Real House Research Articles

Mass subsidized mortgage: No extension, no termination?

After the launch of mass preferential mortgage program in 2020, subsidizing interest rates on housing loans has become a key factor affecting the primary housing market in Russia. In 2024, the portfolio of preferential mortgage lending approached RUB 9 trillion, indicating the high importance of this factor for the financial sector and the entire economy. Nevertheless, the effectiveness of subsidized mortgage programs and their effect on the socio-economic situation remain a subject of debate among economists, politicians and the public. The paper analyzes the impact of these programs on the residential real estate market, house prices and housing affordability. The core part of the paper contains the estimation of the scale of the substitution effect — the share of subsidized mortgage loans that would have been granted under market conditions. Based on the results obtained, alternative methods of housing support are proposed.

Equity Release Mortgages in the UK: Regional Characteristics of Demand and Supply

We consider the factors that affect regional variations in equity release mortgages (ERMs) in the United Kingdom (UK). These are a growing section of the market, but with regional differences in factors that affect demand and supply. We estimate a time series cross-sectional (TSCS) model within a simultaneous equation framework to analyse the number of ERMs (a proxy for the demand for ER debt) and the average loan-to-value (LTV) ratios, a proxy for supplied loan terms. We include variables that cover demographics, demand, pricing, risk, macroeconomic factors and regional dummies. For the number of ER loans, we find positive effects from net pension income and holiday costs, and negative effects from the average LTV ratio levels, state benefits, first-time buyer interest rates, female life expectancy, mortgage price differential, house price growth and gross value added (GVA). For the average LTV ratios, there are positive effects from gross pension income, average borrower age, holiday costs, and the risk premium, as well as negative effects from the number of ERM loans, female life expectancy, and the level of real house prices. Overall, households who are living in southern, wealthier areas have greater access to, and take greater advantage of, ERM loans but require lower LTV ratios. Our key findings are generalisable across the many countries that offer similar mortgage products and so our analysis offers insights for borrowers, lenders, and regulators.

Exploring Internal Factors that Affect Real Estates Prices: Evidence from Singapore

The purpose of this paper is to analyze the internal factors that generate the difference in real estate prices in Singapore. The objectives are to achieve a deeper understanding of the reason why prices of real estate are different at the same period and to provide a standard for investors to detect real estate with prices that are underestimated and consider whether to invest or not. This paper examines intrinsic factors that mainly affect real estate prices. Regression analysis is the core methodology to analyze the factors; the author used normalization to process the data. The result shows there is a strong relationship between the price of real estate and house age, distance to the nearest MRT station, the number of convenience stores, and the latitude. It can be discovered that the price of real estate negatively correlates to the house age and the distance to the nearest MRT station; positively corresponds to the number of convenience stores and the latitude.

Multidimensional house price prediction with SOTA RNNs

This paper introduces insights into the Turkish real estate market, which can be generalized globally. It primarily aims to find the best forecasting algorithms for the housing price index and compare their prediction performance over three, six, nine, and twelve months ahead by using recurrent neural networks (RNN) with a comparison of out-of-sample predicting power of econometrical models. For these purposes, we employ three RNN architectures in twenty-four settings, revealing that certain RNN architectures are the best predictors in forecasting the Turkish real housing price index. The RNN architectures outperform traditional econometric models; however, the more months forecasted, the lower the prediction power. The lagged values of the price-to-rent ratio, real rents, and the lagged USDTRY values contribute more than the other predictors in forecasting the real housing price index. The outcomes suggest that stocks, real estate investment trusts, and gold are neither complementary nor competing financial instruments since housing is an illiquid asset.

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

Real Estate Inflation and Housing Finance in India : Mapping the Correlation between Raising Property Prices & Increasing Home Loans among Indian Cities

Focusing specifically on India — a country that has recently faced recessions partially due to housing bubbles, like many other nations around the world — this research explores in depth how development of real estate linked financing sector have fuelled mortgage led asset price inflation across different cities (both metros & Tier II/III) over decades. Drawing upon a variety of market statistics, policy and economic indicators, the research identifies strong relationships between housing loan availability — by way of loosening mortgage regulations — and property price growth. The study shows that metropolitan cities have witnessed growth in housing loans at a CAGR of 10-12% over last decade (2010–2020) resulting into similar annual price appreciation for real estate standing between 010-15%. Tier II and III cities alternatively, exhibited slower but more stable growth trends in property prices of 6-8% driven by government push & infrastructure developments. The research emphasizes how this relationship has been altered by a number of variables, including as urbanization, demographic changes, government housing programs, and regulatory reforms like RERA and GST. The results imply that although housing financing has played a significant part in promoting the expansion of the real estate market, the influence varies greatly depending on local market dynamics, infrastructural development, and the state of the local economy.

