Housing Market Dynamics Research Articles

A Machine Learning-Based Early Warning System for the Housing and Stock Markets

This study analyzes the relationship between the housing and stock markets, focusing on housing market bubbles. Stock market dynamics generally have a more significant impact on housing price movements than housing market dynamics have on stock dynamics. However, if housing market information is provided as a signal, housing price movements can predict stock market volatility. Accordingly, we build a machine learning-based early warning system (EWS) for the housing market using a long short-term memory (LSTM) neural network. Applying the generalized supremum augmented Dickey-Fuller test to extract the bubble signal in the housing market, we find that the signal simultaneously detects future changes in the housing market prices and future stock market volatility, and our EWS effectively detects the bubble signal. We confirm that the LSTM approach performs better than other benchmark models, the random forest and support vector machine models.

Supplemental Material for Local Housing Market Dynamics Predict Rapid Shifts in Cultural Openness: A 9-Year Study Across 199 Cities

Supplemental Material for Local Housing Market Dynamics Predict Rapid Shifts in Cultural Openness: A 9-Year Study Across 199 Cities

Inter-generational differences, immigration, and housing tenure: Hong Kong 1996–2016

The present work purports to draw the links between two strands of literature: the vast literature on homeownership access across ethnic/migratory groups, and the emerging literature on inter-generational differences in ownership and their implications for wealth inequalities. It examines the case of Hong Kong, where homes are unbelievably expensive irrespective of the large public housing sector, and where recent immigrants from mainland China constitute a quasi-ethnic group even though the great majority of the local populations are Chinese nationals. The study draws upon the micro-data files of the 1996, 2001, 2006, 2010 and 2016 population censuses, and situates the analysis on the changing housing market dynamics and immigration scenes since the eve of the 1997 handover. The findings reveal a significant drop in homeownership among younger generations in recent years, and the drop is more pronounced for recent migrants from the mainland. The latter also suffer from increasing inaccessibility to public housing, rented or owned.

Time-frequency linkages of international housing markets and macroeconomic drivers

PurposeThe studies on international housing markets have not modeled frequency domain and focused only on the time domain. The purpose of the present research is to fill this gap by using the state-of-the-art econometric technique of wavelets to understand how differences in the horizon of analysis across time impact international housing markets’ relationship with some of the key macroeconomic variables. The purpose is to also analyze the direction of causation in the relationships.Design/methodology/approachThe author uses the novel time–frequency analysis of international housing markets’ linkages to the macroeconomic drivers. Unlike conventional approaches that do not distinguish between time and frequency domain, the author uses wavelets to study house prices’ relationship with its drivers in the time–frequency space. The novelty of the approach also allows gaining insights into the debates that deal with the direction of causation between house price changes and macroeconomic variables.FindingsResults show that the relationship between house prices and key macroeconomic indicators varies significantly across countries, time, frequencies and the direction of causation. House prices are most related to interest rates at the higher frequencies (short-run) and per capita income growth at the lower frequencies (long-run). The role of industrial production and income growth has switched over time at lower frequencies, particularly, in Finland, France, Sweden and Japan. The stock market’s nexus with the housing market is significant mainly at high to medium frequencies around the recent financial crisis.Research limitations/implicationsThe present research implies that in contrast to the existing approaches that are limited to the only time domain, the frequency considerations are equally, if not more, important.Practical implicationsResults show that interested researchers and analysts of international housing markets need to account for the both horizon and time under consideration. Because the factors that drive high-frequency movements in housing market are very different from low-frequency movements. Furthermore, these roles vary over time.Social implicationsThe insights from the present study suggest policymakers interested in bringing social change in the housing markets need to account for the time–frequency dynamics found in this study.Originality/valueThe paper is novel on at least two dimensions. First, to the best of the author’s knowledge, this study is the first to propose the use of a time–frequency approach in modeling international housing market dynamics. Second, unlike present studies, it is the first to uncover the direction of causation between house prices and economic variables for each frequency at every point of time.

