Rail station access and housing market resilience: Case studies of Atlanta, Baltimore and Portland

Urban Studies ◽  
2018 ◽  
Vol 55 (16) ◽  
pp. 3615-3630 ◽  
Author(s):  
Timothy F Welch ◽  
Steven R Gehrke ◽  
Steven Farber
Keyword(s):  
Housing Market ◽  
Critical Role ◽  
Housing Price ◽  
Single Family ◽  
Market Values ◽  
Urban Amenities ◽  
Resilience Index ◽  
Negative Impacts ◽  
The Impact ◽  
Rail Station

The recent United States housing market crisis resulted in a significant decline in housing market values. Yet, the extent to which urban amenities such as rail stations moderated the market impacts has not been entirely recognised. This study undertakes a repeat sales analysis to understand the impact of station proximity on housing values before, during and after the market crisis. Specifically, a housing price resilience index assesses market changes from 2002 to 2013 for single-family and multifamily homes within a quarter of a mile, half a mile, one mile and greater distances from the nearest rail station. The analysis is replicated in three cities: Atlanta, Georgia; Baltimore, Maryland; and Portland, Oregon. Although the recession had significant negative impacts on properties in each city, our study finds that access played a critical role in helping transit-orientated submarkets retain their value throughout the recession and recover value at a faster rate than homes without convenient fixed transit access.

The impact of COVID-19 on home value in major Texas cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mira R. Bhat ◽  
Junfeng Jiao ◽  
Amin Azimian
Keyword(s):  
Housing Market ◽  
Mixed Model ◽  
Negative Relationship ◽  
Housing Price ◽  
Single Family ◽  
Related Factors ◽  
Content Type ◽  
Home Value ◽  
Business Cycle Index ◽  
The Impact

Purpose This study aims to analyze the impact of COVID-19 on housing price within four major metropolitan areas in Texas: Austin, Dallas, Houston and San Antonio. The analysis intends to understand economic and mobility drivers behind the housing market under the inclusion of fixed and random effects. Design/methodology/approach This study used a linear mixed effects model to assess the socioeconomic and housing and transport-related factors contributing to median home prices in four major cities in Texas and to capture unobserved factors operating at spatial and temporal level during the COVID-19 pandemic. Findings The regression results indicated that an increase in new COVID-19 cases resulted in an increase in housing price. Additionally, housing price had a significant and negative relationship with the following variables: business cycle index, mortgage rate, percent of single-family homes, population density and foot traffic. Interestingly, unemployment claims did not have a significant impact on housing price, contrary to previous COVID-19 housing market related literature. Originality/value Previous literature analyzed the housing market within the first phase of COVID-19, whereas this study analyzed the effects of the COVID-19 throughout the entirety of 2020. The mixed model includes spatial and temporal analyses as well as provides insight into how quantitative-based mobility behavior impacted housing price, rather than relying on qualitative indicators such as shutdown order implementation.

Urban decline and residential preference: The effect of vacant lots on housing premiums

2020 ◽  
pp. 239980832093390
Author(s):  
Youngre Noh ◽  
Galen Newman ◽  
Ryun Jung Lee
Keyword(s):  
Vacant Land ◽  
Urban Decline ◽  
Socioeconomic Conditions ◽  
Single Family ◽  
Housing Values ◽  
Vacant Lots ◽  
Residential Preference ◽  
Negative Impacts ◽  
The Impact ◽  
The City

Vacant land is a ubiquitous urban phenomenon. The existence of vacant land in a neighborhood can either lower or heighten nearby housing values, depending on its relative development potential. However, this condition has rarely been examined longitudinally, nor has it been examined thoroughly across different socioeconomic conditions. This research examines the impact of vacant lots on housing premiums using 2006–2015 single-family home sale transactions in the City of Minneapolis, Minnesota. The study area was divided into low-, middle-, and high-income levels. The results show that vacant lands have negative impacts on nearby single-family houses and these impacts differ by income level per neighborhood. The study sheds light on how planners and researchers should conceive vacant lands differently in various surroundings and conditions.

scholarly journals The Emerging Role of Ten-Eleven Translocation 1 in Epigenetic Responses to Environmental Exposures

2020 ◽  
Vol 13 ◽  
pp. 251686572091015 ◽  
Author(s):  
Tao Zhu ◽  
Anthony P Brown ◽  
Hong Ji
Keyword(s):  
Therapeutic Potential ◽  
Critical Role ◽  
Environmental Exposures ◽  
Epidemiological Studies ◽  
Epigenetic Changes ◽  
Molecular Processes ◽  
Molecular Events ◽  
Negative Impacts ◽  
The Impact

Mounting evidence from epidemiological studies and animal models has linked exposures to environmental factors to changes in epigenetic markers, especially in DNA methylation. These epigenetic changes may lead to dysregulation of molecular processes and functions and mediate the impact of environmental exposures in complex diseases. However, detailed molecular events that result in epigenetic changes following exposures remain unclear. Here, we review the emerging evidence supporting a critical role of ten-eleven translocation 1 (TET1) in mediating these processes. Targeting TET1 and its associated pathways may have therapeutic potential in alleviating negative impacts of environmental exposures, preventing and treating exposure-related diseases.

