After more than two decades of rapid growth, China's real estate market has gradually contracted in recent years amid economic weakness, with property prices beginning to fall sharply. Since new home sales in China primarily operate under a pre-sale system, where developers secure government land through auctions, mortgage that land to banks for development funding, and rely on bank capital alongside buyers' down payments and mortgages, the price decline not only adversely impacts banks' real estate loan risks but also leads to buyers defaulting due to insufficient collateral value, thereby amplifying systemic financial risks. Against this backdrop, our study examines the mediating role of educational attainment, measuring whether regional housing price fluctuations influence the non-performing loan ratio of commercial banks' real estate loans through educational levels. Using a bank-level panel matched to provincial socio-economic indicators, we estimate fixed effects models and implement a three-step mediation design with bootstrap inference. The evidence reveals a clear mechanism: changes in housing prices are associated with higher regional educational attainment; in turn, education is linked to greater credit expansion and higher non-performing loan ratios. Once this channel is taken into account, the direct link between housing prices and bank risk markedly attenuates, with the bulk of the overall effect operating indirectly through education. These patterns are economically meaningful, robust to alternative education proxies, and extensive resampling. The findings highlight a macroprudential paradox: while better-educated borrowers are typically safer at the micro level, improvements in human capital can, at scale, amplify risk-taking and balance-sheet exposure. Supervisors should therefore monitor human capital trends alongside collateral dynamics and incorporate them into early warning systems and the calibration of borrower and capital-based tools, so that bank risk assessments remain informative even in a housing market downturn.

Immigration and Regional House Prices in Iceland: Evidence from Transaction Data

Leisure and entertainment are one of the basic functions of a city. The leisure and entertainment services of urban residents have become an important symbol of the city and the driving force of social and economic development, and the quality of leisure life has become an important indicator for urban residents to measure their living environment and happiness. In order to explore the relationship of spatial patterns of entertainment service places in Hong Kong between residents' income and regional housing prices, this project studied the layout characteristics of entertainment service places in Hong Kong using R programming and investigated its relationship with residents' income and regional housing prices in the aspects of descriptive statistics, point pattern and area pattern analysis to provide references for entertainment service places planning in the process of urban development.

The aim of the article is to present results of the study on the link between business cycle and house prices in 16 regional capital cities in Poland. Using quarterly data for the period 2010-2024, the study finds that regional business cycle effects on cyclical fluctuations in regional house prices are predominantly positive. Following an increase in the National Bank of Poland (NBP) reference rate, house prices are on a decline in 11 out of 16 regional capital cities. The effects of housing quality and the exchange rate on house prices are ambiguous.

Deep-DFVAR: Dynamic factor vector autoregression with deep learning for regional house price index forecasting

As global climate change intensifies, extreme weather events, sea level rise and persistent droughts have become major challenges to the economic development of countries. Climate change not only affects ecosystems, but also has far-reaching impacts on urban economies, real estate markets and asset values. Real estate, as a typical long-term asset, is highly sensitive to environmental changes, so it is of great academic value and practical significance to study how climate change affects the real estate market, especially the volatility of house prices in different regions. This thesis provides an overview of the mechanisms by which climate change affects real estate market prices, explores how different types of climate risks act on real estate markets globally, and analyses the impacts of regional differences, policy interventions and market psychology on house price changes. In addition, the paper points out the gaps and deficiencies in the current research and proposes directions for future research.

ABSTRACT We document a significant change in the relationship between metropolitan and regional house prices during the COVID-19 pandemic. Given regional centres are spatially disconnected in Australia, we introduce a novel approach to defining submarkets based on common amenity. Treating the COVID-19 pandemic period as a negative shock to urban demand, we find that metropolitan areas became net recipients of house price volatility, while regional markets became net influencers during the pandemic, reversing the pre-COVID-19 submarket spillover pattern. This paper provides an economic context for ongoing regional housing unaffordability and discusses current policy responses that should be considered to address these challenges.

