Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province
Existing systems for analyzing regional business cycles mostly select indicators from the macro perspective of consumption, investment, employment, etc., and use industrial value added or quarterly GDP as the benchmark cycle indicator. In order to better construct the benchmark cycle indicators, we...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/11/2921 |
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| Summary: | Existing systems for analyzing regional business cycles mostly select indicators from the macro perspective of consumption, investment, employment, etc., and use industrial value added or quarterly GDP as the benchmark cycle indicator. In order to better construct the benchmark cycle indicators, we introduce the Denton model to convert the quarterly GDP to the monthly GDP and select it as the benchmark cycle indicator. This study reconstructed a regional economic cycle analysis system from the perspective of energy using the power big data of Guangxi from January 2014 to December 2024. It compares results with macro-perspective and combined energy-macro approaches, demonstrating that the electric power big data approach enables timely reconstruction of the analysis system with maintained accuracy, enhancing the system’s timeliness. Therefore, the regional business cycle analysis system based on electric power big data can effectively avoid the problem of lag in the release of a monthly business cycle index and has important reference significance for building a high-quality macro real-time monitoring system. |
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| ISSN: | 1996-1073 |