Housing Market Trends Research Articles

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.

Housing market trends: analyzing housing dynamics, evaluating mortgage risk, and understanding the impact of filtering on affordability

Housing market trends: analyzing housing dynamics, evaluating mortgage risk, and understanding the impact of filtering on affordability

Pragmatic Socioeconomics: A Way Towards New Findings on Sources of (Housing) Market Instability

ABSTRACT In this paper, we aim to define basic principles of pragmatic socioeconomics that may create a more solid interdisciplinary bridge between sociology and mainstream economics in the study of economic behaviour. The merit of this new concept demonstrates itself in the results of our research on the impact of social norms on home-buying behaviour and the consequences that such behaviour has for the operation of the housing market and housing price trends. That research demonstrates that interdisciplinary economic sociology may significantly enrich contemporary knowledge about housing price volatility – a phenomenon which increasingly determines social and economic stability in the world. Middle-range interdisciplinary research following the concept of pragmatic socioeconomics introduced in this paper is not limited to housing issues and may help fill in gaps in our knowledge of how markets operate in general.

What Is the Effect of Cultural Greenway Projects in High-Density Urban Municipalities? Assessing the Public Living Desire near the Cultural Greenway in Central Beijing.

Cultural greenway projects (CGPs) are widely regarded as an urban planning approach which connects open green spaces and sites of sociocultural value to provide access to living, working and recreational spaces and enhance local social well-being. This paper examines the impact of such CGPs on public living desire before and after a given project is completed through analyzing housing prices in the surrounding area. We deployed a hedonic pricing model (HPM) and differences in differences (DID) model to analyze and record any changes in housing market trends that may have been caused by such a cultural greenway project. Via analysis of single-family home sale transactions in central Beijing from 2013 to 2017, we found substantial evidence that proximity to a cultural greenway project is positively linked with rising property prices. Once complete, CGPs were similarly associated with positive increases per HPM and DID modeling. Our results revealed that the distance to greenway contributed significantly positive impact on the housing market after the cultural greenway project completed. Moreover, our result indicated that once a CGP was open to the public, it increased the price of properties within 1 km by 13.3%. Seller and buyer expectations of the development of local, green public infrastructure also began to factor into housing prices prior to the greenway opening to the public. Post-completion, the positive trend in property pricing due to local CGPs indicates that the public still have an increasing desire to live near the greenway. These results will help policymakers better understand how cultural greenways affect neighborhoods in high-density urban contexts, and will support the development of urban greenway policies for cities in China that reap the maximum economic benefit.

The Effect of the Expected Time-to-Purchase on the Acceptable Price Premium for Green Buildings

Green buildings help to mitigate the impacts of construction on the environment by reducing the use of natural resources and limiting the emission of air pollutants associated with building construction and maintenance. Homebuyers who understand the life-cycle benefits of green buildings (such as lower operating costs, better indoor environment and reduced environmental impacts) are often willing to pay an additional price premium for such buildings. Although several studies examined the factors affecting the acceptable size of green building price premium, how the expected time to home purchase might affect the acceptable size of such premium remains unexplored. Here, we attempt to answer this question by using data from a countrywide survey carried out in Israel, in which responses from 390 potential homebuyers were collected and analyzed. We find that the willingness to pay a price premium for green buildings changes significantly with time to purchase and is the lowest for respondents who state that they do not plan to buy a home anytime in the near future. We explain this rather unexpected result by arguing that people who have no immediate home buying intention, might have only limited knowledge about contemporary housing market trends and thus do not consider green building as a viable alternative to traditional construction.

The price\u2013rent ratio inequality in Scottish Cities: fluctuations in discount rates and expected rent growth

The price to rent ratio can be used to identify properties which are either overvalued or undervalued according to market fundamentals. Fluctuations in the price to rent ratio over time, can be traced to either changes in expectations of future house price growth (expected returns) or rental growth. In this paper, we measure the impact of these latent variables in Scotland’s main cities by implementing a state-space model based on the present value. The model estimates show that the proportion of expected rent growth and expected returns driving the price to rent ratio differs across Scotland. Glasgow seems to be driven mostly by expected returns, while rent growth drives price movements in Edinburgh. A geographic dimension is noted as cities on the East coast share similar expected returns and expected rent growth. Housing market trends in Scotland mostly follow the Edinburgh experience. Further decompositions show that house price changes are driven by an equal combination of expected rent growth and expected returns in Dundee and Aberdeen.