The Monetary Policy of Real Estate Industry Implemented by the Government under the Covid-19

Abstract: Recently, the real estate become more and more prosperous and turn out the mainstay industry of Chinas economy. And monetary policy is a wise choice to control the development of the real estate industry. In the history of the development of Chinas real estate industry, different periods have different monetary policies implemented by the government. Recently, with the influence of COVID-19, the real housing industry has been in a recession. This essay summarizes the past monetary policies implemented by government and extends to the status quo of the real housing industry to find out the fitting monetary policy which can relieve the pressure brought by the COVID-19. The expansive monetary policy would reduce the bubbles of real estate industry while the constrictive monetary policy would enhance the real estate industry. And finally get the conclusion that government should choose to implement a tight monetary policy to boost the economy of the property sector.

Divorce law reforms and house prices in Europe

This study investigates the static and dynamic effects of legal reforms facilitating divorce on housing prices. Multiple mechanisms, such as variations in housing demand and supply, can be influenced by these law reforms. On the one hand, divorced individuals often require separate dwellings, thus increasing housing demand. On the other hand, an increase in supply is often precipitated by the divorcées needing to sell their married home. Detailed information was collected regarding the historical changes in divorce laws across ten European countries from 1960 to 2008. This data was combined with information from the annual Real House Price Index developed by Knoll et al. (Am Econ Rev 107:331–353, 2017). The study regards the divorce law reforms as providing a quasi-experimental setting. This is primarily because the entry timings of these reforms differ across countries and their target is not regulation of the housing market, but rather to simplify the dissolution of marriages. The study finds that divorce law reforms accounted for a substantial 22% of the average interannual increment in the Real House Price Index, particularly 3–6 years post reforms. Such a short-term, yet significant, impact was found to be consistent even after performing identification checks and including time-variant and invariant controls.

Eddison Walters Housing Market Globalization Theory: Building On, Eddison Walters Real Estate Housing Technology Structural Change Transformational Theory

Today’s housing affordability crisis has been caused by failure to acknowledge technological advancements that globalized housing markets that were once local. Policymakers, banking regulators, and the academic community slept at the wheel. On the heels of the Dot.com bubble, policymakers eagerly stepped in to avoid another economic crisis, accepting the false theory of a real estate housing bubble. Policymakers never considered that the growth in home prices could be real. Two decades after the declaration of a housing bubble, home prices continue to increase rapidly today. Evidence is clear the housing bubble never existed. The growth in home prices was real. Despite all the evidence suggesting real estate housing bubbles never existed. Policymakers have struggled to address today’s housing affordability crisis because of the failure to change course on ineffective policies implemented to address a real estate housing bubble that never existed. Lower interest rates will not solve the housing crisis we face today. The experts who concluded housing bubbles existed were wrong. The idea that lower interest rates will decrease housing costs suggests policymakers do not understand the problem. The failure to understand the structural transformation of the housing market means policymakers worldwide are still at a loss for solutions to address today's housing affordability crisis (Walters, 2024). The increased housing costs from the technological-structural transformation of the housing market between 1995 and 1999 resulted in globalized markets (Walters, 2024). The globalization of housing markets caused a significant shift in the demand curve of the global housing market that policymakers failed to address because policymakers accepted the misinformation of real estate bubbles as suggested by Eddison Walters Risk Expectation Theory of The Global Financial Crisis of 2007 and 2008 in Walters (2018). Walters and Djockic (2019) and Walters (2019) presented evidence supporting the theory developed by Walters (2018). The current research presents Eddison Walters Housing Market Globalization Theory that builds on Eddison Walters Real Estate Housing Technology Structural Change Transformational Theory.

Brexit and the London housing market: An empirical contribution

This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.

Influence of daylight on real estate housing prices. A multiple regression model application in Turin

Daylight is crucial in architecture, influencing human health, well-being, energy efficiency, and the post-COVID-19 perception of residential spaces. People often consider daylight among the most important features when buying a home, which potentially affects real estate asset pricing. Within this framework, this study explored the impact of daylight on real estate asset pricing, particularly focusing on its role in the Italian market. The research employed two approaches: (i) simulations of 100 units to determine a large set of daylight metrics and (ii) a statistical approach, applying Hedonic Analysis principles to investigate how house attributes influence pricing. A data sample of 100 housing units was selected in Turin (Italy), including variables such as location, floor area, construction year, façade type, and daylight metrics. By using Multiple Regression Analysis, after Exploratory Analysis and outlier management, we identified significant variables influencing housing listing prices, such as energy class, conservation status, elevator presence, terraces/balconies, and frame type. Notably, two daylight metrics (annual sunlight exposure and useful daylight illuminance) were found to be significant, while others, like average daylight factor and spatial daylight autonomy, were not. The final model was validated by means of a control sample, demonstrating the relevance of daylight in real estate pricing. This research contributes to the literature, providing an in-depth exploration of the impact of daylight on hedonic analysis in a relatively underexplored research space. Precisely, the work contributes to bridging the literature gap about the detection of the influence of daylight on real estate market pricing processes by means of regression analysis.

