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Housing activity is an important indicator of general economic activity, and house price movements are an important variable in international financial markets. In this chapter we utilise vector autoregressive models to examine how the interrelationship between housing activity and general economic activity has evolved in four OECD countries. Our results provide support for the hypothesis that the relationship between housing activity and general economic activity has changed in many OECD countries. For Australia, however, no such evidence was found. These results suggest that caution needs to be exercised when using previous experience to forecast both housing cycles and general economic activity.

It was not until the late 1960s that housing attracted much attention from academic social scientists. Since that time the literature has expanded widely and diversified, establishing housing with a specialised status in economics, sociology, politics, and in related subjects. As we would expect, the new literature covers a technical, statistical, theoretical, ideological, and historical range. Housing studies have not been conceived and interpreted in a monolithic way, with generally accepted concepts and principles, or with uniformly fixed and precise methodological approaches. Instead, some studies have been derived selectively from diverse bases in conventional theories in economics or sociology, or politics. Others have their origins in less conventional social theory, including neo‐Marxist theory which has had a wider intellectual following in the modern democracies since the mid‐1970s. With all this diversity, and in a context where ideological positions compete, housing studies have consequently left in their wake some significant controversies and some gaps in evaluative perspective. In short, the new housing intellectuals have written from personal commitments to particular cognitive, theoretical, ideological, and national positions and experiences. This present piece of writing takes up the two main themes which have emerged in the recent literature. These themes are first, questions relating to building and developing housing theory, and, second, the issue of how we are to conceptualise housing and relate it to policy studies. We shall be arguing that the two themes are closely related: in order to create a useful housing theory we must have awareness and understanding of housing practice and the nature of housing.

The paper aims to provide a better understanding of the interactions between housing investment and economic growth. In particular, the paper emphasizes the separate effects of private housing investment (PHI) on the aggregate economy using quarterly data in the UK from 1974 to 2015. This is important due to the relatively growing interest around the world, including the UK, in encouraging greater private housing investment as a way of boosting economic growth.

The paper used the widely accepted and recognized econometric concepts of unit root, Granger causality and co-integration and provides tentative quantitative evidence of the causal and predictive effect of PHI and economic growth.

The key finding is that the level of investment directed by individual and institution into the private housing sector is key to future development, and will strongly reduce economic performance volatility.

Given that this is a bivariate time series analysis of PHI and economic growth (proxy by gross domestic product), the conclusions of this paper need to treated with caution, as there are other potential variables that might be omitted to make the model more robust so as to reach a more conclusive result.

This study complements existing literature, not only by providing new empirical evidence on the nexus between housing markets and the business cycle but also by being the pioneering attempt at examining the impact of PHI on the economy in the UK.

This paper aims to construct a model procedure to mitigate housing glut by using both qualitative and quantitative approach. The model applied in the Malaysian context analyzes the following: information contained in media articles and reports issued by Bank Negara Malaysia (BNM) on the housing market to extract the true picture of the housing glut issue; the relative impact (effectiveness) of housing affordability, housing prices and economic growth in influencing housing glut, and how it can be overcome so that appropriate preferential policies can be taken to mitigate the problem.

This study uses quarterly data from 2000 to 2017 to conduct economic analysis, economic theory analysis and cointegrating regression, whereas information from media-published housing articles and reports issued by BNM are examined and interpreted to draw the true picture of housing glut.

The results obtained from quantitative analysis show that housing affordability exerts very mild relative effect (0.0097) negatively on housing glut, whereas economic growth and housing price produce a relatively mild positive impact of (0.020) and (0.022), respectively, conflicting to the common consensus that the two factors have a significant effect on housing glut. Qualitatively, the results of this study show that housing glut seems to be relatively larger for affordable housing, which is contrary to the quantitative results, pointing to the existence of other influencing factors.

There is an imperative need for a third-party survey to gain a comprehensive understanding of the market conditions and buyers’ sentiment and preference.

This study compares both quantitative and qualitative results with expected housing market movements and responses based on conventional wisdom.

This study aims to examine dynamic interactions among economic growth, geography and the housing market with public goods financed by the government. A general dynamic equilibrium model of an isolated economy with economic geography, local public goods and capital accumulation is to be constructed. The economy has three sectors, supplying industrial goods, housing, and local public goods. The model synthesizes the main ideas in neoclassical growth theory, the Alonso urban model, and the Muth housing model in an alternative framework to the traditional growth theory.

The model is based on the neoclassical growth theory with an alternative approach to household behavior. The paper shows how to solve the dynamics of the economic system and simulate the model to demonstrate dynamic interactions among economic growth, housing market, residential distribution and public goods over time and space.

The paper simulates equilibrium and motion of the spatial economy with Cobb‐Douglas production and utility functions. The simulation demonstrates, for example, that, as the tax rate on the land income is increased, the total capital stocks and the stocks employed by the three sectors are increased, the rate of interest falls and the output of the industrial sector and the wage rate are increased, the land devoted to local public goods falls and the land rent and housing rent rise over space, the consumption level of the industrial goods and the total expenditures on the public goods are increased.

