|
|
|
| The Effect of Mobile Payments on Household Money Demand: Micro Evidence from the China Household Finance Survey |
| YIN Zhichao, GONG Xue, PAN Beixiao
|
| School of Finance, Capital University of Economics and Business |
|
|
|
Abstract Alibaba reported that on May 4, 2018, there were 870 million global active users of its Alipay application. During the 2018 Spring Festival, the number of WeChat monthly active accounts exceeded one billion. With the development of modern mobile technology and the popularization of mobile devices, mobile payments have rapidly replaced internet payments and become the backbone of third-party transactions. In China, electronic payments have brought great changes to people’s lives, especially mobile payment tools, such as Alipay and WeChat payment. These new payment tools, which combine liquidity and profitability, have caused a shock to the traditional payment methods. Moreover, the financial management tools provided by these applications have given households more money management options, and to some extent have replaced savings deposit. Thus, evidence of the impact of mobile payments on China’s household money demand can provide a theoretical and practical basis for formulating China’s cash management policy.
This paper is divided into seven parts. The first part introduces the research background and the related literature. The second part outlines the theoretical framework of money demand, and the third part introduces the empirical model, data, and variables. In the fourth and fifth parts, we report the empirical results and analyze the heterogeneity, respectively. The sixth part provides the robustness tests and the seventh part concludes the paper.
In this paper, we use the data from the fourth round of the nationwide China Household Finance Survey (CHFS) conducted by Southwestern University of Finance and Economics in 2017 to examine the impact of mobile payments on monetary demand at the household level based on the Baumol-Tobin model. To overcome the endogeneity of mobile payments, we use two stage least squares (2SLS) to do the estimation.
We find that mobile payments lead to a 25% decrease in household cash and have a significant negative impact on the level of money demand. Specifically, the proportion of M1 decreases by 36.1% and the proportion of M2 decreases by 21.7%, indicating that mobile payments reduce the money demand to different degrees. We also find that the coefficient of the cross-terms between the transaction cost proxy variables and mobile payments is significantly negative, indicating that changes in transaction costs may be an important channel for mobile payments to affect the demand for cash. Furthermore, using a quantile regression, we find that the effect of mobile payments on the precautionary money demand is greater than that of transactions.
The impact of mobile payments on the money demand also varies significantly for different age levels, education levels, urban and rural areas, Eastern and Western regions, and different cities. Specifically, mobile payments have a greater negative impact on the proportions of M0 and M1 among elderly households. For households with a lower education level, mobile payments have a relatively large negative impact on M0 and M1, but a relatively small negative impact on M2. We also find that the level of urban development has a significant effect on the role of mobile payments.
Finally, we analyze the effects of debit card, credit card, bank card, and computer payments on the proportion of cash, and the estimated coefficients are all significantly negative. This shows that the change in the method of payment has had a profound impact on the amounts of cash that households hold.
Although mobile payments are very convenient, the web-based and immaterial characteristics of the system pose numerous possible risks in terms of security. To encourage the use of mobile payments, it is necessary to strengthen the supervision of risk during use, formulate laws and regulations to regulate the behavior of both sides of the transaction, and strengthen the security of the platform using fintech, so that mobile payments can play a key role in cash management.
Overall, this paper makes the following contributions. First, from a micro perspective, we study the impact of mobile payments on monetary demand at the household level. Second, we define the M0, M1, M2 of a household according to the monetary level standards set by the People’s Bank of China. Third, we analyze the influence of transaction costs on the demand for cash and confirm the findings of the Baumol-Tobin model.
