Digital Paradox: Platform Economy and High-Quality Economic Development—New Evidence from Provincial Panel Data in China

Abstract

Based on provincial panel data of China from 2011 to 2019, this paper discusses the influence and mechanism of the platform economy on the high-quality development of regional economies. It is found that the platform economy has an inverted U-shaped impact on the high-quality development of regional economies. On the left side of the inverted U-shaped inflection point, the platform economy plays a significant role in promoting high-quality economic development; on the right side of the inflection point, the platform economy has an obvious inhibitory effect on high-quality economic development. Statistical analysis showed that 85% of the observations fell on the left side of the inflection point, indicating that China’s platform economy as a whole is in the early stages of development. From the strong and weak grouping test of the degree of government intervention, it was found that the platform economy only has an inverted U-shaped effect on the high-quality development of the areas with weak intervention. From the point of view of the coefficient, the platform economy has a greater promoting effect on the high-quality development of the areas with strong intervention. From the grouping test of the quality of the market system, it was found that the inverted U-shaped curve is steeper in the areas with higher institutional quality, indicating that, in the early stage of development, the platform economy has a greater promoting effect on the high-quality development of areas with perfect institutions. In addition, the analysis of regional heterogeneity showed that, in the early stage of development, the promoting effect of the platform economy on the high-quality development of the northeastern and western regions is more significant. After exceeding the threshold, the platform economy has an inhibitory effect on the high-quality development of all regions. The mechanism test shows that technology, talent, and capital in the initial stage of development can all play a positive regulatory role; after exceeding the threshold, platform economic monopoly may restrain high-quality economic development by hindering technological progress and causing a mismatch of labor–capital elements and resources.

The Impact of the Digital Economy on Low-Carbon, Inclusive Growth: Promoting or Restraining

“…In other words, the initial stage of the development of the digital economy helps to promote the development of regional low-carbon transformation; when the level of the digital economy is too high, it may restrain regional low-carbon, inclusive growth. This conclusion is consistent with existing research conclusions [51]. According to the calculation, the threshold of the digital economy is 0.3081.…”

“…On the other hand, the digital economy has a negative impact on carbon emission reduction. Some scholars have found that some digital platforms use digital technology to form monopolies, which are not conducive to the sustainable development of the regional economy [50][51][52][53][54]. Therefore, digital technology may lead to market monopolies and market failure, hindering the free flow of resources, which is not conducive to green technology innovation and industrial upgrading.…”

“…As the measurement method of the regional digital economy is relatively perfect, we refer to the practice of Guoge Yang [51,71]. The comprehensive index system of the digital economy is constructed from four aspects: digital infrastructure, digital resources, digital application, and digital finance.…”

“…(1) Tool variable (instru). Based on endogenous consideration and the work of Yang Guoge [51] and others, the digital circuits in the history of each province are used as tool variables and multiplied by the number of Internet users in the previous year to construct panel tool variable data as tool variables of the regional digital economic index for regression. (2) Missing variables.…”

“…Considering the endogenous problems caused by the omitted variables and two-way causality, we use tool variable development to deal with them. Drawing lessons from the work of Guoge Yang and others, the digital circuit in the history of each province is used as a tool variable and estimated with the two-stage least square method (2SLS) [51,76]. Based on the consideration of robustness, generalized method of moments estimation (GMM) is used to test endogenesis.…”