An Analysis of the Impact of the Digital Economy on High-Quality Economic Development in China—A Study Based on the Effects of Supply and Demand

Abstract

The development of information technology draws forth the digital economy, representing the third form of economic and social development following the agricultural and industrial economies. It represents one of the new era’s most important economic growth points. How to use the advantages of the digital economy to escape the “Malthusian trap” has always been an essential part of the attention of economists and policymakers. This paper investigates the degree of development of China’s digital economy and employs the entropy method and fixed-effect model to test how the digital economy has impacted high-quality economic development. Based on the study, digital economy development significantly promotes high-quality economic development. After controlling various factors that influence high-quality economic development and using instrumental variables to correct endogenous estimation biases, the results remain stable. The analysis also finds that the digital economy in economically backward areas has a more significant impact on high-quality economic development. In addition, the analysis of Nax’s “Vicious Circle of Poverty” theory shows that the digital economy can promote high-quality economic development through the supply and demand effect. Therefore, it is imperative to actively promote digital economy development and form a dynamic balance between supply and demand at a higher level by stimulating the consumption potential to ensure high-quality economic growth.

1. Introduction

The key to sustainable economic development lies in the increased production factor input and enhanced production efficiency. Neoclassical and new economic growth theories hold that scientific and technological innovation and revolution can improve production efficiency and promote social progress and economic development in situations where there are limited production factors [1,2,3,4]. In the agricultural economy, despite economic prosperity and the rapid development of science and technology, human beings suffered poverty. In this regard, Malthus conducted research and found that the factors of production are based on arithmetical growth. However, the population is experiencing exponential growth, so there will be resource shortages, famine, war, and long-term economic downturn. This phenomenon is often referred to as the Malthusian trap [5]. The vicious circle of the “Malthusian trap” continued until the industrial revolution. With the help of the technological revolution and technological innovation, world economic development could avoid the “Malthusian trap” [6,7,8,9].

However, with the emergence of the global financial crisis and other crises, various countries’ economic development continues to be weak [10]. For example, COVID-19 has intensified trade protectionism among countries, impacted the global supply chain, and increased the uncertainty of economic development [11,12,13]. Russia–Ukraine, Afghanistan–Taliban and many other wars have resulted in an extreme shortage of energy resources in various countries, and the actual needs of economic development have thus been met with difficulty [14,15]. Extreme weather has caused resource and energy shortages, severely restricted the sustainable economic growth of the affected countries, disrupted the global industrial chain, and inflicted heavy losses on the global economy [16]. This kind of crisis not only severely restricts the sustainable development of economies and causes the sustained downturn of world economic development but also leads all countries to fall into the “Malthusian trap” again [17,18]. According to existing studies on the “Malthusian trap”, the methods to break it and achieve economic development under the conditions of limited survival materials mainly focus on three aspects: to increase the factor input, to control population and reduce the fertility rate, and to improve production efficiency through technological progress [19,20,21,22]. However, at the present stage, under the complex and volatile international economic situation, the economic impact on developing countries is far more significant than that on developed countries [23]. Moreover, by increasing factor input and controlling the population size, the methods for fostering economic growth and the method of breaking the “Malthusian trap” fails [24]. In this regard, many economists and policymakers are focusing on how to achieve technological innovation, ensure high-quality, sustainable development, and break away from the “Malthusian trap” [25,26,27].

The digital economy is regarded as the engine of technological progress [28]. Its development can integrate digital technology into traditional industries, break the predicament of economic downturn through technological innovation and industrial transformation, form new economic growth points, and promote high-quality economic development [29]. Therefore, scholars have conducted in-depth research in this area. Some researchers believe that the digital economy contributes to the transformation of the industrial structure to a higher level and improves total factor productivity by optimizing resource allocation with the purpose of achieving superior economic development [30,31,32,33]. However, other academics have stated that the digital economy is an emerging industry that requires high initial capital investment. As infrastructure construction has been mostly completed in economically developed areas, the speed at which the digital economy is developing is relatively fast, but this also increases regional economic disparities and aggravates the unbalanced development of the economy [34,35]. Due to the development of the digital economy, the traditional mode of production has been transformed, resulting in the flow of capital and labor from economically underdeveloped regions to developed regions in order to earn a higher return on investment. Thus, economically developed areas possess considerable production factors, such as capital and labor, which increase the power of monopolies, exacerbate labor exploitation by capitalists, intensify social contradictions, and hinder high-quality economic development [36,37]. The question of whether the digital economy can be an essential tool for breaking the “Malthusian trap” and achieving high-quality economic progress must thus be further investigated. There are still disagreements in the research on the connection between the digital economy and high-quality economic development, with most research concentrating on the supply side, including industrial structure, factor allocation, and production efficiency [29,30,31,32,33,34,35,36,37], while ignoring the demand side, for instance, purchase desire and effective demand. Based on Nax’s “Vicious Circle of Poverty” theory [38], we conduct research on the aspects of supply and demand to explore whether the digital economy can break the “Malthusian trap” and achieve high-quality economic development.

