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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/11/2921 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850129068347883520 |
|---|---|
| author | Zhiwei Cui Qideng Luo Haoyang Ji Yang Xu Junyi Shi |
| author_facet | Zhiwei Cui Qideng Luo Haoyang Ji Yang Xu Junyi Shi |
| author_sort | Zhiwei Cui |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4d130ed78c434e3288ef0d402cd960a3 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-4d130ed78c434e3288ef0d402cd960a32025-08-20T02:33:06ZengMDPI AGEnergies1996-10732025-06-011811292110.3390/en18112921Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi ProvinceZhiwei Cui0Qideng Luo1Haoyang Ji2Yang Xu3Junyi Shi4Guangxi Power Grid Co., Ltd., Nanning 530023, ChinaGuangxi Power Grid Co., Ltd., Nanning 530023, ChinaSchool of Economics, Peking University, Beijing 100871, ChinaCarbon Econometric Research Center, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaCarbon Econometric Research Center, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaExisting 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.https://www.mdpi.com/1996-1073/18/11/2921composite indexdiffusion indexbusiness cycle analysiselectric power dataDenton model |
| spellingShingle | Zhiwei Cui Qideng Luo Haoyang Ji Yang Xu Junyi Shi Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province Energies composite index diffusion index business cycle analysis electric power data Denton model |
| title | Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province |
| title_full | Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province |
| title_fullStr | Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province |
| title_full_unstemmed | Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province |
| title_short | Research on Reconstructing Regional Business Cycle Analysis System Based on Electricity Big Data—A Case Study in Guangxi Province |
| title_sort | research on reconstructing regional business cycle analysis system based on electricity big data a case study in guangxi province |
| topic | composite index diffusion index business cycle analysis electric power data Denton model |
| url | https://www.mdpi.com/1996-1073/18/11/2921 |
| work_keys_str_mv | AT zhiweicui researchonreconstructingregionalbusinesscycleanalysissystembasedonelectricitybigdataacasestudyinguangxiprovince AT qidengluo researchonreconstructingregionalbusinesscycleanalysissystembasedonelectricitybigdataacasestudyinguangxiprovince AT haoyangji researchonreconstructingregionalbusinesscycleanalysissystembasedonelectricitybigdataacasestudyinguangxiprovince AT yangxu researchonreconstructingregionalbusinesscycleanalysissystembasedonelectricitybigdataacasestudyinguangxiprovince AT junyishi researchonreconstructingregionalbusinesscycleanalysissystembasedonelectricitybigdataacasestudyinguangxiprovince |