Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Series Vol. 68 , 05 January 2024
* Author to whom correspondence should be addressed.
This paper presents an in-depth analysis of the correlation between China’s manufacturing PMI and private equity investment from 2015 to 2022, utilizing correlation and regression analysis methods based on both overall and structural data. The findings reveal a moderate correlation between manufacturing PMI and private equity investment. Specifically, manufacturing PMI demonstrates a predictive effect on private equity investment, with a lead time of one to two quarters. This accounts for 27.7% of the variation in private equity investment. Furthermore, employing the VAR model, this study observes a significant positive effect of manufacturing PMI on private equity investment, with significant positive impacts found during the two and six lagged periods. These results align with the leading indicator characteristic of PMI and suggest that private equity investment serves as a “barometer” for the capital market. Additionally, this paper investigates the correlation between manufacturing PMI and different stages of private equity investments (early, venture capital (VC), and PE investments) while also analyzing the correlation between manufacturing PMI and private equity investments from different funding sources, including RMB and foreign currency private equity investments. The results indicate that, akin to private equity investment in general, early, VC, and PE investments exhibit varying degrees of correlation with manufacturing PMI. Moreover, foreign currency private equity investment demonstrates a stronger correlation with manufacturing PMI compared to RMB private equity investment.
macroeconomic indicator, private equity investment, correlation
1. Zhu, W. (2023). Analysis and Research on the Current Development of Private Equity Funds and Countermeasures in China. China Management Informatization, 3, 133-137.
2. Huang, J. (2023). The Impact of Private Equity Investment on Corporate Value and Performance. China Circulation Economy, 5, 93-95.
3. Sheng, Y., Yang, G. (2016). A Study on the Correlation between Manufacturing PMI and the Stock Market. Journal of Qiqihar University, 2, 49-53.
4. Zhang, C. (2023). Correlation between Official PMI Index and CSI 800. Economic Research, 3, 55-57.
5. Yang, S. (2018). An Empirical Study on the Relationship between the Shanghai Shenzhen CSI 300 and China’s Manufacturing PMI. Modern Communication, 9, 63-65.
6. Ren, J., Li, X., Cao, L. (2023). Manager Mobility and Private Equity Syndications from the Perspective of Coupling Networks: Evidence from China's Private Equity Industry. Journal of Social Computing, 4(2), 150-167.
7. Wilson, R. (1968). The theory of syndicates. Econometrica, 36(1), 119-132.
8. The SPSSAU project (2023). SPSSAU. Retrieved from https://www.spssau.com.
9. Sun, D. (2000). Selection of the Linear Regression Model According to the Parameter Estimation. Wuhan University Journal of Natural Sciences, 5(4), 400-405.
10. William, H. (1998). Greene. Econometric Analysis. Beijing: China Social Sciences Press.
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).