Valuation Modeling within Thin Housing Markets Case Study: Arab Housing Market in Israel

The primary aim of this paper is to introduce valuation modeling applicable to thin housing markets, with a focus on the Arab housing sector in Israel. The estimation procedure utilizes two input values: transaction data and subjective valuations provided by property owners, the data for which are derived from the Israel Tax Authority (ITA) and the Household Expenditure Survey (HES). Average property values are also weighted and ranked according to location, size, and average income factors. The main contribution of these modeling techniques is that they can be employed to estimate the residential property values in markets that experience a low frequency of housing transactions and where information is limited, with the added benefit of understanding housing value movement and market dynamics. Housing policies could be influenced by this deeper understanding of house price behavior within localities and submarkets, potentially with the ability to monitor changes in dwelling values and segmentation and segregation effects.

Exchange rate pass-through to house rental prices. Evidence from the Buenos Aires’ semi-dollarized market

The relationship between the exchange rate and the consumer price index (CPI) has been extensively covered. However, aggregated approaches hinder the possibility of identifying specific features of this effect over different sectors of the economy, particularly regarding changes in relative prices. This paper aims to examine the dynamics of the rental housing market at a given shift in the exchange rate. We evaluate the case of the real estate market of Buenos Aires, due to its peculiar configuration: the coexistence of a highly dollarized sales segment and a market of housing rentals in which the operations are denominated in local currency. For this purpose, we carry out a two-step panel regression of spatially disaggregated offer rent prices to estimate the pass-through in a non-tradable market. The estimates show an exchange pass-through to rental prices exceeding 30%, more significant than we would have expected.

Does Tourism Contribute to Real Estate Boom? A DSGE Modeling in Small Open Economy

This article aims to investigate the relationship between inbound tourism and housing market along with the recent boom in Icelandic real estate sector, in which both house and rental prices have been rising dramatically. To this end, we construct a small open economy dynamic stochastic general equilibrium model enclosing a tourism sector and a housing market with owner-occupied and rental sections. The simulation results unveil a transmission channel that indicates the higher inbound tourism demand raises both house prices and rental prices. Variance decomposition and historical decomposition show that both inbound tourism demand shock and manufacturing technology shock are the key driving forces of the fluctuations of Icelandic house prices, consumption, and investment, whereas housing preference shock plays the most important role in determining the volatility of rental prices. The policy implications indicate that any shocks to tourism could easily spillover to housing market dynamics and aggregate fluctuations.

Housing market shocks in italy: A GVAR approach

In this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004−2016. In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the GVAR model is identified by using theory-driven sign restrictions. The spatio-temporal analysis carried through impulse response functions shows that there is evidence of a “ripple effect” mainly occurring through transaction volumes.

Relationships between young adults’ housing tenure, elements of perceived job security and social capital in Britain

PurposeAgainst the backdrop of the changing trends in tenure in the UK housing system, young adults are faced with different situations that continue to shape their housing consumption and decisions. The purpose of this paper is to investigate the relationships amongst young adults’ housing tenure, social capital and elements of perceived job security in Britain. Socio-psychological dimension of housing tenure decisions has been receiving attention by housing market analysts and practitioners seeking deeper understandings of the UK housing market dynamics, particularly in the wake of changing tastes and preferences of young people concerning housing decisions across major cities of the world.Design/methodology/approachA quantitative approach has been applied to the harmonised version of the British Household Panel Survey (BHPS) from 2001 to 2015.FindingsThe authors discovered that British young adults’ homeownership decisions are increasingly influenced by social capital and elements of perceived job insecurity, depending on their tenure of origin. Furthermore, this study will significantly enhance the understanding of tenure shifts amongst young adults in the UK and provide property developers, local authorities and central governments the knowledge and information to guide economic policies, urban renewal towards achieving better social cohesion and sustainable communities.Originality/valueVery little has been done to investigate the contributions of social capital formation, for example, neighbourhood or social integration and social relations and elements of perceived job security on housing tenure transitions among British young adults. This study will further provide property developers, local authorities and central governments the knowledge and information to guide economic policies, urban renewal towards achieving better social cohesion and sustainable communities.