Since 2012, the Chinese government has focused on the growth of the digital economy, with the Digital Economy Development and Cooperation Initiative launched at the 2016 G20 Summit. China has significantly advanced the growth of the digital economy. Statistics show that, between 2017 and 2021, China’s digital economy presented an increase from USD 3.76 trillion to USD 6.3 trillion, and the average annual growth rate reached 13.6%, ranking among the top nations globally [39]. In addition to having the world’s largest digital market, China has, at present, the world’s largest and most technologically advanced network infrastructure and a full-fledged e-commerce platform [40,41]. Thus, it can be seen that China, as the world’s most populous nation and the biggest developing nation, when facing the problem of the “Malthusian trap”, not only has the opportunity and conditions to take the digital economy as a technological revolution, but also can promote the transformation of production relations through the digital revolution, adjust the structure of supply and demand, and provide momentum for high-quality economic development. So, investigating the connection between the digital economy and high-quality economic development in different regions, this article uses the level of development of the Chinese digital economy as an example.

The essay is structured as follows: First, the article analyzes the supply and demand implications of the digital economy as well as the influence of the digital economy on high-quality economic development. To a certain degree, the article enriches the existing research paths on the digital economy and expands the research on the theory of the “Vicious Circle of Poverty”. Second, the research has certain policy significance. The achievement of a high-quality development of China’s economy has been severely hampered by the mismatch between supply and demand or the imbalance of economic development. Existing studies are usually based on the supply side of the digital economy, ignoring the significance of the demand effect of the digital economy through stimulating consumption to achieve high-quality economic development. Therefore, this article enriches the research direction of the digital economy and provides support for relevant policy formulation. At the same time, the article provides a foundation for the digital transformation and growth of conventional industries in economically underdeveloped areas and demonstrates the influence of the development of the digital economy on economically backward places to some extent. Third, this paper chose China as an example to study the development degree of the digital economy to understand the level of high-quality economic development, which not only offers ideas for developing countries to break the “Malthusian trap” but also provides theoretical support for the global reshaping of factor resources, the restructuring of economies, and the narrowing of differences in economic development between countries.

2. Analysis of the Mechanism

The digital economy is closely related to high-quality economic development. The essence of so-called high-quality economic development relates to being development-oriented in terms of quality and efficiency; it is a higher-level economic development model with low input, consumption, and pollution and high efficiency and profits and continuous provision of quality goods and services to the community as well as improvement of residents’ living standards [42]. There are two important components of economic development that are pervasive throughout the entire process of economic activity: supply and demand. Classical economics believes that supply creates demand [43]. In contrast, as a matter of Keynesian economic theory, demand drives supply [44], and effectively handling the dynamic supply–demand relationship is the primary task to realize high-quality economic development. According to studies into the “Malthusian trap”, Nax analyzed the two aspects of supply and demand and proposed the vicious circle theory. Nax believed that poverty, in economically underdeveloped areas, was a causal cycle [38], and the key to forming a higher level of economic development model was to find a way out of the vicious circle [45].

Digital economy is an emerging economic model that relies on the application of a digital network [46]. As the direction of the new generation of technological innovation, unlike the traditional economy, it can connect supply and demand based on the characteristics of wide coverage, high innovation, and strong penetration, balance the relationship between the two, and ensure the smooth progress of social reproduction [47]. Different from the study of Nax, it is believed that, to break this vicious cycle, increasing large-scale savings or expanding the scale of investment is required [38]. Instead, the Malthusian trap can be broken by increasing productivity and purchasing power through the development of the digital economy. For the supply side, the digital economy can increase production efficiency by enhancing the quality of the supply chain, increasing supply effectiveness, and halting the cycle of poverty. Demand-wise, the development of the digital economy can increase purchasing power by stimulating purchasing desire and increasing total social demand (Figure 1). Thus, the digital economy can break the vicious circle and form a steady state at a higher level in the form of supply pulling demand and demand pushing supply. This will not only lead to the economy developing in a high-quality fashion, but will also break through the Malthusian trap. In this regard, the two dimensions of the influence of supply and demand on the digital economy are addressed for high-quality economic development.

