The Affecting Factors of the Geographic Distribution of the Online Peer-to-peer Lending in China

Abstract

Online peer-to-peer (P2P) lending broadens the radius of traditional financial services with the help of Internet technology and therefore may help the development of inclusive finance without space limitation. But its development still shows a certain geographic distribution. In this paper, taking data from a P2P platform and utilizing spatial statistical analysis and multi-regression analysis methods, we explore the geographic distribution and its affecting factors of online P2P lending in China. The results show that the development of online P2P lending in China represents a certain degree of global autocorrelation. The eastern coastal areas show local high-value agglomeration while the underdeveloped areas in western China show low-value agglomeration. The regression analysis found that the total amount of regional loans, the number of private enterprises, the development of Internet-based finance and the level of regional innovation are the main factors affecting the development of online P2P lending. Hence the geographic distribution of the online P2P lending in China mainly depends on the comprehensive development of regional finance and regional innovation.