Do capital controls absorb global financial shocks? Evidence from emerging market economies

ABSTRACT This paper examines the role of capital controls as an effective policy instrument to insulate Emerging Market Economies (EMEs) from global financial shocks. Using state-dependent Local Projection method on a sample of emerging market economies, we find that economies with strict inflow controls are able to moderate the effects of global financial shock on GDP, real housing prices and private credit. We also find that monetary policy responds countercyclically to global financial shock in strict capital inflow controls state, which provides support for the use of inflow controls as a macroeconomic stabilising policy tool. Further, the results suggest that individual asset category inflow controls significantly contribute to overall effectiveness of capital inflow controls to act as shock absorbers. The findings suggests that the policy makers in EMEs may consider capital controls as an effective policy tool to increase the resilience of their economies against global financial shocks.

Housing Market Appreciation and the White-Black Wealth Gap

Abstract Real house prices in the United States have risen by 55 percent over the last four decades, driving substantial wealth benefits to homeowners. However, research has not explored how this rise in house prices has affected White-Black wealth gaps, or the mechanisms that may underlie this relationship. Using geocoded longitudinal household-level wealth data from the Panel Study of Income Dynamics and tract-level house price index data, I estimate that housing market appreciation between 1984 and 2021 explains 70 percent of the increase in the median White-Black wealth gap over this period. I find that most of this effect is due to White-Black gaps in homeownership, with White-Black gaps in house values playing a smaller role. In contrast to recent findings about racialized housing markets, I do not find that gaps in neighborhood house price appreciation between White and Black homeowners contributed to White-Black wealth gaps in the 2000s and 2010s. These results highlight the importance of cumulative advantage processes in driving wealth inequalities and demonstrate how the legacies of institutional racism contribute to contemporary racial wealth gaps.

Utilizing 31 Chinese province panel data models to investigate the factors influencing house prices

In the realm of data analysis, this research employs regression models to delve into the complexities of housing market dynamics. The construction sector of real estate development companies, the amount invested in real estate development, and the gross regional product have all been found to be important determinants of home prices. Interestingly, the most significant factor is the investment in real estate development, which has a significant impact on house prices. The analysis reveals a positive correlation between the gross regional product and investment amount in real estate development with housing prices, suggesting that as these economic indicators rise, so too do housing prices. Conversely, the author observes a negative correlation between the construction area of real estate development enterprises and housing prices, indicating that an increase in construction area is associated with a decrease in housing prices. These findings underscore the importance of considering these key factors when analyzing housing market trends, providing valuable insights for policymakers, investors, and researchers alike. By understanding these relationships, stakeholders can make more informed decisions to navigate the ever-evolving housing market landscape.

Das House Kapital: A Long-Run Theory of House Prices and Housing Wealth

Abstract Over the last 70 years, many advanced countries have experienced growing real house prices and an increasing housing wealth-to-income ratio. To explain these long-run patterns, this paper introduces a novel multi-sector growth model where housing services are produced using non-reproducible land and reproducible structures. Land is also employed in the non-housing sector. First, we identify two fundamental mechanisms driving the long-run increase in the real house price: (i) technological progress in the construction sector lags behind the technological progress of the rest of the economy and (ii) housing production is more land-intensive than non-housing production. Second, we study transitional dynamics for the US, UK, France, and Germany. Our calibrated model explains most of the observed increase in the housing wealth-to-income ratio since 1950. Counterfactual experiments identify initially low stocks of residential structures and non-residential capital as key exogenous drivers for this increase. The associated investment incentives led to a long-lasting construction boom and steadily increasing land scarcity, boosting residential land prices.