2.1. Research on the Impact of the Digital Economy’s Supply on High-Quality Economic Development

The supply effect regarding the digital economy relates to achieving the increase in total supply by improving the labor enthusiasm of producers and the investment enthusiasm of enterprises using digital economy development. First, the development of a high-quality economy is made possible by the digital economy, which also helps to improve the quality of the supply system. Unlike the economic stagnation and inflation discussed by the Western school, the Chinese school primarily faces a decline in the quality of economic development and structural imbalances caused by market distortions and resource misallocations [48]. Digital platforms can be constructed and widely applied as the digital economy develops rapidly, which allows its wide coverage to be fully realized, fragmented element resources to be effectively integrated, social resources to be intelligently matched, and resource allocation distortions to be alleviated. Additionally, it can help producers and consumers to connect efficiently to achieve disintermediation transactions and establish a new supply and demand relationship. This will not only help to improve the supply system’s quality, but also optimize the economic structure, improve production efficiency, and achieve high-quality economic development [49,50].

Second, the development of the digital economy can potentially improve supply efficiency and achieve high-quality economic development. According to the theory of economic growth, sustainable growth depends on the increase in factor inputs and the improvement in the efficiency of the use of factors. To begin with, digital technology can permeate the whole process of social reproduction, which enhances the supply efficiency of productive activities by transforming scientific and technological achievements into productive forces with new technologies and transforming and upgrading industrial structures [51]. Through the advantages of digitalization and intelligence, the production efficiency and decision-making efficiency of enterprises can be improved, integrating the existing resources to match market development trends and comprehensively improving the internal resource utilization efficiency. In addition, the digital economy can be readily integrated into production and daily life, and supply efficiency can be improved by coordinating it with other factors of production [52]. It is conducive to the cross-regional flow of production factors from low-yield areas to high-yield areas relying on the digital economy‘s development, which facilitates the cultivation of high-quality technical talents, increases productivity, and improves capital utilization, returns on investment, and supply efficiency [53]. Achieving high-quality economic development can be accomplished through the improvement of supply efficiency by efficiently allocating resources, enhancing supply quality, and increasing production efficiency [54].

Third, the digital economy can optimize supply and increase profits to achieve high-quality economic development. By reducing transaction costs, releasing economies of scale, and promoting technological innovation, the digital economy can increase average profits and reconstruct the relationship between supply and demand in economic activities. The widespread use of digital technology can effectively reduce the search cost before signing the contract, the verification cost in the initial stage of cooperation, the information cost in the transaction process, and the supervision cost after signing the contract [55,56]. In addition to reducing transaction costs, the digital economy also eliminates the supply–demand mismatch at the level of productivity. Additionally, the digital economy exhibits a strong externality, whereas the industrial economy does not and can bring about economies of scale. Traditional enterprises have the characteristic of long-term costs that first fall and then rise, limiting the production expansion of enterprises to some degree. In contrast, in the digital economy, constraints can be broken and the business model changed. Enterprises can stimulate consumption by expanding production scale and lowering sales prices, increasing profits with small profits but quick turnover [57,58]. Last, digital economy development promotes digital technology to extend to the traditional industrial chain and value chain, improving the capability of the supply side to innovate. As a supply side enterprise, it can utilize the strong agglomeration power of the digital economy to break geographical boundaries, rely on the network platform to obtain information, upgrade the industrial chain with new technologies to produce new products, and expand markets using new technologies [59]. As well as saving time, opportunity costs and overall costs, it improves supply efficiency and encourages renewal and iteration. In addition to stimulating new energy, creating new supply, and leading to high-quality economic development, it achieves innovation in production, supply, and sales. The development of the digital economy can optimize supply and increase profits for enterprises by saving production costs and increasing product output. It not only promotes the renewal and iteration of enterprises, but also stimulates new growth drivers and creates new supply, thus becoming a catalyst for high-quality economic development.

