House Price Fluctuations Research Articles

Effects of Tax Incentive Policies for Land Use on Local Socioeconomic Conditions: A Case of Tax Policies for Urban Regeneration Projects in Republic of Korea

South Korea has implemented several housing urban regeneration projects (URPs) and offers various tax incentives to support these efforts. However, the reality is that there is insufficient empirical evidence to determine whether these incentives have a socioeconomic impact on URPs. The aim of this study is to examine the effects of tax incentives related to urban regeneration projects (URPTAX) on local socioeconomic factors, such as Gross Regional Domestic Product (GRDP), aging housing reduction, and housing prices. Fixed-effect models and cost–benefit analysis methods were employed in the study. The results demonstrate the following outcomes. Firstly, URPTAX positively contributes to an increase in GRDP, a decrease in the proportion of aging housing, and an increase in housing price fluctuations. However, the effectiveness of these effects varies between metropolitan and non-metropolitan areas. Therefore, this study suggests the significance of providing stronger tax incentives for housing URPs in non-metropolitan areas to encourage active projects and foster balanced regional development in South Korea.

From welfarism to entrepreneurialism: Impacts of the “shanty-area renovation” scheme on housing prices in China

Urban renewal is emerging around the world as a tool for spurring economic growth and social regeneration. Over the past decade, the Chinese government has rolled out a nationwide “Shanty-area Renovation” (SAR) scheme which has been characterized as strong central state intervention and local state entrepreneurism. In order to facilitate the process of SAR, the central state has adopted financial and political tools to encourage local governments to be committed to the SAR scheme. With a change in state strategy, the goal of SAR transferred from a welfare-oriented redevelopment program in the beginning to a property-led oriented redevelopment program for the purpose of de-inventorizing the real estate market, resulting in rocketing housing prices. This study adopts a fixed-effect panel regression model to explain the influencing mechanism of SAR on housing price fluctuations across the country. This research concludes that the policy design of SAR could be directed towards urban regeneration beyond property-led development, and the social, economic and environmental objectives should be integrated into the SAR process.

Expectations and the housing market: A model of house price dynamics

AbstractWe examine the characteristics of housing markets under adaptive and heterogeneous expectations. Model agents have finite horizons, and their borrowings are constrained by the collateral value of housing stock. Our model shows that expectation‐driven housing price dynamics constantly change the direction of movement. The steady‐state process of housing prices follows an endogenous oscillation process, and the magnitude of the cycles can be amplified by external shocks. Our quantitative results imply that (i) short‐term positive and long‐term negative serial correlations in housing price changes are inherent, (ii) house prices and expected house price movements are positively correlated, and (iii) fluctuations in housing prices are not fully explained by fundamentals.

House prices, homeownership, and household consumption: Evidence from household panel data in Korea

Using Korean household panel data, this paper investigates the impact of house price changes on household consumption, focusing on asymmetric responses across homeownership status and the direction of house price fluctuations. I find that rising house prices have little influence on household consumption, whereas a decrease in house prices brings about a substantial impact. Falling house prices reduce homeowners’ consumption and raise renters’ consumption, implying that the opposing pressures on two household groups could substantially offset each other. The responses are found to be asymmetric across several aspects of household heterogeneities. Owners of multiple houses or relatively larger residences and older owners show greater responses. In response to rising house prices, homeowners with loan-to-value ratios at the standard cutoff level for a home equity line of credit substantially increase their consumption. Several pieces of evidence support the operation of the wealth effect and collateral effect channels.

A time-varying of property residential price in Indonesia: a VAR approach

The crisis of 2008 started with asset price bubbles which spread to other sectors, thus driving a recession. Turmoil in the housing sector can directly harm the domestic economy and financial stability. The research aims to analyze macroeconomic variables that can affect asset prices in Indonesia and how the inflation-targeting framework directly affects asset prices. This study contributes to the current research, such as the early warning system for the asset sector that the crisis of 2008 started with asset price bubbles. The Inflation Targeting Framework (ITF) policy used by the Central Bank has shown its effectiveness in the property sector. It can be seen that a negative response is shown from property prices when there are inflationary shocks. The response of interest rates to fluctuations in housing prices is stronger than the response of housing prices to fluctuations in interest rates. It indicates that the interest rate stimulus is more reactive to changes in housing prices as an accommodation of housing price volatility. GDP and money supply will respond negatively to property price fluctuations, which can lead to a crisis because GDP responds negatively. The strengthening of fiscal and monetary policy can soften the volatility of asset prices.

