The sources of house price changes in Malaysia

During the last decade the courts have given attention to public school segregation which results from residential segregation. The precedent was established that when the past actions of school authorities in drawing attendance zones served to create or maintain school segregation, desegregation plans using busing could be imposed as a remedy.' At the same time, neighboring suburbs with their own school systems have not been included in the desegregation plans of affected cities, thus creating the option of moving to the suburbs in order to avoid busing.2 This paper reports on a study of house prices in Columbus, Ohio and neighboring suburbs during a period of increasingly imminent school desegregation. Most research on desegregation has examined changes in enrollment patterns; such a focus yields only an indication of relative shifts in demand for housing. This study directly observed changes in house prices. The study used Multiple Listing Service (MLS) data on 5888 sales between May and August for the years 1975 through 1979. Year to year comparisons were made which matched six suburbs to contiguous city neighborhoods which have similar types of housing. The purpose of the study was to determine the size of any change in the ratio of city to suburban house price differentials and the timing of those changes with respect to major events in the desegregation process. Year to year changes in the ratio of suburban to city house prices can be expected given a relative increase in demand for suburban houses and a housing supply which is inelastic in the short run. Following a typical capitalization argument, suburban and city house prices should in equilibrium adjust to expected school desegregation such that at the margin households are once again indifferent between a suburban or city location. It was hypothesized that the greatest capitalization impact of expected desegregation would be concentrated upon large houses (defined to be houses with four or more bed* I gratefully acknowledge the financial support of the Ohio Board of Realtors. The research has benefited

China has been undergoing significant social and economic structural changes since launching its policy of economic reform and opening up in 1978. This has involved a transformation from a centrally planned economy, where there is no role for the market, to a market-oriented economy in which market principles play a major role. During the last four decades, great achievements have been made in terms of economic growth and social well-being. To name a few indicators: the Gross Domestic Product (GDP) of the country increased from USD 189.65 billion in 1980 to USD 10.866 trillion in 2015, positioning China as the second largest economy in the world, with an average annual growth rate over 10%. Meanwhile, poverty levels have greatly improved. The poverty headcount ratio at USD 1.90 a day (2011 PPP) has decreased dramatically, from 42.15% in 1981 to 10.68% in 2013. The rapid economic growth, combined with the reform of the Hukou registration system, has also accelerated the migration flow from rural areas to urban areas. The population living in urban China in 2015 reached 763 million, making the urbanisation level of 55.61%, almost three times that in 1980. With the rapid growth of the urban population, the welfare-based public housing provision system founded in the central planning era could no longer meet the increasing housing demand of urban residents. Thus, in 1994, comprehensive housing reforms were implemented, aiming to privatize the public housing sector and promote a housing allocation system based on market principles. The milestone of housing reform occurred in 1998, when the government completely suspended the traditional housing allocation system, making the housing market the only way to access housing services (Wang et al. 2012). The emergence of the private urban housing market spurred both housing transactions and prices. In 1998, the housing area traded on the market was approximately 108 million square metres on an average transaction price of 1854 yuan/m2. These two figures were nearly ten and three times higher in 2014, soaring to 1.05 billion square metres and 5933 yuan/m2, respectively. At the regional level, rapid economic development has been accompanied by increasing inequality. Soon after the launch of the economic reforms, some coastal regions, Guangdong and Zhejiang in Eastern China, for example, grew quickly, due to the influx of foreign direct investment (FDI), advanced technologies and equipment, and favourable policies of the central government. The ‘core’ position of these regions in the national economy was further enhanced through a self-reinforcing process (Anderson 2012, p.127), shaping a core-periphery economic structure in China. In 1980, the regional gross product of Eastern China accounted for 43.69% of total GDP in China, while in 2014 this ratio increased to 51.16%, reflecting the polarization of economic activities. Reflecting the distribution of economic activities, the inequality in the cost of housing between regions is also striking. In 2014, the average sale price in 35 main cities in mainland China was approximately 8599 yuan/m2, with the standard error also high, at 4651 yuan/m2, making the coefficient of variance 0.54, thus indicating a high degree of heterogeneity across this city-level housing market. The left panel of Figure 1.1 shows the spatial distribution of average house prices. It is apparent that the prices in the coastal cities of Eastern China are generally greater than the prices of inland cities. However, the picture of house price dynamics is a little different. From 2002 to 2014, the rapid growth in house prices, on average 11.38% per year, seems to be anational phenomenon and there is very little variance between the annual growth rates in different cities; the coefficient of variance is only 0.18, much lower than that of the house price level. Perhaps the most prominent spatial pattern of house price growth rate is that the northeastern cities experienced the lowest price appreciation during the period 2002-2014. This dissertation is fundamentally concerned with the spatial patterns of house prices and their dynamics across cities in China. Although literature on the Chinese housing market has been emerging in recent years, little is known about the spatial interaction of regional housing markets. The following four chapters will be dedicated to responding to questions concerning the emerging market: Why is there a core-periphery structure in the distribution of interurban house prices? To what extent are the house price developments across cities similar? How do house price dynamics in one city affect the house price changes in other cities? The investigation of the spatial dimension of the Chinese housing market has been always hampered by the quality of the data, especially when analysing house price dynamics. This situation has inspired the pursuit of research to construct house price indexes that reflect the house price changes as accurately as possible. In line with a key theme of this study, particular a

