|
|
|
| How Does the Digital Economy Influence China's Inflation? Empirical Tests on the Influence Mechanism and Dynamic Characteristics |
| LIU Jun, TANG Jianwei, ZHOU Bian, E Yongjian, WANG Yunliang
|
| Bank of Communications |
|
|
|
Abstract The digital economy has brought extensive and profound changes to social and economic activities, which in turn have important and far-reaching effects on macroeconomic operations. A global low inflation occurred almost at the same time as the emergence of the digital economy. In recent years, the international literature on the impact of the digital economy on inflation has gradually increased, but unfortunately there is a dearth of relevant domestic literature. Studying how the digital economy affects China's inflation is of great practical significance for judging the long-term trend of China's inflation and improving macro-adjustment policies. Based on the literature, this paper explores the mechanism through which the digital economy affects China's inflation and analyzes the short-term dynamic characteristics of China's inflation against the background of the digital economy. Compared with the literature, the main contributions of this paper are as follows. First, Chinese data are used to empirically test the relationship between the digital economy and inflation, enriching the relevant empirical literature. Second, this paper empirically tests the channels and verifies the mechanism through which the digital economy affects China's inflation. Third, this paper analyzes the characteristics of the short-term dynamic response of inflation to monetary policy shocks under the digital economy, and provides a reference for improving macro-policy adjustments.
Based on the theoretical framework of Riksbank (2015) and the actual situation of China's digital economy, this paper summarizes and determines that the digital economy suppresses inflation through three channels: the low price growth of digital products and services, improved productivity, and e-commerce platform competition. The fixed-effect panel model is used for empirical testing. This paper uses the CPI and PPI growth rates released by the National Bureau of Statistics to measure inflation, and uses the annual digitalization degree index in the Peking University Digital Financial Inclusion Index as the proxy variable of the digital economy. The change rate of the Zhongguancun electronic product price index, the change rate of total factor productivity in each province, and the proportion of e-commerce enterprises in each province are used as the proxy variables of digital product price, productivity, and e-commerce platform competition, respectively. The empirical results show that the inhibitory effect of the digital economy on inflation and its three influence channels are basically confirmed in China. Among them, the digital product channel mainly acts on the annual growth rate of the PPI, the e-commerce platform channel mainly acts on the annual growth rate of the CPI, and the productivity channel has an effect on the annual growth rate of both the CPI and PPI.
To explore the short-term dynamic characteristics of inflation in the context of the digital economy, this paper takes the CPI released by the National Bureau of Statistics as the offline price index, the consumer price index based on online data constructed by Liu Taoxiong et al. (2019) as the online price index (iCPI), and the weighted average of the CPI and iCPI to construct a comprehensive price index (JCPI) based on the proportion of online retail sales to the total retail sales of consumer goods. The VEC model is used to simulate the response of the CPI, iCPI, and JCPI to monetary policy shocks. It is found that the iCPI has the shortest response time to interest rate shocks, the CPI has the longest response time, and the JCPI is in between. The iCPI has the greatest response to money supply and interest rate shocks, followed by the JCPI, and finally, the CPI. As a result, the expansion of online sales has increased the sensitivity of overall inflation to monetary policy. However, due to the sample size, this conclusion needs to be viewed with caution.
The conclusions of this paper have three policy implications. First, in view of the significantly different operating characteristics of online and offline prices, the need to construct a broader range of price indices that cover the characteristics of the digital economy is increasing, and it is necessary to improve the statistical accounting of China's price indices as soon as possible. Second, monetary policy needs to pay attention to the new characteristics of and changes in inflation in the era of the digital economy. As the scale of online sales is continuing to expand, the overall price is more sensitive to monetary policy shocks, and the timing and rhythm of policy operations may need to be adjusted accordingly. Third, in the face of the current global threat of high inflation, the digital economy, as one of the few important long-term factors with an inflation-suppressing effect, continues to accelerate innovation through digital technology itself, and applies it more vigorously and on a larger scale.