Co-movement of house prices across geographical markets (or a lack of such co-movement) has implications for labour mobility and the effectiveness of monetary and other national policies. Previous research on home value co-movement across the UK has yielded mixed findings. In this study we employ a variety of different metrics, and use a sample which includes the covid and post-covid time periods. We find that co-movement has fluctuated greatly over 50 years, but there has not been a clear upward or downward trend in cyclical cohesion over the last five decades. However, there has been a sharp increase in co-movement after the covid pandemic. This reflects a “flattening of the gradient” found in other studies. To the extent that more targeted fiscal transfers to lower-income regions, as well as a relaxation of planning rules for new housing development may encourage greater co-movement, these policies may be worth pursuing.

This paper explores whether a flattening of the gradient between high-price and low-price housing regions occurred in the UK after the outbreak of COVID-19 and assesses whether this flattening can be attributed to changes in demand among owner-occupiers and investors. Two hypotheses are established based on past literature: the Demand Increases Hypothesis and the Capital Inflows Hypothesis. These are used to explain why, in the post-COVID-19 period, the housing price gap decreased between regions with different level housing prices. The paper uses data from the period between January 2005 and October 2022 to test these hypotheses on the flattening of housing prices and identify the influencing factors that are driving the so-called catch-up effect. The two sets, which have different scales and ranges of regional housing markets, are examined: the first set comprises England’s nine regional markets, and the other set comprises the four regional markets of the UK: England, Scotland, Wales, and Northern Ireland. The analysis shows that the pandemic has drawn inter-regional prices closer and that the long-standing North–South divide has become less pronounced since the outbreak of COVID-19. However, the long-term convergence of London with other areas, and the reduction of the North–South divide, are related only to investment demand factors. This paper also finds that the flattening effect in the UK housing market tends to be caused by lower-priced areas rising to approach higher-priced areas. This flattening of the housing price gradient represents the gentrification of the low-priced regions, increasing concerns about housing affordability stress.

When home prices threaten to decline, large mortgage investors can benefit from fostering new lending that boosts demand. We ask whether this benefit contributed to the growth in acquisitions of risky mortgages by the Government Sponsored Enterprises (GSEs) in the first half of 2007. We find that it helps explain the variation of this growth across regions, as well as regional house price and credit changes. The growth predicted by this benefit is on top of the acquisition growth caused by the exit of private-label securitizers. We conclude that the GSEs actively targeted their acquisitions to counter home-price declines. This paper was accepted by Camelia Kuhnen, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.05912 .

When home prices threaten to decline, large mortgage investors can benefit from fostering new lending that boosts demand.We ask whether this benefit contributed to the growth in acquisitions of risky mortgages by the government-sponsored enterprises (GSEs) in the first half of 2007.We find that it helps explain the variation of this growth across regions as well as regional house price and credit changes.The growth predicted by this benefit is on top of the acquisition growth caused by the exit of private-label securitizers.Our results are consistent with the GSEs actively targeting their acquisitions to counter home-price declines.

This article proposes novel inferential procedures for discovering the network Granger causality in high-dimensional vector autoregressive models. In particular, we mainly offer two multiple testing procedures designed to control the false discovery rate (FDR). The first procedure is based on the limiting normal distribution of the t-statistics with the debiased lasso estimator. The second procedure is its bootstrap version. We also provide a robustification of the first procedure against any cross-sectional dependence using asymptotic e-variables. Their theoretical properties, including FDR control and power guarantee, are investigated. The finite sample evidence suggests that both procedures can successfully control the FDR while maintaining high power. Finally, the proposed methods are applied to discovering the network Granger causality in a large number of macroeconomic variables and regional house prices in the United Kingdom. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

The housing markets in districts across the United Kingdom (UK) co-move over time. We use the dynamic factor model to decompose the co-movement in house prices of the smallest possible geographical unit into national, regional, and idiosyncratic factors. Using the Bayesian time-varying parameter VAR (TVP-VAR) model, we study the dynamic impact of uncertainty shocks on synchronization in housing markets. We find that the estimated national factor accurately tracks the overall housing market cycles in the UK and explains nearly all the variations in East, South–East, and South–West districts. Furthermore, the results from TVP-VAR indicate that the estimated response of the national factor to uncertainty shocks is negative. However, the magnitude of the effect is more pronounced and persists longer in the case of housing price uncertainty shocks compared to overall economic uncertainty. Overall, our results suggest that uncertainty about house prices is a primary driver of the national factor.

