24 datasets found
  1. Average real estate sale price in China 1998-2023

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Average real estate sale price in China 1998-2023 [Dataset]. https://www.statista.com/statistics/242851/average-real-estate-sale-price-in-china/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2023, the average price of real estate in China was approximately ****** yuan per square meter, representing a decrease from the previous year. Rising prices in the real estate market Since the 1998 housing reform, property prices in China have been rising continuously. Housing in the country is now often unaffordable, especially considering the modest per capita income of Chinese households. Shanghai and Beijing even have some of the most competitive real estate markets in the world. The rapid growth in housing prices has increased wealth among homeowners, while it also led to a culture of speculation among buyers and real estate developers. Housing was treated as investments, with owners expecting the prices to grow further every year. Risk factors The expectation of a steadily growing real estate market has created a property bubble and a potential debt crisis. As Chinese real estate giants, such as China Evergrande and Country Garden, operate by continuously acquiring land plots and initiating new projects, which often require substantial loans and investments, a slowdown in property demands or a decline in home prices can significantly affect the financial situation of these companies, putting China’s banks in a vulnerable position. In addition, due to a lack of regulations and monetary constraints, the long-term maintenance issues of high-rise apartments are also a concern to the sustainable development of China’s cities.

  2. Replication dataset for PIIE WP 23-5, Why China's housing policies have...

    • piie.com
    Updated Jun 14, 2023
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    Tianlei Huang (2023). Replication dataset for PIIE WP 23-5, Why China's housing policies have failedby Tianlei Huang (2023). [Dataset]. https://www.piie.com/publications/working-papers/2023/why-chinas-housing-policies-have-failed
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    Dataset updated
    Jun 14, 2023
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Tianlei Huang
    Area covered
    China
    Description

    This data package includes the underlying data files to replicate the data and charts presented in Why China's housing policies have failed, PIIE Working Paper 23-5.

    If you use the data, please cite as: Huang, Tianlei. 2023. Why China's housing policies have failed. PIIE Working Paper 23-5. Washington, DC: Peterson Institute for International Economics.

  3. F

    Real Residential Property Prices for China

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
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    (2025). Real Residential Property Prices for China [Dataset]. https://fred.stlouisfed.org/series/QCNR628BIS
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    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for Real Residential Property Prices for China (QCNR628BIS) from Q2 2005 to Q1 2025 about China, residential, HPI, housing, real, price index, indexes, and price.

  4. Floor space of completed buildings in China 1998-2024

    • statista.com
    Updated Jan 30, 2025
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    Statista (2025). Floor space of completed buildings in China 1998-2024 [Dataset]. https://www.statista.com/statistics/243316/floor-space-completed-buildings-in-china/
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    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2024, real estate developers in China completed 737.43 million square meters of floor space, representing a significant drop of almost 28 percent from the previous year. Housing completion figures in China have generally decreased over the last decade, owing to structural challenges in the real estate industry. The ups and downs of the Chinese real estate market Following the marketization of the housing sector in the late 1990s, China's real estate industry has enjoyed more than two decades of prosperity. The output value of the sector multiplied several times, with home prices rising sharply across the country and some properties in urban centers such as Beijing and Shanghai being among the most expensive in the world. While being a pillar industry in the country’s economy, the real estate sector has also stimulated the development of many related industries, such as construction and financial services. The property bubble and unfinished buildings The former expansion of the housing market had created a considerable bubble in the sector, which finally burst during the COVID-19 pandemic. Many apartments, especially the tower blocks in small or medium-sized cities and towns remained unsold or left unoccupied, leading to financial turmoil for real estate developers. The failure of major market players such as China Evergrande and Country Garden resulted in more than a million unfinished apartments in China.

  5. f

    Descriptive statistics of housing bubble index.

    • plos.figshare.com
    xls
    Updated Jan 11, 2024
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Descriptive statistics of housing bubble index. [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t003
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

  6. o

    Replication data for: The Great Housing Boom of China

    • openicpsr.org
    Updated Oct 12, 2019
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    Kaiji Chen; Yi Wen (2019). Replication data for: The Great Housing Boom of China [Dataset]. http://doi.org/10.3886/E114102V1
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    Dataset updated
    Oct 12, 2019
    Dataset provided by
    American Economic Association
    Authors
    Kaiji Chen; Yi Wen
    Area covered
    China
    Description

    China's housing prices have been growing nearly twice as fast as national income over the past decade, despite a high vacancy rate and a high rate of return to capital. This paper interprets China's housing boom as a rational bubble emerging naturally from its economic transition. The bubble arises because high capital returns driven by resource reallocation are not sustainable in the long run. Rational expectations of a strong future demand for alternative stores of value can thus induce currently productive agents to speculate in the housing market. Our model can quantitatively account for China's paradoxical housing boom.

