The Experts below are selected from a list of 35967 Experts worldwide ranked by ideXlab platform
Justin Marion - One of the best experts on this subject based on the ideXlab platform.
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the effects of Low Income Housing tax credit developments on neighborhoods
Journal of Public Economics, 2009Co-Authors: Nathaniel Baumsnow, Justin MarionAbstract:Abstract This paper evaluates the impacts of new Housing developments funded with the Low Income Housing Tax Credit (LIHTC), the largest federal project based Housing program in the U.S., on the neighborhoods in which they are built. A discontinuity in the formula determining the magnitude of tax credits as a function of neighborhood characteristics generates pseudo-random assignment in the number of Low Income Housing units built in similar sets of census tracts. Tracts where projects are awarded 30% higher tax credits receive approximately six more Low Income Housing units on a base of seven units per tract. These additional new Low Income developments cause homeowner turnover to rise, raise property values in declining areas and reduce Incomes in gentrifying areas in neighborhoods near the 30th percentile of the Income distribution. LIHTC units significantly crowd out nearby new rental construction in gentrifying areas but do not displace new construction in stable or declining areas.
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The Effects of Low Income Housing Tax Credit Developments on Neighborhoods.
Journal of public economics, 2009Co-Authors: Nathaniel Baum-snow, Justin MarionAbstract:This paper evaluates the impacts of new Housing developments funded with the Low Income Housing Tax Credit (LIHTC), the largest federal project based Housing program in the U.S., on the neighborhoods in which they are built. A discontinuity in the formula determining the magnitude of tax credits as a function of neighborhood characteristics generates pseudo-random assignment in the number of Low Income Housing units built in similar sets of census tracts. Tracts where projects are awarded 30 percent higher tax credits receive approximately six more Low Income Housing units on a base of seven units per tract. These additional new Low Income developments cause homeowner turnover to rise, raise property values in declining areas and reduce Incomes in gentrifying areas in neighborhoods near the 30th percentile of the Income distribution. LIHTC units significantly crowd out nearby new rental construction in gentrifying areas but do not displace new construction in stable or declining areas.
Moheeb El-said - One of the best experts on this subject based on the ideXlab platform.
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A simulation optimisation tool for planning of Low-Income Housing projects
Civil Engineering and Environmental Systems, 2013Co-Authors: Mohamed Marzouk, Osama A. Omar, Manal S. Abdel Hamid, Moheeb El-saidAbstract:Construction of Low-Income Housing projects is a recurring process and is associated with uncertainties that arise from the unavailability of resources. This paper presents a case study that discusses how computer simulation and optimisation are used to aid government agencies and/or contractors in planning of such projects. It illustrates the optimisation of project objectives, taking into consideration the interaction amongst involved resources. As such, total duration and the associated total costs, including direct and indirect costs, can be estimated and optimised. One Youth Habitation project that is executed in 6th of October City in Egypt is analysed in a step-by-step procedure to demonstrate the capability of proposed computer simulation and optimisation prototype (named LIHouse{_}Sim) in the modelling construction of Low-Income Housing projects using bearing block walls with holLow core technique. The presented tool proves its practicality to contractors in estimating the time and costs of the r...
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An optimization algorithm for simulation-based planning of Low-Income Housing projects
Journal of Advanced Research, 2010Co-Authors: Mohamed Marzouk, Osama A. Omar, Manal S. Abdel Hamid, Moheeb El-saidAbstract:Abstract Construction of Low-Income Housing projects is a replicated process and is associated with uncertainties that arise from the unavailability of resources. Government agencies and/or contractors have to select a construction system that meets Low-Income Housing projects constraints including project conditions, technical, financial and time constraints. This research presents a framework, using computer simulation, which aids government authorities and contractors in the planning of Low-Income Housing projects. The proposed framework estimates the time and cost required for the construction of Low-Income Housing using pre-cast holLow core with holLow blocks bearing walls. Five main components constitute the proposed framework: a network builder module, a construction alternative selection module, a simulation module, an optimization module and a reporting module. An optimization module utilizing a genetic algorithm enables the defining of different options and ranges of parameters associated with Low-Income Housing projects that influence the duration and total cost of the pre-cast holLow core with holLow blocks bearing walls method. A computer prototype, named LIHouse_Sim, was developed in MS Visual Basic 6.0 as proof of concept for the proposed framework. A numerical example is presented to demonstrate the use of the developed framework and to illustrate its essential features.
Kelly D. Edmiston - One of the best experts on this subject based on the ideXlab platform.
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Low-Income Housing Tax Credit Developments and Neighborhood Property Conditions
SSRN Electronic Journal, 2015Co-Authors: Kelly D. EdmistonAbstract:Assisted Housing has long been a contentious issue for cities and regions. On one hand, there is an acute need for affordable Housing in Low- and moderate-Income communities. But the massing of public or otherwise subsidized Housing in disadvantaged neighborhoods has given rise to concerns that “public Housing” has led to the decay of these communities. The intention of this paper is to use analytical tools to evaluate the conventional wisdom that Lower-Income Housing developments are somehow disadvantageous for the Lower-Income communities in which they generally are placed. The focus is on the evaluation of Low-Income Housing tax credit (LIHTC) financed developments, as this is the typical way for developing Low-Income Housing units today. Results suggest that while large new construction projects tend to diminish property conditions nearby, the effects of small new construction projects and larger rehabilitation projects generally are positive.
