House Price Fluctuations Research Articles

시차분포모형을 이용한 인구변화와 주택가격의 인과성 분석

This study analyzed the causality between population changes and housing price fluctuations by applying a distributed lag model and Granger causality test. First, the causality between housing sale prices and the three demographic factors was analyzed. The analysis results revealed that marriage and housing sale prices mutually influence each other, while housing sale prices affect mortality, and birth rates are influenced by housing sale prices. Next, the causality between housing lease prices (jeonse) and the three demographic factors was analyzed. The results showed no bidirectional Granger causality between housing lease prices and any of the three demographic factors. This indicates that birth rates, mortality, and marriage do not have mutual influences with housing lease prices. The findings of this study revealed that changes in housing sale prices have causality with demographic changes, whereas housing lease prices (jeonse) do not exhibit such causality. Therefore, a key policy implication is that demographic changes must be closely analyzed and addressed to ensure the stability of the real estate market in the future.

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.

The Spillover Effects of Public Attention and Real Estate Market: A Case Study from Shanghai, China

The real estate industry is closely linked to the national economy, and fluctuations in house prices have long been a major focus of public attention. This study explores the relationship between public attention and the real estate market, using public attention as a focal point. It systematically explains how public attention affects investment decisions in real estate. Taking Shanghai as a case, this study empirically examines the dynamic time-varying relationship between public attention and house prices, sales, investment and floor space completed by building a Time-Varying Parameter Vector Autoregression (TVP-VAR) model with data from 2011 to 2024.The research shows that the spillover index of house prices on public attention is positive and house prices acting as the sender of the shock, with rising house prices boost public attention. Conversely, the spillover index of public attention on house prices is negative, with public attention acting as the receiver of the shock. Based on the empirical results, it is recommended to incorporate public attention into the real estate market monitoring system, observe the real estate industry using multiple indicators, and enhance the regulation of online media to ensure policy transparency.

Does US Dollar Supply Trigger House Price Fluctuations? An International Comparison

Cyclical fluctuations in asset prices are closely related to the overall stability of the macroeconomy and have thus become a significant topic in academic and professional exploration. Among these fluctuations, changes in the supply of the U.S. dollar, the global reserve, and primary settlement currency have a broad and far-reaching impact on international financial markets. Since COVID-19, asset prices across various countries have shown differing trends due to fluctuations in the U.S. dollar supply. Housing prices, a key focus in asset pricing research, have been affected to varying degrees. This thesis utilizes seven house price indices from representative cities worldwide from 2020 to 2023 to compare the differential impacts across various countries using an empirical approach. The results indicate that the impact of the U.S. dollar money supply (M2) diminishes in a gradient from the U.S. to East Asia, and then to Europe.

Analysis of the Combined Impact of Socio-Economic Factors on House Price Volatility in the Housing Market

As an important variable in China’s economic system, real estate price is a key point closely linked to the country’s economy and people’s livelihood. It is of great practical significance to study the impact of socio-economic factors in the housing market on China’s house prices and its transmission mechanism, so as to put forward corresponding policy recommendations for stabilizing house prices and preventing real estate market and financial risks. Taking China’s time series data from 2014 to 2023 as a sample, this paper empirically investigates the law of the relationship between socio-economic factors in the housing market and house price fluctuations by constructing a structural vector autoregressive model, and employs impulse response function and variance decomposition to analyze the relationship between the two dynamically. The study shows that the 15-period variance decomposition effect of itself and residents’ disposable income are the main influencing factors of house price fluctuation, and the degree of explanation of its fluctuation is 55.5% and 23.2% respectively. In a market economy, real estate prices fluctuate up and down around their value due to the law of value. Therefore, real estate prices cannot rise indefinitely, and the final result should be stabilized within a reasonable level.

Energy Price Fluctuation and Real Estate Market Risk Prevention—Empirical Evidence at the Prefecture-Level City Level in China

Abstract The impact of energy price fluctuation on the macro economy is a hot issue that is continuously concerned by the academic community, but few literature have paid attention to the impact of energy price fluctuation on housing price and the financial risks that may arise. Based on the data of cities at and above the prefecture level in China, this paper empirically examines the impact of energy price fluctuation on the price fluctuation of the domestic real estate, and analyzes its influencing mechanism and transmission pathways. The results show that changes of energy price will significantly affect the fluctuation of domestic real estate price, and it is more obvious in large cities and megacities. Energy price affect the demand for housing through changes of interest rate levels on the one hand, and the supply of the real estate market through the cost of housing construction on the other hand, which leads to housing price fluctuation. After a series of robustness tests, the results are still valid. At the same time, the effect is asymmetric, that is, higher energy price increases the fluctuation of house price, but the impact of falling energy price is not significant. Therefore, when preventing real estate market risks, energy price should be considered as a forward-looking indicator to focus on, and the regulation and control policies of the real estate market should be scientifically formulated. This paper not only provides a new perspective on the mechanism of housing price formation, but also enriches the research on the interconnection between energy and financial markets.

