Sponsor(s): Shanghai University of Finance and Economics
12 issues per year
Current Issue: Issue 05, 2020
Journal of Finance and Economics is supervised by Ministry of Education of PRC, and sponsored by Shanghai University of Finance and Economics. It aims to include research results on the major theories and practical problems in China’s reform and opening up and modernization of economic construction. Its scope covers all the major fields of Economics, including Public Economy, Finance, Accounting, Economic history, Regional Economics, Industrial Economics, International Economics. The Journal is included in CSSCI.
Journal of Finance and Economics,2020,Vol 46,No. 05
In recent years, the development of FinTech has brought about profound changes to the banking industry. In the field of inclusive finance, the use of the latest IT technologies such as big data, cloud computing, AI and blockchain has given new solutions to the financial constraint problems of SMEs. For this reason, as representatives of traditional financial institutions, commercial banks have also begun to apply financial technology actively and have started strategic transformation. At the same time, people are generally concerned about the extent to which FinTech can empower commercial banks, and what changes will be brought to the market structure. In the process of transformation, large banks represented by state-owned banks and national joint-stock banks often invest hugely and comprehensively, relying on their advantages in capital, technology and talents. However, small and medium banks have comparative advantages in shorter decision-making chains and more flexible responsiveness. Therefore, to which side will the use of FinTech bring more help is a question worth discussing. Using Python tools to crawl web pages, this paper constructed the FinTech application index of commercial banks, and used data from 261 Chinese banks in 2010–2018 to conduct research. The results show that large commercial banks have significantly reduced their risk levels and improved risk tolerance ability after applying FinTech, and the improvement is better than that of small and medium banks. In addition to the impact on individual banks, FinTech will also change the structure of the market. FinTech application has reduced the information asymmetry between banks and enterprises, and narrowed the gap between large banks and small and medium banks in their ability to acquire soft information. In the meanwhile, by virtue of advantages in lower capital cost, large banks are therefore able to identify and more easily attract SMEs with relatively low risks, thus forming a dimensionality reduction on small and medium banks in the field of inclusive finance, which has brought negative impacts on small and medium banks. The results show that by the application of FinTech, large banks' loans to SMEs have increased significantly, but the risks have not changed significantly. In contrast, small and medium banks' loans to SMEs have not increased significantly, but the risks have increased significantly. This phenomenon reflects the loss of high-quality customers in small and medium banks and the existence of market crowding-out effect. The main contributions of this paper are as follows. Firstly, based on the existing literature, we use Python tools to improve the text mining method, constructing the FinTech application index that is detailed to the individual level of commercial banks. Secondly, for the first time we quantitatively examine the heterogeneous impact of FinTech on traditional banks and the interaction between different banks from the perspective of commercial banks applying FinTech. Thirdly, for the first time we quantitatively examine the crowding-out effect between large banks and small and medium banks by applying FinTech in the field of inclusive finance. This paper has innovations in the index construction and mechanism testing, and is meaningful to the commercial banks that use FinTech for digital transformation, as well as competition and structural changes in banking industry caused by FinTech development.
Journal of Finance and Economics,2020,Vol 46,No. 05
Securities analysts are the backbone of transmitting capital market information and influencing resource allocation. However, the uncertainty in the development of China’s capital market and the lagging of public governance mechanisms have led companies to rely on relational contracts formed by long-term transactions. Since each transaction of a relational contract has its own particularity, one must be embedded within the network of relationships to obtain information between the parties, in order to evaluate a company’s operating activities and value. Therefore, this paper explored the impact of social capital formed by analysts embedded in the company’s regional relationship network (herein referred to as “hometown network capital”) on the accuracy of analyst forecasts. Specifically, based on the research report released by 6970 analyst teams in China’s capital market from 2006 to 2016, this paper achieved the following findings. (1) Analysts are more accurate in predicting the profits of the listed companies where their household registration is located, with an average error being 3% lower than that of other analysts. (2) In the area where the social relationship network is more complex and social capital is more important, analysts’ hometown network capital has a greater comparative information advantage. (3) Research reports released by analysts with hometown network capital have led to stronger short-term and long-term market reactions. In addition, this paper found that the information advantage of analysts’ hometown network capital is reflected not only in the acquisition of private information, but also in the interpretation of public information. At the same time, analysts are more likely to be invited to participate in the research activities of hometown listed companies. The research contributions of this paper are as follows. Firstly, it enriches the relevant research on the social relationship network of securities analysts. Different from the direct social relations between analysts and executives of listed companies, the essence of hometown network capital of analysts concerned in this paper is a kind of regional social capital of analysts, whose scope includes direct social relations and indirect social relations, thus expanding the research field of analysts’ social relations. Secondly, it supplements the relevant literature about the influence of geographic distance on information transmission mechanism. By comparing the differences between social network distance and geographic distance in information acquisition, this paper provides a new research dimension for understanding the influence of distance on information transmission. Finally, because the transaction behavior and content of a company under the relational transaction mode are dependent on the relationship network of the transaction subject, it is difficult for the analysts as an information intermediary to be independent of the company’s relationship network. With the emergence of the sci-tech innovation board and the registration system, the capital market operation system with information disclosure as the core needs to be established urgently.
Journal of Finance and Economics,2020,Vol 46,No. 05
After the 2008 international financial crisis, the global economy entered a period of deep adjustment, and global value chains (GVCs) faced restructuring issues. At the same time, the development of China’s open economy has also entered a new stage. There are two prominent changes and characteristics. One is that under the condition that the price of production factors continues to rise and the traditional low-cost advantage is gradually lost, the pattern of China’s integration into the GVC division of labor must also be transformed from passive participation to active construction; the other is a shift from the past focus on “bring in” to the focus on both “bring in” and “going out.” This raises a very interesting and practical question. Does China’s outward foreign direct investment (OFDI) help build the GVC? Based on the theoretical analysis, this paper used the trade in value-added measurement method proposed by Koopman et al. (2012) to construct a bilateral value chain correlation index and a value chain relative position index, and refined them between countries, that is, to measure the value chain relationship between two countries and the upstream and downstream relationship of the value chain separately. Using Chinese empirical data, this paper incorporated the spatial lag item to quantitatively analyze the value chain construction effect and its spatial spillover brought by OFDI, and answered how the value chain correlation and the value chain relative position index are affected by the influence of China’s OFDI to the host country and China’s OFDI to the neighboring countries of the host country. It divided the host countries according to the countries along the Belt and Road and the countries not along the Belt and Road to study the spatial spillover effect of the value chain construction effect within and between regions, so as to better grasp the actual value chain construction effect of OFDI in China under GVCs. The measurement results show that China’s OFDI not only enhances the value chain relationship with the host countries, but also further closes the value chain relationship with other countries through the spatial spillover effect; at the same time, it also plays a positive role in improving China’s division of labor in GVCs, not only in terms of the relative improvement of the division of labor compared with the host countries, but also in improving the division of labor compared with the third countries due to the spatial spillover effect. The above findings are not only helpful for us to objectively understand and evaluate the practical effect of China’s OFDI in building the GVC, but also have some policy implications for how to further reshape and optimize the GVC to better play the role of “going out.”