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The 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.

The 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.

The 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.

The 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.

The 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.

The 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.

The 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.

By considering the rapid and continuous increase of housing prices in Turkey recently, this study aims to examine the determinants of the residential property price index (RPPI). In this context, a total of 12 explanatory (3 macroeconomic, 8 markets and 1 pandemic) variables are included in the analysis. Moreover, the residential property price index for new dwellings (NRPPI) and the residential property price index for old dwellings (ORPPI) are considered for robustness checks.

A quantile regression (QR) model is used to examine the main determinants of RPPI in Turkey. A monthly time series data set for the period between January 2010 and October 2020 is included. Moreover, NRPPI and ORPPI are examined for robustness.

Predictions for RPPI, NRPPI and ORPPI are carried out separately at the country (Turkey) level. The results show that market variables are more important than macroeconomic variables; the pandemic and rent have the highest effect on the indices; The effects of the explanatory variables on housing prices do not change much from low to high levels, the COVID-19 pandemic and weighted average cost of funding have a decreasing effect on indices while other variables have an increasing effect in low quantiles; the pandemic and monetary policy indicators have a negative and significant effect in low quantiles whereas they are not effective in high quantiles; the results for RPPI, NRPPI and ORPPI are consistent and robust.

The results of the study emphasize the importance of the pandemic, rent, monetary policy indicators and interest rates on the indices, respectively. On the other hand, focusing solely on Turkey and excluding global variables is the main limitation of this study. Therefore, the authors encourage researchers to work on other emerging countries by considering global variables. Hence, future studies may extend this study.

The COVID-19 pandemic and market variables are determined as influential variables on housing prices in Turkey whereas macroeconomic variables are not effective, which does not mean that macroeconomic variables can be fully ignored. Hence, the main priority should be on focusing on market variables by also considering the development in macroeconomic variables.

Emerging countries can make housing prices stable and affordable, which will increase homeownership. Hence, they can benefit from stability in housing markets.

The QR method is performed for the first time to examine housing prices in Turkey at the country level according to the existing literature. The results obtained from the QR analysis and policy implications can also be used by other emerging countries that would like to increase homeownership to provide better living conditions to citizens by making housing prices stable and keeping them under control. Hence, countries can control housing prices and stimulate housing affordability for citizens.

The neighborhoods north and northwest of downtown St Louis are blighted by their abundance of substandard, abandoned, and demolished housing. Crime, poverty, and unemployment are high while family stability, educational achievement, and health outcomes are low. These conditions are not unique to St Louis, but can be found in neighborhoods in every city in America. How did this happen? What factors led to the demise of these neighborhoods? This chapter examines the history of St Louis along with theories of neighborhood succession to identify possible explanations for the city's collapse.

In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective.

This study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019.

The results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities.

Few policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.

Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social and structural challenges, homeownership by the low and lower middle-income household is pivotal for its structural transformation process. In spite of these potential benefits, research on the affordable housing market in the context of South Africa is limited. This study aims to contribute to this knowledge gap by answering the question “do changes in household income per capita have a symmetric or asymmetric effect on affordable house prices?”

A survey of the international literature on house prices and income revealed that linear modelling that assumes symmetric reaction of macroeconomic variables dominates the empirical strategy. This linearity assumption is restrictive and fails to capture possible asymmetric dynamics inherent in the housing market. The authors address this empirical limitation by using asymmetric non-linear autoregressive distributed lag models that can test and detect the existence of asymmetry in both the long and short run using data from 1985Q1 to 2016Q3.

The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and logIncome[−] are 1.080 and −4.354, respectively, implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. The positive increase in affordable house prices creates wealth, helps low and middle-income household climb the property ladder and can reduce inequality, which provides support for the country’s structural transformation process. Conversely, a decline in affordable house prices tends to reduce wealth and widen inequality.

This paper recommends both supply- and demand-side policies to support affordable housing development. Supply-side stimulants should include incentives to attract developers to affordable markets such as municipal serviced land and tax credit. Demand-side policy should focus on asset-based welfare policy; for example, the current Finance Linked Income Subsidy Programme (FLISP). Efficient management and coordination of the FLISP are essential to enhance the affordability of first-time buyers. Given the enormous size of the affordable property market, the practice of mortgage securitization by financial institutions should be monitored, as a persistent decline in income can trigger a systemic risk to the economy.