Purpose – This study examines how GDP growth, interest rates, and unemployment rates influence residential real estate prices in politically and economically stable Eastern Euro- pean countries, aiming to identify key drivers of property value changes in the region. Research methodology – The study uses multiple linear regression and Pearson correlation (r) to assess the relationship between variables and housing prices, with ARIMA (3,1,0) applied for short-term price forecasts based on cyclical time series trends. Findings – The findings show a strong correlation between macroeconomic indicators and residential real estate prices, with the key influencing factor varying by country, reflecting diverse market sensitivities and regional economic contexts. Research limitations – The research is limited to Eastern European countries with stable political and economic conditions, excluding those facing instability. Future studies could expand the analysis to include such regions to provide a more comprehensive view. Practical implications – The results provide valuable guidance for policymakers and investors in crafting strategies tailored to specific macroeconomic conditions, enhancing market predictions and stability. Originality/Value – By focusing on the underexplored residential real estate market in Eastern Europe, this study contributes novel insights into regional housing price determinants and offers a foundation for further research on macroeconomic impacts in real estate markets.

This article is devoted to econometric modeling of factors influencing regional housing prices. In the national economy, the development of the residential real estate market is of significant relevance, since residential real estate objects play the role of the main investment asset for the real sector of the Russian economy. At the same time, the analysis of regional housing prices allows us to determine the current state of the residential real estate market, the determinants affecting it, and emerging trends. The results of such analysis become the basis for recommendations for developers and investors in the context of legal and economic reforms in the Russian Federation. At the same time, a comprehensive study of the domestic residential real estate market enables various stakeholders to make informed management decisions on the acquisition, construction of housing, or financial investments in it. Practical application of the panel regression model of pricing in the domestic residential real estate market contributes to a deeper understanding of the impact of existing determinants on housing prices, which increases the accuracy of further forecasts of the market in question.

This study analyzed the dynamic characteristics of household debt through an analysis of cash flow data for Bogeumjari loans. The overall loan balance was found to be largely influenced by mortgage inflows, whereas mortgage outflows remained relatively stable. Mortgage inflows, in particular, were strongly correlated with regional housing price fluctuations, with regions exhibiting more significant price fluctuations where inflow volatility was higher. A vintage analysis revealed that Bogeumjari loan borrowers maintained an average monthly repayment of around KRW 700,000 over an extended period. However, the repayment burden has risen rapidly following the rise in housing prices in 2022. A noticeable trend was observed in the increasing proportion of interest payments relative to principal payments, with interest repayments exceeding principal repayments from 2021 onward. Next, using a mortgage inflow and outflow projection model, this study predicted shifts in the distribution of the Bogeumjari mortgage pool. At the time of loan origination, loan-to-value (LTV) ratios were concentrated around regulatory thresholds (e.g., 60% and 70%), underscoring the role of LTV regulation in determining loan size. By contrast, the projected current loan-to-value (CLTV) distribution based on simulations showed a leftward shift in the central distribution, with a wider spread than the original distribution. This implies that changes in collateral housing prices have a greater impact than borrowers’ repayment behaviors. Lastly, an analysis of the distribution characteristics by CLTV levels revealed that high-CLTV borrowers held significantly larger loan amounts and exhibited slower debt repayment rates. This indicates that for effective household debt management and deleveraging, focusing on gradual principal repayment by high-CLTV borrowers is necessary. Moreover, incentivizing early repayment through fee waivers and fostering mortgage refinancing in low-interest-rate environments is crucial for stable management of household debt.

Inter-regional rail travel and housing markets connectedness between London and other regions

Monetary policy and house price heterogeneity: Evidence from the U.K

Although there is evidence that more regional airport activities can increase regional house prices, no study has examined the relevant impacts of aviation discontinuity. My unique quasi-experiment data comes from New Zealand where Jetstar withdrew its domestic services from four airports/regions in December 2019. The synthetic control method (SCM)'s results reveal that the withdrawal created different impacts on the house prices of the regions involved, in which the overall effect was negative in the short run but the housing market in New Zealand has recovered in the long run.

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