Real House Prices Research Articles

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.

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.

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.

Does monetary policy contribute to housing price booms? Empirical evidence from the US economy

Purpose This study aims to investigate the effect of monetary policy on housing prices for US economy. It specifically examines whether nominal or real interest rates are the key drivers behind fluctuations in housing prices in US. Design/methodology/approach Monthly data from January 1991 to July 2023 and various appropriate analytical tools such as unit root tests, Johansen’s cointegration test, vector error correction model (VECM), impulse response function and Granger causality test were applied for the data analysis. Findings The Johansen cointegration findings reveal the presence of a long-term relationship among the variables. VECM results indicate a negative correlation between nominal and real interest rates and housing prices in both the short and long terms, suggesting that a strict monetary policy can help in controlling the housing price increase in the USA. However, housing prices are more responsive to changes in nominal interest rates than to real interest rates. Additionally, the study reveals that the COVID-19 pandemic contributed to the upsurge in housing prices in the USA. Originality/value This study contributes by examining the role that nominal or real interest rates play in shaping housing prices in the USA. Moreover, given the recent significant upsurge in housing prices, this study presents a unique opportunity to investigate whether these price increases are influenced by the Federal Reserve's monetary policy decisions regarding nominal or real interest rates. Additionally, using monthly data, this study provides a deeper understanding of the fluctuations in housing prices and their connection to monetary policy tools.

Effect of conventional and unconventional monetary policy shocks on housing prices in Canada

This paper investigates the relative importance and effect of conventional and unconventional Canadian monetary policy surprises on housing prices. Using a credible approach to identify structural monetary policy shocks in Canada and a comprehensive Bayesian VAR model to analyze their effects on financial and macroeconomic variables, we find that both conventional monetary policy and quantitative easing shocks have a significant and persistent effect on housing prices in Canada. However, the inflationary effect of a quantitative easing shock is more pronounced than that of an easing target monetary policy surprise. Specifically, the peak effect of a 25-basis point expansionary conventional monetary policy shock is a 2.30% increase in real housing prices while a comparable quantitative easing surprise leads to a peak of 4.56% increase in real housing prices. We conclude that expansionary monetary policy in various forms has had significant inflationary effects on Canadian housing prices. But quantitative easing surprises stand out as the most prominent contributory factor to the escalating Canadian real estate price. Quantitative easing impact consistently outweighs the effects of forward guidance and conventional monetary policy shocks.

Türkiye’nin Gelenek Dışı Para Politikasının Lisanssız Güneş Santrallerinin Kârlılığı Üzerine Etkisinin Değerlendirilmesi

Türkiye’s unorthodox monetary policy implemented between September 2021 and June 2023 affected many macroeconomic indicators including inflation. Turkish Central Bank’s (CBRT) continuous lowering of the policy interest rate increased the negative real interest rate constantly. As a result, households invested in alternative assets including housing, foreign currency and gold in order to hedge against inflation. This increase in demand soared real estate prices. Besides, land is an important cost item for solar power plant investments. Considering the linear relationship between land prices and housing prices, this paper investigates the effect of the increase in housing prices on the capital expenditure (CAPEX) of 37 unlicensed solar power plant projects in Türkiye. According to the results, a correlation of -0.97 was determined between the real interest rate and housing price index in Türkiye. In addition, a correlation of 0.20 was found between housing price index and the CAPEX of unlicensed solar power plants. This situation indicates that the increase in housing prices primarily due to the unorthodox monetary policy might adversely affected the profitability of unlicensed solar power plants, since CAPEX is an important factor affecting the profitability. Although the unconventional monetary policy has been abandoned as of July 2023, the negative effects of this policy on the economy, especially inflation, still continue. Policies and practices that would increase the profitability of solar power plants will make significant contribution to the renewable energy investors and Türkiye's green transition. In this context, development and issuance of carbon development credits under the voluntary carbon market standards such as Global Carbon Council (GCC) Standard and International Carbon Standard (ICR) presents additionality to support solar power plant investors and help the country to reach her carbon neutrality target.

