Geospatial Heterogeneity in Monetary Value of Proximity to Waterfront Ecosystem Services in the Gulf of Mexico

Open spaces, including waterfront areas, are critical to coastal communities and provide many benefits, including recreation opportunities, economic development, ecological benefits, and other ecosystem services. However, it is not clear how values of waterfront ecosystem services vary across geographical areas which prevents development and adoption of site-specific natural resource conservation plans and suitable long-term land management strategies. This study estimated the monetary value of distance to different waterfront types in coastal counties of Mississippi and Alabama (U.S.) using a geographically weighted regression (GWR) approach as an extension to a traditional hedonic pricing method (HPM). In addition, the study utilized publicly available data from the U.S. Census Bureau instead of certified rolls of county property assessors and Multiple Listing Service (MLS) data which can be costly and difficult to obtain. Residents valued most waterfront types which was reflected in greater assessed prices for houses in proximity to these waterfronts. However, the value of ecosystem services associated with waterfronts differed geospatially. The marginal implicit prices ranged from −$6343 to $6773 per km depending on a waterfront type. These estimates will be useful to city developers, land-use planners, and other stakeholders to make more informed and balanced decisions related to natural resource preservation associated with coastal areas, land-use planning, and zoning. In addition, information from this study can be used in developing healthy living environments where local economy can benefit from increased property tax revenues associated with waterfronts and their ecosystem services.

Green Housing or Green Gentrification?

Research on green-certified buildings has often been focused on the benefits of green standards, such as energy efficiency, smart growth, resource conservation, and health protection. Recent studies suggest the adoption of a reductionist sustainability planning language can turn green-certified houses into luxury goods, attracting White, prime-age, college-educated households with some pro-environmental attitudes who replace existing long-term, lower-income residents in core urban areas. While many factors may work together in driving neighborhood change and gentrification in cities, the question this study aims to address is to what extent the supply of green-certified units can affect neighborhood change and gentrification? We use Central Virginia’s Multiple Listing Service (MLS) housing market transactions data and the U.S. Census Bureau’s socioeconomic data to present the differential effect of new construction of market-rate, green-certified units in a natural experiment using difference-in-differences estimates. We find that neighborhoods that include new, green-certified units have experienced a statistically significant increase in population, supporting new construction and positively affecting house prices. We also detect some negative effects on minorities and minority owners, but these effects have not yet reached statistical significance. This study finds strong evidence of green housing providing the conditions that make areas ripe for gentrification, but more studies should follow up to better measure and generalize this finding.

Brokering Sales

This chapter examines how real estate brokerage routines pressured agents to use the racist market rubric in their work and how brokerages’ silence about unofficial yet potentially discriminatory routines served as a form of approval for agents adopting these routines. When agents interpreted established brokerage routines through the racist market rubric, they cultivated relationships with White individuals and excluded Asian, Black, and Latinx individuals. At times, brokerage routines—such as the automated use of the local real estate board’s market area map—required agents to advertise homes according to a racial–spatial hierarchy. In addition, brokerages remained silent when White agents pursued alternate routines outside the bounds of brokerage organizations, such as when they took on pocket listings—that is, homes not advertised on the Multiple Listing Service. Given the racial patterns of real estate networking in Houston, White home buyers had disproportionate access to pocket listings, yet White agents faced no verbal, professional, or legal sanctions for adopting this behavior.

Improving the Institutional and Organizational Mechanisms to De-Shadow Relations in the Field of Real Estate Transactions

