Data Analysis of Economic Policy Uncertainty and the Number of Enterprise Employees based on Panel Regression Model -Taking China's A-share Listed Companies as an Example

Yifan Zhou

2022

Abstract

To make a systematic analysis of the uncertainty of economic policy and then to propose effective countermeasures has been an important subject of business management for many years. This paper selects the asset data of China’s A-share listed companies from 2011 to 2020 and the economic policy uncertainty index EPU formulated by Baker to create a panel regression model, focusing on studying the impact of economic policy uncertainty on the number of employees, and trying to find out the factors that inhibit the impacts of economic policy uncertainty on employment. EPU is an uncertainty index constructed by Baker based on keywords in the South China Evening News, using technical means such as big data crawlers and text analysis. The data results show that economic policy uncertainty is negatively correlated with the number of employees. It is further found that enterprises with large financing constraints and non-state-owned enterprises are more affected by economic policy uncertainty. Finally, based on this conclusion, suggestions and countermeasures are made to relevant policy makers.

Paper Citation

in Harvard Style

Zhou Y. (2022). Data Analysis of Economic Policy Uncertainty and the Number of Enterprise Employees based on Panel Regression Model -Taking China's A-share Listed Companies as an Example. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 406-412. DOI: 10.5220/0011738600003607

in Bibtex Style

@conference{icpdi22,
author={Yifan Zhou},
title={Data Analysis of Economic Policy Uncertainty and the Number of Enterprise Employees based on Panel Regression Model -Taking China's A-share Listed Companies as an Example},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={406-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011738600003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Data Analysis of Economic Policy Uncertainty and the Number of Enterprise Employees based on Panel Regression Model -Taking China's A-share Listed Companies as an Example
SN - 978-989-758-620-0
AU - Zhou Y.
PY - 2022
SP - 406
EP - 412
DO - 10.5220/0011738600003607
PB - SciTePress