverty & precarity --- Machine learning --- Poverty --- Consumption --- National accounts --- Poverty measurement --- Income --- Technology --- Currency crises --- Informal sector --- Economics --- United States
Choose an application
Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United States over the last four decades. Employing a price index that appears appropriate for low income households, we show that poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our results are threefold. First, we identify the poor as more likely to be minorities, without a college education, never married, and living in the Midwest. Second, the importance of some factors, such as race and ethnicity, for determining poverty has declined over the last decades but they remain significant. Third, we find that social and economic factors can only partially capture the likelihood of being poor, pointing to the possibility that random factors (“bad luck”) could play a significant role.
United States --- Macroeconomics --- Economics: General --- Poverty and Homelessness --- Intelligence (AI) & Semantics --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Measurement and Analysis of Poverty --- Government Policy --- Provision and Effects of Welfare Program --- Welfare, Well-Being, and Poverty: General --- Macroeconomics: Consumption --- Saving --- Wealth --- Aggregate Factor Income Distribution --- Technological Change: Choices and Consequences --- Diffusion Processes --- Economic & financial crises & disasters --- Economics of specific sectors --- Poverty & precarity --- Machine learning --- Poverty --- Consumption --- National accounts --- Poverty measurement --- Income --- Technology --- Currency crises --- Informal sector --- Economics
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