  7. Top Chinese property developers on the Fortune China 500 ranking 2024

    • statista.com
    Updated Apr 23, 2025
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    Statista (2025). Top Chinese property developers on the Fortune China 500 ranking 2024 [Dataset]. https://www.statista.com/statistics/454494/china-fortune-500-leading-chinese-real-estate-companies/
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    Dataset updated
    Apr 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    China
    Description

    On the 2024 Fortune China 500 ranking for real estate companies, China’s leading real estate developer Poly Real Estate ranked first with a total revenue of 74 million U.S. dollars, followed by Greenland Holdings and Country Garden. Real estate market in China  In the last 20 years, China’s real estate market has experienced its most prosperous development. Land purchase has also become an important source of financial revenue for many local governments. The housing price increased so rapidly, especially in larger cities, that the government had to take measures to restrict investment. With the slowdown of China’s economic development and gradually saturated market, people are also afraid of the burst of the real estate bubble. While the real estate price in smaller cities tended to stay stable or even decrease, there is still growing potential for real estate prices in larger cities, especially the first-tier cities. China’s consumers are increasingly interested in the high-quality real estate products built by leading real estate developers. Leading real estate developers in China  Compared to the ranking in 2021, there were three new members entering the leading ten real estate developer club in 2022. The larger developers became stronger as they had advantages in land acquisitions, financing, marketing and pricing power which is difficult for smaller developers to catch up with. Thus, consolidation is also very common among China’s real estate developers. In 2022, two real estate giants disappeared from the fortune 500 ranking list, Evergrande and Sunac. Affected by the changing real estate market, they were facing cash flow problems and were affected heavily by the debt crisis.

  8. C

    China Home Loan Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated May 7, 2025
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    Market Report Analytics (2025). China Home Loan Market Report [Dataset]. https://www.marketreportanalytics.com/reports/china-home-loan-market-99530
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    May 7, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    China
    Variables measured
    Market Size
    Description

    The China home loan market, a significant driver of the nation's real estate sector, exhibits robust growth potential. With a market size exceeding [Estimate based on available data – e.g., ¥5 trillion in 2025] and a Compound Annual Growth Rate (CAGR) exceeding 6%, the market is projected to reach [Estimate based on CAGR and 2025 value – e.g., ¥7.5 trillion] by 2033. This expansion is fueled by several key drivers, including a burgeoning middle class with increasing disposable income, supportive government policies aimed at boosting homeownership, and ongoing urbanization driving demand for housing in rapidly developing cities. Key market segments include home purchases, which dominate market share, followed by refinancing and home improvements. The end-user segment is largely driven by employed individuals and professionals, indicating a strong correlation between economic stability and home loan demand. Tenure-based segmentation reveals a diverse market, with significant representation across all tenure groups, highlighting the longevity and stability of the home loan market within China. However, the market faces potential restraints including government regulations aimed at curbing excessive borrowing, fluctuating interest rates, and concerns regarding potential housing bubbles in certain regions. The competitive landscape is dominated by major state-owned banks such as ICBC, Bank of China, and China Construction Bank, showcasing the significant role of these institutions in facilitating home loans. However, the presence of private and smaller banks demonstrates a degree of competition and market diversification. Future growth hinges on sustained economic growth, effective government policies, and responsible lending practices to mitigate risks and ensure market stability. Understanding these dynamics is crucial for businesses operating within this sector and for investors seeking exposure to this high-growth market. Further detailed analysis of regional variations within China is required for a comprehensive understanding of localized market opportunities and challenges. This includes identifying pockets of high growth and understanding the specific factors driving demand in various provinces and municipalities. Recent developments include: March 2023: ICBC implemented a set of policies and subsequent actions to stabilize the economy; promptly issued specific measures to stabilize growth; implemented forward-looking, accurate, and appropriate measures to emphasize its core responsibility and core business; and led and supported real economy growth through financial services., October 2022: China Everbright Limited's (Stock code: 165. HK) CEL-Catalyst China-Israel Fund is pleased to announce that its portfolio company SatixFy successfully listed on NYSE American on 28th October 2022 with the symbol 'SATX', via a merger with Endurance Acquisition Corp. (NASDAQ: EDNC), a publicly traded special purpose acquisition company, or SPAC.. Key drivers for this market are: Real Estate Market Trends, Government Policies. Potential restraints include: Real Estate Market Trends, Government Policies. Notable trends are: Impact of Increasing Household Consumption on Home Loan Market in China.

