Quality Evaluation of GDP Data Based on Structural Matching in the Context of Big Data
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DOI: 10.25236/icbdem.2020.061
Corresponding Author
Yue Siwei
Abstract
Based on the connotation of GDP data structure matching, a GDP data quality evaluation model was constructed from three aspects: factor input structure, aggregate structure, and production structure, and the construction model was used to evaluate Chongqing's GDP data quality from 2000 to 2018. It is found that Chongqing ’s GDP data is normal from the perspective of factor input structure, Chongqing ’s GDP data is of poor quality from the perspective of aggregate structure matching, Chongqing ’s GDP data quality is from the perspective of production structure stability. There is still room for improvement. From the consistency of the results of the three assessment models, the internal structure of Chongqing's GDP data quality is still not balanced. Taken together, the overall development trend of Chongqing's GDP data quality is good. The current data quality of GDP in terms of total structure matching is the main factor affecting Chongqing GDP data quality.
Keywords
GDP; Data quality; Structural matching; Chongqing