IDEAS home Printed from https://ideas.repec.org/a/spr/jecstr/v6y2017i1d10.1186_s40008-017-0096-5.html
   My bibliography  Save this article

How to evaluate the reliability of regional input–output data? A case for China

Author

Listed:
  • Haoyang Zhao

    (University of Chinese Academy of Sciences)

  • Jian Xu

    (University of Chinese Academy of Sciences)

  • Xinteng Liu

    (University of Chinese Academy of Sciences)

Abstract

Accurate statistical data are essential to a credible and cogent empirical analysis. However, there currently is no mature and specialized methodology to evaluate the accuracy of input–output (IO) data. This research constructs a comprehensive yet relatively concise framework for evaluating the accuracy of regional IO data by including several indicators that measure all three quadrants. The framework examines regional IO data from the perspectives of time consistency and variation, coefficient correlation and its homogeneity with national-level data. A score indicating the overall accuracy and detailed information that presents concrete shortcomings of regional IO data could be offered after analysis using this framework. As an example, the provincial-level IO data for 30 provinces for 3 years (2002, 2007 and 2012) are analyzed by this framework, and possible explanations of the results are offered. The main contribution and innovation of this research is the construction of an applicable and exhaustive quality evaluation framework for regional IO data. This framework enables researchers to realize flaws in IO data before utilizing them. It also allows government agencies to improve the quality of their data by avoiding issues that emerged in previous data quality evaluations.

Suggested Citation

  • Haoyang Zhao & Jian Xu & Xinteng Liu, 2017. "How to evaluate the reliability of regional input–output data? A case for China," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 6(1), pages 1-22, December.
  • Handle: RePEc:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0096-5
    DOI: 10.1186/s40008-017-0096-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40008-017-0096-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1186/s40008-017-0096-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sinton, Jonathan E., 2001. "Accuracy and reliability of China's energy statistics," China Economic Review, Elsevier, vol. 12(4), pages 373-383.
    2. Huenemann, Ralph W., 2001. "Are China's recent transport statistics plausible?," China Economic Review, Elsevier, vol. 12(4), pages 368-372.
    3. Mehrotra, Aaron & Pääkkönen, Jenni, 2011. "Comparing China's GDP statistics with coincident indicators," Journal of Comparative Economics, Elsevier, vol. 39(3), pages 406-411, September.
    4. Park, Albert & Wang, Sangui, 2001. "China's poverty statistics," China Economic Review, Elsevier, vol. 12(4), pages 384-398.
    5. repec:zbw:bofitp:2011_001 is not listed on IDEAS
    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. Francisco Orlando Rosales & Brian D. Fath & Grace Yolanda Llerena, 2023. "Quantifying a virtual water metabolic network of the Metropolitan District of Quito, Ecuador using ecological network methods," Journal of Industrial Ecology, Yale University, vol. 27(5), pages 1304-1318, October.

    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. Holz, Carsten A, 2013. "Chinese statistics: classification systems and data sources," MPRA Paper 43869, University Library of Munich, Germany.
    2. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    3. Ma, Ben & Song, Guojun & Zhang, Lei & Sonnenfeld, David A., 2014. "Explaining sectoral discrepancies between national and provincial statistics in China," China Economic Review, Elsevier, vol. 30(C), pages 353-369.
    4. Mayo, Robert, 2015. "Hidden Risk: Detecting Fraud in Chinese Banks’ Non-performing Loan Data," MPRA Paper 98435, University Library of Munich, Germany.
    5. Du, Yimeng & Takeuchi, Kenji, 2019. "Can climate mitigation help the poor? Measuring impacts of the CDM in rural China," Journal of Environmental Economics and Management, Elsevier, vol. 95(C), pages 178-197.
    6. Teng, Meixuan & Burke, Paul J. & Liao, Hua, 2019. "The demand for coal among China's rural households: Estimates of price and income elasticities," Energy Economics, Elsevier, vol. 80(C), pages 928-936.
    7. Liao, Hua & Wei, Yi-Ming, 2010. "China's energy consumption: A perspective from Divisia aggregation approach," Energy, Elsevier, vol. 35(1), pages 28-34.
    8. Ma, Ben & Zheng, Xinye, 2018. "Biased data revisions: Unintended consequences of China's energy-saving mandates," China Economic Review, Elsevier, vol. 48(C), pages 102-113.
    9. Björn Gustafsson & Li Shi & Hiroshi Sato, 2004. "Can a subjective poverty line be applied to China? Assessing poverty among urban residents in 1999," Journal of International Development, John Wiley & Sons, Ltd., vol. 16(8), pages 1089-1107.
    10. Xing, Li & Fan, Shenggen & Luo, Xiaopeng & Zhang, Xiaobo, 2006. "Village Inequality in Western China," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25390, International Association of Agricultural Economists.
    11. Souche, Stéphanie, 2009. "Un exemple d’estimation de la demande de transport urbain," Revue d'économie régionale et urbaine, Editions NecPlus, vol. 2009(04), pages 759-779, December.
    12. Michieka, Nyakundi M. & Fletcher, Jerald & Burnett, Wesley, 2013. "An empirical analysis of the role of China’s exports on CO2 emissions," Applied Energy, Elsevier, vol. 104(C), pages 258-267.
    13. Meng, Lingsheng, 2013. "Evaluating China's poverty alleviation program: A regression discontinuity approach," Journal of Public Economics, Elsevier, vol. 101(C), pages 1-11.
    14. Pang, Ke & Siklos, Pierre L., 2016. "Macroeconomic consequences of the real-financial nexus: Imbalances and spillovers between China and the U.S," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 195-212.
    15. Zhang, Chunni & Xu, Qi & Zhou, Xiang & Zhang, Xiaobo & Xie, Yu, 2014. "Are poverty rates underestimated in China? New evidence from four recent surveys," China Economic Review, Elsevier, vol. 31(C), pages 410-425.
    16. Steenhof, Paul A., 2006. "Decomposition of electricity demand in China's industrial sector," Energy Economics, Elsevier, vol. 28(3), pages 370-384, May.
    17. Xing, Li & Fan, Shenggen & Luo, Xiaopeng & Zhang, Xiaobo, 2006. "Village inequality in Western China: implications for development strategy in lagging regions," DSGD discussion papers 31, International Food Policy Research Institute (IFPRI).
    18. Heiner Mikosch & Ying Zhang, 2014. "Forecasting Chinese GDP Growth with Mixed Frequency Data," KOF Working papers 14-359, KOF Swiss Economic Institute, ETH Zurich.
    19. Price, L & Sinton, J & Worrell, E & Phylipsen, D & Xiulian, H & Ji, L, 2002. "Energy use and carbon dioxide emissions from steel production in China," Energy, Elsevier, vol. 27(5), pages 429-446.
    20. Wang, Xin, 2011. "On China's energy intensity statistics: Toward a comprehensive and transparent indicator," Energy Policy, Elsevier, vol. 39(11), pages 7284-7289.

    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:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0096-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.