The paper provides some possible implications of the model for complicated consequences of government policy over time and space. In particular, the paper shows that a change in government policy not only has a macroeconomic impact over time, but also affects the economic geography of the national economy.

The paper offers insights into the linkage among growth, national public policies and economic geography.

The housing sector in Egypt represents a considerable share of the gross domestic product (GDP) and accordingly the economy. Further, it is considered vital for any population around the world, because it provides the shelter needed by people. Egyptian housing market is facing many problems which need to be solved. The paper aims to discuss these issues.

This research reviews and analyzes the Egyptian public and private housing market’s key variables. As such, it highlights the importance of informed decision making through detailed analysis and study of the market, especially when planning for the future by any housing market stakeholder. The research proposes the use of system dynamics (SD) modeling to analyze the market by creating a stock and flow model using STELLA modeling and simulation software.

The results reveal that the expected newly established families will be nearly 800,000 families in year 2015/2016. Out of these numbers, 600,000 families require economic housing units, while the expected supply is nearly 300,000 units.

A study is made for the economic housing market, which is a very big housing market and population segment that has been suffering from negligence for years.

This paper aims to document the economic importance of the housing sector, as measured by its contribution to gross domestic product (GDP), which is not fully recognized. In response to the joint economic and health crises caused by the COVID-19 pandemic, there is an opportunity for emerging market countries to develop and implement inclusive housing strategies that stimulate the economy and improve community health outcomes. However, so far housing does not feature prominently in the recovery plans of many emerging market countries.

This paper uses national account data and informal housing estimates for 11 emerging market economies to estimate the contribution of housing investments and housing services to the GDP of these countries.

This paper finds that the combined contribution of housing investments and housing services represents between 6.9% and 18.5% of GDP, averaging 13.1% in the countries with information about both. This puts the housing sector roughly on par with other key sectors such as manufacturing. In addition, if the informal housing sector is undercounted in the official national account figures used in this analysis by 50% or 100%, for example, then the true averages of housing investments and housing services’ contribution to GDP would increase to 14.3% or 16.1% of GDP, respectively.

Further efforts to improve data collection about housing investments and consumption, particularly imputed rent for owner occupiers and informal activity require national government to conduct regular household and housing surveys. Researcher can help make these surveys more robust and leverage new data sources such as scraped housing price and rent data to complement traditional surveys. Better data are needed in order to capture housing contribution to the economy.

The size of the housing sector and its impact in terms of employment and community resilience indicate the potential of inclusive housing investments to both serve short-term economic stimulus and increase long-term community resilience.

The role of housing in the economy is often limited to housing investment, despite the importance of housing services and well-documented methodologies to include them. This analysis highlights the importance of housing to the economy of emerging market countries (in addition to all the non-GDP related impact of housing on welfare) and indicate data limitation that need to be addressed to further strengthen the case for focusing on housing as part of economic recovery plans.

The housing market in South Africa has the potential to drive economic growth and attract foreign investment, but it can be affected by various risk factors. This paper aims to conduct an empirical analysis of the effect of country risk components on the housing market in South Africa.

Linear and nonlinear autoregressive distributed lag (ARDL) models were used to evaluate the effects of the economic, financial and political risk factors of country risk on the prices of different segments of houses based on 276 monthly time-series data from January1995 to December 2015.

First, the results established that the three housing indices were more sensitive to political risk in the long run. Second, short run results showed that the three housing indices were largely influenced by their own preceding adjustments in the short run albeit minimal influences from political risk. Third, large housing segments indicated a higher magnitude of the country risk effect in South Africa.

This paper concluded that the response of housing prices to changes in the country risk components differed across the three segments of the housing market in South Africa. Consequently, this study presented the first comparison of the reactions of different housing segments to different components country risk.

In the past few years, numerous economic uncertainty challenges have occurred globally. These uncertainties grasp the attention of the researchers and they examine the role of economic policy uncertainties in several aspects. Therefore, this study contributes to the literature by exploring the house prices volatility and economic policy uncertainty nexus in G7 countries.

The authors applied the newly introduced econometric technique, the GARCH-MIDAS model, to the sample size of January 1998–May 2021.

The result shows a significant relationship between house prices volatility and economic policy uncertainty. Moreover, economic policy uncertainty acts as a significant determinant of house prices volatility. In addition, the out-of-sample also shows that the economic policy uncertainty is an effective predictor and the GARCH-MIDAS has a better predictive ability.

This paper makes a unique contribution to the literature with reference to developed economies, being a pioneering attempt to investigate the GARCH-MIDAS model to analyze the relationship between housing prices volatility and economic policy uncertainty by applying more rigorous and advanced econometric techniques.