  9. f

    Robustness test (Random effect).

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jan 11, 2024
    + more versions
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Robustness test (Random effect). [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t018
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

  10. Approximated hazard rate.

    • plos.figshare.com
    xls
    Updated Sep 6, 2024
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    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). Approximated hazard rate. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t005
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    xlsAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Housing markets are often characterized by price bubbles, and governments have instituted policies to stabilize them. Under this circumstance, this study addresses the following questions. (1) Does policy tightening change expectations in housing prices, revealing a regime change? (2) If so, what determines the housing market’s reaction to policy tightening? To answer these questions, we examine the effects of policy tightening that occurred in 2016 on the Chinese housing market where a price boom persisted in the post-2000 period. Using a log-periodic power law model and employing a modified multi-population genetic algorithm for parameter estimation, we find that tightening policy in China did not cause a market crash; instead, shifting the Chinese housing market from faster-than-exponential growth to a soft landing. We attribute this regime shift to low sensitivity in the Chinese housing market to global perturbations. Our findings suggest that government policies can help stabilize housing prices and improve market conditions when implemented expediently. Moreover, policymakers should consider preparedness for the possibility of an economic crisis and other social needs (e.g., housing affordability) for overall social welfare when managing housing price bubbles.

  11. House-price-to-income ratio in selected countries worldwide 2024

    • statista.com
    • ai-chatbox.pro
    Updated May 6, 2025
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    Statista (2025). House-price-to-income ratio in selected countries worldwide 2024 [Dataset]. https://www.statista.com/statistics/237529/price-to-income-ratio-of-housing-worldwide/
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    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

  12. f

    Difference in difference.

    • plos.figshare.com
    xls
    Updated Jun 3, 2025
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    Fang Liu; Chen Liang (2025). Difference in difference. [Dataset]. http://doi.org/10.1371/journal.pone.0325274.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Fang Liu; Chen Liang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Considering the notable influence of traditional Confucian culture on China’s housing market, this study introduces an innovative index to quantify the magnitude of the real estate bubble within China, employing a familial generational iterative model. Utilizing rent-buy policy as a conceptual framework, our research constructs a difference-in-differences model to investigate the impact of macroeconomic policies on the housing bubble phenomenon. Empirical observations from 2022 reveal pronounced bubble dynamics in first and second-tier cities, while housing prices in third and fourth-tier cities, alongside select fifth-tier cities, exhibit a declining trend. On a national scale, apart from minor affordability observed during 2005–2007, no significant affordability was identified in other years, with the housing price bubble index demonstrating a downward trajectory from 2020 to 2022. Furthermore, the implementation of the rent-buy policy that equality the rights of renter and owner has directly influenced the housing market, notably mitigating the overall escalation of housing prices. Additional analysis indicates that the rent-and-buy policy has been more successful in curbing price hikes in newly constructed and smaller-sized housing units compared to second-hand and larger-scale properties.

  13. Bubble Tea Market Study by Black Tea, Green Tea, Oolong Tea, and White Tea...

    • factmr.com
    csv, pdf
    Updated Jul 16, 2024
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    Fact.MR (2024). Bubble Tea Market Study by Black Tea, Green Tea, Oolong Tea, and White Tea in Ready-to-Drink and Instant Bubble Tea Mix Kits from 2024 to 2034 [Dataset]. https://www.factmr.com/report/bubble-tea-market
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    csv, pdfAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Fact.MR
    License

    https://www.factmr.com/privacy-policyhttps://www.factmr.com/privacy-policy

    Time period covered
    2024 - 2034
    Area covered
    Worldwide
    Description

    The global bubble tea market is estimated to reach a size of US$ 1.71 billion in 2024. The market has been projected to climb to a value of US$ 3.72 billion by the end of 2034, expanding at a CAGR of 8.1% over the next ten years.

    Report AttributeDetail
    Bubble Tea Market Size (2024E)US$ 1.71 Billion
    Projected Market Value (2034F)US$ 3.72 Billion
    Global Market Growth Rate (2024 to 2034)8.1% CAGR
    East Asia Market Growth Rate (2024 to 2034)8.4% CAGR
    North America Market Share (2024E)23.7%
    Black Tea Segment Value (2024E)US$ 736.2 Million
    Flavored Bubble Tea Segment Value (2024E)US$ 1.45 Billion
    Key Companies ProfiledKung Fu Tea; Ten Ren Tea, Inc.; Boise Boba; Woop Bubble Tea; Coco Tea; Empire Eagle Food Co.; Yen Chuan International Co., Ltd.; Gong Cha USA Ltd.; Quickly Corporation; BobaTea Factory; Possmei International Co., Ltd.; Bubble Tea House Company; Boba Guys, Inc.; Chatime; 8tea5; Tapioca Express, Inc.; The Inspire Food Company; TACHUNGHO; Sharetea.

