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To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price, the Chinese government has been exploring the most effective policies for regulating the housing market. Measuring the effect of real estate regulation policies has been a challenge for present studies. This study innovatively employs big data technology to obtain Internet search data (ISD) and construct market concern index (MCI) of policy, and hedonic price theory to construct hedonic price index (HPI) based on building area, age, ring number, and other hedonic variables. Then, the impact of market concerns for restrictive policy, monetary policy, fiscal policy, security policy, and administrative supervision policy on housing prices is evaluated. Moreover, compared with the common housing price index, the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand. The results indicate that (1) a long-term interaction relationship exists between housing prices and market concerns for policy (MCP); (2) market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect. The results could serve as a useful reference for governments aiming to stabilize their real estate markets.

Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory