The Impact of Internet-Using on Household Consumption—An Empirical Study Based on Multiple Linear Regression
- DOI
- 10.2991/978-94-6463-210-1_11How to use a DOI?
- Keywords
- Multiple Linear Regression; Ordinary Least Square model; Internet-using; Household consumption expenditure
- Abstract
Purpose-this paper is to study the impact of Internet-using on household consumption expenditure. Methodology-based on the data of Chinese General Social Survey in 2017, this study uses Stata16 software and multiple linear regression to test hypothesis. Findings-the results show that Internet-using significantly increases the total household expenditure, and has a significant positive impact on subsistence and development consumption. In terms of consumption structure, the regression coefficient of Internet-using on expenditure in food, clothing, leisure and entertainment, transportation and communication are positive and significant, while the coefficient is negative and not significant on housing, education, and health expenditures. The empirical results show that Internet-using is helpful to promote the household consumption.
- Copyright
- © 2023 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 - Ti Wang AU - Jie Liu PY - 2023 DA - 2023/07/25 TI - The Impact of Internet-Using on Household Consumption—An Empirical Study Based on Multiple Linear Regression BT - 2023 4th International Conference on E-Commerce and Internet Technology (ECIT 2023) PB - Atlantis Press SP - 90 EP - 96 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-210-1_11 DO - 10.2991/978-94-6463-210-1_11 ID - Wang2023 ER -