Residential Market Research Articles

A Spatial Mapping for Profitability Consideration of Rental Houses in South Jakarta

Abstract: The population of South Jakarta reached 2.235.606 people as of 2023 (BPS, 2024), with a percentage of occupying owned residential buildings of 51,36% (BPS, 2022). Estimates indicate that only approximately 1,148,207 people currently reside in private assets. Rental prices need to be considered based on the strategic location to minimize the risk of rental house business owners suffering losses. The imbalance in the supply and demand of the residential market will cause the availability of land in productive areas to be increasingly limited. The existence of an imbalance in market supply and demand can be an opportunity for prospective property entrepreneurs in the field of rental houses. The analysis was carried out by calculating income predictions using multiple linear regression methods and spatial analysis between rental houses and the accessibility of public facilities in South Jakarta City. The results obtained indicate that the accessibility of public facilities in Setia Budi Sub-district provides an opportunity for high income. Keywords: Boarding House, Income Rediction, Multiple Linear Regression, Spatial Analysis

Aggregated Housing Price Predictions with No Information About Structural Attributes—Hedonic Models: Linear Regression and a Machine Learning Approach

A number of studies have shown that, in hedonic models, the structural attributes of real property have a greater influence on price than external attributes related to location and the immediate neighbourhood. This makes it necessary to include detailed information about structural attributes when predicting prices using regression models and machine learning algorithms and makes it difficult to study the influence of external attributes. In our study of asking prices on the primary residential market in Warsaw (Poland), we used a methodology we developed to determine price indices aggregated to micro-markets, which we further treated as a dependent variable. The analysed database consisted of 10,135 records relating to 2444 residential developments existing as offers on the market at the end of each quarter in the period 2017–2021. Based on these data, aggregated price level indices were determined for 503 micro-markets in which primary market offers were documented. Using the analysed example, we showed that it is possible to predict the value of aggregated price indices based only on aggregated external attributes—location and neighbourhood. Depending on the model, we obtained an R2 value of 75.8% to 82.9% for the prediction in the set of control observations excluded from building the model.

Legacy and urban regeneration: long-term local impact of the London 2012 Olympic Games

ABSTRACT The 2012 London Olympics Games bid emphasized using the Olympics as an urban regeneration catalyst of one of London’s poorest areas and one of the Games’ legacies. This study’s contribution is an examination of this legacy using 2001–2022 data, analysing the pricing and sales changes in the residential property market in London’s 656 electoral wards, before and after the IOC announced the location of the Games in 2005, and when the Games were held in 2012. The results reveal a slight and short-lived positive difference between the Olympic Park wards and the rest of the city, particularly after the awarding announcement and the Games themselves. Regeneration efforts were successful but not necessarily in the ways outlined in the bid, as the local community (as was prior to the announcement) is not necessarily the main benefactor due to the predictable migration and gentrification of the area. The London Games exemplify the potential legacy of the Olympic Games but is also a cautionary tale for local communities in host cities.

Capturing the Value of Walkability

Capturing the value infrastructure investments add to the residential market is a longstanding policy to defray their expense. Unfortunately, estimates of the added value of infrastructure, generally, and estimates of the added value of walkability, specifically, are scarce. Novel, multiscale models free independent variables to manifest simultaneously at different scales of analysis to greatly improve specifications to precisely estimate walkability valuation. Results from analysis of years of transactions within walking distance of heavy rail stations suggest that walkability adds value available for capture locally, not systemically. Stakeholders confront myriad problems to replicate the accessibility characteristics shown to add value given the distinct cluster where walkability adds value available for capture in a heavy rail system.

Comparative Statistical Analysis of Changes in Average Asking Prices for Housing in the Administrative Districts of Moscow

The article presents the results of a comparative analysis of the residential real estate market in nine administrative districts of Moscow in 2016 and 2024. The paper focuses on the features of housing price formation and considers factors influencing pricing, including socio-economic conditions and transport infrastructure. The study outlines the role of housing construction and the investment attractiveness of various districts of the capital.The authors used official data from Russia's largest real estate technology service (CIAN) on asking prices for apartments for sale depending on their parameters. The article draws on such indicators as the local average price per square meter of the total area of dwellings and the number of offers of apartments for sale. It is shown that apartment prices in two administrative districts (AO) of Moscow have a stable growth trend in 2024, which was not observed in 2016. It is concluded that the real estate markets in the districts of Moscow in 2016 (exception for the Central AO) were strongly differentiated in price offers in 2024, and, therefore, it is incorrect to use the average price per square meter of Moscow residential real estate as a characteristic of housing quality in 2024.The article lists events that influenced changes in the Moscow residential real estate market without specifying the relative strength of their impact. According to the authors, each event had its causes, but their almost simultaneous appearance led to tension in the housing market for all participants.In conclusion, the significant impact of inflation and the restoration of residential premises (after renting) on the growth of residential property values and the potential for using housing as an investment object is emphasized

