This article studies blockchain's economic functions. First, by explaining blockchain technologies from an economic perspective, it introduces the Token Paradigm to summarize mainstream blockchain systems, discusses the true meaning of consensus and trust in the blockchain field, and analyzes the functions of smart contract. Next, it categorizes major blockchain applications according to how they use tokens and discusses relevant economic problems such as tokens? monetary features, tokens? impacts on platform projects, blockchain?s governance functions, and the performance and security of blockchain systems.

This paper uses the annual report data of 263 banks from 2011 to 2015 and the city-level Digital-financial inclusion index constructed by Institute of Digital Finance to explore the impact of the Fintech development on bank behavior. The study finds that the Fintech development actually promotes the interest rate liberalization at the depository side, changes the bank's debt structure, reduces the proportion of banks' retail deposits, and increases the proportion of wholesale financing such as interbank liabilities. Change of liabilities structure leads to a rise in the bank asset risky, but both the average interest rate of assets and net interest margin decline. It suggests that banks choose to use higher-risk assets to make up for the losses caused by rising costs on the liability side rather than transferring costs to downstream companies. At the same time, this paper also finds that larger banks are less affected by the Fintech development.

Based on the method of big data analysis proposed by Jurado et al. (2015), this paper uses the 280 monthly economic and financial variables to construct the 2002-2017 monthly China's financial uncertainty index. We make an empirical analysis of China's financial uncertainty index from two aspects: stock market volatility and systemic risk of financial institutions. The empirical results show that the financial uncertainty index can well predict the realized volatility in the stock market after controlling the lagged volatility; we also find that an increase in financial uncertainty will significantly increase the systemic risk of financial institutions, especially the larger financial institutions. Out results suggest that the financial uncertainty is an important source of volatility in financial markets.

This paper makes a theoretical discussion and empirical test on the impact of the development of digital inclusive finance on household consumption. The conclusions show that: (1) The development of digital inclusive finance has significantly promoted household consumption in the sample period, and this promotion effect is more obvious in rural areas, in the central and western regions, and in the middle and lower income groups. At the same time, in addition to the coverage of digital inclusive financial development, the depth of use and its three sub-indicators: payment, insurance and money funds significantly promote household consumption. (2) Digital inclusive finance promotes the household consumption in the sample period mainly by easing the liquidity constraints and facilitating the payment of households. (3) Using the instrumental variable and replacing the data set with the estimation results of the Chinese labor force dynamic survey data prove that the results are robust and reliable. (4) The results of sub-sample regression of human capital differences show that the higher the education level of the head of household and the stronger the cognitive ability, the more obvious effect of digital inclusive finance on the household consumption in the sample period. (5) The development of digital inclusive finance significantly promotes consumption for clothing, housing, equipment supplies and services, transportation and other goods and services.(6) The sub-sample regression results of household debt-to-income ratio show that the development of digital inclusive finance only promotes the household consumption with low or medium debt-to-income ratio, while there is no the significant inhibitory effect on the consumption of high debt-to-income ratio households. The development of digital inclusive finance has indeed increased the debt-to-income ratio of households. Therefore, while actively promoting the development of digital inclusive finance, it is also necessary to beware of the excessive and over-growth of household debt.

Based on the Chinese Household Financial Survey and Digital Inclusive Financial Index of Peking University, this paper adopts a model with instrumental variables on panel data to study the heterogeneity of digital finance on different types of rural formal financial needs. The results show that different formats of digital finance have different effects on rural financial demand. On the one hand, development of digital finance reduces the level of productive rural formal credit demand. The effects with people using smartphones are more obvious. On the other hand, the demand for rural consumptive formal credit has increased with development of digital finance, especially for groups with higher education levels and online shopping habits, reflecting the multidimensional effects of digital finance such as improving transaction efficiency, and boosting consumption. For the first time, this paper conducts empirical research on the relationship between digital finance and rural financial needs, and also provides references for future rural financial policies.

By using the transaction data of RenrenDai, a representative online Peer-to-Peer lending platform, and the housing price data of 70 large and medium-sized cities in China, this paper investigates the impact of the rising housing price on the borrowing cost of P2P online lending market. Empirical results suggest that the rising housing price significantly increases the borrowing rate of P2P lending. Further analysis finds that rising housing price has significant positive effects on the borrowing rate of the production and operation, house-purchase and other consumption loan projects in the P2P lending market, and the increasing effect is more obvious in the business operation and house-purchase loan projects. In addition, heterogeneity analysis finds that the increasing effect of rising housing price on the P2P borrowing rate is more obvious in the third-tier and fourth-tier cities compared with first-tier and second-tier cities. Our findings indicate that the mechanism of rising housing prices on the emerging Internet credit market exists, which provides references and supplements for relevant departments to formulate policies on housing price regulation and Internet financial supervision policies.