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Low-Income Housing tax credit developments and neighborhood property conditions
2011Co-Authors: Kelly D. EdmistonAbstract:Public Housing has long been a contentious issue for cities and regions. While there is a great need for affordable Housing in many communities, neighbors of Low-Income Housing developments fret about neighborhood decay. This paper evaluates the notion that Low-Income Housing developments damage the communities in which they are placed. The focus is on the evaluation of Low-Income Housing tax credit (LIHTC) financed developments, and the neighborhood indicator of interest is the physical condition of nearby properties. The results of the empirical analysis suggest that proximity to LIHTC developments generally has a positive impact on neighborhood property conditions. However, extended analysis that separates LIHTC developments by type and size suggests that only small new construction developments and large rehab developments impact neighborhood property conditions. Further analysis reveals that when the model does not control for crime, the effect of proximity to LIHTC developments on property conditions is negative.
Alireza Moghayedi - One of the best experts on this subject based on the ideXlab platform.
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Use and performance of conventional and sustainable building technologies in Low-Income Housing
Sustainable Cities and Society, 2021Co-Authors: Abimbola Windapo, Emmanuel Dele Omopariola, Oluseye Olugboyega, Alireza MoghayediAbstract:Abstract Few studies have investigated the use and performance of conventional and sustainable building technologies of use in Low-Income Housing construction. Hence, this study investigates the use and performance of the conventional and sustainable building technologies used in Low-Income Housing construction towards proposing the most sustainable technological solution for Low-Income Housing development in South Africa. Using a case study research approach, the study developed a rating tool for use in assessing the sustainability performance of the Reconstruction and Development Programme (RDP) Low-Income houses within the nine provinces of South Africa with measures drawn from the Green Building Council of South Africa (GBCSA) technical manual. Findings of this study show that the most commonly used method of construction for Low-Income Housing in South Africa are concrete floor slab, brick and mortar for the external envelope and a combination of timber structures fitted with Inverted Box Rib (IBR) sheeting for the roof system. The results also show that conventional building components had a much Lower sustainability level due to the high use of concrete and that innovative building components have a Lower environmental impact due to the Low carbon dioxide emission associated with the manufacturing process. The study concludes with regards to the socio-economic and environmental dimensions of sustainability that buildings constructed using sustainable technologies are more sustainable than those produced using conventional methods. The study recommends that public sector clients involved in the provision of Low-Income Housing should encourage the use of sustainable construction technologies. Further, the research also suggests that the GBCSA should develop measures which specifically targets Low-Income Housing development to alLow for the determination of both the socio-economic viability and environmental impact of the RDP houses produced in South Africa.
Glorian Sorensen - One of the best experts on this subject based on the ideXlab platform.
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financial hardship and self rated health among Low Income Housing residents
Health Education & Behavior, 2013Co-Authors: Reginald Tuckerseeley, Amy E Harley, Anne M Stoddard, Glorian SorensenAbstract:Background. Self-rated health (SRH) has been shown to be predictive of morbidity and mortality. Evidence also shows that SRH is socioeconomically patterned, although this association differs depending on the indicator of socioeconomic status used. The purpose of this study was to determine the association between SRH and financial hardship among residents of Low-Income Housing. Methods. We analyzed cross-sectional data from the Health in Common Study (N = 828), an observational study to investigate social and physical determinants of cancer risk–related behaviors among residents of Low-Income Housing in three cities in the Boston metropolitan area. Modified Poisson regression models were used to obtain the relative risk of Low SRH (fair or poor), adjusting for demographic and socioeconomic characteristics. Results. Unadjusted models revealed that the respondents reporting financial hardship were 53% more likely to report Low SRH compared with those not reporting financial hardship. After controlling for d...
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The social environment and walking behavior among Low-Income Housing residents
Social science & medicine (1982), 2012Co-Authors: Caitlin E. Caspi, Ichiro Kawachi, S. V. Subramanian, Reginald D. Tucker-seeley, Glorian SorensenAbstract:Walking, both for leisure and for travel/errands, counts toward meeting physical activity recommendations. Both social and physical neighborhood environmental features may encourage or inhibit walking. This study examined social capital, perceived safety, and disorder in relation to walking behavior among a population of Low-Income Housing residents. Social and physical disorder were assessed by systematic social observation in the area surrounding 20 Low-Income Housing sites in greater Boston. A cross-sectional survey of 828 residents of these Housing sites provided data on walking behavior, socio-demographics, and individual-level social capital and perceived safety of the areas in and around the Housing site. Community social capital and safety were calculated by aggregating individual scores to the level of the Housing site. Generalized estimating equations were used to estimate prevalence rate ratios for walking less than 10 min per day for a) travel/errands, b) leisure and c) both travel/errands and leisure. 21.8% of participants walked for travel/errands less than 10 min per day, 34.8% for leisure, and 16.8% for both kinds of walking. In fully adjusted models, those who reported Low individual-level social capital and safety also reported less overall walking and less walking for travel/errands. Unexpectedly, those who reported Low social disorder also reported less walking for leisure, and those who reported high community social capital also walked less for all outcomes. Physical disorder and community safety were not associated with walking behavior. For Low-Income Housing residents, neighborhood social environmental variables are unlikely the most important factors in determining walking behavior. Researchers should carefully weigh the respective limitations of subjective and objective measures of the social environment when linking them to health outcomes.
