Investigating house price diffusion across eight major cities of India

The long-run behaviour of house prices is explored by concentrating on the existence of house price diffusion and lead-lag relationship across eight major cities of India using a quarterly house price index for the period 2009: Q4-2021: Q1. Autoregressive distributed lag (ARDL) bounds approach to cointegration and Granger non-causality were deployed to test for the long-run and short-run regional housing price dynamics. This is first known study to provide short-run and long run estimates of regional house price interrelatedness for India. The ARDL results support stable long run cointegrating relationship amongst housing markets of eight cities. The findings also establish the pairs of complement and substitute housing markets between the cities. Additionally, the short run, long run and joint Granger Causality results ratify that the pattern of house price diffusion is not distinct rather it is mixed. On one hand the empirical evidence demonstrates that in terms of house price diffusion, Mumbai and Pune are the most influential cities, on the other, mega cities such as Bengaluru and Kolkata are least influenced, while Delhi exhibits a definite pattern. The results have an important inference, since understanding about the pattern of house price diffusion would help investor to leverage the risk and facilitate the government to address housing shortages and to build up new housing stock in existing cities, which are policy measures towards sustainable urban development.