Not all about the money: Service quality information improves consumer decision-making

Information asymmetries are pervasive in many industries and can result in large losses in consumer welfare. Does providing product quality information result in improved consumer decision-making? We study this question in a market where quality is notoriously hard to determine ex ante: the residential energy market. Using a discrete choice experiment (N = 1,002), we document a substantial willingness-to-pay (37–45 % of the median bill) for four service quality attributes (transparency, agency, authenticity, and convenience). In an incentivized search task (N = 432), we show that how quality information is presented matters: consumers who view information in the form of ratings and stamps of approval are (i) 4 % more likely to opt in to the search task, and (ii) 20 % more likely to correctly identify given levels of quality, relative to consumers who are provided with bar graphs, pie charts, and text. Finally, using a decision experiment (N = 510) with real company names familiar to our participants, we find that the provision of quality information increases choices of the best-rated company more than 20-fold, relative to the control scenario where quality information is absent, in which consumers select companies predominantly on price and brand awareness. Our findings are applicable to other markets in which information asymmetries are present, where policymakers should consider interventions that promote transparency and quality information provision.

Determination of outliers when building a multivariate regression model of prices in residential real estate market of the region

The paper is aimed at selecting the optimal method for identifying outliers in the initial data when building a multivariate regression model of prices in the regional residential real estate market. The study was based on offers for sale of apartments in prefab flat blocks located in Irkutsk. In this regard, a basic multiplicative multivariate regression model was built, describing the dependence of cost indicators on the pricing factors of real estate. The identified outliers were iteratively removed from the basic model. The methods for detecting outliers included calculation of standard deviation (z-score), calculation of the Mahalanobis distance, as well as a method developed in the study for bringing the prices of objects to the characteristics of the reference object. The optimal method for detecting outliers in the initial data was selected by comparing the characteristics of the final variable-based multivariate regression models obtained after removing outliers from them. The analysis of the results proved the method of bringing the prices of objects to the characteristics of the reference object to be the optimal method of identifying outliers when building a multivariate regression model of prices in the regional residential real estate market. This method significantly reduces the approximation errors of the basic multivariate regression model of the market, thereby increasing the adequacy of the results of the real estate valuation conducted on its basis.

A Study of the Mediating Effect and Path of Customer Fit in Repeat Purchase Behavior in the Residential Market Driven by Digital Marketing Technology

Improving the repeat purchase intention of customers of real estate enterprises from marketing strategies is increasingly important for real estate enterprises to achieve the goal of stable and increasing long-term profits. This paper, driven by digital marketing technology, takes customer repeat purchase behavior in residential commodity market as the research object. The variables of brand community value, customer fit and repeat purchase behavior are first defined and selected. Then the relationship model of brand community value, customer fit and repeat purchase behavior was established, questionnaire research was conducted on mature real estate community members, and data analysis and structural equation model fitting were carried out using SPSS and AMOS software in order to test the mediating effect of customer fit in repeat purchase behavior in the residential market as well as the path. The study concluded that the standardized coefficient of customer fit on customers’ repeat purchase intention is 0.36, which has a significant positive effect. Meanwhile, customer fit has a mediating effect between the five dimensions of brand community value and repeat purchase behavior, and all five dimensions have a partial mediating effect in the process of influencing repeat purchase intention.

Credit and House Prices in the Irish Residential Market

Credit and House Prices in the Irish Residential Market

“How do I put this gently?”: articulating the link between racial selectivity in the sexual market and neighborhood selection in the residential market of a global city

Abstract The global city is acted upon by a myriad of forces—commercial, cultural, diasporic, digital, identitarian, and political to name a few—on local, national, and transnational scales that produce steadily morphing patterns and concentrations of LGBTQ+ residential settlement in and across neighborhoods. Research has sought to unpack the push–pull factors and adhesive elements that exert influence on such residential configurations. This forum piece ventures to articulate empirically one such pattern that has not been approached in the literature, but has, as the title portends, been addressed in anecdote gently (read: cautiously) for some time: the link between an individual’s stated racial preference in sexual-partner choice and that individual’s selection of a neighborhood to live in that has a high percentage of residents of the preferred race.