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The commercial residential industry has high added value and comprehensive economic benefit so the commercial residential industry is naturally a hot-spot issue. The core issue of the commercial housing is the price. This thesis conducts the descriptive statistic analysis of residential real estate prices, urban resident income and other relevant data in China’s 30 provinces (excluding Tibet) from 1998 to 2006. The change trend and the difference feature of both the residential real estate price and the urban resident income in those regions are revealed, which is expected to make a contribution to the macro-control in China’s real estate. In recent years, the real estate market in China is growing rapidly. On the one hand, it plays a vital role in both promoting the national economic growth and improving the living standards of urban residents. On the other hand, some problems in the development of China’s current real estate market have been fully exposed, such as the overheated investment, the unbalance in supply and demand, insufficient financing channels, soaring property prices and so on. In particular, the rapid growth in the housing price has brought challenges to the sound development in both China’s real estate market and the whole national economy and it has also become a hot-spot and difficult issue in the current academia. Such relevant research as whether the rapid growth of China’s housing prices has become disjointed with resident income seriously or not and what the rules of the changes in income and housing prices in China’s different regions are is realistically significant for guiding the micro-control in China’s real estate. I. Index Selection and Disposal of Comparability The samples selected in this thesis are composed of the fluctuating residential real estate prices in China’s 30 provinces (excluding Tibet) from 1998 to 2006, urban resident income and other relevant panel data that are from various years of China Statistical Yearbook. The data of the real estate prices adopts the real estate prices in urban areas. The income indexes adopt the annual per capita disposable income of urban residents. In order to remove the impacts of the price and make indexes of various types had comparability in time series, the disposal of comparability has been conducted in indexes of different types in the thesis and their present value has been turned into the value of the constant price, namely, on the basis of the constant price in 1998, the concrete calculation method is that the housing price is deflated by the housing sales price index and the disposable income is deflated by the consumer price index of urban residents. II. Analysis of Commercial Housing Price Variance among Provinces According to the average housing prices and their growth rates in provinces from 1998 to 2006, thirty provinces, cities and autonomous regions across the country can be divided into three types in accordance with the mean and the growth rate of their average housing prices. It’s found that the provinces, cities and autonomous regions of the three types also have common in geographic areas so they can be divided into such three regions as the eastern region, the central region and the western region on the basis of their geographic areas. For the regional division of the average housing price in China, Figure 1 compares the changes in the average housing prices in the central, western and eastern regions from 1998 to 2006. It’s found that the average housing price in the east is prominently higher than those in the western and International Conference on Education Technology, Management and Humanities Science (ETMHS 2015) © 2015. The authors Published by Atlantis Press 1100 central regions and the trend of its average housing prices is on the rise. In particular, the rising trend of the average housing prices is obvious after 2004. The changes in the average housing prices in eastern and western regions are comparatively similar. However, the average prices in the central region are rising slowly while for the western region, a small decline also appears in its slightly rising process. Besides, the average housing prices in the eastern region surpass those in the western region after 2004. III. Analysis of the Differences in the Income Change among Regions Figure 1: Changes in the housing prices in the central, eastern and western regions Figure 2: Changes in the income in the central, eastern and western regions For the regional division of the average housing price in China, Figure 2 compares the changes in the income in the central, western and eastern regions from 1998 to 2006. It’s found that the per capita income in the east is prominently higher than those in the western and central regions and its trend is uniformly on the rise.