    Country-wise Insights

    AttributeUnited States
    Market Value (2024E)US$ 179.3 Million
    Growth Rate (2024 to 2034)8.5% CAGR
    Projected Value (2034F)US$ 407.3 Million
    AttributeChina
    Market Value (2024E)US$ 184.7 Million
    Growth Rate (2024 to 2034)8.1% CAGR
    Projected Value (2034F)US$ 403.2 Million

    Category-wise Insights

    AttributeGreen Tea
    Segment Value (2024E)US$ 538.1 Million
    Growth Rate (2024 to 2034)8.2% CAGR
    Projected Value (2034F)US$ 1.19 Billion
    AttributeFlavored Bubble Tea
    Segment Value (2024E)US$ 1.45 Billion
    Growth Rate (2024 to 2034)8.2% CAGR
    Projected Value (2034F)US$ 3.17 Billion
  14. f

    Effects of house prices’ deviation from the fundamental prices on output.

    • plos.figshare.com
    xls
    Updated Jan 11, 2024
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Effects of house prices’ deviation from the fundamental prices on output. [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t010
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Effects of house prices’ deviation from the fundamental prices on output.

  15. f

    Estimation results in China.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Fengyun Liu; Deqiang Liu; Reza Malekian; Zhixiong Li; Deqing Wang (2023). Estimation results in China. [Dataset]. http://doi.org/10.1371/journal.pone.0173287.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Fengyun Liu; Deqiang Liu; Reza Malekian; Zhixiong Li; Deqing Wang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    Estimation results in China.

  16. f

    Impacts of housing price’s deviation from the basic price on consumption.

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jan 11, 2024
    + more versions
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Impacts of housing price’s deviation from the basic price on consumption. [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t005
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Impacts of housing price’s deviation from the basic price on consumption.

  17. f

    Output responses to changes in house prices’ deviation from the fundamental...

    • figshare.com
    xls
    Updated Jan 11, 2024
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Output responses to changes in house prices’ deviation from the fundamental prices. [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t009
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Output responses to changes in house prices’ deviation from the fundamental prices.

  18. f

    The result of variance decomposition of corporate R&D investment.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu (2023). The result of variance decomposition of corporate R&D investment. [Dataset]. http://doi.org/10.1371/journal.pone.0257106.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The result of variance decomposition of corporate R&D investment.

  19. f

    Johansen cointegration test results for each given variable.

    • plos.figshare.com
    xls
    Updated Jun 9, 2023
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    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu (2023). Johansen cointegration test results for each given variable. [Dataset]. http://doi.org/10.1371/journal.pone.0257106.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Johansen cointegration test results for each given variable.

  20. f

    Comparison of the effectiveness of measurement models.

    • plos.figshare.com
    xls
    Updated Jun 9, 2023
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    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu (2023). Comparison of the effectiveness of measurement models. [Dataset]. http://doi.org/10.1371/journal.pone.0257106.t002
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    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chen Wang; Xiaowei Ma; Hyoungsuk Lee; Zhen Chu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Comparison of the effectiveness of measurement models.

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Statista (2025). Average real estate sale price in China 1998-2023 [Dataset]. https://www.statista.com/statistics/242851/average-real-estate-sale-price-in-china/
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Average real estate sale price in China 1998-2023

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

In 2023, the average price of real estate in China was approximately ****** yuan per square meter, representing a decrease from the previous year. Rising prices in the real estate market Since the 1998 housing reform, property prices in China have been rising continuously. Housing in the country is now often unaffordable, especially considering the modest per capita income of Chinese households. Shanghai and Beijing even have some of the most competitive real estate markets in the world. The rapid growth in housing prices has increased wealth among homeowners, while it also led to a culture of speculation among buyers and real estate developers. Housing was treated as investments, with owners expecting the prices to grow further every year. Risk factors The expectation of a steadily growing real estate market has created a property bubble and a potential debt crisis. As Chinese real estate giants, such as China Evergrande and Country Garden, operate by continuously acquiring land plots and initiating new projects, which often require substantial loans and investments, a slowdown in property demands or a decline in home prices can significantly affect the financial situation of these companies, putting China’s banks in a vulnerable position. In addition, due to a lack of regulations and monetary constraints, the long-term maintenance issues of high-rise apartments are also a concern to the sustainable development of China’s cities.

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