Research on the Statistical Accounting Method of Fixed Assets Investment
Authors
Yanzuo Chen1, *, Lei Ma2, Haibo Lu2
1State Grid Zhejiang Economic and Technological Research Institute, Hangzhou, Zhejiang, China
2State Grid Zhejiang Electric Power Co., LTD., Hangzhou, Zhejiang, China
*Corresponding author.
Email: chenyanzuo@jyy.zj.sgcc.com.cn
Corresponding Author
Yanzuo Chen
Available Online 13 November 2024.
- DOI
- 10.2991/978-94-6463-562-1_10How to use a DOI?
- Keywords
- Statistical accounting method of fixed assets investment; image progress method; financial expenditure method
- Abstract
The statistical data of fixed assets investment is an important basis of national economic accounting and an important indicator of social and economic development. This paper comprehensively expounds the development of statistical accounting methods for fixed assets investment in China, studies the differences between financial expenditure method and image progress method from four dimensions: filling basis, measurement benchmark, statistical start and end points, and investment statistical range, and carries out calculation and analysis of investment completion under the two algorithms.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yanzuo Chen AU - Lei Ma AU - Haibo Lu PY - 2024 DA - 2024/11/13 TI - Research on the Statistical Accounting Method of Fixed Assets Investment BT - Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024) PB - Atlantis Press SP - 102 EP - 112 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-562-1_10 DO - 10.2991/978-94-6463-562-1_10 ID - Chen2024 ER -