Foreign buyers and housing price dynamics

This paper investigates the relationship between changes in interest rate and house prices from the period 1975 to 2023 in five countries: United States, United Kingdom, China, Germany and Indonesia. Results show that contrary to the paradigm of real estate pricing, housing prices increase with interest rates. Furthermore we find that changes in house prices are independent of monetary policies and interest rate changes set by the central bank. Economically developed nations exhibit a stronger correlation between the two variables. We demonstrate that this is due to the 2008 financial crisis, where houses fell by nearly 30%, creating a fear of recession and the resulting policy of low interest rates to encourage investment.

We investigate the health effects of short-term macroeconomic fluctuations as described by changes in unemployment rate, house, and stock market price indexes. The 'Great Recession' provides the opportunity to conduct this analysis as it involved contemporaneous shocks to the labor, housing, and stock markets. Using panel data from the Health and Retirement Study over the period 2004-2010, we relate changes in hypertension status to changes in state-level unemployment rate and house prices and to changes in stock market prices. We consider hypertension, a disease related to stress and of high prevalence among older adults, that has received little attention in the literature linking macroeconomic conditions to individual health. Our analysis exploits self-reports of hypertension diagnosis as well as directly measured blood pressure readings. Using both measures, we find that the likelihood of developing hypertension is negatively related to changes in house prices. Also, decreasing house prices lower the probability of stopping hypertension medication treatment for individuals previously diagnosed with the condition. We do not observe significant associations between hypertension and either changes in unemployment rate or stock market prices. We document heterogeneity in the estimated health effects of the recession by gender, education, asset ownership, and work status. Copyright © 2016 John Wiley & Sons, Ltd.

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.

The long- and short-run influences of housing prices on migration

Editor's Introduction

Housing accounts for the largest portion of households' total assets in Turkey. It is an economic sector that requires careful analysis, especially considering the government's housing sector support policies and the significant price increases in recent years. This study utilizes the theoretical model developed within the Efficient Markets Hypothesis framework and the SVAR methodology to estimate house price changes. These changes are then decomposed into structural shocks, including supply, residential demand, and speculative demand shocks. The empirical results highlight the significant role of speculative demand in driving house price changes, with house price expectations being the main factor influencing speculative demand shocks. The behavior of the banking sector and interest rates also play a significant role in this process. Consequently, policies to stabilize house prices should consider these factors and not solely focus on credit regulations when consumer expectations are the driving force behind house price changes.