Extrapolative time-series modelling of house prices: a case study from Sydney, Australia

PurposeHouse price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.Design/methodology/approachWe specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.FindingsMultiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.Research limitations/implicationsWe demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.Originality/valueTo the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

주택시장과 거시경제의 관계에 관한 실증분석

The purpose of this paper is to analyze the relationship between the housing market and the macroeconomy using macroeconomic variables, and housing price variables of South Korea from the first quarter of 1991 to the fourth quarter of 2021. In consideration of the macroeconomic transmission mechanism of housing price fluctuations, I built a VAR model with variables such as real GDP, private consumption, housing investment, private credit, policy interest rate, and housing transaction price. In respect of the impulse response, the result of the analysis showed that housing prices rose when real GDP, private consumption, housing investment, and private credit had risen. When housing prices rose, real GDP, prices, private consumption, private credit, and policy interest rates rose. As a result of forecast error variation decomposition, I found that the contribution of changes in housing prices to changes in each variable was not significant, but changes in real GDP and interest rates had a major impact on changes in housing prices. In the historical decomposition I performed, the contribution of policy interest rates to fluctuations in housing prices was also high. In particular, private credit was considerably affected by the rapid increase in housing prices in 2020. Based on the above results, I found that the increase in housing prices had a relatively long-term impact on the credit market but a poor impact on the real economy through increased consumption and housing investment, while I confirmed that the GDP and interest rates had a major effect on changes in housing prices.

Overcapacity-driven regional waste incineration facility network planning with residential land value maximization involved: A case study of Shanghai, China

The effective implementation of garbage classification policies in metropolises appears to bring the government into a new quandary about the overcapacity of regional waste incineration facilities (WIFs). This paper proposes a bi-objective robust optimization model to replan the WIFs’ location and their logistics network toward operational cost minimization and regional residential land value maximization. Shanghai is selected as a real-case, and the garbage classification rate and house price fluctuation coefficient are considered as uncertain parameters. All Pareto solutions depict that the regional residential land value released by WIF's closure and subsequent "Not in My Back Yard" effect mitigation is huge, ranging from 74 to 102 billion yuan. Furthermore, the trade-off's robust solutions show that keeping 3 WIFs in the suburbs essentially maximizes the land value, while keeping 6 WIFs evenly distributed throughout the city has the lowest operating cost. Notably, the robust model has good anti-disturbance and the ability to adapt to external changes. As the population migrates to five new cities from the central city and reaches its peak, similar Pareto solutions are observed as those in the baseline scenario without the influence of policies.

Analysis of Factors Affecting the Dynamics of Residential Real Estate Prices in Russia

In this paper, we have constructed a VAR model to identify and assess the impact of real interest rate shocks, real estate demand, oil prices, uncertainty, and aggregate business activity on residential real estate prices in Russia. The relevance of the research is due to the following: the dynamics of real estate prices determines the consumer and investment behavior of households, and serious fluctuations in real estate prices lead to adverse consequences in many areas of life, so more and more researchers are asking questions about the presence of bubbles in the real estate market, which can be dangerous to the stability of the economy. In addition, a sharp increase in the cost of housing in Russia in 2020 is an open question for researchers. Our goal is to determine what factors caused the rise in real estate prices in Russia in the time interval from the Q1 of 2000 to the Q2 of 2022. A VAR model with a Cholesky decomposition was used for the evaluation. Several specifications were considered with the inclusion of the real oil price as an exogenous variable and a set of endogenous variables: real GDP, real interest rate, uncertainty index and housing price index. The main conclusion of the paper is that the housing market is sensitive to identified macroeconomic shocks, and a decrease in the interest rate leads to an increase in demand and real estate prices. The estimate of the long-term elasticity of housing prices for oil prices was 0.35, the dynamics of oil prices explained a significant proportion of the variation in real estate prices, but the predominant role in housing price fluctuations is given to housing demand shocks. The housing demand shocks in Russia itself had a negligible impact on GDP.

Is there a national housing market bubble brewing in the United States?

AbstractWe use a time-varying parameter dynamic factor model with stochastic volatility estimated using Bayesian methods to disentangle the relative importance of the common component in Federal Housing Finance Agency house price movements from state-specific shocks, over the quarterly period of 1975Q2 to 2017Q4. We find that the contribution of the national factor in explaining fluctuations in house prices is critical. We then use a Bayesian change-point vector autoregressive model that allows for different regimes throughout the sample period, to study the impact of aggregate supply, aggregate demand, (conventional) monetary policy, and term-spread shocks, identified based on sign restrictions on the national component of house price movements. While monetary policy and other shocks are found to be quite dominant early on, we find evidence that the national factor has been detached from the identified macroeconomic shocks since 2014, thus suggesting that a “national bubble” might be brewing again in the US housing market.