2.2. Research on the Impact of the Digital Economy’s Demand on High-Quality Economic Development

The effects of demand on the digital economy relate to the fact that its development can promote product upgrades to meet the needs of more consumers and then achieve an increase in total social demand. The increase in total social demand can be attributed to two main factors: enterprises and consumers. The increase in aggregate social demand mostly manifests itself in two aspects: enterprises and consumers. First, the development of the digital economy can stimulate an increase in corporate demand and then achieve high-quality economic development. The theory of information asymmetry states that in a market system, the amount of information means different risks and benefits are associated with it [60]. In economic activities, in contrast to the disadvantageous position of government departments and enterprises due to a lack of information, enterprises not only face the risk of investment failure caused by misjudging market prospects, but also encounter problems such as overcapacity, oversupply, and slow sales, which hinder the expansion of enterprise scale. However, the digital economy develops accompanied by strengthened communication mechanisms between the government and businesses, promoting the openness and transparency of information and reducing risk costs caused by information asymmetry [61]. Achieving the openness of government affairs and reducing administrative interference and corruption in the private sector improve the market mechanism, and competition becomes fairer; this results in competition for the private sector. A reduction in enterprise risk, financing and transaction costs result in increased profit margins; new enterprises seek profits to enter the market, or the original industry continuously adjusts production scales to achieve a new equilibrium that maximizes profits, thus increasing consumer demand for enterprises [62]. Therefore, the development of the digital economy stimulates enterprise vitality, increases the number of enterprises, expands employment channels, stimulates demand, contributes to smoothing social reproduction, and accelerates the economic cycle to facilitate high-quality economic development.

Second, developing the digital economy helps promote consumers’ desire to buy and thus achieve high-quality economic development. Peter Schumpeter’s theory of innovation purports that creative destruction drives economic growth [63]. As the digital economy grows, the innovation rate improves, and technological innovation is no longer limited to changing a single technology but instead is focused satisfying consumers’ desire to increase consumption by improving the essential value, functional value, and spiritual value of products [64]. Additionally, the digital economy improves channel efficiency through the Internet, e-commerce sales, etc., changing the traditional consumption mode. Consumption choices can be made according to real demand, and market supply can be determined according to consumer demand [65,66]. Lastly, the digital economy facilitates the development of new products through technological advancements, which assists consumers in transforming their consumption from basic to functional or spiritual. Based on Marx’s theory of consumption, new demands drive changes in production and management, and when consumers’ needs are constantly upgraded, enterprises respond quickly and upgrade their products and services in order to capture the market, providing consumers with customized products, promoting production through consumption, reforming the supply from the demand, achieving a dynamic balance between supply and demand, and achieving high-quality economic growth.

3. Model Settings and Sample Selection

3.1. Selection of Core Indicators

3.1.1. Interpreted Variables

Traditional economic development features an economic growth rate and scale, typically measured by the GDP, the GDP per capita, and the growth rate. However, high-quality economic development should be considered more comprehensively, and the measurement process should also consider the quality and efficiency of development. Connotation traits, measures, influencing factors, pathways, and internal mechanisms are the current areas of study for high-quality development. [67,68,69]. In view of the fact that scholars have different views on high-quality economic development, the index system is constructed differently, so the outcomes are likewise different. Innovation, coordination, openness, green values, and sharing are the five development concepts proposed by China based on high-quality economic development and the development direction of China’s economy. We thus constructed indicators from these five dimensions and using sources like Shifu, Zhang Yunping, and Ren Baoping for reference in the selection and building of high-quality economic development [70,71,72]; see

Table 1. Level of high-quality economic development index.