|
|
Received: 19 July 2018
Published: 24 October 2019
|
|
|
|
|
| [1] |
陈莹和李淑锦,2017,《第三方互联网支付对预防性货币需求影响的实证研究》,《金融与经济》第3期,第46~53页。
|
| [2] |
樊玉红,2010,《银行卡对货币流通速度的影响》,《生产力研究》第5期,第95~96页。
|
| [3] |
王山,2017,《电子支付工具对现金需求影响的实证研究》,《金融经济》第4期,第147~148页。
|
| [4] |
王信和郭冬生,2017,《瑞典无现金社会建设启示》,《中国金融》第18期,第79~81页。
|
| [5] |
吴雨、彭嫦燕和尹志超,2016,《金融知识、财富积累和家庭资产结构》,《当代经济科学》第4期,第19~29页。
|
| [6] |
巫云仙和杨洁萌,2016,《中国货币流通中现金(M0)变化的经济学分析——基于互联网金融发展的背景》,《改革与战略》第5期,第77~81页。
|
| [7] |
谢平和刘海二,2013,《ICT、移动支付与电子货币》,《金融研究》第10期,第1~14页。
|
| [8] |
尹志超、宋全云和吴雨,2014,《金融知识、投资经验与家庭资产选择》,《经济研究》第4期,第 62~75页。
|
| [9] |
尹志超、宋全云、吴雨和彭嫦燕,2015,《金融知识、创业决策和创业动机》,《管理世界》第1期,第87~98页。
|
| [10] |
约翰·梅纳德·凯恩斯,1983,就业利息和货币通论. 商务印书馆。
|
| [11] |
周光友,2006,《电子货币发展对货币流通速度的影响——基于协整的实证研究》,《经济学(季刊)》第3 期5卷,第1219~1234页。
|
| [12] |
周光友,2009,《电子货币的替代效应与货币供给的相关性研究》,《数量经济技术经济研究》第3期,第129~138页。
|
| [13] |
周光友,2010,《电子货币对货币流动性影响的实证研究》,《财贸经济》第7期,第13~18页。
|
| [14] |
周光友和施怡波,2015,《互联网金融发展、电子货币替代与预防性货币需求》,《金融研究》第5期,第67~82页。
|
| [15] |
周袁民,2017,《第三方支付对金融消费者的持币影响和冲击》,《区域金融研究》第10期,第55~60页。
|
| [16] |
Bagnall, J., D. Bounie, K. P. Huynh.A.kosse,T.Schmidt,S.Schun and H.Stix, 2014. “Consumer Cash Usage: A Cross-Country Comparison with Payment Diary Survey Data,” DNB Working Papers, 12(4), pp. 1~61.
|
| [17] |
Baumol, W. J., 1952. “The Transactions Demand for Cash: An Inventory Theoretic Approach,” Quarterly Journal of Economics, 66(4), pp. 545~556.
|
| [18] |
Boeschoten, W. C., 1998. “Cash Management, Payment Patterns and the Demand for Money,” De Economist, 146(1), pp. 117~142.
|
| [19] |
Fujiki, H. and E. Shioji, 2006. “Bank Health Concerns, Low Interest Rates and Money Demand: Evidence from the public Opinion Survey on Household Financial Assets and Liabilities,” Monetary and Economic Studies, 11, pp. 73~123.
|
| [20] |
Fujiki, H. and M. Tanaka, 2009. “Currency Demand, New Technology and the Adoption of Electronic Money: Evidence Using Individual Household Data,” Imes Discussion Paper.
|
| [21] |
Heijden, H. V. D., 2002. “Factors Affecting the Successful Introduction of Mobile Payment Systems,”BLED 2002 proceedings ,2002:20.
|
| [22] |
Humphrey, D. B., 2004. “Replacement of Cash by Cards in US Consumer Payments,” Journal of Economics & Business, 56(3), pp.211~225.
|
| [23] |
Duca, J.V. and W.C. Whitesell, 1995. “Credit Cards and Money Demand: a Cross-sectional Study, ” Journal of Money Credit & Banking, 27(2), pp.604~623.
|
| [24] |
Kalckreuth, U. V., T. Schmidt and H. Stix, 2014. “Choosing and Using Payment Instruments: Evidence from German Microdata,” Empirical Economics, 46(3), pp. 1019~1055.
|
| [25] |
Lippi, F. and A. Secchi, 2009. “Technological Change and the Households’ Demand for Currency,” Journal of Monetary Economics, 56(2), pp. 222~230.
|
| [26] |
Priyatama, A. and A. Apriansah, 2010. “Correlation between Electronic Money and the Velocity of Money,” Global Management Conference.
|
| [27] |
Snellman, H. and M. Viren, 2009. “ATM Networks and Cash Usage, ” Applied Financial Economics, 19(10), pp.841~851.
|
| [28] |
Stock, J. H. and M. Yogo, 2005. “Testing for Weak Instruments in Linear IV Regression, ” Nber Technical Working Papers, 14(1), pp.80~108.
|
| [29] |
Tobin, J., 1956. “The Interest-elasticity of Transactions Demand for Cash,” Review of Economics & Statistics, 38(3), pp. 241~247.
|
|
|
|