The Impact of the COVID-19 Epidemic on the Housing Market in China

The Spatial Dimension of House Prices

The economic reform in China, launched in the late 1970s, gradually promotes the free mobility of capital and labour between rural and urban areas, and between cities. The following housing market reform in the late 1990s thoroughly terminates the socialist allocation of housing and introduces market forces into the housing sector. Such institutional shifts have profound effects on the evolution of the Chinese interurban housing market. Yet, little is known about the spatial behaviour of house prices across cities in the post-reform era. How do the housing markets of different cities organise across space? What is the relationship between the house price dynamics of different cities? To answer these questions, this research performs economic and econometric analysis of the spatial dimension of the Chinese interurban housing market. In addition, this research also concerns the construction of a reliable house price index in the presence of spatial heterogeneity and dependence in the urban housing market of China. A reliable house price index is essential to the analysis of house price dynamic behaviour. However, owing to the data problem, this part is conducted based on the housing market of a Dutch city. This research discovers the spatial regularities of house prices across Chinese prefecture cities in an economic common area and investigates the underlying formation process. It reveals an uneven distribution of house prices across cities, with those large and/or higher-tier cities and their neighbours having significantly higher house prices. Such an uneven pattern of house prices demonstrates the agglomeration spillovers in the interurban housing market. Two forms of spillovers are empirically examined. The first is the urban hierarchy distance effect, which is related to the position of a city in a hierarchical urban system. In general, the distance penalty of higher-tier urban centres is confirmed, that is, all else being equal, the further away a city is from the higher-tier city, the lower the house price. The second form of spillovers relates to a city’s position in a city network system, in which no hierarchical structure is imposed. In such a situation, the spillovers arise from the interaction with neighbouring cities and it is found that a city that has larger neighbours tends to have higher house prices. These two forms of spillovers are somewhat correlated with each other because a higher-tier city is always associated with a larger urban size. It is argued that the spillovers in the interurban housing market work through two channels: the productivity and amenity channel. First, because of the economies of agglomeration, a location that has good access to large urban concentrations is likely to enjoy some productivity advantages and thus can bear higher house prices. Second, a location that is surrounded by large urban concentrations can easily get access to some unique amenities that need a large market potential to survive; households value such access and thus bid up the house price there. However, it seems that the role that the productivity channel plays is much more important than the role of the amenity channel. In addition to the static distribution of house prices across space, this research also concerns the time series behaviour of house price dynamics across Chinese cities. Geography plays an important role in explaining the cross-city differences of house price dynamics. For the housing markets of major cities across the whole of China, the cluster analysis generally uncovers two relatively homogeneous groups, within which the house price growth series share a similar dynamic pattern. One cluster contains mainly the cities in the undeveloped central, western and northeast China, whereas the other is composed of the most important economic centres in eastern China. However, the spatial segregation of housing markets is more likely to occur in the most recent period. In the early period before 2010, the house price dynamics of cities are much more homogeneous. The similarities and/or dissimilarities among house price dynamics of different cities indicate the complicated interrelationships between each of the markets. This research further examines various spatial interrelationships between the housing markets of an economic common area in south China. The spatial causal relationships between housing markets are first tested by the Granger causality test. The results reveal a complicated pattern, but it can be tentatively confirmed that house price changes in the developed eastern-central markets ‘cause’ the house price dynamics in the less-developed western markets. Then a spatial-temporal model is built to depict the diffusion pattern of house prices between markets. In general, a shock given to the house price of a certain market gradually spreads to its neighbouring cities. However, the interurban housing market can hardly remain an equilibrium relationship in the long-run, that is, it tends to be divergent. The last part of this research concerns the treatment of spatial effects in the hedonic house price model as well as its influence on the construction of hedonic imputation indexes, which measure the pure house price changes over time. It is argued that the value of a dwelling can be split into the value of the land and the value of the structure, and that the value of the location characteristics of a dwelling is capitalised into the price of the land. Thus, land prices can be expected to vary significantly across space. Indeed, the mixed geographically weighted regression framework adopted in this research, which allows the shadow price of structure to be constant across space and the implicit price of land to be property-based, is found to be superior to, in terms of model prediction, those models that restrict the spatial variation of land prices. Nevertheless, the Fisher imputation house price index based on the most sophisticated model is almost identical to those based on the simple specifications. The land and structure price indexes, on the other hand, are sensitive to the treatment of location in land prices. This research underlines market forces in the operation of Chinese interurban housing markets in the post-reform era, and contributes to the understanding of spatial dimension of house prices, not only in China, but also in other market-oriented economies.

Purpose– The purpose of this paper is to address a key issue fundamental to the operation of land and housing markets, that is, the relationship between land and house prices. The study identifies possible causation between established house and vacant allotment prices using the metropolitan area of Adelaide, Australia as a case study.Design/methodology/approach– A key outcome of the study is the construction of a Site Adjusted Land Price Index against which a Quality Adjusted House Price Index is compared.Findings– The results show that there is a lagged effect of land prices on house prices and that this is significant at an interval of eight lag periods. The results also imply that the lead lag relationship between established house and vacant allotment prices is not unidirectional. This suggests that, while a change in house prices leads to a change in land prices in the short-run, the long-run position is for increasing land prices to lead to a delayed increase in house prices.Research limitations/implications– Rising house prices do not simply and solely reflect a shortage of land. There are suggested effects both immediate from house to land and delayed from land to house, particularly in a rising market.Originality/value– The lead lag relationships of both indexes are tested using Granger causality estimates to assess whether theoretical Ricardian concepts still hold in a modern urban land market.