|
|
Received: 24 February 2022
Published: 01 April 2023
|
|
|
|
|
| [1] |
巴曙松、黄文礼和杨可桢,2018,《数字经济:方兴未艾,未来可期》,《现代商业银行》第21期,第34～37页。
|
| [2] |
傅秋子和黄益平,2018,《数字金融对农村金融需求的异质性影响——来自中国家庭金融调查与北京大学数字普惠金融指数的证据》,《金融研究》第11期,第68～84页。
|
| [3] |
郭峰、王靖一、王芳、孔涛、张勋和程志云,2020,《测度中国数字普惠金融发展:指数编制与空间特征》,《经济学(季刊)》第4期,第1401～1418页。
|
| [4] |
郭吉涛和梁爽,2021,《数字经济对中国全要素生产率的影响机理:提升效应还是抑制效果?》,《南方经济》第10期,第9~27页。
|
| [5] |
姜婷凤、汤珂和刘涛雄,2022,《基于在线大数据的通货膨胀“现时”预测》,《计量经济学报》第3期,第597～619页。
|
| [6] |
荆文君和孙宝文,2019,《数字经济促进经济高质量发展:一个理论分析框架》,《经济学家》第2期,第66～73页。
|
| [7] |
刘涛雄、汤珂、姜婷凤和仉力,2019,《一种基于在线大数据的高频CPI指数的设计及应用》,《数量经济技术经济研究》第9期,第81～101页。
|
| [8] |
龙少波和陈璋,2013,《引进式技术进步下的中国工业生产率与通货膨胀率关系研究》,《经济与管理研究》第7期,第13～22页。
|
| [9] |
卢盼盼和张长全,2013,《金融脱媒对商业银行稳健性影响的实证研究》,《上海金融》第1期,第29～33页。
|
| [10] |
田涛,2016,《电商发展对 CPI 的影响研究——基于大数据背景下线上线下价格波动的同步性分析》,《上海经济研究,》第3期,第112～119页。
|
| [11] |
万晓榆和罗焱卿,2022,《数字经济发展水平测度及其对全要素生产率的影响效应》,《改革》第1期,第101～118页。
|
| [12] |
许小年,2020,《商业的本质和互联网》,机械工业出版社2020年1月第一版。
|
| [13] |
张成思,2012,《通货膨胀、经济增长与货币供应:回归货币主义?》,《世界经济》第8期,第3～21页。
|
| [14] |
张勋、万广华、张佳佳和何宗樾,2019,《数字经济、普惠金融与包容性增长》,《经济研究》第8期,第71～86页。
|
| [15] |
张延群,2021,《基于在线大数据的 iCPI 与 CPI 关系的研究》,《调研世界》第10期,第71～80页。
|
| [16] |
周小川,2020,《拓展通货膨胀的概念与度量》,《中国金融》第24期,第9～12页。
|
| [17] |
Abdirahman, M., D. Coyle, R. Heys, and W. Stewart, 2017, “A Comparison of Approaches to Deflating Telecoms Services Output”, Economic Statistics Centre of Excellence (ESCoE) Discussion Paper, 4(12): 5～23.
|
| [18] |
Battese, G.E. and T. J Coelli, 1995, “A Model for Technical Inefficiency Effects in A Stochastic Frontier Production Function for Panel Data”, Empirical Economics, 20(2): 325～332.
|
| [19] |
Blanchard, O., 2009, “The State of Macro”, Annual Review of Economics, 1(1): 209～228.
|
| [20] |
Buchheim, V. and M. Kedert, 2016, “ Digitisations Effects on The Inflation Rate-An Empirical Analysis of Possible Digitisation Channels” Master of Science Thesis INDEK, No. 27.
|
| [21] |
Byrne, D. and C. Corrado, 2017, “Accounting for Innovation in Consumer Digital Services: Implications for Economic Growth and Consumer Welfare”, International Monetary Fund Statistics Forum.
|
| [22] |
Cavallo, A., 2018, “More Amazon Effects:Online Competition and Pricing Behaviors”, NBER Working Paper, No. 25138.
|
| [23] |
Charbonneau, K., A. Evans, S.Sarker, and L. Suchanek, 2017, “Digitalization and Inflation: A Review of the Literature”, Bank of Canada Working Paper.
|
| [24] |
Csonto, B., Y. Huang, and C.E. Tovar, 2019, “Is Digitalization Driving Domestic Inflation”, International Monetary Fund Working Paper, No. 271.
|
| [25] |
Engle, R.F. and C.W.J. Granger, 1987, “Co-Integration and Error Correction: Representation, Estimation, and Testing”, Econometrica, 55(2): 251～276.
|
| [26] |
Goolsbee, A. and P. J. Klenow, 2018, “Internet Rising, Prices Falling: Measuring Inflation in a World of E-Commerce”, NBER Working Paper, No. 24649.
|
| [27] |
Koyuncu, J Y. and M. Unver, 2018, “The Impact of Internet on Inflation in OECD Countries”, Cataloging-In-Publication Data,10: 261～265.
|
| [28] |
Lorenzani, D. and J. Varga, 2014, “The Economic Impact of Digital Structural Reforms”, European Commission Economic Papers, No. 529.
|
| [29] |
Riksbank, 2015, “ Digitisation and Inflation. Monetary Policy Report” , Riksbank, February.
|
| [30] |
Wadhwani, S., 2000, “The Impact of the Internet on UK Inflation” ,Bank of England Quarterly Bulletin,40(2):184～231.
|
|
|
|
