Fuzzy Set Qualitative Comparative Analysis (fsQCA) Applied to the Driving Mechanism of Total Factor Productivity Growth
With the gradual improvement of fuzzy set qualitative comparative analysis (fsQCA), it is introduced into more and more fields to analyze practical problems. This paper calculates the total factor productivity index and analyzes its development trend based on relevant economic development theories a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/8182454 |
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| Summary: | With the gradual improvement of fuzzy set qualitative comparative analysis (fsQCA), it is introduced into more and more fields to analyze practical problems. This paper calculates the total factor productivity index and analyzes its development trend based on relevant economic development theories and China’s inter-provincial panel data from 1999 to 2019. We use the fsQCA method to study the interaction of factors influencing total productivity in various regions. Two specific paths to improve total factor productivity are obtained, which provide a reference for different areas to improve total factor productivity according to local conditions. |
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| ISSN: | 2314-4785 |