IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i9p5121-d548320.html
   My bibliography  Save this article

A Study of Multiregional Economic Correlation Analysis Based on Big Data—Taking the Regional Economy of Cities in Shaanxi Province, China, as an Example

Author

Listed:
  • Shouheng Tuo

    (School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an 710121, China)

  • Hong He

    (College of Economics and Management, Xi’an University of Posts and Telecommunications, Xi’an 710121, China)

Abstract

To enhance the sustainability of the regional economy, this study attempts to integrate historical big data of multiregional and multi-industry economic indicators, aiming to explore and discover the correlations among regions, industries, or cross-regional economic indicators. In this paper, two correlation analysis models (the 2-order correlation model and the elastic-net regularized generalized linear model) are used to conduct a correlation analysis study of multiregional and multi-industry economies, and 20 years of historical data from 9 prefecture-level cities in Shaanxi (778 indicators in total) are analyzed empirically. The results show that the proposed method can mine complex correlations from economic big data.

Suggested Citation

  • Shouheng Tuo & Hong He, 2021. "A Study of Multiregional Economic Correlation Analysis Based on Big Data—Taking the Regional Economy of Cities in Shaanxi Province, China, as an Example," Sustainability, MDPI, vol. 13(9), pages 1-13, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5121-:d:548320
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/9/5121/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/9/5121/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antonakakis, N. & Badinger, H., 2016. "Economic growth, volatility, and cross-country spillovers: New evidence for the G7 countries," Economic Modelling, Elsevier, vol. 52(PB), pages 352-365.
    2. Huan Zhou & Shaojian Qu & Xiaoguang Yang & Qinglu Yuan, 2020. "Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-14, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shouheng Tuo & Tianrui Chen & Hong He & Zengyu Feng & Yanling Zhu & Fan Liu & Chao Li, 2021. "A Regional Industrial Economic Forecasting Model Based on a Deep Convolutional Neural Network and Big Data," Sustainability, MDPI, vol. 13(22), pages 1-11, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Akhilesh K. Verma & Rajeswari Sengupta, 2021. "Interlinkages between external debt financing, credit cycles and output fluctuations in emerging market economies," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(4), pages 965-1001, November.
    2. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    3. Alejandro Parot & Kevin Michell & Werner D. Kristjanpoller, 2019. "Using Artificial Neural Networks to forecast Exchange Rate, including VAR‐VECM residual analysis and prediction linear combination," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 3-15, January.
    4. J A Edwards & C B Naanwaab & S P Simkins, 2023. "The Great Recession and Small States," Economic Issues Journal Articles, Economic Issues, vol. 28(1), pages 81-103, March.
    5. Arčabić, Vladimir & Škrinjarić, Tihana, 2021. "Sharing is caring: Spillovers and synchronization of business cycles in the European Union," Economic Modelling, Elsevier, vol. 96(C), pages 25-39.
    6. Papież, Monika & Rubaszek, Michał & Szafranek, Karol & Śmiech, Sławomir, 2022. "Are European natural gas markets connected? A time-varying spillovers analysis," Resources Policy, Elsevier, vol. 79(C).
    7. Binh Thai Pham & Hector Sala, 2022. "Cross-country connectedness in inflation and unemployment: measurement and macroeconomic consequences," Empirical Economics, Springer, vol. 62(3), pages 1123-1146, March.
    8. Fateh Belaid & Amine Ben Amar & Stéphane Goutte & Khaled Guesmi, 2023. "Emerging and advanced economies markets behaviour during the COVID‐19 crisis era," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1563-1581, April.
    9. Jiang, Yong & Zhou, Zhongbao & Liu, Qing & Lin, Ling & Xiao, Helu, 2020. "How do oil price shocks affect the output volatility of the U.S. energy mining industry? The roles of structural oil price shocks," Energy Economics, Elsevier, vol. 87(C).
    10. Hkiri, Besma & Hammoudeh, Shawkat & Aloui, Chaker & Yarovaya, Larisa, 2017. "Are Islamic indexes a safe haven for investors? An analysis of total, directional and net volatility spillovers between conventional and Islamic indexes and importance of crisis periods," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 124-150.
    11. Kollmann, Robert, 2016. "International business cycles and risk sharing with uncertainty shocks and recursive preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 115-124.
    12. Gnangnon, Sèna Kimm, 2021. "Tax reform and public debt instability in developing countries: The trade openness and public revenue instability channels," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 54-67.
    13. Mensi, Walid & Hamed Al-Yahyaee, Khamis & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Dynamic spillover and connectedness between oil futures and European bonds," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    14. Antonakakis, Nikolaos & Gupta, Rangan & Tiwari, Aviral K., 2017. "The time-varying correlation between output and prices in the United States over the period 1800–2014," Economic Systems, Elsevier, vol. 41(1), pages 98-108.
    15. Trypsteen, Steven, 2017. "The growth-volatility nexus: New evidence from an augmented GARCH-M model," Economic Modelling, Elsevier, vol. 63(C), pages 15-25.
    16. Pinar Deniz & Thanasis Stengos & M. Ege Yazgan, 2021. "Revisiting the link between output growth and volatility: panel GARCH analysis," Empirical Economics, Springer, vol. 61(2), pages 743-771, August.
    17. Lastrapes, William D. & Wiesen, Thomas F.P., 2021. "The joint spillover index," Economic Modelling, Elsevier, vol. 94(C), pages 681-691.
    18. Jae Young Jang & Erdal Atukeren, 2019. "Sustainable Local Currency Debt: An Analysis of Foreigners’ Korea Treasury Bonds Investments Using a LA-VARX Model," Sustainability, MDPI, vol. 11(13), pages 1-23, June.
    19. Loayza,Norman V. & Ouazad,Amine & Ranciere,Romain, 2017. "Financial development, growth, and crisis: is there a trade-off ?," Policy Research Working Paper Series 8237, The World Bank.
    20. Huang, Wenli & Li, Shi & Qi, Zhen & Zhang, Qi, 2022. "Macro disagreement and international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5121-:d:548320. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.