Spillover effect analysis of home-purchase limit policy on housing prices in large and medium-sized cities: Evidence from China.

Home-purchase limit is a unique administrative housing policy of China and has non-negligible influences on the housing price. The objective of this study is to analyze the spillover effect of home-purchase limit policy on housing prices in 35 large and medium-sized cities. The panel data of these cities and the spatial Durbin model are employed in this study. The results indicate that the spillover effect of home-purchase limit policy is positive and significant in all of 35 cities. However, when we categorize these cities into high-risk, medium-risk, and low-risk based on housing price characteristics, the spillover effect of home-purchase limit policy is different. It is not significant in high-risk cities, is negatively significant in medium-risk cities, and is positively significant in low-risk cities. This paper suggests that local governments can pay more attention to the precise design and implementation of home-purchase limit policy, and maintain policy continuity to avoid further spillover fluctuations in housing prices.

The Impact of Housing Demand on Housing Price Fluctuations—Taking Wuhan as an Example

The housing problem is related to the well-being of the people's livelihood, and the housing price problem has always been a hot topic of social concern. Since the beginning of the 21st century, the problem of expensive housing in big cities has become more prominent, and the problem of housing prices has plagued the people. With the rapid economic development of big cities, more and more people are pouring into big cities to work and buy houses, and house prices are also rising sharply. Due to the government's macro-control policies and the epidemic, housing prices have also been affected. This paper intercepts the time series data such as the average house price and the gross regional product (GDP), price index (CPI), the number of permanent residents and the per capita disposable income of residents in Wuhan from 2000 to 2020. Using multiple regression model, it is concluded that the demand-side factors such as GDP, price index and disposable income of residents in Wuhan will positively affect housing prices, and thus predict the fluctuation trend of house prices in Wuhan in the future and put forward corresponding suggestions.

1기 신도시 재정비 발표가 일산신도시 대상 아파트 가격에 미치는 영향 연구

This study empirically analyzed the impact of the announcement of the 1st new town redevelopmentplan on the price of apartments subject to redevelopment in Ilsan New Town. The actual transaction ofapartments over 30 years ago was turned into data, and a trend analysis and multiple regression analysiswere conducted. First, the transaction volume of Ilsan New Town is similar to that of the entire city of Goyang, but theactual transaction price is higher than the average of the entire city of Goyang. It seems that thelocation conditions, such as the subway station, are relatively good, and there are expectations forreorganization. Second, as a result of multiple regression analysis, the variables that have a positive (+) effect on theapartment price are the number of households, exclusive area, number of floors, and distance to thesubway station. Consistent with previous studies, it was found that the closer the apartment is, the moreit has a positive effect on the apartment price. The results of this study suggest that the announcement of the 1st phase of new town reorganizationis not a continuous factor influencing apartment sales prices in the Ilsan area, but appears to have beenreflected in housing price fluctuations as a short-term shock. It is presumed to be the reason for thecalm of anxiety and the return to wait-and-see attitude.

Real estate assets, heterogeneous firms, and debt stability

By constructing a “financial accelerator” model that combines real estate assets and heterogenous enterprises, we use China’s housing price data to explore the effect of real estate assets on corporate debt and macroeconomic stability in the context of the Chinese economy. Based on the dynamic economic characteristics of the model, we find that the financial accelerator mechanism of housing prices further amplifies the various effects of housing price fluctuations when transmitted to the macroeconomic system, resulting in the size of corporate debt closely related to the economic boom–bust cycles. However, owing to the institutional factors, heterogenous firms have some differences in debt stability under the influence of asset price fluctuations. There is an obvious crowding-out effect of state-owned enterprise (SOE) credit on private-owned enterprise (POE) credit, and the existence of the implicit guarantee ratio of SOE credit will weaken the external financing constraints on the SOE and promote the expansion of SOE credit. Finally, the effect of fiscal and monetary policies on corporate debt stability is somewhat divergent, institutional factors can similarly weaken policy effects.

House price volatility in China: Demand versus supply

AbstractThis paper studies the transmission mechanisms that underlie China's house price fluctuations using a dynamic stochastic general equilibrium (DSGE) model. The model is estimated with Bayesian methods, which accounts well for business cycle properties of the housing market. Results show that shocks to housing productivity and the government land supply to housing developers are the primary contributors to house price volatility, accounting for 37% of house price volatility in the short run and 32% in the long run. The importance of housing valuation shocks and shocks to migration only increases in models without the supply side of the housing market.

