Do Local Economic Conditions Affect Homelessness? Impact of Area Housing Market Factors, Unemployment, and Poverty on Community Homeless Rates

Hanratty, Maria J.

doi:10.1080/10511482.2017.1282885

Cited by 60 publications

(30 citation statements)

References 12 publications

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“…In other words, the poverty rate in 12 districts and 7 cities in West Sumatra Province is also influenced by the low level of open unemployment. This is in accordance with the theory put forward by (Hanratty, 2017) which states that there is a very close relationship between the high level of unemployment and poverty. For most people who do not have permanent jobs or only part-time, they are always among very poor groups of people.…”

Section: Effect Of Unemployment Rate On Poverty Ratesupporting

confidence: 93%

Analysis of The Effect of Education Level, Economic Growth, and Unemployment Rate on The Poverty Rate In Sumatera Barat, Indonesia

Akhir¹,

Idris²,

Yulhendri³

2019

Proceedings of the Third Padang International Conference on Economics Education, Economics, Business and Management, Accounting

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Poverty is a multidimensional problem that is of concern to all countries in the world. The purpose of this study is to look at the influence of education levels, economic growth, and unemployment rates on poverty rates in the West Sumatra Province of Indonesia. This study uses the Fixed Effect Square Dummy Variable / FEM LSDV approach with panel data which is a combination of 12 districts and 7 cities in West Sumatra Province with a span of time from 2010 to 2016. The results of the research conducted indicate that there are negative influences but not significant between education level variables and poverty rates, while economic growth variables have a negative and significant effect on poverty rates in West Sumatra Province. As with the unemployment rate variable which shows a positive and significant influence on the level of poverty in the Province of West Sumatra. Based on the results of this study, the authors suggest the need to optimize policies related to efforts to increase the level of education, economic growth in addition to emphasizing the unemployment rate in the West Sumatra Province of Indonesia in order to welcome the current digital era.

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Section: Effect Of Unemployment Rate On Poverty Ratesupporting

confidence: 93%

Analysis of The Effect of Education Level, Economic Growth, and Unemployment Rate on The Poverty Rate In Sumatera Barat, Indonesia

Akhir¹,

Idris²,

Yulhendri³

2019

Proceedings of the Third Padang International Conference on Economics Education, Economics, Business and Management, Accounting

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“…On a single night in 2017, just under 193,000 people were found unsheltered in the United States—in places not intended for human habitation such as sidewalks, parks, cars, or abandoned buildings (U.S. Department of Housing and Urban Development, ). The extent of unsheltered homelessness varies widely across cities in the United States, and research has documented important determinants of this variation, including climate (e.g., Corinth & Lucas, ), housing prices (e.g., Early, ; Hanratty, ; Quigley, Raphael, & Smolensky, ), and policy differences (e.g., Corinth, ; Early & Olsen, ; Lucas, ; Raphael, ).…”

Section: Introductionmentioning

confidence: 99%

“…Our paper contributes to a large literature on the determinants of homeless populations, including some studies that analyze unsheltered homeless populations separately. Common findings in this literature are that warmer climates and higher housing prices are strongly and positively associated with homeless populations (e.g., Byrne, Munley, Fargo, Montgomery, & Culhane, ; Corinth, ; Corinth & Lucas, ; Hanratty, ; Honig & Filer, ; O'Flaherty, ; Quigley et al, ). Several studies have examined the determinants of homeless shelter populations in New York City specifically (e.g., Cragg & O'Flaherty, ; O'Flaherty & Wu, , ).…”

Section: Introductionmentioning

confidence: 99%

The geography of unsheltered homelessness in the city: Evidence from “311” calls in New York

Corinth

Finley

2020

Journal of Regional Science

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We provide the first detailed evidence on the distribution of unsheltered homelessness within the city. We rely on “311” call data reporting unsheltered homeless individuals to New York City authorities, based on evidence that the distribution of calls reflects their actual locations. Centrality dominates an otherwise important role of median income in explaining variation in unsheltered homelessness across neighborhoods. Subway stations and restaurants are important as well. We also find that police respond more quickly to calls in more affluent and central neighborhoods. This suggests that the distribution of homelessness across neighborhoods could affect the city's overall response.

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“…As a concrete example, if ZRI increases by 1% in continuum i from one year to the next, the expected log odds of homelessness will increase by .01φ i . The connection between increased rental costs and homelessness rates is well established in the homelessness literature (Hanratty, 2017;Fargo et al, 2013;Byrne et al, 2013;Stojanovic et al, 1999;O'Flaherty, 1995;Sclar, 1990)). To explicitly model this positive relationship, the regression coefficient φ i is truncated at zero.…”

Section: Homeless Population Modelmentioning

confidence: 95%

“…In addition to rising counts of homeless, rental costs in these cities are significantly increasing as well. The relationship between housing costs and homelessness is a topic of great public importance and has received considerable attention (Hanratty, 2017;Fargo et al, 2013;Byrne et al, 2013;Stojanovic et al, 1999;O'Flaherty, 1995;Sclar, 1990).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of homelessness in urban America

Glynn¹,

Fox²

2019

Ann. Appl. Stat.

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The relationship between housing costs and homelessness has important implications for the way that city and county governments respond to increasing homeless populations. Though many analyses in the public policy literature have examined inter-community variation in homelessness rates to identify causal mechanisms of homelessness Lee et al., 2003;Fargo et al., 2013), few studies have examined time-varying homeless counts within the same community (McCandless et al., 2016). To examine trends in homeless population counts in the 25 largest U.S. metropolitan areas, we develop a dynamic Bayesian hierarchical model for time-varying homeless count data. Particular care is given to modeling uncertainty in the homeless count generating and measurement processes, and a critical distinction is made between the counted number of homeless and the true size of the homeless population. For each metro under study, we investigate the relationship between increases in the Zillow Rent Index and increases in the homeless population. Sensitivity of inference to potential improvements in the accuracy of point-in-time counts is explored, and evidence is presented that the inferred increase in the rate of homelessness from 2011-2016 depends on prior beliefs about the accuracy of homeless counts. A main finding of the study is that the relationship between homelessness and rental costs is strongest in New York,

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Do Local Economic Conditions Affect Homelessness? Impact of Area Housing Market Factors, Unemployment, and Poverty on Community Homeless Rates

Cited by 60 publications

References 12 publications

Analysis of The Effect of Education Level, Economic Growth, and Unemployment Rate on The Poverty Rate In Sumatera Barat, Indonesia

Analysis of The Effect of Education Level, Economic Growth, and Unemployment Rate on The Poverty Rate In Sumatera Barat, Indonesia

The geography of unsheltered homelessness in the city: Evidence from “311” calls in New York

Dynamics of homelessness in urban America

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