Analysis of Regional Relationships in Housing Price Fluctuations : Focusing on Busan-Si, Changwon-Si and Gimhae-Si

Analysis of Regional Relationships in Housing Price Fluctuations : Focusing on Busan-Si, Changwon-Si and Gimhae-Si

Inheritance dynamics and housing price fluctuations: Evidence from the China household finance survey

The demographic shift towards an older population has a profound impact on the economy, particularly in the real estate sector. The evolving housing demand, shaped by changing family structures and financial circumstances, is influenced by inheritance considerations, which in turn affect investment decisions and market dynamics. This study uses data from the China Household Finance Survey (2013–2019) to explore the impact of aging on housing prices, with a focus on inheritance motives and the influence of male descendants. While ageing tends to decrease prices, inheritance motives, particularly those of male heirs, tend to offset this effect. The geographical distribution of this impact varies, with the level of education also playing a role. It is therefore vital to address demographic shifts and cultural norms in order to maintain stability in the housing market.

Labour supply and the cost of house price booms and busts

Fluctuations in house prices generate substantial heterogeneity in the price of purchase of similar dwellings depending on the time of purchase. These differences in the price of purchase have large effects on income-net-of-housing-costs. We document these effects using the large house price fluctuations during the recent housing boom-bust in Spain. Households can mitigate these impacts through changing labour supply. Men work more subsequent to paying higher house prices at purchase , whereas the correlation of house prices and labour supply for women is driven by selection: households where women work more, buy more expensive houses.

Research on Financial Crisis Warning Based on Vulnerability Index

After the global financial crisis in 2008, the early warning of financial crisis has become a necessary and urgent issue. It is of great significance to analyze the factors affecting financial crisis and clarify the relationship between credit growth, housing price fluctuation, current account deficit and financial risk in order to objectively and accurately predict the degree of influence of financial risk. This paper takes 41 global economies, including developed economies and emerging economies, from 1980 to 2019 as research objects, and analyzes the early warning ability of financial vulnerability indicators such as credit growth, housing price and current account deficit in a unified framework through panel Logit model. It is found that credit is not the only important indicator to predict crisis: when housing price, current account deficit and credit are under the same research framework, housing price and current account deficit have a lot of leading information, which can predict the occurrence of financial crisis; However, as house prices and current account deficits are added to the model, the early-warning power of credit is significantly lower than that of house prices. Paying attention to house price fluctuations and current account deficits has some implications for future policy making. In view of this, we should do a good job of cross-cycle policy adjustment, persist in curbing real estate financialization and bubbles, pay close attention to the direction and extent of current account adjustment, and prudently manage related financial risks.

Credit easing, income gap, and housing price fluctuation

The COVID-19 pandemic has caused a global economic recession, forcing several countries to adopt credit easing policies. This study examines the impact of credit easing on housing price fluctuations from an income gap perspective. Through the construction and analysis of a heterogeneous agent model, we reveal that credit easing promotes the rise of house prices and a positive correlation exists between the income gap and the effect of credit easing on house prices. Additionally, credit easing substantially enhances the housing demand of low-income people, increasing debt and house prices. The analysis using panel data from 36 countries from 1970 to 2018 confirms that compared to rising income for high-income people, a decline in the income level of low-income people significantly increases credit easing effect on house prices.

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.

An Analysis of the Impact of House Price Fluctuations on Subscription or Termination of Reverse Mortgage

An Analysis of the Impact of House Price Fluctuations on Subscription or Termination of Reverse Mortgage

ASSET‐MARKET SENTIMENTS AND BUSINESS CYCLE FLUCTUATIONS

AbstractWe present a tractable model that accommodates asset‐market sentiment in a standard Dynamic Stochastic General Equilibrium (DSGE) setting, allowing us to quantitatively evaluate sentiment‐driven macroeconomic fluctuations. In our model, changes in households' perceived uncertainty about housing prices lead to self‐fulfilling fluctuations in housing prices, which then impact investment and output through entrepreneurs' collateral constraints. Household sentiment shocks hence are transmitted and propagated to the macroeconomy, generating boom–bust cycles. Uncertainty, housing prices, and the real economy are linked. Quantitatively, the sentiment shock in the form of risk–panic is a crucial driver of business cycle fluctuations despite the presence of various competing shocks.

Housing, Distribution, and Welfare

AbstractHousing is a long‐lived asset whose value is sensitive to variations in expectations of long‐run growth rates and interest rates. When a large fraction of households has leverage, housing price fluctuations cause large‐scale redistribution and consumption volatility. We find that a practical way to insure the young and the poor from the housing market fluctuations is through a well‐functioning rental market. In practice, homeownership subsidies keep the rental market small and the housing cycle affects aggregate consumption. Removing homeownership subsidies hurts old homeowners, while leverage limits hurt young homeowners.

