8 datasets found
  1. T

    Chinese Yuan Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jan 3, 2017
    + more versions
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    TRADING ECONOMICS (2017). Chinese Yuan Data [Dataset]. https://tradingeconomics.com/china/currency
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    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jan 3, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 2, 1981 - Sep 26, 2025
    Area covered
    China
    Description

    The USD/CNY exchange rate fell to 7.1414 on September 26, 2025, down 0.01% from the previous session. Over the past month, the Chinese Yuan has strengthened 0.11%, but it's down by 2.30% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on September of 2025.

  2. H

    Is the Chinese Currency Substantially Misaligned to Warrant Further...

    • dataverse.harvard.edu
    • data.niaid.nih.gov
    Updated Feb 4, 2010
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    Duo Qin; Xinhua He (2010). Is the Chinese Currency Substantially Misaligned to Warrant Further Appreciation? [Dataset] [Dataset]. http://doi.org/10.7910/DVN/TTRH5M
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 4, 2010
    Dataset provided by
    Harvard Dataverse
    Authors
    Duo Qin; Xinhua He
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    1993 - 2009
    Area covered
    Saudi Arabia
    Description

    This study provides quarterly time-series estimates of the misalignment in the REER of the Renminbi (RMB). The estimation is based on a commonly used economic approach, but with a wider and more up-to-date coverage of data and a more extensive use of econometric modelling techniques. Our estimates corroborate and explain most of the previous estimates. More importantly, our estimates demonstrate that there is no significant undervaluation in the REER of the RMB though downward misalignment exists in the trilateral rates between the RMB, US$ and euro. The finding refutes the claim that RMB appreciation is the primary and necessary solution to the current global trade imbalance.

  3. f

    Data.

    • plos.figshare.com
    application/x-rar
    Updated Mar 26, 2025
    + more versions
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    Minjie Hu; Xuemei Yuan (2025). Data. [Dataset]. http://doi.org/10.1371/journal.pone.0319570.s001
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    application/x-rarAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Minjie Hu; Xuemei Yuan
    License

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

    Description

    Under the dollar-dominated international monetary system, the cross-border capital flows of emerging economies reverse sharply following policy shifts by the Fed. To investigate the sensitivity of cross-border capital inflows to dollar shocks, we analyze 33 emerging economies from 2006Q1 to 2021Q4 and use the panel quantile model to explore the dynamic evolution of dollar appreciation shocks at different stages of capital inflows, especially the tail effects. We find that dollar appreciation shocks reduce the total cross-border capital inflows of emerging economies. This impact is mainly through internal and external financial cycle difference channels. Dollar shock impacts differ significantly across different quantiles of capital inflows. Specifically, dollar appreciation shifts the capital inflow to the left and increases the severity of the left-tail risk of capital flows. More flexible exchange rate regimes exacerbate the negative effects of dollar shocks across the distribution of capital inflows. The moderating effect of the fixed exchange rate and intermediate exchange rate systems on external shocks are effective in low quantiles of capital inflows. The sensitivity of “capital flows at risk” to dollar shocks depends on national structural characteristics. As a key risk factor for emerging economies, US dollar appreciation can predict the trend of cross-border capital inflows. Countries should adopt policy measures to curb the adverse effects of US dollar fluctuations.

  4. Data from: Taxonomic re-evaluation of the subspecies of Hebius vibakari...

    • gbif.org
    Updated Jul 11, 2024
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    Zong-Yuan Gao; Jun-Jie Huang; Li Ding; Ke Jiang; Jie Mao; Jin-Long Ren; Zong-Yuan Gao; Jun-Jie Huang; Li Ding; Ke Jiang; Jie Mao; Jin-Long Ren (2024). Taxonomic re-evaluation of the subspecies of Hebius vibakari (Boie, 1826) (Reptilia: Serpentes: Natricidae), with new evidence from central and northern China [Dataset]. http://doi.org/10.15468/ykcem6
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    Dataset updated
    Jul 11, 2024
    Dataset provided by
    Global Biodiversity Information Facilityhttps://www.gbif.org/
    Plazi
    Authors
    Zong-Yuan Gao; Jun-Jie Huang; Li Ding; Ke Jiang; Jie Mao; Jin-Long Ren; Zong-Yuan Gao; Jun-Jie Huang; Li Ding; Ke Jiang; Jie Mao; Jin-Long Ren
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset contains the digitized treatments in Plazi based on the original journal article Gao, Zong-Yuan, Huang, Jun-Jie, Ding, Li, Jiang, Ke, Mao, Jie, Ren, Jin-Long (2024): Taxonomic re-evaluation of the subspecies of Hebius vibakari (Boie, 1826) (Reptilia: Serpentes: Natricidae), with new evidence from central and northern China. Zootaxa 5474 (5): 503-521, DOI: 10.11646/zootaxa.5474.5.3, URL: http://dx.doi.org/10.11646/zootaxa.5474.5.3

