Impacts of Different Factors of G20 Countries on the Covid-19 Vaccine Rates Based on Empirical Analysis

DOI

10.2991/978-94-6463-024-4_3How to use a DOI?

Keywords

COVID-19; Vaccination rate; Regression analysis; factor; country

Abstract

COVID-19 vaccine is critical to terminate the global pandemic. Intended to examine the impacts of various factors of a country on its COVID-19 vaccine rate, a data set of new cases per day, hospital beds per person, GDP, population density, and stringency index is collected. We do correlation analysis on the variables. We applied OLS linear regression model to the data set. We find the coefficient of different variables, observe p-value of each variable to examine its significance. Then, we applied lasso variable selection to the variables to find more important variables and put them in the linear regression models in order to solve the problems of variables being insignificant and multicollinearity.

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.

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TY  - CONF
AU  - Yihan Lei
PY  - 2022
DA  - 2022/12/12
TI  - Impacts of Different Factors of G20 Countries on the Covid-19 Vaccine Rates Based on Empirical Analysis
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 14
EP  - 29
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_3
DO  - 10.2991/978-94-6463-024-4_3
ID  - Lei2022
ER  -