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The impact of income, economic openness and interest rates on housing prices in China: evidence from dynamic panel quantile regression

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  • Huiming Zhu
  • Zheng Li
  • Peng Guo

Abstract

The rapid growth of housing prices has attracted the attention of the whole of society in China. This article adopts the dynamic panel quantile regression to investigate the impact of income, economic openness and interest rates on housing prices in China, based on the panel data of 35 major cities from 2002 to 2012. Compared with previous studies, we can more precisely and reasonably discuss the impact of these variables on different levels of housing prices. The empirical results indicate that the impact of independent variables on housing prices is heterogeneous across quantiles. Specifically, the impact of income is positive and significant across quantiles, and the impact becomes greater at the 90th and 95th quantiles. Economic openness has a positive and significant effect at the 5th–80th quantiles, which support the Balassa–Samuelson effect, but it is insignificant at the 90th and 95th quantiles. The impact of interest rates is positive and significant at low quantiles, but the impact is negative and insignificant at high quantiles. Furthermore, we also find that the coefficients of interest rates at various quantiles are smaller. In addition, the population has a significant positive effect across quantiles. Finally, we provide important policy implications.

Suggested Citation

  • Huiming Zhu & Zheng Li & Peng Guo, 2018. "The impact of income, economic openness and interest rates on housing prices in China: evidence from dynamic panel quantile regression," Applied Economics, Taylor & Francis Journals, vol. 50(38), pages 4086-4098, August.
    • Handle: RePEc:taf:applec:v:50:y:2018:i:38:p:4086-4098
    DOI: 10.1080/00036846.2018.1441512
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    Cited by:

    1. Mateusz Tomal & Agata Gumieniak, 2020. "Agricultural Land Price Convergence: Evidence from Polish Provinces," Agriculture, MDPI, vol. 10(5), pages 1-20, May.
    2. Mengzhu Zhang & Si Qiao & Xiang Yan, 2021. "The secondary circuit of capital and the making of the suburban property boom in postcrisis Chinese cities," Environment and Planning A, , vol. 53(6), pages 1331-1355, September.
    3. Khan, Muhammad Tariq Iqbal & Yaseen, Muhammad Rizwan & Ali, Qamar, 2019. "Nexus between financial development, tourism, renewable energy, and greenhouse gas emission in high-income countries: A continent-wise analysis," Energy Economics, Elsevier, vol. 83(C), pages 293-310.
    4. Simplice A. Asongu & Cheikh T. Ndour & Judith C. M. Ngoungou, 2023. "The effects of gender political inclusion and democracy on environmental performance: evidence from the method of moments by quantile regression," Working Papers of the African Governance and Development Institute. 23/060, African Governance and Development Institute..
    5. Benjamin Kwakye & Chan Tze Haw, 2020. "Interplay of the Macroeconomy and Real Estate: Systematic Review of Literature," International Journal of Economics and Financial Issues, Econjournals, vol. 10(5), pages 262-271.
    6. Shahzadi, Irum & Yaseen, Muhammad Rizwan & Iqbal Khan, Muhammad Tariq & Amjad Makhdum, Muhammad Sohail & Ali, Qamar, 2022. "The nexus between research and development, renewable energy and environmental quality: Evidence from developed and developing countries," Renewable Energy, Elsevier, vol. 190(C), pages 1089-1099.
    7. Tomal Mateusz, 2019. "House Price Convergence on the Primary and Secondary Markets: Evidence from Polish Provincial Capitals," Real Estate Management and Valuation, Sciendo, vol. 27(4), pages 62-73, December.
    8. Panayiotis Tzeremes, 2022. "The Asymmetric Effects of Regional House Prices in the UK: New Evidence from Panel Quantile Regression Framework," Studies in Microeconomics, , vol. 10(1), pages 7-22, June.
    9. Ali, Qamar & Yaseen, Muhammad Rizwan & Anwar, Sofia & Makhdum, Muhammad Sohail Amjad & Khan, Muhammad Tariq Iqbal, 2021. "The impact of tourism, renewable energy, and economic growth on ecological footprint and natural resources: A panel data analysis," Resources Policy, Elsevier, vol. 74(C).

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