TITLE:
Exploration of the Impact Mechanism of Government Credibility Based on Variable Screening Method
AUTHORS:
Jiajun Wu, Yuxiang Ma, Helin Zou, Chun Zhang, Ran Yan
KEYWORDS:
Government Credibility, Variable Selection Models, Social Statistics, Regression Based Approach, Method Based on Random Forest
JOURNAL NAME:
Journal of Data Analysis and Information Processing,
Vol.12 No.3,
August
27,
2024
ABSTRACT: Government credibility is an important asset of contemporary national governance, an important criterion for evaluating government legitimacy, and a key factor in measuring the effectiveness of government governance. In recent years, researchers’ research on government credibility has mostly focused on exploring theories and mechanisms, with little empirical research on this topic. This article intends to apply variable selection models in the field of social statistics to the issue of government credibility, in order to achieve empirical research on government credibility and explore its core influencing factors from a statistical perspective. Specifically, this article intends to use four regression-analysis-based methods and three random-forest-based methods to study the influencing factors of government credibility in various provinces in China, and compare the performance of these seven variable selection methods in different dimensions. The research results show that there are certain differences in simplicity, accuracy, and variable importance ranking among different variable selection methods, which present different importance in the study of government credibility issues. This study provides a methodological reference for variable selection models in the field of social science research, and also offers a multidimensional comparative perspective for analyzing the influencing factors of government credibility.