scholarly journals The role of news in the fluctuations of housing price

2018 ◽  
Vol 15 (3) ◽  
pp. 294-303
Author(s):  
Nazar Dahmardeh ◽  
Reza Khaki ◽  
Marziyeh Esfandiari
Keyword(s):  
Housing Market ◽  
Housing Price ◽  
Price Volatility ◽  
Annual Data ◽  
Price Fluctuations ◽  
Empirical Results ◽  
Negative News ◽  
The Impact ◽  
Do So

The main purpose of this paper is to evaluate the impact of the news on the housing price volatility in Iran. To do so, symmetric and asymmetric models such as GARCH, T-ARCH, EGARCH and APGARCH are applied by using annual data for the period 1971–2013. The empirical results confirm the asymmetric and leverage effects of news in Iran housing market. Also the impact of shocks indicates that negative news affect the housing price fluctuations further more than positive news with the same size.

THE ADVERSE EFFECTS OF ECONOMIC POLICY UNCERTAINTY ON INDEMNIFICATORY HOUSING MARKET IN CHINA

2020 ◽  
pp. 1-17
Author(s):  
JIAN FU ◽  
XIAOFEN YU ◽  
CHUN KWONG KOO ◽  
WAI CHOI LEE
Keyword(s):  
Economic Policy ◽  
Adverse Effects ◽  
Housing Market ◽  
Housing Price ◽  
Housing Unit ◽  
Policy Uncertainty ◽  
Housing Investment ◽  
Economic Policy Uncertainty ◽  
The Right ◽  
The Impact

This paper empirically examines the impact of the economic policy uncertainty (EPU) index on market indicators of indemnificatory houses in China for the period from January 2012 to December 2018. We use three indicators of the indemnificatory housing market: (i) the price of commodity housing unit, (ii) the number of completion for indemnificatory housing unit and (iii) the amount of investment for indemnificatory housing unit. The findings from the Granger Causality in Distribution test show that the EPU causes the commodity housing price at the left-tail and the right-tail, but not at the centre of the distribution. Besides, the EPU causes the indemnificatory housing completion volume at the right tail, but not at the left and the centre of the distribution. Finally, we observe that the EPU causes the indemnificatory housing investment at the right tail but not at the left and the centre of the distribution. These findings indicate that the indemnificatory housing market in China is mainly affected by the extreme changes in the EPU.

scholarly journals Price Determinants and GIS Analysis of the Housing Market in Vietnam: The Cases of Ho Chi Minh City and Hanoi

2018 ◽  
Vol 10 (12) ◽  
pp. 4720
Author(s):  
You Chung ◽  
Ducksu Seo ◽  
Jaehwan Kim
Keyword(s):  
Housing Market ◽  
Central Government ◽  
Housing Price ◽  
Real Estate Market ◽  
Hedonic Model ◽  
Ho Chi Minh City ◽  
Infrastructure Development ◽  
Related Factors ◽  
Price Determinants ◽  
The Impact

Since the introduction of the Doi Moi economic reform in 1986, the real estate market in Vietnam has witnessed a sharp increase in foreign investment inflows and a remarkable growth in the housing market, particularly for high-rise apartments in large cities. This study investigates the determinants of apartment prices in Ho Chi Minh City (HCMC) and Hanoi, the two most representative cities in Vietnam. The spatial distribution of apartments and their price determinants were addressed by the spatial analysis of Geographic Information System (GIS) and the hedonic model. The price determinants of both cities were closely associated with downtown-related factors; moreover, the externalities of urbanization affected each city. While HCMC was more related to the locational attributes of urban amenities and community density as well as programs because of unmanaged urbanization, Hanoi was more related to housing attributes, since the majority of apartment projects were developed under urban infrastructure development supported by the central government. Apartment cluster maps of each city clearly show the contrast of housing distribution. Our findings clarify the impact of government policies on housing price determinants and can be a reference for private- and public-sector stakeholders seeking to undertake economically and socially sustainable housing development projects in Vietnam.

Impact of COVID-19 on Housing Market: A Review of Emerging Literature

2021 ◽  
Vol 15 (2) ◽  
pp. 66-74
Author(s):  
Jibrin Katun Mohammed ◽  
Abdullahi Alhaji Aliyu ◽  
Usman Abubakar Dzukogi ◽  
Abdulafeez Abiodun Olawale
Keyword(s):  
Housing Market ◽  
Housing Prices ◽  
The Novel ◽  
Academic Journal ◽  
Negative Effects ◽  
Secondary Sources ◽  
Negative Impacts ◽  
Novel Coronavirus ◽  
The Impact ◽  
Conference Papers

The housing market over the years has been impacted by various factors in different ways. This review paper examines the growing literature on the impact of COVID-19 on the housing market to ascertain its positive and negative effects. Thus, a total of 40 published conference papers, thesis, academic journal articles, and others obtained from secondary sources were reviewed and revealed that the novel coronavirus (COVID-19) in some scenarios had positive and negative impacts on the housing market. The paper found that the positive impacts include a rise in housing prices, increase in housing supply and reduction in mass evictions in some locations, while the negative impacts are on housing prices, demand and supply, constraints in mortgage return maintenance and delay in the construction of new housing apartments. The paper, therefore, concludes that both positive and negative impacts of the COVID-19 pandemic are felt on the housing market globally. These thereby form a basis for further studies on the growing impacts of the pandemic concerning the housing market.