The heterogeneous response of real estate prices during the Covid-19 pandemic

Abstract We estimate the transmission of the pandemic shock in 2020 to the residential and commercial real estate market by causal machine learning, using granular data for Germany. We exploit differences in the incidence of Covid infections and short-time work at the municipal level for the identification of epidemiological and economic effects of the pandemic. We find that (i) a larger incidence of Covid infections temporarily reduced rents for retail real estate; (ii) a larger incidence of short-time work temporarily reduced rents of office real estate; (iii) the pandemic increased prices, particularly in the top price segment of commercial real estate.

Incentive mechanism and scenario simulation of residential energy-efficiency retrofits – From the perspective of tripartite evolutionary game

Energy-efficiency retrofits (EER) are increasingly becoming a key tool for sustainable building development. Compared to extensive urban renewal, refined building energy retrofits hold more practical value. Of this, the complexities arising from the differences in the claims of multiple stakeholders deserve our attention. However, limited efforts have been made in the existing literature to explore this issue. This paper constructs a tripartite evolutionary game model for residential EER from the perspective of engineering management. Taking a typical building in an old neighborhood in Nanchang, Jiangxi Province as an example, the theoretical model is validated. The results indicate that participants in the residential EER market display varying decision-making behaviors at different developmental stages. The government’s implementation of appropriate punitive measures in the early stages will encourage enterprises to participate in EER. Simultaneously, attention should also be paid to the demands of residents to ensure the smooth progress. Market-based renovation models should be actively promoted, and specific renovation programs should be created to accommodate varying requirements. This paper offers theoretical guidance for decision-making and developing residential EER.

Tax Induced Divestment in the Residential Market - Insights from Investors and Non-investors

Tax Induced Divestment in the Residential Market - Insights from Investors and Non-investors

A DSGE Model of the Russian Residential Real Estate Market

The paper develops a dynamic stochastic general equilibrium (DSGE) model of the Russian economy based on an endogenous housing sector and three categories of homeowners – patient, impatient and non-Ricardian. The DSGE model is applied from the first quarter of 2010 to the fourth quarter of 2019 using a Bayesian method for minimizing the discrepancy between theoretical and empirical impulse responses to a shock due to modified terms of trade. The model is then employed to provide a quantitative assessment of how macro variables respond to shocks generated by the housing market, interest rates, mortgage subsidies, financial liberalization, and altered terms of trade. At the same time, the impact of shocks on a number of economic indicators is largely determined by the functional form of household utility, as demonstrated by the robustness test. The results obtained based on the model also do not demonstrate a strong inertial effect in the economy due to the revival of the residential real estate construction sector, and they contradict a number of studies and expert estimates based primarily on the input-output model. One reason for this discrepancy may be the analysis, which is based on a horizontal supply curve, resulting in an overestimation of the impact of the construction sector on the economy. This DSGE model can serve as a starting point for scenario-based projections of the dynamics of the residential real estate market and the associated mortgage market, for testing the impact of various policy measures on the housing sector, and for assessing their effects on various categories of households.

Modeling Nairobi Residential Real Estate Prices using ARIMA

The residential real estate market is big and affords investors investment opportunities. The price changes are key in determining the overall return. Structural and atheoretical models are the two main approaches to modeling real estate prices. Structural models link prices to fundamental factors such as economic indicators and property supply, amongst others. Atheoretical models attempt to predict prices by leveraging on the statistical properties of time series data and may be extended to augment fundamental factors. This study focused on time series modeling using ARIMA. The objective of the paper was to identify a suitable ARIMA model that is efficient in predicting house prices in Nairobi. The training data was for the period 2010Q3 to 2019Q2. The out of sample test data was for six quarters: 2019Q3 to 2020Q4. The Box-Jenkins methodology was adopted. Seven ARIMA models and six AR models were identified, estimated, and used in predicting prices using out of sample data. The study found out that AR models outperformed ARIMA models. The paper contributes to knowledge being among the first to apply ARIMA in Nairobi house market using hedonic house prices. The paper may inform investment strategy and portfolio management by investors. It may inform policy since house price forecasts may have social and economic effects.

