Abstract
From the perspective of big data, this paper uses panel vector autoregressive model (PVAR) and Granger causality test model to analyze the dynamic relationship between public attention and housing prices, and further uses variance house to verify the level of economic development and macroeconomic development of external factors. Control policies and the degree of supply in the real estate market affect the difference between public attention and housing prices. Granger causality shows that in the case of a lagging period, public attention affects housing price fluctuations in one direction; variance decomposition shows that long-term quantitative monetary policy can regulate the healthy development of the real estate market.
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This work was financially supported by National Natural Science Foundation of China (71974003).
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Wang, L., Hu, H., Wang, X. (2021). Public Attention and Housing Prices: City Panel Data Based on Search Big Data. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-030-79197-1_6
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DOI: https://doi.org/10.1007/978-3-030-79197-1_6
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