An examination of house price movements in Queensland resource communities

ABSTRACT Successive mining “booms” have created wide-ranging, long-term socioeconomic impacts in many parts of Australia. Property markets were both directly and indirectly affected by the mining booms. Towns associated with mining activities experienced significant, rapid shifts in supply and demand levels for housing as well as changes to the amount and type of development occurring. The most recent “mining boom” in Queensland impacted on housing market dynamics, with impacts evident at all stages of the resource cycle. Housing markets were also indirectly affected by new actors and new drivers for buying property in these markets – as an investment. This paper aims to show that the “mining boom” was only one stage of a more complete cycle, and the impacts of this resource cycle on housing were particularly nuanced. Even in the short term, the importance of housing market stability-particularly measured through availability and affordability is important to the wellbeing of a town, and the underlying community. During the most recent cycle, housing markets in Queensland mining towns were uniquely affected.

A Dynamic Study on Housing and Stock Market in Europe : Focused on Greece

Purpose - This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), M3, real rate of interest (IR_REAL) and household credits (LOAN). We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology - Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration, Granger causality test, and impulse response function and variance decomposition analysis by EViews 11.0. Results - The statistical tests show that all variables under consideration have one unit root and there is a longterm equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK and LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions - It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

Revisiting the housing market dynamics and its fundamentals: new evidence from Cyprus

PurposeStudies have shown that economic expansion is characterized by the activities in the productive and industrial sectors. And, recently, the Republic of Cyprus has consistently experienced a relative economic growth. In this light, the current study revisits the dynamics of the housing market and its fundamentals for Cyprus using the quarterly data from 2005Q1 to 2016Q4.Design/methodology/approachProducer price and industrial production indices were employed along with the gross domestic product per capita and urban population as control variables. The empirical technique employed is the dynamic and fully modified ordinary least square approaches where unobserved factors are potentially controlled.FindingsEmpirical evidence of long-run relationship exists between the observed indicators and the house price. Indicatively, statistical evidence reveals a positive and significant long-run relationship between the producer price index and the house price. In a similar manner, there is a strongly significant but a negative long-run nexus of industrial production index and the house price. And, expectedly, the observed long-run nexus of the house price and each of real gross domestic product per capita and the urban population is positive and significant. Interestingly, there exists significant unidirectional Granger causality from each of the independent variables to the housing price. Lastly, the robustness check and the diagnostic test of the investigation suggest a very consistent result and stable model with no problems of serial correlation and heteroskedasticity.Research limitations/implicationsThe fragility of Cyprus's housing market suggests the need for the adoption of an effective policy framework.Originality/valueAlthough the housing market has been studied in the context of the Republic of Cyprus, the novelty is hinged on the joint incorporation of the industrial and producer price indices in a housing model of the study.

The Decision to Move House and Aggregate Housing-Market Dynamics

Abstract Using data on house sales and inventories, this paper shows that housing transactions are driven mainly by listings and less so by transaction speed, thus the decision to move house is key to understanding the housing market. The paper builds a model where moving house is essentially an investment in match quality, implying that moving depends on macroeconomic developments and housing-market conditions. The number of transactions has implications for welfare because each transaction reduces mismatch for homeowners. The quantitative importance of the decision to move house is shown in understanding the U.S. housing-market boom during 1995–2003. (JEL: D83, E22, R31)

The false promise of homeownership: Homeowner societies in an era of declining access and rising inequality

In the late 20th century, homeownership became entrenched in a wider societal project that sought to transform the economy and increase social inclusion. This project focused on mortgaged owner-occupation as a means not only to acquire a stable home, but also to realise greater economic security via asset accumulation. The underlying ideology featured an implicit promise that homeownership would be widespread, equalising and secure. Despite transformations in market conditions, such narratives have continued to underscore policy approaches and housing marketisation. This article directly confronts this promise. It first unpacks its key tenets before investigating their currency across three classic ‘homeowner societies’: the US, the UK and Australia. Our empirical findings reveal declining access to homeownership, increasing inequalities in concentrations of housing wealth and intensifying house-price volatility undermining asset security. The article contends that the imperative of homeownership that has sustained housing policy since the 1970s may be increasingly considered a ‘false promise’. Our analyses expose contemporary housing market dynamics that instead appear to enhance inequality and insecurity.

