The Predicting Model of Urban Residents Pension Income and Expenditure based on Multiple Linear Regression

DOI

10.2991/icaset-16.2016.73How to use a DOI?

Keywords

Multiple linear regression, Pension gap, Gross error analysis, Gray correlation degree

Abstract

In order to keep the social security system have sustainable development and solve the problem of population aging, this paper adopts the method of grey correlation degree analysis among the influencing factors of pension income and expenditure, picking out the best index to reflect the income and expenditure of urban residents' pension, using multiple linear regression method, establishing the predicting model of income and expenditure of urban residents' pension, so as to test the validity and rationality of the model. The results showed that this model had high fitting degree with small error, and the results were reasonable and reliable. It can be knew from the prediction results of the model that: by 2020, it will exist pension gap, the pension gap in 2025 will exceed 500 billion. Thus, it can provide the theoretical basis for the relevant departments to develop the relevant policies.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuanjing Liu
AU  - Xiaotao Shi
AU  - Jiatai Gang
PY  - 2016/05
DA  - 2016/05
TI  - The Predicting Model of Urban Residents Pension Income and Expenditure based on Multiple Linear Regression
BT  - Proceedings of the 2016 6th International Conference on Applied Science, Engineering and Technology
PB  - Atlantis Press
SP  - 363
EP  - 368
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaset-16.2016.73
DO  - 10.2991/icaset-16.2016.73
ID  - Liu2016/05
ER  -