Research Article
Analysis of Factors Influencing the Demand for Agricultural Insurance Based on Grey Correlation and Principal Component Analysis - An Example from Liaoning Province
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334429, author={Xiaoting Dong and Hui Che and Tingrui Liu}, title={Analysis of Factors Influencing the Demand for Agricultural Insurance Based on Grey Correlation and Principal Component Analysis - An Example from Liaoning Province}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={agricultural insurance demand grey correlation principal component analysis panel data}, doi={10.4108/eai.19-5-2023.2334429} }- Xiaoting Dong
Hui Che
Tingrui Liu
Year: 2023
Analysis of Factors Influencing the Demand for Agricultural Insurance Based on Grey Correlation and Principal Component Analysis - An Example from Liaoning Province
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334429
Abstract
Tn this paper, grey correlation analysis was conducted on 17 characteristic indicators from various perspectives, such as socio-economic and agricultural production, and 12 indicators with higher correlation were selected to provide a basis for demand forecasting. Secondly, principal component analysis was used to reduce the dimensionality of the 12 indicators, and finally the expressions of the five principal components and the comprehensive scores were obtained. Subsequently, principal component regression analysis was used to empirically analyse the panel data of 14 cities in Liaoning Province from 2004 to 2020, and a multiple linear regression model was derived and the regression equation was obtained. The regression equation is derived from the regression model.