Determinants of Indian housing market: effects and counter-effects

PurposeThe purpose of this paper is to study the effect of the 2008 global financial crisis on housing market dynamics in an emerging economy like India using quarterly data (Q4 2008–2009 to Q1 2018–2019). The study explores the extent of linkages between housing prices, monetary policy and financial stability by explaining the nature of the shocks to the housing sector and the degree of impact of those shocks; the possibility of adverse feedback loop which is beyond the natural levels; and the usefulness of explicit and direct role of monetary policy for the housing market stability, which was the loudest demand immediately after the crisis.Design/methodology/approachThe paper follows a three-step methodology: data transformations, a variable selection process “general-to-specific modelling” with the help of OxMetrics 6 Package, and vector autoregressive modelling with the help of EViews 10. F-test was used to describe the short-term relationships between the variables. Impulse response and variance decomposition were used to explain the type of relationship (negative or positive) and the period of the relationships, respectively.FindingsThe study finds that the housing sector is sensitive to the monetary policy shocks, whereas the contribution of the housing market shocks to the fluctuations in other market variables is not substantial, though not negligible. As far as the nature of the shocks is concerned, the observed dynamics in the real house prices are diverging from their fundamental levels. The housing market shocks are more or less static; it rules out the chances for a self-reinforcing feedback loop with the existing setup.Research limitations/implicationsThe study concludes that the observed dynamics in the real house prices are diverging from their fundamental levels. Given the limitation, the researchers could extend this study by decomposing the part of the risk to the sector contributed by the other drivers, which may be inherent imperfections in housing markets, weak and unreliable wealth effect, and the presence of behavioural biases.Practical implicationsThe present study finds countercyclical measures to be more useful for this sector as compared to the forward-looking monetary policy reforms in this sector. The central bank in India should continue to refrain from responding directly to the housing sector fluctuations. Investors can enjoy investing in the housing sector without any fear of the crisis as of now. The effect of speculation is small but not negligible, which enjoins the investors and the policy-makers to remain watchful. Interest rate, money supply and inflation lead (Granger-cause) the housing prices. This information is relevant for spending and investment decisions.Social implicationsThe study feels that banks should avoid using monetary policy to balance the house prices. This will be beneficial both for the economy and the society, as any change in monetary policy to especially curb out surging housing prices may adversely affect the output, and finally, may lead to the deflation. The fear of deflation may cause devastating economic, financial and social effects.Originality/valueThe study contributes to the literature by shedding some new insights about the interrelationship between macroeconomic variables, housing prices and financial stability in the aftermath of the 2008–2009 financial crisis. Such types of studies are absent from emerging markets, particularly from India.

Towards Increasing Residential Market Transparency: Mapping Local Housing Prices and Dynamics

This article attempts to use spatial maps as a way of presenting additional information about the phenomena occurring in the housing market. In our opinion, spatial maps may facilitate understanding and provide more detailed information, which undoubtedly should increase the transparency of the housing market. The study used 12,219 transactions of apartments in Poznań in the years 2013–2017. General principles of price visualization activity and housing market dynamics were established in this study. The map of prices may reflect the location values determined by the quality of the urban infrastructure, distance from specific locations, and environmental factors. Market activity maps reveal areas where the market is dynamically developing, while information on trends in the number of transactions and price changes may demonstrate the growing or declining attractiveness of areas. The research is based on a model of hedonic regression in the form of ordinary least squares (OLS), quantile regression (QR), and geographically weighted regression (GWR). The maps presented should increase the transparency of the residential market (e.g., by providing more detailed information). However, one should bear in mind the limitations in the use of these methods resulting from a small number of transactions in a thin market.