Based on the database of Fintech research center, National Institute of Financial Research, Tsinghua University and other statistical P2P data, this paper focuses on investor's ability to identify risky platforms and normal platforms according to the degree of information disclosure. Constructing the logit model and the Cox proportional risk regression model to study the Ezubao event in December 2015 and the “explosion” phenomenon after the record postponement in June 2018,this paper examines the relationship between information disclosure, risk and trading volume of platforms. It is found that information disclosure is an important factor affecting platforms' risk. The higher degree of platform information disclosure, the longer the operation time is, and the lower the possibility of risk. In addition, the higher the degree of information disclosure, the stronger the ability to resist risks. During the period of risk contagion, the higher the degree of information disclosure, the higher the platform turnover is, and less influenced by the market's negative emotions. These two points indicate that investors attach importance to information disclosed by platforms and have certain ability to identify information. Finally, it is also found that there are significant differences between the risky platforms that appear in the two risky events and those that are still in normal operation, indicating that it is a normal phenomenon of market clearance. There is no evidence that a large number of normal platforms have been dragged into risky platforms.

In accordance with the Real Option Theory, we build a structural model for the study of P2P lending risk events,aiming to find out the mechanism in which P2P lending risk events occur. In the model, we liken the occurrence of a P2P lending risk event to the optimal exercise of a perpetual American put option, and within the framework of Geometric Brownian Motion, we work out the value of the P2P lending platform according to the optimal stopping theory. And then by applying Laplace Transform we work out an explicit solution to the theoretical probability of the occurrence of P2P lending risk events, and we discover that the increases in the P2P borrowers' repaid money, the variations in the P2P borrowers' repaid money, the size of the risk reserves etc. would affect the theoretical probability of the occurrence of P2P lending risk events.And by numerical simulation we find out that the bigger the increases in the P2P borrowers' repaid money, the lower the theoretical probability that P2P lending risk events would occur, the bigger the variations in the P2P borrowers' repaid money, the higher the theoretical probability that P2P lending risk events would occur, and the larger the size of the risk reserves, the lower the theoretical probability that P2P lending risk events would occur.

Based on 388522 loans of Renrendai.com, this paper makes the special dictionary in P2P lending and analyzes how the signaling of words in descriptions affect the behaviors in network lending. The empirical results show the following conclusions. First, the signals of the different kinds of words in descriptive texts provided by P2P borrowers have significant impacts on lenders' decision-making. The proportion of positive words and the proportion of financial words are positively related with the success rate. The proportion of negative words, the proportion of strong modals and the proportion of weak modals are negatively related with the success rate. Second, when the borrowers are of different age levels and income levels, the word signals of their descriptive texts have significantly different influences on lenders' decision-making. And the difference of gender and the different levels of education almost have no effect on the word signals. Finally, the quality signals of different kinds of words are partly effective in the lenders' decision-making. To be specific, the signals of financial words are effective and they are identified correctly by investors. The signals of strong modals are also effective but they are not recognized correctly by lenders. Other categories of words are not effective signals.

Cash loans are controversial because of their high interest rates, unsecured, no-scenario, and totally online. On the one hand, its service objects have certain inclusive characteristics, and some unemployed lending by some practitioners make the industry gradually become the object of strict supervision. In order to measure the impact of the cash loan interest rate on the loaner's loan amount and overdue performance, we use the full loan data of April-August 2017 of a cash loan platform. We perform a regression discontinuity design. We find that as interest rates fall as the level rises, the amount of loans increases and the overdue rate decreases slightly, and this effect varies with loan maturities, interest rates, applicants' financial status, and media sentiment. Combining the research on the payday loan in the United States, we believe that cash loan satisfies the actual and rational needs of some people to a certain extent.

The substitution of electronic money for the existing money has brought appreciably challenges to traditional finance, especially the impact on the money supply. This paper will use the electronic money in the form of third-party payment as the research object, introduce it into the theoretical analysis framework of money supply, and analyze the motivation of micro-subject's cash-holding and the driving factors of electronic money substitution by establishing the game model of consumers and merchants. This paper analyzed the impact of electronic money on the money supply, and the SVAR model is constructed for empirical testing. The results show that the cash leakage rate and electronic money usage are endogenous variables that affect the broad money multiplier. The substitution of electronic money for traditional currency will increase the broad money multiplier in the short run, but will suppress the money multiplier to further expand in the middle and later stages. On the whole, the contribution of the two endogenous factors to the broad money multiplier impact feedback is stable at 1.18% and 4.92% in the medium and long term.

Based on China Household Finance Survey data in 2013, by choosing Instrumental Variable and using Maximum Likelihood estimation, this paper finds financial availability can significantly improve households' credit demand and reduce the probability of households' credit constraints. Further, this paper finds financial availability can significantly reduce the probability of households' demand credit constraints and supply credit constraints. In addition, this paper finds, under the condition of the formal financial unavailability, internet finance can significantly promote households' credit demand and can significantly reduce the probability of households' credit constraints. The policy implication is that improving financial availability and popularizing internet finance can release households' credit demand, alleviate households' credit constraints and improve the level of household consuption.