The Dynamic Correlation among Financial Leverage, House Price, and Consumer Expenditure in China

Abstract

With the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian dynamic conditional correlational autoregressive conditional heteroscedasticity (Bayesian DCC-GARCH) model, this study analyzes the interaction mechanism and dynamic correlation among financial leverage, house price, and consumer expenditure (the survey data are collected from China’s National Bureau of Statistics from January 2000 to December 2019; the data on financial leverage and consumer expenditure are from the Wind economic database, and the price of commercial housing was calculated based on the sales volume and area of commercial housing on the official website of China’s National Bureau of Statistics). Empirical results show that an increase in financial leverage significantly increases house prices and reduces consumer expenditure, that a rise in house prices inhibits financial leverage and weakens consumer expenditure, and that an increase in consumer expenditure raises financial leverage and stimulates a rise in house prices. In addition, house price and consumer expenditure are most relevant, followed by financial leverage and consumer expenditure, and then by financial leverage and house price. Therefore, systematic analysis of dynamic correlation among the three variables has important practical significance for formulating appropriate financial policies to stabilize house prices and promote the growth of consumer expenditures. Specially, financial leverage is an important factor to hold back soaring house prices and shrinking consumer expenditure. Therefore, monetary and macroprudential policies should be used to deal with financial leverage variables in order to achieve a balanced and sustainable development of the macroeconomy in China.

Does the House Slave Effect Depress International Tourism Travelling?

“…Family liabilities can smooth income, promote consumption, and improve residents' subjective well-being, but they may also bring corresponding economic pressure in reducing the level of welfare (Wang, Dong & Guo, 2019). Empirical testing conducted by Dong et al (2021) using the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian dynamic conditional correlational autoregressive conditional heteroscedasticity (Bayesian DCC-GARCH) model shows that an increase in financial leverage significantly increases house prices and reduces consumer expenditure. By applying time-series co-integration regressions, the assessment undertaken by Fereidouni, Al-mulali & Mohammed (2017) shows that the wealth effect from real estate has a positive and significant impact on Malaysian outbound travel demand; the same is confirmed for the EU using similar technique by Šergo (2020).…”

The Effect of Housing Assets on Private Consumption Expenditures in Iran

“…Kai Dong et al (2021) studied the dynamic relationship between financial leverage, house prices, and consumer expenditure in China. Using the timevarying parameter vector autoregression model with stochastic volatility (TVP-SV-VAR) and the Bayesian dynamic conditional correlational autoregressive conditional heteroskedasticity (Bayesian DCC-GARCH) model, this study analyzes the interaction mechanism and dynamic correlation between financial leverage, house prices, and consumer expenditure (survey data were collected from China's National Bureau of Statistics from January 2000 to December 2019; the financial leverage and consumer expenditure data were obtained from the Wind Economic Database, and the price of commercial real estate was calculated based on the sales volume and area of commercial real estate on the official website of China's National Bureau of Statistics).…”

“…Another result of this study is the positive significant effect of financial assets on private consumption in Iran. Various studies in this field around the world show the importance of this issue, such as Dong et al (2021), Mian et al (2016), Burrowss (2018), Cho (2016), Lacoviello (2015, Beatrice & Kengne (2015), and other researchers who have studied the impact of housing prices on household expenditure in China, Chicago, South Korea, the United States, the United Kingdom, etc.…”

A Real Estate Valuation Model Using Boosted Feature Selection

“…The relationship between house prices and environmental factors has been evaluated from various perspectives. A review of the literature showed that many factors influence the house price [1], [4], [18], with interest rates, housing construction, unemployment, and household income as important explanatory factors for house prices. This analysis indicated that house prices react quickly and strongly to changes in interest rates.…”