Purpose This study aims to decompose the short-term fluctuations of housing prices in China and analyze the influencing factors of short-term fluctuations in housing prices. Design/methodology/approach This study divides housing prices into long-term trend components and short-term fluctuation components based on wavelet denoising method. Using the decomposition results, the evolution characteristics of short-term fluctuations in housing prices were further analyzed, and the dynamic correlation between various short-term influencing factors and short-term fluctuations in housing prices was empirically tested using the MS-BVAR model to explore which factors played the main role in short-term fluctuations in housing prices under different states. Findings Empirical findings indicate that the short-term volatility of China’s housing prices can be classified into three distinct regimes: a stable state, an oscillatory state and a bubble state, with the oscillatory state serving as the potential developmental regime for the bubble state; during the short-term fluctuation period of housing prices, key drivers include per capita income, credit supply, policy uncertainty, gross domestic product (GDP) growth rate and unemployment rate. Whereas in the bubble phase of short-term housing price fluctuations, both per capita income, GDP growth rate and exchange rate exert a greater impact on price volatility, while credit supply and policy uncertainty also remain significant influencing factors. Originality/value There is a lack of research on the short-term fluctuations of Chinese housing prices and their influencing factors, especially the exploration of the short-term driving mechanism of housing prices after considering structural changes. This study contributes to the body of research on factors influencing short-term fluctuations in China’s housing prices, and holds significant practical implications for stabilizing housing prices and curbing housing price bubbles.
Li et al. (Mon,) studied this question.