A system dynamics model to evaluate the housing market response to vulnerability reduction promotion policies

Interventions such as seismic retrofits and reconstruction of vulnerable buildings can minimize the social and economic consequences of future earthquakes. Various policies can reduce the vulnerability of communities in the face of future earthquakes by enhancing the public risk perception and reducing the costs of interventions for the landlords. There is a need for appropriate tools that can characterize the dynamics of the housing market in response to these policies. The simulation model presented in this manuscript addresses this need. In this model, the decision of the tenants and landlords is characterized by utilizing prospect theory. The impact of candidate policy interventions on the housing market dynamics, the vulnerability reduction measures implementation rates, and the resultant reduction in the vulnerability of the building stock can be evaluated using the proposed model. The capabilities of the proposed model in simulating the policy-induced shifts in the demand between the housing units with different levels of seismic vulnerability, the response of the landlords to these shifts in the demand, and the consequent price movements are shown in the illustrative example. The results indicate that subsidizing the costs of interventions or solely enhancing public awareness may not lead to desired outcomes. It also provides valuable insights into the impact of individuals’ risk- and loss-aversion on their response to the evaluated policies. Practitioners can use the proposed model to design new policies that effectively enhance the resilience of communities.

The housing market and agricultural land dynamics: Appraising with Economic Policy Uncertainty Index

AbstractAgricultural land is a main component of the environment and ecological system. Therefore, this study employs the panel cointegration approach to investigate the dynamic relationship between the housing market vis‐à‐vis housing price (hp) and agricultural land (land) of a panel of 15 countries (countries with the gross domestic product–weighted average of the national Economic Policy Uncertainty index) over the period 1997–2015. Additionally, Granger causality approach of Dumitrescu–Hurlin is employed for the investigation. The model adjusts to the long‐run equilibrium with an annual speed of 11% from any situation of disequilibrium and with elasticities of −3.97 and −0.67, respectively, for a land and Global Economic Policy Uncertainty (gepu). Meanwhile, the impact during a short run of gepu is statistically significant and positive on hp, whereas it is not significant for land. Interestingly, the investigation reveals Granger causality from agricultural land to the housing price with feedback. The research presents an indication that policymaker(s) and urbanization stakeholders should be more concern about effective and sustainable long‐term policies. Future anomalies of food scarcity and skyrocketing house prices associated with agricultural land–house price trade‐off challenges could potentially be mitigated by such effective policy frameworks.

Real Estate Time-to-construct, Housing Market Dynamics, and Aggregate Fluctuations in China

ABSTRACT We study how construction delays determine the influence of various external shocks on China’s real estate market and macroeconomic fluctuations. We find that construction delays amplify housing price fluctuations due to demand-side shocks, but mitigate the effect of supply-side shocks; moreover, such delays weaken the influence of policy shock on output volatility, while increasing its influence on house price fluctuations. Under the presence of construction delays, loan-to-value ratio is more effective to stabilize housing market in the short run, whereas interest rate policy has more persistent impact over the longer term. To maintain both steady economic growth and stable housing prices, the government should encourage real estate enterprises to innovate and improve housing returns, while relaxing various approval processes to accelerate investment and encourage more timely supply of housing.

Equality as a driver of inequality? Universalistic welfare, generalised creditworthiness and financialised housing markets

Scandinavian countries are known for their universalistic welfare states, corporatist coordination, strong economic performances and egalitarian outcomes, an institutional combination often referred to as the ‘Nordic model’. However, these countries also possess volatile and increasingly vulnerable housing markets characterised by periods of sharp increases in prices and rents and some of the highest debt to income ratios in the world. The combination of a universalistic welfare state and housing market dynamics sets off a self-reinforcing process of increased stratification and re-familialisation. How did these orderly, egalitarian and welfare-oriented societies end up with housing markets that expose their citizens to increasing risk while driving inequality? The key lies in the effect the Nordic welfare state has on financialised housing markets. Successful decommodification of human lives leads to generalised creditworthiness which stimulates asset price inflation and new wealth and risk inequalities.