The Dynamic Relationship Between House Prices and Output: Evidence From Us Metropolitan Areas

Apergis, Nicholas; Simo-Kengne, Beatrice Desiree

doi:10.3846/1648715x.2015.1072857

Cited by 14 publications

(10 citation statements)

References 27 publications

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“…In summary, the relevant literature on volatility spillover effects across housing markets can be classified into two main categories. one group of papers has explored the relationship between housing price variability and national macroeconomic development indicators like gDP, population, unemployment rate, and income (Apergis et al 2015). Prominent examples of this category include the study by Dolde and Tirtiroglu (2002), who examined the relationship between housing price variability and the national macroeconomic conditions in the united States (uS) from 1975 to 1993.…”

Section: Literature Reviewmentioning

confidence: 99%

On Price Co-Movement and Volatility Spillover Effects in China’s Housing Markets

Weng

Gong

2017

International Journal of Strategic Property Management

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The soaring property prices in many Chinese cities have recently attracted increasing attention. This study uses the data on housing price indices from January 2005 to December 2014 in 10 large Chinese cities to analyze volatility spillover effects and to identify the determinants of price co-movement across the China’s regional housing markets. This research proposes a novel dynamic spatial panel data model that accounts for multivariate asymmetrical generalized autoregressive conditional heteroskedasticity components in disturbances to address these issues empirically. Results reveal that housing prices in cities are significantly influenced by population, income, mortgage rates, policy factors, and the national macroeconomic situation. The analysis further indicates that the housing returns of regions in China that are in close geographic and economic proximities exhibit strong co-movement and volatility spillovers. Evidence of significantly positive leverage effects in regional housing markets is also determined. This study’s findings have significant implications for academic researchers, financial experts, and policy makers.

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Section: Literature Reviewmentioning

confidence: 99%

On Price Co-Movement and Volatility Spillover Effects in China’s Housing Markets

Weng

Gong

2017

International Journal of Strategic Property Management

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“…Differences of marginal propensity to consume in housing/stock markets are generally explained by the well-documented differences in nature and risk characteristics of housing/stock as the asset classes (see, [25,33]). For example, ref.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ref. [33] examine the nature and causal direction of the relationship between house prices and economic growth proxied by per capita personal income for a panel of 351 U.S. metropolitan statistical areas. The authors find a long-run relationship between local house prices and per capita personal income and also the existence of a bi-directional causality between real house prices and real per capita personal income over both long and short-horizons.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Horizon Financial and Housing Wealth Effects across the U.S. States

et al. 2021

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We investigate for the presence of multi-horizon wealth effects across U.S. states over the period of 1975:Q2 to 2012:Q2 by utilizing multi-horizon non-causality testing and multi-horizon causality measurement. At the state/aggregate level, we document that housing wealth has more statistically significant and persistent impact on private consumption than financial wealth. We also find that state-level housing/financial wealth effects are present at long time horizons and exhibit heterogeneity across the U.S. From a policy perspective, we suggest that state-level policies may specifically utilize the housing market to support consumption and growth.

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“…The ARDL approach has been used by several researchers to analyse housing market dynamics (e.g., Bangura & Lee, 2020) and to test the relationship between house prices and other economic and political variables (e.g., Apergis et al, 2015;Inglesi-Lotz & Gupta, 2013).…”

Section: Modelmentioning

confidence: 99%

Urban House Prices and Business Establishment in Malaysia: A Sectoral Approach

Gholipour

Khin

Tan-Kantor

et al. 2021

International Journal of Strategic Property Management

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The purpose of this study is to examine the long-run and short-run relationship between house prices and business formation in various industries. Using data from Malaysian states over the period of 2000–2016 and applying ARDL/PMG models, our results show that changes in house prices have a positive and significant association with business establishment in specific economic sectors, including manufacturing, wholesale and retail trade, information and communication, and financial and insurance in the long-run. However, the long-run relationship between house prices and business formation is negative and significant for electricity, gas, steam and air conditioning supply, construction, transportation and storage, accommodation and food service activities, and real estate industries. The short-run analysis indicates that there is a difference in the responses of business establishment in various industries to the changes in house prices.

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The Dynamic Relationship Between House Prices and Output: Evidence From Us Metropolitan Areas

Cited by 14 publications

References 27 publications

On Price Co-Movement and Volatility Spillover Effects in China’s Housing Markets

On Price Co-Movement and Volatility Spillover Effects in China’s Housing Markets

Multi-Horizon Financial and Housing Wealth Effects across the U.S. States

Urban House Prices and Business Establishment in Malaysia: A Sectoral Approach

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