  5. f

    Panel quantile regressions: Effect of exchange rate regime.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Mar 26, 2025
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    Minjie Hu; Xuemei Yuan (2025). Panel quantile regressions: Effect of exchange rate regime. [Dataset]. http://doi.org/10.1371/journal.pone.0319570.t009
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Minjie Hu; Xuemei Yuan
    License

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

    Description

    Panel quantile regressions: Effect of exchange rate regime.

  6. f

    Endogeneity analysis.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Mar 26, 2025
    + more versions
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    Minjie Hu; Xuemei Yuan (2025). Endogeneity analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0319570.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Minjie Hu; Xuemei Yuan
    License

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

    Description

    Under the dollar-dominated international monetary system, the cross-border capital flows of emerging economies reverse sharply following policy shifts by the Fed. To investigate the sensitivity of cross-border capital inflows to dollar shocks, we analyze 33 emerging economies from 2006Q1 to 2021Q4 and use the panel quantile model to explore the dynamic evolution of dollar appreciation shocks at different stages of capital inflows, especially the tail effects. We find that dollar appreciation shocks reduce the total cross-border capital inflows of emerging economies. This impact is mainly through internal and external financial cycle difference channels. Dollar shock impacts differ significantly across different quantiles of capital inflows. Specifically, dollar appreciation shifts the capital inflow to the left and increases the severity of the left-tail risk of capital flows. More flexible exchange rate regimes exacerbate the negative effects of dollar shocks across the distribution of capital inflows. The moderating effect of the fixed exchange rate and intermediate exchange rate systems on external shocks are effective in low quantiles of capital inflows. The sensitivity of “capital flows at risk” to dollar shocks depends on national structural characteristics. As a key risk factor for emerging economies, US dollar appreciation can predict the trend of cross-border capital inflows. Countries should adopt policy measures to curb the adverse effects of US dollar fluctuations.

  7. f

    Dollar shocks and cross-border capital inflows: Robustness test.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Mar 26, 2025
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    Minjie Hu; Xuemei Yuan (2025). Dollar shocks and cross-border capital inflows: Robustness test. [Dataset]. http://doi.org/10.1371/journal.pone.0319570.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Minjie Hu; Xuemei Yuan
    License

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

    Description

    Dollar shocks and cross-border capital inflows: Robustness test.

  8. Dollar shocks and cross-border capital inflows: Mechanism analysis.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Mar 26, 2025
    Share
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    Click to copy link
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    Minjie Hu; Xuemei Yuan (2025). Dollar shocks and cross-border capital inflows: Mechanism analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0319570.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Minjie Hu; Xuemei Yuan
    License

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

    Description

    Dollar shocks and cross-border capital inflows: Mechanism analysis.

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    Learn how you can add new datasets to our index.

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TRADING ECONOMICS (2017). Chinese Yuan Data [Dataset]. https://tradingeconomics.com/china/currency

Chinese Yuan Data

Chinese Yuan - Historical Dataset (1981-01-02/2025-09-26)

Explore at:
54 scholarly articles cite this dataset (View in Google Scholar)
xml, csv, excel, jsonAvailable download formats
Dataset updated
Jan 3, 2017
Dataset authored and provided by
TRADING ECONOMICS
License

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

Time period covered
Jan 2, 1981 - Sep 26, 2025
Area covered
China
Description

The USD/CNY exchange rate fell to 7.1414 on September 26, 2025, down 0.01% from the previous session. Over the past month, the Chinese Yuan has strengthened 0.11%, but it's down by 2.30% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on September of 2025.

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