Primary Housing Market in the Context of Wages and Creditworthiness in Selected Cities in Poland in the Years 2006-2019

Purpose: The paper presents the evolution of average unit prices of apartments in selected primary local markets in Poland in 2006-2019. The period covers the end of the price increase phase, their correction, and then stabilization and another upward phase. A characteristic feature of the study is that prices of apartments were presented not only in nominal terms, but also in several real term approaches. Design/Methodology/Approach: The research was conducted using publicly available data on residential prices in selected cities. Prices were adjusted in a traditional way, i.e. by means of inflation indices, but also through the perspective of salary growth and creditworthiness. The results were presented graphically by means of charts. Findings: It turns out that the above approach to the evolution of housing prices may lead to conclusions that are quite different from the stereotypical ones concerning the assessment of the housing market situation, its forecasts, as well as the assessment of threats and consequences of relations among prices viewed in varying ways. In particular, it has been shown that the observed tendencies do not seem favorable, since they lead to the perception of an apartment as an exceptionally expensive good, which, unfortunately, will not become apparent until turbulence of interest rates and income hit the market. Practical Implications: The results of the research can be applied to forecasts of housing market trends and are particularly useful to developers, banks, realtors, potential apartment buyers as well as the government bodies responsible for housing policy. Originality/Value: Similar research has not yet been conducted in the local housing markets in Poland. The conclusions from the study can provide an important signal regarding the direction of changes on the housing market.

Relationship between Stock Market & Housing Market Trends and Liquidity

Relationship between Stock Market & Housing Market Trends and Liquidity

Income stagnation and housing affordability in the United States

Between 1980 and 2016 the share of households in the bottom quintile of the income distribution that owned their own home declined by 10 percentage points. For the same households, the share of monthly income spent on rent increased from 28% in 1960 to over 42% in 2016. To asses the extent to which income stagnation is responsible for the decline in affordability, I use Census microdata to construct counterfactual simulations that capture the evolution of housing market trends under alternative assumptions about the distribution of income. Income stagnation explains nearly the entire decline in affordability for the bottom quintile. Housing market frictions that cause the price of housing to deviate from marginal cost matter more to households further up the income distribution. Using Atkinson-type welfare-based inequality measures, I find that the counterfactual distribution of income – with inequality held constant – results in greater welfare for nearly all possible levels of inequality aversion.

SCENARIO METHODS FOR FORMING SUSTAINABLE ARCHITECTURE OF APARTMENT BUILDINGS

The article is devoted to the problem of preventing the moral aging of multifamily housing. The development of sustainable housing architecture facilitated by increasing the adaptability and transformability of architectural and planning decisions of such housing.The purpose of the study is to analyze the role of scripting methods in shaping a sustainable multi-family housing architecture. Scenarios for housing market trends are difficult to follow by extrapolation methods. Scenarios are to be created on a variant basis. The diffusion of scripting methods in architecture leads to the transformation of modern typology of buildings into an alternative methodology for their formation, based on the use of time-based models. The scenarios of possible changes in the housing architecture classified as follows. Among that are e the possibility of dividing the base apartments into parts that become independent small-sized apartments. In second - apartments and suites that are optimal for mass housing, providing the ability to combine individual apartments of a smaller size options. In third - realized the possibility of internal transformation of individual dwelling cells with a decrease in the number of rooms, or vice versa - with an increase in the size of the rooms while reducing their number in the apartment. At lust – the transformation of separate apartments on the first floors into non-residential premises with dismantling of internal partitions and redevelopment of space; the possibility for creating large halls on the first, intermediate or upper floor. Methods of creating adaptive housing architecture are within the current global movement for the formation of sustainable architecture, which, in the course of careful forecasting and design, tailored to fit the functional needs of parts of the home to changing needs. Adaptability of apartments to different scenarios of family development depends on the chosen structural system of a dwelling house. Possibilities of transformation of the space of the apartment considered taking into account planning cells with different wide step of bearing walls (steps: 6, 6.6, 7.2, 9 m). These studies, which carried out at an earlier stage of architectural development, are still relevant because architects continue to design homes, even with the use of prefabricated buildings, mainly based on the current sales situation, without taking into account the projected changes.

