scholarly journals A Hedonic Analysis of the Impact of Marine Aquaculture on Coastal Housing Prices in Maine

2017 ◽  
Vol 46 (2) ◽  
pp. 242-267 ◽  
Author(s):  
Keith S. Evans ◽  
Xuan Chen ◽  
Christina A. Robichaud
Keyword(s):  
Spatial Variation ◽  
Spatial Data ◽  
Housing Prices ◽  
Single Family ◽  
Industry Growth ◽  
Marine Aquaculture ◽  
Coastal Aquaculture ◽  
Home Sales ◽  
Potential Benefits ◽  
The Impact

Converting coastal waters to farmed production of seafood may generate conflicts with other resource users. This study explores the impact of marine aquaculture development on coastal homeowners. Using single-family home sales from 2012–2014 and spatial data on coastal aquaculture activity, we employ hedonics to assess the impacts of mariculture development in three study areas of Maine, USA. Our results suggest modest impacts on residential property values with significant spatial variation across study areas. This spatial variation represents a challenge for managers and highlights the potential benefits from coordinating the development of aquaculture to balance resource users' objectives with industry growth.

Bankruptcy filings, flooding, real estate prices and Leading Index

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Housing Prices ◽  
The United States ◽  
Flood Insurance ◽  
Single Family ◽  
Personal Bankruptcy ◽  
Content Type ◽  
Independent Variables ◽  
Flooding Event ◽  
Flooding Events ◽  
The Impact

PurposeFlood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can purchase flood insurance. The Netherlands and Asian countries generally do not offer flood insurance protection to homeowners. Uninsured households incur the entire cost of repairing/replacing properties damaged due to flooding. Homeowners’ policies do not cover damage caused by flooding. The paper examines the link between personal bankruptcy and the severity of flooding events, property prices and financial condition levels.Design/methodology/approachA fully modified ordinary least squares (FMOLS) regression model is developed which uses personal bankruptcy filings as its dependent variable during the years 2000 through 2018. This time-series model considers the association between personal bankruptcy court filings and costly, widespread flooding events. Independent variables were selected that potentially act as mitigating factors reducing bankruptcy filings.FindingsThe FMOLS regression results found a significant, positive association between flooding events and the total number of personal bankruptcy filings. Higher flooding costs were associated with higher bankruptcy filings. The Home Price Index is inversely related to the bankruptcy dependent variable. The R-squared results indicate that 0.65% of the movement in the dependent variable personal bankruptcy filings is explained by the severity of a flooding event and other independent variables.Research limitations/implicationsThe severity of the flooding event is measured using dollar losses incurred by the National Flood Insurance program. A macro-case study was undertaken, but the research results would have been enhanced by examining local areas and demographic factors that may have made bankruptcy filing following a flooding event more or less likely.Practical implicationsThe paper considers the impact of the natural disaster flooding on bankruptcy rates filings. The findings may have implications for multi-family properties as well as single-family housing. Purchasing flood insurance generally mitigates the likelihood of severe financial risk to the property owner.Social implicationsNatural flood insurance is underwritten by the federal government and/or by private insurers. The financial health of private property insurers that underwrite flooding and their ability to meet losses incurred needs to be carefully scrutinized by the insured.Originality/valuePrior studies analyzing the linkages existing between housing prices, natural disasters and bankruptcy used descriptive data, mostly percentages, when considering this association. The study herein posits the same questions as these prior studies but used regression analysis to analyze the linkages. The methodology enables additional independent variables to be added to the analysis.

scholarly journals Organization of the Building Space of Developments and Its Impact on Residential Housing Prices

2020 ◽  
Vol 12 (18) ◽  
pp. 7622
Author(s):  
Edward Preweda ◽  
Elżbieta Jasińska
Keyword(s):  
Urban Space ◽  
Spatial Data ◽  
Laser Scanning ◽  
Housing Prices ◽  
The Sustainable Development ◽  
Terrain Model ◽  
Property Prices ◽  
Elevation Data ◽  
Land Use Development ◽  
The Impact

This study has examined the process of urban space development in Krakow (southern Poland) using two developments as an example. The planning documents were analysed and spatial data obtained from the CAPAP (Centre for Spatial Analysis of Public Administration) project were processed. The data source for analysis comprised 2D outlines of certain buildings from the topographic object database (BDOT10k), elevation data from lidar aerial laser scanning at a density of 12 points per square meter and a numerical terrain model (NMT) with a one-meter mesh grid. In addition, existing models of the boundaries of the plots including their numbers and the ownership structure were used. On this basis, a digital mock-up of the analysed site was created. The issue surrounding the purchasing of these sites is interesting, since on the primary market, the apartments are bought long before the start of the first construction works. For this reason, the buyer is not necessarily aware of how the buildings surrounding his/her property will ultimately look, including whether or not they will obscure the sun’s rays. Until now, there has been no need to analyse the density of buildings, as there was no definitive impact of this feature on property prices; discussions were only held in relation to one of the developments built, as to how the sustainable development of the city should look. The positive actions applied during the implementation of the investment were detailed and the negative aspects of the resulting developments were identified. This allowed general analysis of land use development. The work used a model of regressive trees to determine the impact of certain attributes on the property prices.