UTJECAJ ODABRANIH MAKROEKONOMSKIH VARIJABLI NA CIJENE STAMBENIH OBJEKATA U HRVATSKOJ

Recognizing the macroeconomic determinants that have a statistically significant influence on the formation of house prices is in the interest of the general public due to its informative effect on various interest groups involved in housing construction. Thus, real estate buyers, investors, as well as local government and self-government units should be interested in this information because monitoring of standard macroeconomic variables can provide conclusions about the possible development of residential property prices. Previously conducted research can be classified into four distinctive categories depending on what they take as determining variables: microelements specific to individual micro location, the impact of the COVID-19 pandemic, standard macroeconomic variables, or tourism development. The aim of this study is to analyze the influence of selected macroeconomic variables on residential property prices in Croatia. This study employs Autometrics, i.e. an automatic computer implementation of general-to-specific VAR (vector autoregressive) modelling framework and quarterly data on real GDP, domestic credit, consumer prices, interest rate, tourist arrivals and house prices in the period from March 2005 to September 2022. Performed Granger causality tests and impulse response functions analysis indicate that an increase in real GDP, domestic credit and tourist arrivals increases house prices in Croatia while an increase in consumer prices and interest rate reduces them.

Assessing the impact of urban expansion on carbon emission

Urban expansion is not only a driving force for economic growth and development but also a perilous element for anthropogenic carbon emission coinciding with population growth, urban expansion, land use pattern, urban sprawl. The study compares urban expansion and its impact on the carbon emission pattern for Rajshahi, a city of Bangladesh where land cover data is an important determinant. At first, the study aims to evaluate the pattern of urban expansion and the second step quantifies the carbon emission trend. The satellite images are used for land cover detection of urban expansion and Support Vector Machine (SVM) algorithm is applied for its classification. Similar carbon emission data are examined to relate carbon emission quantification rate by remote sensing algorithm. It indicates that urban expansion significantly explains carbon emission by comparing with similar secondary data to extract carbon emission and energy consumption. After accentuating urban expansion and carbon emission rate, the spatiotemporal pattern is analyzed in 16 different directions revealing that the urban expansion and emission trend expands to north-western and north-eastern directions of Rajshahi, turning it into a low carbon absorbed city. The responsible landmarks are real estate housing complex, educational institutions, student dormitories, industrial areas, brickfields and mango wholesale business. In order to understand the effects of uncontrolled urban expansion, this study will assist policymakers and urban planners in developing a comprehensive and well-organized strategy.

Do surging house prices discourage fertility? Global evidence, 1870–2012

This paper examines the relationship between house prices and fertility rates during the global fertility transition. We establish an analytical framework that considers the complementary nature of children and housing, leading to the hypothesis of a negative effect of house prices on fertility when they are highly complementary. We utilize a newly published house prices dataset spanning 1870 to 2012, covering multiple countries, and employ fixed effect and dynamic panel estimations to address identification challenges including unobserved heterogeneity and dynamic effects. Results show that surging house prices discourage fertility, with a ten percent increase in real house prices associated with a reduction of 0.01 to 0.03 births per woman. These effects are comparable to the impact of increased female education. Our findings offer insights into the evolving patterns of global fertility trends, underscoring the role of increased housing costs in shaping demographic changes.

주택매매시장에서의 거품에 관한 실증연구

This study examines the monthly real house price index movements over the period 1986-2023 using the GSADF method to determine whether bubbles existed in the Korean housing market, where they occurred, when they occurred, and how long they lasted by housing type (total, apartment, detached house, and townhouse). We summarise the main findings from our empirical analysis as follows. First, there were multiple bubbles in housing prices across the nationwide, Seoul, and all provincial metropolitan areas. However, there are many differences in how bubbles occurred across regions and types of housing. Second, the post-bubble period lasted much longer in the detached house market than in the apartment and row house markets. Third, many housing market bubbles occurred during periods of abundant liquidity. Fourth, while most bubbles are positive, appearing during periods of rapid house price appreciation, negative bubbles appeared in some areas (Busan, Gwangju, and Ulsan) during the 1998 Asian financial crisis. Fifth, the detached house markets in Busan and Ulsan are found to be bubbling at the end of the sample (December 2023). These results suggest that the GSADF test can not only detect historical bubble periods, but can also detect bubbles in real time, providing early warning of bubbles.

Project Environmental Factors, And Performance of Real Estate Development Housing Projects in Kenya; A Case of Real Estate Construction Housing Projects in Busia County, Kenya

This study aimed at providing practical strategies for reducing the influence of environmental factors on real estate housing building projects in Busia County. Data for this study was collected via focus groups, interview schedules, and questionnaires. Descriptive and inferential statistics were used to analyze the data. Respondents indicated agreement on a Likert scale that project environmental elements affect the success of real estate building housing projects in Busia County. The data analysis of the research indicated that project environmental variables somewhat impacted the performance of these projects. The research participants' views indicated a strong positive correlation (r=0.779) between Project Environmental Factors and Performance of real estate building housing projects in Busia County, with a statistically significant p-value of 0.000 < α=0.05. This indicates a strong correlation between the two variables, which back the alternative hypothesis and dismisses the null hypothesis.