Residential property market determinants: evidence from the 2018 Australian market downturn

PurposeThe purpose of this paper is to validate and uncover the key determinants revolving around the Australian residential market downturn towards the 2020s.Design/methodology/approachApplying well-established time series econometric methods over a decade of data set provided by Australian Bureau of Statistics, Reserve Bank of Australia and Real Capital Analytics, the significant and emerging drivers impacting the Australian residential property market performance are explored.FindingsBesides changes in the significant levels of some key traditional market drivers, housing market capital liquidity and cross-border investment fund were found to significantly impact the Australian residential property market between 2017 and 2019. The presence of some major positive economic conditions such as low interest rate, sustainable employment and population growth was perceived inadequate to uplift the Australian residential property market. The Australian housing market has performed negatively during this period mainly due to diminishing capital liquidity, excess housing supplies and retreating foreign investors.Practical implicationsA better understanding of the leading and emerging determinants of the residential property market will assist the policy makers to make sound decisions and effective policy changes based on the latest development in the Australian housing market. The results also provide a meaningful path for future property investments and investigations that explore country-specific effects through a comparative analysis.Originality/valueThe housing market determinants examined in this study revolve around the wider economic conditions in Australia that are not new. However, the coalesce analysis on the statistical results and the current housing market trends revealed some distinguishing characteristics and developments towards the 2020s Australian residential property market downturn.

Eleven Ways Demographic and Economic Change Is Reframing American Housing Policy

ABSTRACTIn this article we identify 11 contemporary housing market and policy trends that will frame the next 10 years of federal housing policy. In each case, we review the relevant numbers before summarizing the policy issues raised by those realities. In some cases, these issues prompt specific policy recommendations. In other cases, they point to the need for greater research and debate.

Is social polarization related to urban density? Evidence from the Italian housing market

The aim of this work is to assess variations in housing market polarization in Italian cities since 2008, during the years of economic recession in Italy. An index of market polarization was constructed and correlated with urban density and socio-economic factors, as proxies for urban development of the Southern Euro countries.The hypothesis is that social polarization has increased since 2008, when an economic and sovereign debt crisis began, and is negatively correlated with housing market trends in more densely populated cities than in sprawl territories. Multivariate regression on housing price variations since 2008, with a dataset of economic variables concerning 112 Italian provincial capitals, was used to verify the hypothesis, and analysis confirmed that housing market polarization had increased since 2008 and shows significant statistical correlations with urban density, socio-economic characteristics, and housing affordability. Empirical evidence also demonstrates the close relationship among price trends, urban density, and the socio–economic structure of urban populations.

International population and housing market trends

International population and housing market trends

UK Social Housing and Housing Market in England: A Statistical Review and Trends

Around 80% of the 63 million people in the UK live in urban areas where demand for affordable housing is highest. Supply of new dwellings is a long way short of demand and with an average annual replacement rate of 0.5% more than 80% of the existing residential housing stock will still be in use by 2050. A high proportion of owner-occupiers, a weak private rental sector and lack of sustainable financing models render England’s housing market one of the least responsive in the developed world. As an exploratory research the purpose of this paper is to examine the provision of social housing in the United Kingdom with a particular focus on England, and to set out implications for housing associations delivering sustainable community development. The paper is based on an analysis of historical data series (Census data), current macro-economic data and population projections to 2033. The paper identifies a chronic undersupply of affordable housing in England which is likely to be exacerbated by demographic development, changes in household composition and reduced availability of finance to develop new homes. Based on the housing market trends analysed in this paper opportunities are identified for policy makers to remove barriers to the delivery of new affordable homes and for social housing providers to evolve their business models by taking a wider role in sustainable community development.

