Background: According to International Real Estate Group Knight Frank, Chinese cities account for the top eight rankings in Global Residential Cities Index, as indicated that regional cities such as Nanjing, Shanghai, Shenzhen and Beijing grew over 30%in year 2016. (Lenaghan, 2016) Since regional house prices play pivotal roles in China’s regional economy as well as in Chinese’ daily lives, to understand regional house price dynamics is of utmost importance.

Research questions: This paper poses two research questions:

RQ1.Is there house price spill over effects among the top 13 cities in China?

RQ2.Is there regional house price heterogeneity between the first and second - tier housing markets in China?

Research methodology: The paper describes the application of combined enhanced rigorous econometric frameworks, such as the Principal Component Method, the Vector Error Correction Model (VECM), Granger Causality, Variance Decomposition and Generalised Impulse Response tests to provide an in depth understanding of regional house price dynamics in China.

Findings: The empirical findings reveal that first tier cities such as Beijing, Shanghai, and second tier city Chongqing, function as a source of spillovers. Spillover effects occur among all of the target cities in China.

Further, the result indicates there is close relationship between house prices in two major segments of China housing markets and macroeconomic variables including interest rate (IR), China share market performance (CNSHARE), unemployment rate (UNEMP) and GDP in China. Moreover, heterogeneity on house price dynamics was identified. Second tier top 8 cities housing prices are self – corrected to long run equilibrium at quicker speed than those in first tier cities. This may reflect the information transmission mechanism in second - tier cities are much simpler than those in first - tier bigger cities.

Originality and value: The foremost contribution of this paper is that it is the first rigorous study of house price dynamics and the spill over effects of the top 13 cities at the first and second - tier housing markets in China. Additionally, the data set renders the study of particular interest, because it incorporates an analysis of the "golden era" of China’s prosperity performance of house prices from 2003 – 2013, and "new normal" age (2014 onwards) slowed down period.