Purpose By modelling China’s property price changes and their effect on GDP, this study aims to develop a more general model of the costs and benefits driving price bubbles. Design/methodology/approach The authors develop a five-sector dynamic model (using data from China and seven other comparator jurisdictions), resulting in a bubble risk factor. The authors then correlate this risk factor with changes in property prices and resulting changes in GDP. Findings The authors find that economic structures (the way GDP, property prices and other variables change relative to each other) can change during/after a financial crisis. The authors also find that price disequilibria can help predict the risk of a property price fall – which thus reverberates into GDP change. Originality/value To the best of the authors’ knowledge, no dynamic models of price bubbles exist (though many exist of financial bubbles). The authors provide both theoretical novelties (such as providing a model of risk using non-linear differential equations) and practical ones (showing when we can expect Chinese GDP to fall).
No takes yet. Share an insight, caveat, or question.
Michael et al. (2021) studied this question.
Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context: