Population Density, House Prices and Mortgage Design

Miles, David

doi:10.1111/j.1467-9485.2012.00589.x

Cited by 26 publications

(16 citation statements)

References 21 publications

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“…As the main subject of investing, consuming, using and disposing of real estate, the human factor has gradually become the research focus. With regard to the research into demographic factors, the existing literature has focused on the demographic age structure [41][42][43][44][45][46], demographic scale [47], demographic density [48], family demographic characteristics [16], population migration [4,[49][50][51] and other perspectives to explore the relationship between these and housing prices. For instance, regarding demographic age structure, studies by Levin et al [41] and Saita et al [47] have shown that the age of the population was negatively correlated with housing prices and positively correlated with population scale; in further exploration of the demographic structure, research by Hiller and Lerbs [52] showed that the price growth of apartments and small-sized houses was negatively correlated with the old-age dependency ratio, while aging was positively correlated with the actual rent growth; Choi and Jung [45] found that the proportion of the economically active population (aged from 15 to 64 years old) to the total population had a significant impact on housing price growth.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Population Migration on Urban Housing Prices: Evidence from China’s Major Cities

Lin

Zhao

et al. 2018

Sustainability

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With increasingly high housing prices, the urban housing problem has changed from an economic issue to a livelihood issue in China. Taking 32 major cities in China as an example, this paper employed data from 2007 to 2016 to build a panel data model to empirically study the impact of population migration on urban housing prices. From the two perspectives of the national level and regional level (eastern region, central region and western region), the results of this study showed that (1) on the national level, population inflow had a significant positive correlation with urban housing prices, where a population inflow rate increase of 1% increased urban housing prices by 0.31%; and (2) on the regional level, a population inflow rate increase of 1% increased urban housing prices in the eastern region by 1.34%, but population inflow had no obvious impact on the urban housing prices in the central and western regions. Based on the results, this study suggested addressing housing supply imbalances through housing product diversification and affordable housing system improvement, and addressing construction land supply imbalances by building a perfect system linking land-use planning to population; at the same time, it also suggested building more nationally central cities following the urbanization trend, and taking this as the key to developing urban agglomerations, reasonably decentralizing the population flow, promoting the healthy and stable development of the real-estate market and advancing sustainable urbanization. The above conclusions have practical significance for China and other developing countries to coordinate population and urban development in the process of rapid urbanization.

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Section: Introductionmentioning

confidence: 99%

The Impact of Population Migration on Urban Housing Prices: Evidence from China’s Major Cities

Lin

Zhao

et al. 2018

Sustainability

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“…Demographic elements are also highlighted since they play an important role in the evolution of demand for housing, and are a key element in the determination of real housing price appreciation. The relevance of demographics in the explanation of housing prices has been suggested by previous contributions such as Miles (2012), which is focused on the United Kingdom. In particular, the growth of population exerts a significant impact in the case of Australia, Belgium, Canada, Finland, France, the Netherlands, New Zealand, Norway, Spain, Switzerland and the United Kingdom.…”

Section: Preliminary Analysis and Long-run Relationshipsmentioning

confidence: 94%

Modelling the housing market in OECD countries

Arestis

González

2013

International Review of Applied Economics

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Recent episodes of housing bubbles, which occurred in several economies after the burst of the United States housing market, suggest studying the evolution of housing prices from a global perspective. We utilise a theoretical model for the purposes of this contribution, which identifies the main drivers of housing price appreciation, such as, for example, income, residential investment, financial elements, fiscal policy and demographics. In a second stage of our analysis, we test our theoretical hypothesis by means of a sample of 18 OECD countries from 1970 to 2011. We employ the vector error correction econometric technique in terms of our empirical analysis, which permits us to model the long-run equilibrium relationship and the short-run dynamics, which also helps to account for endogeneity and reverse causality problems.JEL Classifications: C22, R31 IntroductionThe occurrence of several episodes of housing bubbles in a number of developed economies in the second half of the 2000s, suggests the necessity of identifying the main drivers of this market.In order to contribute to the existing debate, we begin by proposing a theoretical explanation of housing prices, which puts forward the role of the basic fundamentals of this market, for example, disposable income, real residential investment, mortgage rates and demographics. Our model also accounts for the behaviour of monetary authorities by including credit standards. Moreover, in our specification there is room for the public sector to perform its role by means of taxation. We then proceed to test the validity of our theoretical model by applying cointegration analysis (Johansen 1995) on a sample of 18 OECD economies during the period 1970-2011. Our econometric results assure the existence of a long-run relationship among the variables and capture the adjustment in the short run by means of a Vector Error Correction Model (VECM). This technique also accounts for endogeneity and reverse causality problems.In terms of economic policy our analysis upgrades the role of the prudential and fiscal policies in relation to monetary policy. Moreover, our results also point to disposable income as the cornerstone of the model.

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“…The studies that supposedly identify the key determinants of house price volatility found that economic indicators such as employment, net migration, and income growth can significantly impact house prices [41,42]. Reference [43] explored that a linkage between rises in population density and increasing levels of house prices. The findings are also supported by [44,45].…”

Section: The Influencing Factors Of Housing Pricesmentioning

confidence: 99%

Exploring the Trend of New Zealand Housing Prices to Support Sustainable Development

2019

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The New Zealand housing sector is experiencing rapid growth that has a significant impact on society, the economy, and the environment. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in the housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: autoregressive integrated moving average (ARIMA) and multiple linear regression (MLR) analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

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Population Density, House Prices and Mortgage Design

Cited by 26 publications

References 21 publications

The Impact of Population Migration on Urban Housing Prices: Evidence from China’s Major Cities

The Impact of Population Migration on Urban Housing Prices: Evidence from China’s Major Cities

Modelling the housing market in OECD countries

Exploring the Trend of New Zealand Housing Prices to Support Sustainable Development

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