House price, gender spatial allocation, and the change of marriage matching

<abstract> <p>We investigated the relationship between changes in housing prices and marriage patterns among Chinese residents, considering the evolving real estate market and increasing prevalence of homogamous marriages. Using microdata from the China Household Income Project (CHIP) and urban housing price data, our results showed the following: First, housing price levels significantly decreased the likelihood of residents engaging in hypergamous mating and marrying individuals from lower social strata. Second, regional fluctuations in housing prices could influence residents' marital matches by affecting the spatial distribution of genders. Specifically, the higher the level of urban house prices, the greater the crowding out effect on marriageable men, and the less likely men in that area were to match downwards and marry women from lower social classes. Third, heterogeneity analysis indicated that residents in the eastern regions, younger populations, and migrants faced greater housing price pressures in the process of marital matching, resulting in a more substantial impact on these groups. The study contributes to marriage matching theories and offers policy insights for real estate reforms.</p> </abstract>

Influence Factor Analysis and Forecast of US House Prices Based on Linear Regression and Time Series

In the United States, house prices remain a perennial topic of interest for every resident. Beyond influencing individual housing choices, fluctuations in house prices play a pivotal role in shaping pleasant lifestyles and ensuring the nation's stable economic growth. The housing market, in fact, underpins the entire U.S. economic system. This study employed a multifaceted approach, utilizing both multiple linear regression models and time series analysis, to delve deeply into the factors influencing U.S. house prices. The research identified that residential construction spending and GDP are the most significant drivers leading to an increase in the American House Price Index (HPI). Additionally, through time series analysis, various graphical representations were constructed to visualize the quarterly trends in the American HPI, rendering the findings more comprehensible. In essence, this research offers a scientific foundation for future adjustments in housing price policies. It holds substantial relevance for all stakeholders in the real estate market, from buyers and sellers to developers and policymakers.

Study on the Dynamic Relationship Between Individual Mortgage Policy and Housing Price Fluctuation in Zhejiang Province -Empirical Analysis Based on SVAR

The eastern Chinese province of Zhejiang is highly developed and contributes to the real estate business. The paper uses quarterly data from 2011 to 2021 to create a Structural Vector Autoregressive (SVAR) model to explore the empirical dynamics between personal housing credit policies and house price changes in Zhejiang Province, China. Impulse response and variance decomposition research reveal that loan interest rates considerably affect housing values. Interest rates affect property values by 0.85% to 30.19% over time. The initial rise in loan interest rates boosts real estate values, but the successive increase will lower them until stability is reached. Large personal mortgage loans also affect housing prices. Throughout time, the share of factors affecting property prices with respect to mortgage loans ranges from 2.32% to 4.31%. The size of mortgage debt boosts home values. Thus, a corresponding easing of mortgage borrowing ceilings will boost home prices. The causal relationship between GDP and housing price swings is unclear, although its impact is stable with modest variations within a limited range. Zhejiang Province should be cautious when adjusting personal mortgage loans and interest rates while improving regulatory control. These techniques reduce market speculation and negative factors to ensure market stability and longevity.

Application of Machine Learning in Boston House Price Prediction

House prices are an important economic indicator for a country or region, rising house prices are often associated with economic growth and increased employment opportunities, while a decline in house prices may indicate an economic slowdown or other unfavorable factors. Governments and relevant agencies need to understand the dynamics of housing prices to formulate appropriate housing policies and plan urban development. As one of the major economic centers in the United States, the fluctuations in Boston's housing prices can reflect the local economic conditions and development trends. This paper selects data from Boston in 1970. Each record in this database describes a Boston suburb or town. The proposed method was evaluated using 5 metrics. By comparison, the paper ends up with the result that XGBoost works best out of the four regression models.

Housing prices and household consumption: a threshold effect model analysis in central and western China

The relationship between housing prices (HP) and household non-housing consumption (CON) is a key topic worldwide. By developing a panel threshold model and utilizing data from 18 provinces in central and western China from 2005 to 2020, this study investigates the impact of housing prices on household non-housing consumption given housing credit constraints. The results show that (1) housing credit constraints play a single threshold role in the impact of housing prices on household non-housing consumption; (2) the elasticity of housing price fluctuation on household non-housing consumption was negative in the western region during the entire sample period, and the elasticity of housing price fluctuation on household non-housing consumption decreased when housing credit constraints exceeded its threshold value; (3) the effects of housing price fluctuation on household non-housing consumption in the central region changed from negative to positive when housing credit constraints exceeded its threshold value. These outcomes implies that housing credit constraints are not a factor driving a low household non-housing consumption rate in the studied regions. Importantly, our findings suggest that unaffordable housing prices and homeownership linked to better public education resources in combination were a key factor leading to a low non-housing consumption rate in the studied regions. The main contribution of this paper is to supplement the current academic research on low levels of consumption in underdeveloped regions of China and the impact of housing prices on consumption.