The study results illustrate the importance of homeownership by low- and middle-income households and that the development of the affordable market segment can boost wealth creation and reduce residential segregation. This, in turn, provides support to the country’s structural transformation process.

The affordable housing market in South Africa is of strategic importance to the economy, accounting for 71.4% of all residential properties. Homeownership by low and lower middle-income households creates wealth, reduces wealth inequality and improves revenue collection for local governments. This paper contributes to the empirical literature by modelling the asymmetric behaviour of affordable house prices to changes in household income per capita and other macroeconomic fundamentals. Based on available evidence, this is the first attempt to examine the dynamic asymmetry between affordable house prices and household income per capita in South Africa.

This paper aims to examine the main characteristics of the housing taxation and subsidy systems in six European Union countries. The structure of this support over the past two decades, before and after the global financial crisis has been investigated and its total effective dimensions have been approximated.

Official national data and existing literature on housing policy expenses have been analysed and the authors add their own estimations of missing data, where possible. Latest changes in housing policy guidelines and expenses were interpreted.

It was found that state support for housing is heavily underestimated by official data in most countries, mainly due to missing estimates for the value of imputed rents tax relief, reduced VAT rates and low real estate and capital gains taxation. Our estimates suggest that total public support for the housing sector reaches more than 3 per cent of the gross domestic product in three of the six countries, and about 2 per cent in the others. State support to the housing sector has developed quite differently in the investigated countries over the past decades. In particular, there was no universal downward trend.

This is the first attempt to provide a more comprehensive analysis of national housing policy expenses applying a very broad definition of state support for housing. In particular, we consider indirect tax advantages to the housing sector that are generally not taken into account. Furthermore, we apply a discounted present value approach of current housing policy expenses to facilitate international comparison.

This study attempts to find the response of the real estate market to economic changes by identifying cause-effect relationships between mortgage, residential investment, and Saudi employment.

A quantitative approach to analytically examine the relationship among the variables. To find out the impact of investment, mortgage and Saudi employment on the Saudi real estate growth from 1970 to 2019. All data sets were obtained from the General Authority for Statistics (GAST), Saudi Central Bank (SAMA) and World Bank Group.

This study reveals a positive relationship between the mortgage and GDP in the Saudi Arabian real estate market. The same results for employment and investment; both have a positive effect on the GDP of the real estate market.

Analyzing the impact of real estate financing on various industries and the extent to which it is related to employment and unemployment rates is essential for future research. Moreover, this research can be applied to different countries and compared based on similarities and differences in implementing mortgage-related policies.

The government must encourage investment in various ways and establish a stable structure that ensures market stability and finds a balance between supply and demand.

This study reflects the importance of real estate financing not only to individuals and governments but also to investors and business workers, and it is essential to analyze the impact of real estate financing on various industries, as well as the extent to which it is related to employment and unemployment rates. This research can be applied to different countries and compared based on similarities and differences in the implementation of mortgage-related policies.

This study contributes to testing this study’s hypothesis: that mortgage positively impacts the real estate market of Saudi Arabia.

Information transparency is crucially important in price setting in real estate, particularly when information asymmetry is concerned. This paper aims to examine how a change in government policy in relation to information disclosure and transparency impacts residential real estate price discovery. Specially, this paper investigates how real estate traders determined asking prices in the context of the Scottish housing market before and after the implementation of the Home Report, which aimed to prevent artificially low asking prices.

This paper uses spatial lag hedonic pricing models to empirically observe how residential asking prices are determined by property sellers in response to a change in government policy that is designed to enhance market transparency. It uses over 79,000 transaction data of the Aberdeen residential market for the period of Q2 1998 to Q2 2013 to test the models.

The empirical findings provide some novel insights in relation to the price determination within the residential market in Scotland. The spatial lag models suggest that spatial autocorrelation in property prices has increased since the Home Report came into effect, indicating that property sellers have become more prone to infer asking prices based on prior sales of dwellings in close vicinity. The once-common practice of setting artificially low asking prices seems to have dwindled to a certain extent statistically.

The importance of understanding the relationship between information transparency and property price determination has gathered momentum over the past decade. Although spatial hedonic techniques have been extensively used to study the impact of various property- and neighbourhood-specific attributes on residential real estate market in general, surprisingly little is known about the empirical relationship between spatial autocorrelation in real estate prices and information transparency.