Working with Chinese Government Data Sets: Potential Issues and Solutions
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LIM, Edward Junhao, STUBBS, Jennifer and XU, Qinghua (2019) Working with Chinese Government Data Sets: Potential Issues and Solutions. Paper presented at: IFLA WLIC 2019 - Athens, Greece - Libraries: dialogue for change in Session 185 - Government Information and Official Publications.
Bookmark or cite this item: https://library.ifla.org/id/eprint/2511
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English (Original)
Available under licence Creative Commons Attribution.
Bookmark or cite this item: https://library.ifla.org/id/eprint/2511/1/185-lim-en.pdf
Abstract
Working with Chinese Government Data Sets: Potential Issues and Solutions
This paper will provide an overview of selected official statistics and data sets collected in the People’s Republic of China, with a particular focus on economic and financial data on mainland China. It will explore options beyond the official statistics, such as CNKI, China Data Online, and CEIC CDMNext, and discuss the strengths and weaknesses of these databases. It will also review the existing arguments surrounding the use of official Chinese statistics and how researchers need to identify any issues behind their data choices. The key takeaway is to avoid generalizing and judging the quality of Chinese data based on exceptions, but instead to approach official Chinese data with a nuanced approach.Item Type: | Conference or Workshop Item (Paper) | ||||||||||||
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Conference details: | IFLA WLIC 2019 - Athens, Greece - Libraries: dialogue for changeSession 185 - International Financial Institutions, Governments, and Austerity: Banks, Bailouts and Information on the Global Debt Crisis - Government Information and Official Publications |
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Divisions: | Division 2 Library Collections > Government Information and Official Publications Section | ||||||||||||
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Uncontrolled Keywords: | Government data; China; Statistical yearbooks; Economic statistics; National Bureau of Statistics | ||||||||||||
Date Deposited: | 16 Jul 2019 15:00 | ||||||||||||
Last Modified: | 16 Jul 2019 15:00 | ||||||||||||
URI: | https://library.ifla.org/id/eprint/2511 |
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