Systems	Subsystems	Specific Indicators	Direction	Reference
The level of high-quality economic development	Innovation	Share of R & D funds in GDP	+	[71]
		Number of authorized patent applications	+	[71]
		Technology market turnover	+	[71]
	Coordination	Urbanization rate	+	[71]
		Urban–rural consumption level ratio	−	[71]
		Urban–rural income level ratio	−	[71]
		Advanced industrial structure	+	[31]
		Deviation degree of the industrial structure	−	[73]
		Gini coefficient between urban and rural areas	−	[74]
		Consumer price index	−	[72]
		Degree of aging	−	[72]
		Capacity for population growth	+	[75]
	Green	Wastewater discharge volume per unit of GDP	−	[71]
		Sulfur dioxide emissions per unit of GDP	−	[71]
		Industrial solid waste discharge per unit of GDP	−	[71]
		Percentage of forest cover	+	[71]
	Openness	Growth rate in fixed-asset investment	+	[76]
		Proportion of tertiary industry investment	+	[76]
		Share of total imports and exports in GDP	+	[71]
		Share of total foreign direct investment in GDP	+	[71]
	Sharing	Enrollment number of institutions of higher learning	+	[71]
		Number of community health service centers	+	[71]
		Employment rate	+	[77]
		Social security and employment expenditure	+	[71]
		Divorce rate	−	[72]
		Green coverage rate of the built-up areas	+	[71]

Note: All populations refer to the Chinese people.

.

3.1.2. Core Explanatory Variables: The Development Degree of the Digital Economy

The China National Bureau of Statistics noted in the Statistical Classification of Core Industries of Digital Economy in China (2021) that the digital economy should be divided into two categories, digitalization and digital industrialization, in order to gradually harmonize the measurement standards of the development level of the digital economy in China [78]. The mainstream institutions studying the domestic digital economy are CAICT, Tencent Research Institute, and CCID Consulting. Despite these agencies’ efforts to offer pertinent digital economy metrics, the data sources are unstable and difficult to acquire. Therefore, the research in the article draws upon the research methods of relevant scholars [71,79,80], such as from the China Academy of Communications, to construct an evaluation system to achieve digital economy development, which is portrayed from the perspectives of digital industrialization and industrial digitalization. The construction of digital industrialization focuses primarily on three aspects: infrastructure construction, communication service innovation potential in the digital industry, and training capability for digital talent. The construction of industrial digitalization is mainly measured according to the digital development of the three industries. In

Table 2. Development degree of the digital economy index.

Systems	Subsystems	Hierarchies	Specific Indicators	Direction	Reference
The degree of development of the digital economy	Digital industrialization	Infrastructure construction, communication capacity, and service level	Mobile phone penetration rate	+	[71]
			Long-distance optical cable line length	+
			Fixed phone users	+
			Mobile phone users	+
			Total postal and telecommunications business	+
			Total telecom business	+
		Innovation potential of the digital industry	High and new tech enterprises	+
			Number of new and high technology practitioners	+
			Main business income of high and new technology enterprises	+
			Total profits of new and high technology enterprises	+
		Digital talent, training ability	R & D personnel full-time equivalent	+
			R & D funds and internal expenses	+
			Number of degrees awarded by colleges and universities	+
	Industrial digitization	Digital level of the primary industry	Rural electricity consumption	+
			Total output value of agriculture, forestry, animal husbandry, and by-fishery	+
		Digital level of the secondary industry	Return rate of industrial enterprises above designated size	+
			Expenditure on the technology funds of industrial enterprises above designated size	+
			Expenditure for technical transformation	+
		Digital level of the tertiary industry	Express business volume	+
			Total retail sales of social consumer goods	+
			Public finance, culture, sports, and media expenditure	+
			Software business revenue	+

Note: All populations refer to the Chinese people.

, specific indicators are listed.

3.2. Evaluation Methodology

There are subjective and objective evaluation methods in the comprehensive evaluation process. An objective weighting method is used to build indicators in order to prevent the intrusion of human variables. In our study, the entropy method serves for determining the weight of the correlation index using information entropy [81,82,83]. The specific evaluation model is as follows.

First, the data were standardized. Upon constructing the high-quality economic development level and the degree index system of digital economy development, the magnitude and units of relevant indicators were not unified, and the order of magnitude difference was quite large. Therefore, in this regard, we standardized the primary data and used the standardized data for comprehensive analysis.

$$\mathrm{Positive} \mathrm{indicator}:Va{r}_{it}^{\prime }=\frac{va{r}_{it}-va{r}_{min}}{va{r}_{max}-va{r}_{min}}$$

(1)

$$\mathrm{Negative} \mathrm{indicator}:Va{r}_{it}^{\prime }=\frac{va{r}_{max}-va{r}_{it}}{va{r}_{max}-va{r}_{min}}$$

(2)

