Real Estate

56 pages, 1824 KiB

Open AccessArticle

An Agent-Based Market Analysis of Urban Housing Balance in The Netherlands

by Erik Wiegel and Neil Yorke-Smith

Real Estate 2024, 1(1), 80-135; https://doi.org/10.3390/realestate1010006 (registering DOI) - 28 Apr 2024

The Dutch housing market comprises three sectors: social-rented, private-rented, and owner-occupied. The contemporary market is marked by a shortage of supply and a large subsidised social sector. Waiting lists for social housing are growing, whereas households with incomes above the limit do not or cannot leave the social sector. Government policy and market regulations change frequently, not least for political reasons. In view of commonly recognised problems in the housing market, this article considers the ‘internal demand’ of those households that are dissatisfied with their current residence. We examine the effects of regulatory policy by means of an exploratory agent-based simulation. The results provide perspectives on how internal demand is impacted by regulations in a housing market that is suffering from a shortage, and allow decision makers to weigh the pros and cons of policy measures. Full article

(This article belongs to the Special Issue Homeownership and Development)

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15 pages, 1432 KiB

Open AccessArticle

Impact of Green Features on Rental Value of Residential Properties: Evidence from South Africa

by Tawakalitu Bisola Odubiyi, Rotimi Boluwatife Abidoye, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala, Adeyemi Samuel Ademiloye and Olalekan Shamsideen Oshodi

Real Estate 2024, 1(1), 65-79; https://doi.org/10.3390/realestate1010005 - 20 Mar 2024

Abstract

In recent years, scholars have called for an increase in the usage of green features in the built environment to address climate change issues. Governments across the developed world are implementing legislation to support this increased uptake. However, little is known about how the inclusion of green features influences the rental value of residential properties located in developing countries. Data on 389 residential properties were extracted and collected from a webpage. Text mining and machine learning models were used to evaluate the impact of green features on the rental value of residential properties. The results indicated that floor area, number of bathrooms, and availability of furniture are the top three attributes affecting the rental value of residential properties. The random forest model generated better predictions when compared with other modelling techniques. It was also observed that green features are not the most common words mentioned in rental adverts for residential properties. The results suggest that green features add limited value to residential properties in South Africa. This finding suggests that there is a need for stakeholders to create and implement policies targeted at incentivising the inclusion of green features in existing and new residential properties in South Africa. Full article

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24 pages, 334 KiB

Open AccessFeature PaperArticle

Using Co-Ordinate Systems in Hedonic Housing Regressions

by Steven B. Caudill, Neela Manage and Franklin G. Mixon, Jr.

Real Estate 2024, 1(1), 41-64; https://doi.org/10.3390/realestate1010004 - 12 Mar 2024

Abstract

Hedonic house price studies typically incorporate information about location by including either a set of dummy variables to represent individual locations called “neighborhoods” or by using a set of distance (or travel time) variables to characterize locations in terms of proximity to amenities and dis-amenities. As an alternative to these, relatively recent research advocates a latitude–longitude co-ordinate system for incorporating distance information into hedonic house price regressions. This study shows that many of the claims made in this research, particularly those referencing the elimination or diminution of “biases of coefficients of non-distance variables”, are given the particulars of the Monte Carlo experiments, not possible to investigate. We further show, both analytically and with our simulations, that there is no omitted variable bias present in their simulations because their randomly generated non-distance variable is uncorrelated with any of the other variables used in their regression models. Full article

15 pages, 641 KiB

Open AccessArticle

Real Estate Valuations with Small Dataset: A Novel Method Based on the Maximum Entropy Principle and Lagrange Multipliers

by Pierfrancesco De Paola

Real Estate 2024, 1(1), 26-40; https://doi.org/10.3390/realestate1010003 - 31 Jan 2024

Abstract

Accuracy in property valuations is a fundamental element in the real estate market for making informed decisions and developing effective investment strategies. The complex dynamics of real estate markets, coupled with the high differentiation of properties, scarcity, and opaqueness of real estate data, underscore the importance of adopting advanced approaches to obtain accurate valuations, especially with small property samples. The objective of this study is to explore the applicability of the Maximum Entropy Principle to real estate valuations with the support of Lagrange multipliers, emphasizing how this methodology can significantly enhance valuation precision, particularly with a small real estate sample. The excellent results obtained suggest that the Maximum Entropy Principle with Lagrange multipliers can be successfully employed for real estate valuations. In the case study, the average prediction error for sales prices ranged from 5.12% to 6.91%, indicating a very high potential for its application in real estate valuations. Compared to other established methodologies, the Maximum Entropy Principle with Lagrange multipliers aims to be a valid alternative with superior advantages. Full article

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22 pages, 2043 KiB

Open AccessFeature PaperArticle

Housing Choices of Young Adults in Sweden

by Mats Wilhelmsson

Real Estate 2024, 1(1), 4-25; https://doi.org/10.3390/realestate1010002 - 12 Dec 2023

Abstract

This study investigates why young adults live with their parents in Sweden. As young adults’ living arrangements affect decisions about marriage, education, childbirth, and participation in the workforce, more knowledge for policymakers is crucial to implementing effective policies to support young adults and promote financial independence and well-being. Using a data set from 1998 to 2021 at the municipal level in Sweden, we used a spatial autoregressive panel data model to examine the proportion of young adults living at home and the regional disparities. The study uncovered intraregional variations that illustrate how different municipalities in Sweden exhibit different patterns of young adults living at home. Our findings reveal that economic factors such as unemployment significantly impact this pattern. Housing market dynamics, demographic factors, cultural differences, and location-specific characteristics also play an essential role in explaining this pattern. These findings suggest that the key drivers are the lack of rental housing, high unemployment rates, a high degree of urbanisation, interregional migration, and social capital (such as social cohesion and inclusion). Full article

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3 pages, 331 KiB

Open AccessEditorial

Real Estate: Discovering the Developments in the Real Estate Sector Using the Current Research Challenges

by Pierfrancesco De Paola

Real Estate 2024, 1(1), 1-3; https://doi.org/10.3390/realestate1010001 - 08 Oct 2023

Abstract

“Agenda 2030” is a wide-reaching plan established by the United Nations, in which 17 Sustainable Development Goals (SDGs) with 232 related indicators highlight the most important economic, social, environmental and governance challenges of our time [...] Full article

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