Real estate transactions have been one of the most shadowed sectors of the national economy. The COVID-19 pandemic and the quarantine measures introduced in 2020 to prevent its spreading have led to a sharp increase in the shadowing of the real estate sector, thus reversing the positive trend of the previous years. The study aims at finding ways to de-shadow the real estate sector and substantiating them. Changes in the level of shadowing relations in the real estate sector in 2020 are analyzed. It is found out that the quarantine restrictions introduced in 2020 had though short-term but major negative impact on activities in the real estate market, thus increasing the shadowing of the real estate transactions sector. Emphasis is placed on letting residential real estate as one of the most shadowed segments of the real estate sector. Gaps in the de-shadowing measures in the real estate sector in recent years are highlighted and critically assessed, in particular: Bill № 3618 “On Real Estate Activities in Ukraine”; Bill № 3928-1 "On Amendments to the Tax Code of Ukraine with a view to stimulate the de-shadowing of income received from letting residential real estate"; introduction of a Multiple Listing Service based on real estate appraisal reports; activities of tax authorities in the field of identifying shadow transactions in the rental market. To minimize the level of shadowing the real estate sector, it is suggested to: conduct public awareness campaign as for the benefits of conducting legal activities in the rental market, e.g., protection of the rights of tenants and landlords in the field of real estate transactions; to amend the Tax Code of Ukraine regarding the taxation of income received from letting residential real estate; create a "Legal Lease" online portal, etc.

Green Affordable Housing: Cost-Benefit Analysis for Zoning Incentives

In the year 2017, about 89% of the total energy consumed in the US was produced using non-renewable energy sources, and about 43% of tenant households were cost burdened. Local governments are in a unique position to facilitate green affordable housing, that could reduce cost burdens, environmental degradation, and environmental injustice. Nonetheless, limited studies have made progress on the costs and benefits of green affordable housing, to guide decision-making, particularly in small communities. This study investigates density bonus options for green affordable housing by analyzing construction costs, transaction prices, and spillover effects of green certifications and affordable housing units. The authors employ pooled cross-sectional construction cost and price data from 422 Low-Income Housing Tax Credit (LIHTC) projects and 11,016 Multiple Listing Service (MLS) transactions in Virginia. Using hedonic regression analyses controlling for mediating factors, the study finds that the new construction of market-rate green certified houses is associated with small upfront costs, but large and statistically significant price premiums. In addition, the construction of market-rate green certified houses has large and statistically significant spillover effects on existing non-certified houses. Existing non-certified affordable housing units show small and often insignificant negative price impacts on the transaction prices of surrounding properties. The study concludes that the magnitude of social benefits associated with green building justifies the local provision of voluntary programs for green affordable housing, where housing is expensive relative to its basic cost of production.

Green Affordable Housing: Implications of Costs and Benefits for Municipal Incentives

In the year 2017, about 89 percent of the total energy consumed in the US was produced using non-renewable energy sources, and about 43 percent of tenant households were cost-burdened. Local governments are in a unique position to facilitate green affordable housing that could reduce cost burdens, environmental degradation, and environmental injustice. Nonetheless, limited studies have made progress on costs and benefits of green affordable housing to guide decision-making, particularly in small communities. This study investigates density bonus options for green affordable housing by analyzing construction costs, sale prices, and spillover effects for green certifications and affordable housing units. The authors employ construction costs and sale data from 422 Low-Income Housing Tax Credit (LIHTC) projects and 11,418 Multiple Listing Service (MLS) transactions in Virginia. Using hedonic regression analyses controlling for mediating factors, we find that the new construction of market-rate green certified houses is associated with small upfront costs but large and statistically significant price premiums. The construction of market-rate green certified houses has large and statistically significant spillover effects on existing non-certified houses. Existing non-certified affordable housing units show small and statistically insignificant negative price impacts on transactions of surrounding properties. The magnitude of social benefits associated with green building justifies the local provision of voluntary programs for green affordable housing where housing is expensive relative to its basic costs of production to promote sustainable development.

International Real Estate Review

This paper considers the information content of Multiple Listing Service (MLS) descriptions and employs a significantly larger data set than previous studies. The analysis first catalogs the most frequently used terms by real estate agents in MLS descriptions. Using hedonic modeling, we estimate the effect of this qualitative information on transaction price and days on the market. Finally, we extend earlier empirical work by utilizing our larger MLS data set to forecast the probability that a house will sell after it is listed. This last contribution further sheds light on the role of qualitative information to infer property condition or circumstances that surround the sale of the property.