Equation (1) is mainly used to measure positive indicators. The larger the value, the greater the likelihood that high-quality economic or digital economy development will occur. Equation (2) mainly measures negative indicators, and a smaller value indicates better results. For the data of indicator i after standardization in year t, var_it is the raw data, var_min is the minimum value, and var_max is the maximum value of the selected relevant indicators. m is the number of years evaluated, and n denotes the number of indicators.

$$\mathrm{Determine} \mathrm{indicator} \mathrm{weights}:y_{it}=\frac{va{r}_{it}^{\prime }}{{\displaystyle \sum _{t=1}^{m}va{r}_{it}^{\prime }}}$$

(3)

$$\mathrm{Calculate} \mathrm{the} \mathrm{entropy} \mathrm{value} \mathrm{of} \mathrm{the} \mathrm{index} i: e_i=-k{\displaystyle \sum _{t=1}^m(y_{it}\times \ln y_{it})}$$

(4)

$$\mathrm{The} \mathrm{information} \mathrm{utility} \mathrm{value} \mathrm{of} \mathrm{the} \mathrm{indicator} i:d_i=1-e_i$$

(5)

$$\mathrm{The} \mathrm{weight} \mathrm{of} \mathrm{each} \mathrm{indicator}:w_i=\frac{d_i}{{\displaystyle \sum _{t=1}^n{d}_t}}$$

(6)

$$\mathrm{Calculate} \mathrm{the} \mathrm{composite} \mathrm{score} \mathrm{of} \mathrm{the} \mathrm{indicator}:inde{x}_t={\displaystyle \sum _t(w_t\times {\mathrm{var}}_{it}^{\prime })}$$

(7)

For construction of the rationality of the index system, the calculated data were compared with the data published in the White Paper on China’s Digital Economy [84] and the Comparison Report on the Evaluation of the Comprehensive Economic and Social Development (Autonomous Regions and Municipalities) during the “Thirteenth Five-Year Plan” Period [85]. It was found that the results are similar, which to a certain extent proves that the constructed index system was rational and reliable.

3.3. Analysis of Evaluation Results

In terms of the whole country, China’s economy is shifting toward high-quality development through high-speed growth due to differences in historical development, initial economic foundation, cultural environment, and industrial structure between regions. In the development process, there is a lag in the transformation of construction strategies in some areas. Based on constructing an evaluation system, we carried out a dynamic spatial description of the high-quality economic development of China from 2014 to 2019. The high-quality economic development level is relatively high in the eastern coastal areas of the country, but relatively weak in the central, western, and northeastern areas (Figure 2). From 2014 to 2019, as the Chinese region with the quickest economic development, Guangdong Province in the east had some advantages in its economic base. Its score also grew the fastest, reaching 15%. Anhui Province in the central region had a score of high-quality economic development that increased by as high as 15.5%. The scores of Ningxia and Xinjiang Autonomous Region in the western area were not high in terms of high-quality economic development, but their overall growth rate was relatively high at around 24%; Sichuan and Guizhou also increased by approximately 22%. As a region that mainly whose main industries are agriculture and heavy industry, Heilongjiang Province’s score for high-quality economic development increased by 13.1%, ahead of Jilin Province and Liaoning Province.

During continuous development, China’s digital economy presents unbalanced development because of the differences between different regions in the original industrial structure as well as the economic development level. To further reflect the unbalanced changes in the digital economy development among areas, the digital economy development level among regions was investigated by constructing a relevant index representing the digital economy development level from 2014 to 2019. The digital economy development in China has significant spatial structural characteristics (Figure 3). In the southeastern coastal areas of the country, the digital economy presents a relatively prominent development level, showing a trend of agglomeration. In 2014 and 2019, the digital economy development of Guangdong and Shanghai in the eastern region was in a leading position. Except for Guangdong, a robust economic province, the national ultimate growth rate of digital economic development was 45.8%, led by the western region. The digital economy in Sichuan, Yunnan, and Guizhou provinces presents relatively high growth rates, i.e., 42.8%, 42.6%, and 33.1%, respectively. Since Huawei, Alibaba, Tencent, and other companies have set up data centers in Guizhou Province, Guizhou’s digital economy has flourished and has propelled the development of the surrounding provinces. However, the digital economy has developed relatively slowly in Northeast China, often having even negative growth.