CMOs의 가치평가에 관한 연구

This study empirically analyzed whether real estate policies have a significant effect on housing sales, jeonse prices, and land sales prices using MBS is not active in Korea due to difficulties in evaluation. In the appraisal of MBS, the default risk is a cost that someone has to bear even if the government agency removes it through relevant guarantees. In this study, five CMOs data are evaluated and analyzed through the financial model developed based on traditional capital budgeting theory, option pricing theory, and Cho & Jun(2019)’s model recognizing that housing price fluctuation is an important factor affecting the default risk in MBS. Finally, the results drawn from this study help provide a theoretical framework for the valuation of MBS and show relevant implications for rational decision-making to MBS-related entities.

A theory of housing demand shocks

Housing demand shocks in standard macroeconomic models are a primary source of house price fluctuations, but those models have difficulties in generating the observed large volatility of house prices relative to rents. We provide a microeconomic foundation for the reduced-form housing demand shocks with a tractable heterogenous-agent framework. In our model with heterogeneous beliefs, an expansion of credit supply raises housing demand of optimistic buyers and boosts house prices without affecting rents. A credit supply shock also leads to a positive correlation between house trading volumes and house prices. The theoretical mechanism and model predictions are supported by empirical evidence, and the results are robust to alternative specifications of heterogeneity.

A Theory of Housing Demand Shocks

Housing demand shocks in standard macroeconomic models are a primary source of house price fluctuations, but those models have difficulties in generating the observed large volatility of house prices relative to rents. We provide a microeconomic foundation for the reduced-form housing demand shocks with a tractable heterogenous-agent framework. In our model with heterogeneous beliefs, an expansion of credit supply raises housing demand of optimistic buyers and boosts house prices without affecting rents. A credit supply shock also leads to a positive correlation between house trading volumes and house prices. The theoretical mechanism and model predictions are supported by empirical evidence, and the results are robust to alternative specifications of heterogeneity.

MACROPRUDENTIAL POLICY, HOUSE PRICE FLUCTUATION AND HOUSEHOLD CONSUMPTION

House purchasing has become an important asset allocation choice for most families in China. House price fluctuation is also one of the important factors that leads to systematic risks in the financial market, which might cause economic crises and then reduce consumption. Since China formally established the dual-pillar management framework of macroprudential policy in 2019, it has played a crucial role in maintaining the stability of house prices. This article employs the mediating effect model to comb the internal mechanism of the interaction between macroprudential policies, housing prices, and household consumption and test by the panel data of 30 provinces and cities in China from 2004 to 2019. Experience implies that macroprudential policy can not only stabilize consumption demand directly and effectively, but also affect consumption indirectly through the cross of the real estate market and the credit market. Further research has also found that macroprudential policies may fail between regions with higher GDP and high-income groups. This finding will contribute to research on the relationship between macroprudential policies and real economics. In addition, it would be helpful in making policies to increase consumption.

Analysis of Housing Price Fluctuations Using Bayesian Approach

본 연구는 베이지안 접근법을 이용하여 주택가격에 영향을 미치는 요인에 대한 파급효과를 분석하고, 다양한 형태의 사전분포를 실증분석에 사용하여 주택가격 예측에 가장 적합한 모형을 확인하였다. 분석결과, 매매가격과 전세가격 모두 자기 자신의 충격에 가장 큰 영향을 받았으며, 이자율 상승은 매매가격과 전세가격을 하락시킨 반면, 물가와 생산의 상승은 매매가격과 전세가격을 상승시키는 것으로 나타났다. 예측력을 비교한 결과, 일부 구간별로 차이는 있지만 대체로 Sims-Zha 베이지안 VAR의 예측력이 양호한 것으로 나타났다. 특히, 전국주택매매가격과 서울아파트전세가격은 모든 예측구간에서 사전제약을 강하게 부과할수록 실측치와 예측치간 오차가 작아졌으나, 서울아파트매매가격은 6개월 구간에서, 전국주택전세가격은 각각 3개월과 6개월 구간에서만 사전제약의 효과가 있었다. 또한 전국주택매매가격과 서울아파트매매가격은 모든 예측구간에서 장기균형관계를 고려한 가중치가 작을수록 예측의 정확도가 높게 나타났으나, 전국주택전세가격은 1개월 구간에서, 서울아파트전세가격은 각각 1개월과 3월과 구간에서만 장기균형관계의 가중치가 작은 모형이 우수한 예측력을 보였다. 본 연구는 거시경제 분야에서 많이 활용되는 다양한 형태의 사전분포를 활용하여 우리나라 주택가격 예측에 적합한 모형을 제시하였다는 점에서 의의가 있다.