scholarly journals Las Cruces housing price fluctuations

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Steven L. Fullerton ◽  
James H. Holcomb ◽  
Thomas M. Fullerton Jr
Keyword(s):  
Theoretical Model ◽  
Housing Market ◽  
Supply And Demand ◽  
Housing Prices ◽  
Housing Price ◽  
Medium Size ◽  
Single Family ◽  
Content Type ◽  
Price Fluctuations ◽  
National Housing

Purpose This paper aims to analyze the median price for existing single-family housing units in Las Cruces, New Mexico. The proposed theoretical model accounts for the interplay between supply and demand sides of a metropolitan housing market. Design/methodology/approach This study analyzes the median price for existing single-family housing units in Las Cruces, New Mexico. The proposed theoretical model accounts for the interplay between supply and demand sides of a metropolitan housing market. Explanatory variables used in the analysis are real per capita income, the housing stock, real mortgage rates, real apartment rents and the median real price of single-family units in the USA. Annual frequency data are collected for a 1971–2017 sample period. Parameter estimation is completed using two-stage generalized least squares. Empirical results confirm several, but not all, of the hypotheses associated with the underlying analytical model. In particular, Las Cruces housing prices are found to be reliably correlated with local income and national housing prices. Findings Empirical results confirm several of the hypotheses associated with the underlying analytical model. In particular, Las Cruces housing prices are found to be reliably correlated with local income and national housing prices. Research limitations/implications Results obtained support only a subset of the hypothetical relationships associated with the theoretical model. Additional testing for other small and/or medium sized is required to clarify whether these outcomes are unique to Las Cruces. Practical implications Local income fluctuations and national housing price fluctuations appear to be reliably related to housing price fluctuations for this metropolitan economy. Originality/value Comparatively little housing market research has been conducted for small and medium size urban economies. There is no guarantee that results obtained for large metropolitan housing markets are representative of smaller regional housing markets. The model developed has fairly moderate data requirements and may be applicable to other small and medium size economies such as Las Cruces.

The influence of privately initiated rezoning on housing prices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jeffrey G. Robert ◽  
Velma Zahirovic-Herbert
Keyword(s):  
Housing Prices ◽  
Housing Price ◽  
Quantitative Information ◽  
Single Family ◽  
Residential Housing ◽  
Content Type ◽  
Price Effects ◽  
Family Housing ◽  
Residential Use ◽  
The Impact

Purpose The purpose of this paper is to evaluate the parcel-level impacts of the zoning change. Design/methodology/approach Using hedonic regression and propensity score matching econometric techniques, this paper analyses single-family housing prices within Fulton County Georgia. This paper combines data on the parcel-level zoning changes with nearby housing sales transactions to study the potential externality effects because of rezoning induced by private parties. Findings The paper finds evidence of heterogeneous rezoning effects, depending upon the type of rezoning conducted. At a distance within 0.75 miles, housing prices appreciate by 8.31% when nearby privately initiated rezoning maintains the residential character of a neighbourhood. However, housing prices decline by 21.26% when residential housing zones are converted to non-residential housing zones. The negative influences of rezoning residential use to non-residential uses decline as distance increases. Originality/value The analysis provides quantitative information on the impact of rezoning on residential property prices. Planning officials and developers can use these results to assuage homeowner fears of potential negative housing price effects associated with rezoning.

scholarly journals USING SVR AND MRA METHODS FOR REAL ESTATE VALUATION IN THE SMART CITIES

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 21-26
Author(s):  
A. U. Akar ◽  
S. Yalpir
Keyword(s):  
Real Estate ◽  
Smart Cities ◽  
Critical Role ◽  
Support Vector ◽  
The Real Estate ◽  
Market Values ◽  
Systems Model ◽  
Real Estate Valuation ◽  
Real Estate Management ◽  
The Impact

Abstract. Determination of real estate value plays a very critical role in economic development and basic needs of people. Increasing demand for real estate together with population growth is making it difficult to determine real estate value. In applications where real estate is the main subject, such as urban activities, smart cities and urbanization, urban information system and valuation systems, model-based value estimations are essential for effective land/real estate policy. The type of real estate and impact degree of features depending on the type should be known as well as value estimation. It will be beneficial to follow a method that both determines the real estate value and factor impact degree. With the studies to be carried out using such methods, both region-specific valuation models can be created and the model is established with the optimum variable. This paper aimed to determine real estate value by using Support Vector Regression (SVR) and Multi Regression Analysis (MRA) methods for effective real estate management. Besides, both methods were examined by revealing the impact degrees of features that affect the value. The methods were applied to 319 parcels in Konya. For each parcel, 31 land features and market values were collected. The parcel data collected since 2018 were included in the models. From the results, the RBF-SVR model reached the highest R2 value with 0.88, while the MRA model reached 0.86.

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