3.4. The Setting of the Model and Data Sources

3.4.1. Setting of Model

We constructed a panel data using the data collected from the digital economy development degree and the high-quality economic development level of 30 provinces, municipalities, and autonomous regions between 2014 and 2019. The research sample of this paper does not include Taiwan, Hong Kong, and Macau Special Region. In addition, due to the lack of relevant data on the Tibet Autonomous Region, this paper mainly analyzes the remaining 30 provinces. The empirical model is as follows:

$$index\_dev{e}_{it}=\alpha +\beta digita{l}_{it}+\gamma X_{it}+{\delta }_i+{\mu }_t+{\epsilon }_{it}$$

(8)

where index_deve_it refers to the high-quality economic development level of region i in the year t, digital_it refers to the digital economy development degree of region i in the year t, X_it is a set of control variables associated with the development of the digital economy, such as fiscal size (fiscal revenue and expenditure as a proportion of regional GDP), the marketization level (marketization index), education investment (education expenditure as a proportion of GDP), and economic growth rate.

Table 3. The descriptive statistics of variables.

Variable Name	Mean	Std.Dev	Min	Max
Level of high-quality economic development (HQED)	180	0.458	0.063	0.332
2014	30	0.440	0.066	0.332
2019	30	0.470	0.623	0.376
Development degree of the digital economy (digital)	180	0.230	0.147	0.045
2014	30	0.211	0.129	0.053
2019	30	0.257	0.170	0.045
GDP per capita (lnpergdp)	180	10.872	0.416	10.135
Fiscal size (fiscal)	180	36.988	11.262	19.224
Level of marketization (market)	180	5.868	1.284	2.312
Education investment (education)	180	5.461	1.719	2.866
Economic growth rate (growth)	180	7.259	1.674	0.500

lists the specific indicators. The variables α, δ_i, μ_t, and ε_it are intercept terms, time, region fixed effects, and random perturbation terms, respectively.

3.4.2. Data Sources and Descriptive Statistics

To ensure the objectivity, rigor, and authenticity of the data selected for this research, the data sources were the China Statistical Yearbook published by the China National Bureau of Statistics, China Statistical Yearbook by Provinces, China Statistical Yearbook of Science and Technology, China Marketization Index Report by Provinces published by the Beijing National Economic Research Institute, and the EPS data service platform built by the BFIT Company. Basic statistical information on the main variables used in the regression model is provided in Table 3.

4. Analysis of Empirical Results

4.1. Result of Baseline Regression

Table 4. Benchmark regression results of digital economy affecting high-quality economic development.

Variables	HQED (1)	HQED (2)	HQED (3)	HQED (4)	Lnpergdp (5)
Digital	0.325 ***	0.245 ***	0.169 ***	0.186 ***	0.366 **
	(14.768)	(6.987)	(8.026)	(4.655)	(2.344)
Fiscal			0.001 *	−0.001 ***	−0.008 ***
	data		(1.661)	(−3.448)	(−8.322)
Market			0.026 ***	0.002	−0.009
			(8.084)	(0.525)	(−1.132)
Education			−0.004	0.008 ***	−0.031 **
			(−1.083)	(2.882)	(−2.277)
Growth			−0.001	0.003 ***	0.006 *
			(−0.662)	(3.524)	(1.965)
Constant	0.384 ***	0.495 ***	0.267 ***	0.483 ***	11.965 ***
	(62.143)	(36.685)	(8.567)	(18.249)	(125.243)
Time/Regional effect	NO	YES	NO	YES	YES
Observed	180	180	180	180	180
R-squared	0.569	0.981	0.704	0.984	0.997

Note: Robustness standard error is included in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. “YES” indicates that the variable is controlled in the model; the same applies to tables below. Model (1), (4), and (5): The estimation method is the two-sided fixed effect model of the panel data.

presents the regression results of panel data from 30 provinces between 2014 and 2019. When mixed regression and bilateral fixed effects were adopted without adding control variables, models (1) and (2) showed regression results for the relationship between the degree of digital economy development and high-quality economic development. The model results show a strong correlation between the degree of digital economy development and high-quality economic development. According to model (1), the level of high-quality economic development increases by approximately 0.3 units for every unit increase in the degree of digital economy development. However, the mixed regression results used in model (1) may be affected by the heterogeneity of the observed individuals, temporal trends, and missing variables; so, we analyzed the data using a bilateral fixed model. Model (2) demonstrates that the level of high-quality economic development increases by about 0.25 for every unit increase in digital economic development. As a result of adding the control variables of fiscal scale, marketization index, educational investment, economic growth, and high-quality economic development to models (3) and (4), the regression results indicate an obvious positive correlation between the digital economy development level with the high-quality economic development level. Using bilateral fixed-effects estimation, model (4) estimates that each unit increase in the growth of the digital economy results in an increase of high-quality economic development of roughly 0.19. We used GDP per capital as an alternative variable to the economic development level in model (5), which showed a significant positive correlation.