Improving decision-making performance through argumentation: An argument-based decision support system to compute with evidence

While research has shown that argument based systems (ABSs) can be used to improve aspects of individual thinking and learning, relatively few studies have shown that ABSs improve decision performance in real world tasks. In this article, we strive to improve the value-proposition of ABSs for decision makers by showing that individuals can, with minimal training, use a novel ABS called Pendo to improve their ability to predict housing market trends. Pendo helps to weight and aggregate evidence through a computational engine to support evidence-based reasoning, a well-documented deficiency in human decision-making. It also supports individuals in the creation of knowledge artifacts that can be used to solve similar problems in the same domain.An unexpected finding and one of the major contributions of this work is that individual unaided decision-making performance was not predictive of an individual's performance with Pendo, even though the average performance of assisted individuals was higher. We infer that the skills activated when using the tool are substantially different than those enacted to solve the same problem without that tool. We discuss the implications this result has for the design and application of ABSs to decision-making, and possibly other decision support technologies.

The Impact of Abandoned Properties on Nearby Property Values

Previous research has shown that housing abandonment contributes to neighborhood decline by depressing nearby property values. However, most past research estimated the impact of abandonment through cross-sectional analysis without controlling for nearby foreclosures or local housing market trends. Therefore, it remains unclear whether abandoned properties reduce nearby property values or whether abandonment is more common in areas with already lower-valued properties. Prior research also has not explored how the duration of abandonment influences nearby property values. Therefore, to extend the current level of understanding of the impact of abandonment, this research examines the impact of abandoned properties on nearby property values in Baltimore, Maryland, from 1991 to 2010 using longitudinal data sets while simultaneously controlling for both nearby foreclosures and local housing market trends. This research finds that as properties are abandoned for longer periods of time, the impact on nearby property values not only increases in magnitude but also is seen increasingly farther away.

Housing Bubbles and Expected Returns to Homeownership: Lessons and Policy Implications

House prices in many industrial countries increased dramatically in the years prior to 2007. Countries with the largest increases in household debt relative to income experienced the fastest run-ups in house prices over the same period. During the run-up, many economists and policymakers maintained that U.S. housing market trends could be explained by fundamentals. But in retrospect, studies now mostly attribute events to a classic bubble driven by over-optimistic projections about future house prices which, in turn, led to a collapse in lending standards. A common feature of all bubbles which complicates the job of policymakers is the emergence of seemingly-plausible fundamental arguments that seek to justify the dramatic rise in asset prices. A comparison of the U.S. housing market experience with ongoing housing market trends in Norway once again poses the question of whether a bubble can be distinguished from a rational response to fundamentals. Survey evidence on people’s expectations about future house prices can be a useful tool for diagnosing a bubble. In light of the severe economic fallout from the recent financial crisis, central bank views on the use of monetary policy to lean against bubbles appear to be shifting 1 .

The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales

We demonstrate how data from search engines such as Google provide an accurate but simple way to predict future business activities. Applying our methodology to predict housing market trends, we find that a housing search index is strongly predictive of future housing market sales and prices. For state-level predictions in the US, the use of search data produces out-of-sample predictions with a smaller mean absolute error than the baseline model that uses conventional data but lacks search data. Furthermore, we find that our simple model of using search frequencies beat the predictions made by experts from the National Association of Realtors by 23.6% for future US home sales. We also demonstrate how these data can be used in other markets, such as home appliance sales. In the near future, this type of “nanoeconomic” data can transform prediction in numerous markets, and thus business and consumer decision-making.

From global to local : Human mobility in the Rome coastal area in the context of the global economic crisis*

This paper focuses on the way problems caused by global changes overlap with local problems in coastal zones. It verifies the existence and dimensions of the global-local phenomenon by examining the impact of the recent international economic crisis on the core and ring administrative subdivisions of the coastal zone of the Rome metropolitan area from 2008 to 2010. In particular, it compares housing market trends with available statistics on tourism and migration to provide an indicator of the economic crisis. The results of the research show that to some extent, there is a connection between a drop in house prices and a decreased flow of human mobility.