Homelessness Is a Housing Problem

Homelessness Is a Housing Problem

Author: Gregg Colburn

Publisher: Univ of California Press

Published: 2022-03-15

Total Pages: 283

ISBN-13: 0520383796

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Using rich and detailed data, this groundbreaking book explains why homelessness has become a crisis in America and reveals the structural conditions that underlie it. In Homelessness Is a Housing Problem, Gregg Colburn and Clayton Page Aldern seek to explain the substantial regional variation in rates of homelessness in cities across the United States. In a departure from many analytical approaches, Colburn and Aldern shift their focus from the individual experiencing homelessness to the metropolitan area. Using accessible statistical analysis, they test a range of conventional beliefs about what drives the prevalence of homelessness in a given city—including mental illness, drug use, poverty, weather, generosity of public assistance, and low-income mobility—and find that none explain the regional variation observed across the country. Instead, housing market conditions, such as the cost and availability of rental housing, offer a far more convincing account. With rigor and clarity, Homelessness Is a Housing Problem explores U.S. cities' diverse experiences with housing precarity and offers policy solutions for unique regional contexts.


Big Data for Twenty-First-Century Economic Statistics

Big Data for Twenty-First-Century Economic Statistics

Author: Katharine G. Abraham

Publisher: University of Chicago Press

Published: 2022-03-11

Total Pages: 502

ISBN-13: 022680125X

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Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.


Permanent Supportive Housing

Permanent Supportive Housing

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2018-08-11

Total Pages: 227

ISBN-13: 0309477042

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Chronic homelessness is a highly complex social problem of national importance. The problem has elicited a variety of societal and public policy responses over the years, concomitant with fluctuations in the economy and changes in the demographics of and attitudes toward poor and disenfranchised citizens. In recent decades, federal agencies, nonprofit organizations, and the philanthropic community have worked hard to develop and implement programs to solve the challenges of homelessness, and progress has been made. However, much more remains to be done. Importantly, the results of various efforts, and especially the efforts to reduce homelessness among veterans in recent years, have shown that the problem of homelessness can be successfully addressed. Although a number of programs have been developed to meet the needs of persons experiencing homelessness, this report focuses on one particular type of intervention: permanent supportive housing (PSH). Permanent Supportive Housing focuses on the impact of PSH on health care outcomes and its cost-effectiveness. The report also addresses policy and program barriers that affect the ability to bring the PSH and other housing models to scale to address housing and health care needs.