The Impact of Immigration on Wages, Internal Migration, and Welfare

2020 ◽  
Author(s):  
Suphanit Piyapromdee
Keyword(s):  
Internal Migration ◽  
Census Data ◽  
Housing Prices ◽  
Welfare Effects ◽  
Welfare Losses ◽  
Spatial Equilibrium Model ◽  
Potential Benefits ◽  
Negative Impacts ◽  
The Impact ◽  
High Skill

Abstract This article studies the impact of immigration on wages, internal migration, and welfare. Using U.S. Census data, I estimate a spatial equilibrium model where labour differs by skill level, gender, and nativity. Workers are heterogeneous in city preferences. Cities vary in productivity levels, housing prices, and amenities. I use the estimated model to assess the distributional consequences of several immigration policies. The results show that a skill selective immigration policy leads to welfare gains for low skill workers, but welfare losses for high skill workers. The negative impacts are more substantial among the incumbent high skill immigrants. Internal migration mitigates the initial negative impacts, particularity in cities where housing supplies are inelastic. However, the negative wage impacts on some workers intensify. This is because an out-migration of workers of a given type may raise the local wages for workers of that type, while reducing the local wages of workers with complementary characteristics. Overall, there are substantial variations in the welfare effects of immigration across and within cities. Further, I use the model to assess the welfare effects of the border wall between Mexico and the U.S. The results show that the potential benefits are significantly smaller than the proposed cost of construction.

scholarly journals EPC Labels and Building Features: Spatial Implications over Housing Prices

2021 ◽  
Vol 13 (5) ◽  
pp. 2838
Author(s):  
Alice Barreca ◽  
Elena Fregonara ◽  
Diana Rolando
Keyword(s):  
Real Estate ◽  
Spatial Data ◽  
Housing Stock ◽  
Housing Prices ◽  
Energy Performance ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Spatial Error ◽  
The Impact

The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to the empirical evidence that emerged in some previous studies. Furthermore, the presence of the spatial effects reveals that the impact of energy attributes changes in different sub-markets and thus has to be spatially analysed.

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.

Do hurricanes matter?

2017 ◽  
Vol 10 (3) ◽  
pp. 352-370 ◽  
Author(s):  
Jesse Saginor ◽  
Yue Ge
Keyword(s):  
Housing Market ◽  
Practical Implication ◽  
Extended Period ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Single Family ◽  
Housing Values ◽  
Content Type ◽  
Home Sales ◽  
The Impact

Purpose The purpose of this research is to analyze a county’s housing market over 23 years to determine what impact, if any, multiple hurricanes have had on the residential real estate market. Design/methodology/approach This research uses a hedonic price model to determine the impacts that multiple hurricanes had on housing values. Findings There was a significant and negative countywide impact on housing sales values in the 1996, which can directly be attributed to three hurricanes impacting Brunswick County. Economic factors, rather than hurricanes and related storms, are more likely to impact sales values in all other years. Research limitations/implications This research is limited only to single-family home sales in Brunswick County, North Carolina, from 1984 to 2007. The model does not include multi-family residential uses. Practical implications Unlike many other areas that have been studied regarding natural disasters, Brunswick County has been hit multiple times by hurricanes and related storms, providing some insight into the long-term implications of the impact of storms on housing values over an extended period of time. The practical implication is that despite the likelihood of hurricanes and proximity to the ocean, people are willing to pay to live in coastal areas, even an area with a history of repeated direct and indirect strikes by hurricanes. Originality/value Unlike much of the peer-reviewed research that looks at a single occurrence of a natural disaster, this research looks at the impacts of multiple hurricanes on a single county over 23 years to determine what impact, if any, these storms have on the overall housing market.

Housing Prices and Government Approval: The Impact of Housing Booms on Left- and Right-Wing Governments in 16 Advanced Industrialized Countries

2021 ◽  
Vol 54 (1) ◽  
pp. 163-185
Author(s):  
Sung Min Han ◽  
Mi Jeong Shin
Keyword(s):  
Housing Prices ◽  
Right Wing ◽  
Industrialized Countries ◽  
Left Wing ◽  
Approval Ratings ◽  
The United Kingdom ◽  
Level Data ◽  
Left And Right ◽  
The Government ◽  
The Impact

AbstractIn this article, we argue that rising housing prices increase voter approval of incumbent governments because such a rise increases personal wealth, which leads to greater voter satisfaction. This effect is strongest under right-wing governments because those who benefit from rising prices—homeowners—are more likely to be right-leaning. Non-homeowners, who are more likely to vote for left-leaning parties, will view rising housing prices as a disadvantage and therefore feel the government does not serve them well, which will mitigate the advantage to left-wing governments. We find support for our arguments using both macro-level data (housing prices and government approval ratings in 16 industrialized countries between 1960 and 2017) and micro-level data (housing prices and individuals’ vote choices in the United Kingdom using the British Household Panel Survey). The findings imply that housing booms benefit incumbent governments generally and right-wing ones in particular.

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