Does the government relocation promote housing prices: Evidence from the micro-housing transaction data

ZHOU Mo, YANG Chao, LING Aifan, YANG Xiaoguang

Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (9) : 2180-2197.

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Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (9) : 2180-2197. DOI: 10.12011/SETP2020-0270

Does the government relocation promote housing prices: Evidence from the micro-housing transaction data

  • ZHOU Mo1, YANG Chao1, LING Aifan1, YANG Xiaoguang2
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Abstract

Government relocation has become more common in recent years. Based on the micro-housing transaction data from 2007 to 2018, this paper examines the impact of government relocation on China's housing prices and its mechanism by DID model. The empirical results show that the government relocation has a significant negative effect on average housing prices of the city where the government relocation occurred, and increased the housing prices in districts where the government moved in and moved out, while decreased housing prices in other districts. Through mechanism analysis, this study find that the government relocation attracts the inflow of the permanent residents and improves the development of real estate, which results in housing prices growth in moved-in districts. In addition, the government relocation has larger impact on the prices of medium-sized houses and roughcast houses. We also find that the government relocation has a significant "time effect" on the housing prices. The positive impact of government relocation on the housing prices of the moved-in and the moved-out districts increases year by year, and the negative impact in other districts has gradually decreased, and finally turned into a positive impact.

Key words

government relocation / housing prices / land prices / DID regression

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ZHOU Mo , YANG Chao , LING Aifan , YANG Xiaoguang. Does the government relocation promote housing prices: Evidence from the micro-housing transaction data. Systems Engineering - Theory & Practice, 2021, 41(9): 2180-2197 https://doi.org/10.12011/SETP2020-0270

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Funding

National Natural Science Foundation of China (71703062, 71771107, 72071098); Thousand Talent Program for Jiangxi Provincial (JXSQ2019201130)

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