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

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