IMPACT OF SOME FACTORS ON PRICING IN THE REAL ESTATE MARKET OF RUSSIAN MEGACITIES

The authors analyze pricing in the residential real estate market in Moscow and St. Petersburg – the largest cities of the Russian Federation in the article. The issue of the cost of residential real estate is one of the most important for the residents of Russian megapolises. Megapolicies are the largest centers of migration, both from other regions and from other countries. The population of such cities is expanding at a significant rate, and the construction industry is increasing the rate of creation of new real estate objects. Under such conditions, it is crucial to realize the dependence of real estate value and key externalities.Within the framework of the study, the authors rely on the works in the field of real estate valuation and statistical methodology. The group of authors puts forward statistical hypotheses about the impact of some factors, in particular the level of cumulative inflation, the key rate set by the Central Bank of the Russian Federation, the average level of wages in the region and the weighted average rate on mortgage loans to citizens on the formation of the weighted average cost per square meter of housing in Russian cities.The statistical method of factor analysis is used to assess the significance of each of the factor variables on the resulting parameter. Regression modeling allows estimating the degree of impact of significant factors on the cost per square meter of residential real estate. The models allow to assess the trends of changes in the cost of real estate on the primary and secondary residential real estate markets in Russian megacities, as well as provide an opportunity to consider the differentiation in the impact of each factor between different types of markets in different cities.The results of the study may be useful in building industry forecasts and developing government measures to support residential construction.

Analysis of the current state and forecasts of the development of the residential real estate market of the Republic of Kazakhstan

Purpose of the study – describe the state of the Kazakhstan residential real estate market, identify the features and trends of its development. The authors of the study pay special attention to the analysis of the main indicators characterizing the residential real estate market, as well as the processes taking place in the mortgage lending market. Methodology – the study was conducted using methods of economic and statistical analysis, graphic method, method of description and generalization. The research sources were offi cial statistical materials of the National Bank of Kazakhstan, analytical reviews of consulting companies and fi nancial organizations, the «Krisha.kz» real estate platform and the «Kn.kz» real estate information portal, scientifi c research by Kazakh and foreign authors, as well as materials of scientifi c and practical conferences. Originality / value of the study – the authors carried out a detailed analysis of the state and problems of the residential real estate market of the Republic of Kazakhstan in recent years and gave forecasts for its future development. Findings. According to the results of research and analysis of the current state of the Kazakh residential real estate market in recent years, the authors identifi ed problems and identifi ed current trends in the development of the housing market, as well as forecasts of its future development. The results of the scientifi c article can be useful for real estate agencies, industry experts, as well as the scientifi c community involved in studying the real estate market.

Returns to solar panels in the housing market: A meta learner approach

This paper aims to estimate the returns to solar panels in the UK residential housing market. Our analysis applies a causal machine learning approach to Zoopla property data containing about 5 million observations. Drawing on meta-learner algorithms, we provide strong evidence documenting that solar panels are directly capitalized into sale prices. Our results point to a selling price premium above 6% (range between 6.1% to 7.1% depending on the meta-learner) associated with solar panels. Considering that the average selling price is £230,536 in our sample, this corresponds to an additional £14,062 to £16,368 selling price premium for houses with solar panels. Our results are robust to traditional hedonic pricing models and matching techniques, with the lowest estimates at 3.5% using the latter. Despite the declining trend, the additional analyses demonstrate that the positive premium associated with solar panels persists over the years.

POLAND AND UKRAINE: PERSPECTIVE OF INSTITUTIONAL ECONOMICS

The residential real estate market is one of the most important elements of any economy, based on housing objects that can be owned by different households on certain rights. Identifying all forms and rights of ownership in the housing market of Poland and Ukraine in accordance with the theses of institutional economics and comparing them was the main goal of the study. In our analysis, we want to confirm the hypothesis that the structure of property rights that exists in the residential real estate market and is described in various literature provides only a general description of the real situation. Therefore, the result of our research was the determination that the property rights operating on the housing market in Poland and Ukraine are much more diverse and complex than the five main forms described in the Ostrom model, which is the main basis for defining property rights. This made it possible to identify the existing forms of property rights, in particular for apartments that exist in the analyzed markets, and to establish the distribution of these rights among possible co-owners of these objects.

Occupational risk management in construction supply chain

The building is historically a driver of the economy, creating thousands of direct and indirect jobs, moving a huge chain of suppliers of raw materials, supplies and services, besides building a country’s infrastructure and the homes of millions of people. But working conditions in this sector that is so important to the country are not the best, exposing workers to risks of work accidents and occupational diseases. Therefore, this study sought to present the main occupational hazards in the construction industry, discussing alternatives for effective risk management by reducing the rates of accidents and illness among workers. In this research, case studies were done in small and medium-sized construction sector facing the residential construction market. It was also proposed solutions for the implementation of risk management and occupational health and safety for businesses to succeed and lower the rates of accidents at work, health and safety, and quality of work life in these companies.