Ripple effects of house prices of China’s three key regions including first tier and second tier main 29 cities

This paper identifies the ripple effects of house prices of China’s key three regions including first tier 5 cities (LOG(ALL5)), second tier top 8 cities (LOG(ALL8)) and second tier 16 cities (LOG(ALL16)) for 2010Q1 to 2019Q2 periods, together with the impulses from fixed assets investments toward China three key regions’ house prices covering period from 2010Q1 to 2019Q2. The empirical analysis is conducted using the robust econometric multiple frameworks, undertaken the forms of principal component method (PC), VAR and Generalized Impulse Response (GIR) techniques. Over the 20 quarters tested, strong evidences of ripple effects were found from Q1 to Q10. Stronger positive ripple effects were identified between two regions of second tier cities (LOG(ALL16) and LOG(ALL8)) versus first tier region (LOG(ALL5)) and second tier regions (LOG(ALL16) and LOG(ALL8)). This result suggests the first-tier cities in China have become less attractive to households and investors whereas second tier cities became more attractive due to their pristine nature and improved infrastructure. Furthermore, over the 20 quarters tested, a negative response was noticed on house price return of LOG(ALL5) toward LOG(FAINVEST) while house price returns of LOG(ALL8) and LOG(ALL16) toward impulses from LOG(FAINVEST) are positive. The result confirms our finding of stronger ripple effects of two regions of second tier cities due to improved infrastructure from fixed asset investments. This paper also assists readers who are interested in investing in China real estate markets. Policy makers could reference this research to set feasible housing policy with the aim to better housing market stability.