Revisiting international house price convergence using house price level data

The literature on house price convergence largely relies on house price indices, based in an arbitrary year, rather than on actual price levels. This is essentially due to the scarcity of comparable house price level data. However, this severely constrains the analysis. In particular, it often forces to discard a large part of the data sample, which leads to a great loss of information and hampers analysis on sub-periods. In this paper, we combine the price level estimates produced by Bricongne et al. (2019) with long OECD house price series to analyse long-run house price convergence across 18 OECD countries. Applying the Phillips and Sul (2007) procedure, we find convergence in OECD nominal house prices, but two separate convergence clubs in real house prices. We find some convergence in euro area real house prices, but no evidence of strengthening after the introduction of the euro. β-convergence regressions (linking changes in house prices to their initial levels) point to conditional convergence, related to the evolution of gaps in real GDP per capita, long-term interest rates and population growth across countries.

Drivers of household saving in East Central European countries. A push and pull model perspective

ABSTRACT There is no consensus in the economics theory about the determinants of household saving. The article composes vector error correction (VEC) models to identify the determinants of household saving in the East Central European countries from 2005–2020. Its novelty is that it identifies push and pull factors in accordance with the Keynesian and neoclassical theories whose mixed approach has not been included in the methodology of relevant papers in relation with East Central European countries. The examined countries are indicated to be homogenous from macroeconomic perspective. Results confirm that household saving increases because of decreases in consumer confidence, unemployment, and inflation rates. Increases in the deposit rate and real house price index are related to these pull factors, while decreases in the official share index correlates withincreases in household saving. Results can serve as guidelines for policy makers about incentives which stimulate household saving most effectively in the region.

Analysis of macroeconomic determinants of non-performance in consumer and mortgage loans

We investigate the macroeconomic determinants of non-performing loans (NPLs) in two dynamic unbalanced panels: consumer loans and mortgages, utilizing quarterly data for eight countries from 1992 to 2019. The article assesses which variables are key determinant factors, both in and out-of-sample, and whether they have the same impact in both portfolios. These variables are the lagged ratio of NPLs, credit level, real GDP, short-term real interest rates, real house price indices, and stock indices. We compare different econometric techniques applied to intermediate-sized panels and evaluate forecasting abilities. Results support pooled estimations, and mortgages exhibit higher sensitivities and better forecasting performance.

The measurement of financial support for real estate and house price bubbles and their dynamic relationship: An empirical study based on 31 major cities in China

<p>In recent years, China's real estate prices have continued to rise, preventing the bursting of the house price bubble, and the various risks it triggers has become an important issue that governments at all levels have to face. In this paper, the backward sup ADF (BSADF) method was used to dynamically portray the evolution of real estate price bubbles in 31 large and medium-sized cities in China over a period of 11 years, from 2013 to 2021, and the dynamic relationship between the degree of financial support for real estate (hereinafter referred to as financial support) and house price bubbles in cities was investigated by employing a panel vector autoregressive (PVAR) model with panel data. The results showed that: Multiple cyclical bubbles significantly existed in the real estate markets of the cities during the study period, and in general, house price bubbles appeared earlier in the more economically developed regions than in the less economically developed regions and have spread to the less economically developed regions. Financial support contributed to house price bubbles, supporting the theory of excessive financial support. Furthermore, the results of the sub-sample showed that financial support contributed most strongly to house price bubbles in cities in the northern region.</p>

Are There Housing Bubbles in Seoul Metropolitan Areas?: Evidence from Right-Tailed Unit Root Test

This study examines the explosive behaviors of house prices in Seoul and its metropolitan areas during 2008Q1~2023Q1. In order for the relationship between house prices and cash flows to reflect better the Korean housing market, this study adopts price-to-income ratio, real transaction-based house prices and personal income. Based on the generalized supremum ADF (GSADF) test, our empirical findings show that housing bubbles are identified in all three markets. According to the starting period, duration periods, and magnitude and prominent peaks among GSADF statistics, the bubbles in Seoul housing market appear to be most serious and further be transmitted to the housing markets of its metropolitan area, Incheon and Gyeonggi-do. Since the methodology used in this study provides policy-makers and investors with real-time information on bubbles, they could formulate a better early warning system to tackle the bubble problem. Specially, our empirical finding helps policy makers to prioritize Seoul over the other housing markets to cope with ongoing bubbles.

House prices and labour productivity growth: Evidence from OECD countries

This study examines the association between real house prices and labour productivity growth in 24 OECD countries over the period 1972–2019. By applying the panel fixed effects and Pooled Mean Group-Autoregressive Distributed Lag (PMG-ARDL) estimators, the results show that labour productivity growth is negatively and significantly associated with real house prices. This finding provides empirical support for the ongoing discussion on the adverse impact of excessive housing market activities on productivity.

Financial technologies and the effectiveness of monetary policy transmission

This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.