4.2. Robustness Testing

4.2.1. Endogeneity Testing

We found, from comparing models (2) and (4) in Table 4, that even with adding the control variables, the regression estimation results indicate the ability of the digital economy to enhance the level of high-quality economic development, but the regression coefficient is quite different. Despite choosing the bilateral fixed-effects model for estimation, the coefficient of model (4) was lower than that of model (2) by about 0.06, which indicates that we can minimize the estimation bias resulting from the missing variables that do not change over time. However, there may still be other missing variables that produce endogenous estimation bias because they are difficult to observe, adversely affecting the study of the digital economy and high-quality economic development.

Essentially, the digital economy is an extension of information technology, meaning that its development is a consequence of the growth of the information industry and the widespread application need for technology [86]. The term “informatization” refers to the productivity achieved through communications, networks, and databases. Post and telecommunications development in China during the Republic of China period was slow and limited by technological constraints from developed countries. Therefore, in 1978, the usage rate of fixed telephones in China did not exceed 0.5%, far below the world average. Slow information technology growth has long been a barrier to China’s economic and social progress. Since its reform and opening-up policies, the Chinese government has provided substantial assistance for developing information technology, particularly in the telecom infrastructure and communications field [87]. Therefore, informatization development in areas with high telephone diffusion rates has a long history and a high degree of acceptance of new technological advancements, indicating a better prospect for digital economy development. Accordingly, this satisfies, to some extent, the premise of the assumption that the number of telephones as an instrumental variable is correlated with the degree of digital economic development. Furthermore, in 1990, the Shanghai Stock Exchange was established and adopted electronic trading, which marked the beginning of Chinese financial informationalization as well as the integration and development of information technology across various industries. In this case, the number of telephone subscribers in 1990 was used as the instrumental variable. However, the estimation method in this paper was a bilateral fixed-effects model; if the instrumental variable chosen was the telephone users’ number in 1990, this part of the data is no more than the cross-sectional data without a time dimension, and the instrumental variable method would fail. For this issue to be fixed, we drew on the research methods of Nunn and other scholars [88,89]. We selected the interaction terms of the number of telephone calls per million people in each province in 1990 and the number of Internet users in the country in the previous year as the instrumental variables for the degree of digital economic development. Last, as intelligent communication methods have gradually gained popularity, traditional telephones have slowly withdrawn from history. Their geographical distribution results from a specific historical period, which cannot significantly affect the level of high-quality economic development currently being experienced. Meanwhile, the increased number of nationwide Internet users in the previous year will not significantly change the economic development at the provincial level, which satisfies the assumption of instrumental variable exclusivity.

A two-stage regression analysis by the instrumental variable method can be seen in

Table 5. IV-2SLS regressions of digital economy affecting high-quality economic development.

Variables	First Stage	Two Stage
IV: Number of phones * The number of mobile Internet users of the last year	0.041 ***
	(6.729)
Core explanatory variables: Digital		0.119 *
		(1.905)
Constant	0.298 ***	0.503 ***
	(5.870)	(16.604)
F test	1187.59
Control variable/time/regional effect	YES	YES
Observed	180	180
R-squared	0.994	0.983

Note: Robustness standard error is included in parentheses; *** p < 0.01, * p < 0.1. Model estimation method is bilateral fixed effect model for panel data; control variables include fiscal (%), market, education (%), growth (%) (same as for table below).

. According to the first regression stage, the number of telephones remarkably and positively impacts the digital economy development. In 1990, the region with many telephones had better information and digital economy development. The F statistics in the first stage of the regression are 1187.59, greater than 10, proving that weak instrumental variables are not a concern. According to model (2), high-quality economic development increases by about 0.119 for every unit increase in the digital economy. The value in this regression result decreased more obviously relative to Table 4 in model (4), indicating that an endogenous estimation bias is present in the regression results obtained by selecting the OLS without using instrumental variables, and it is effectively corrected when instrumental variables are introduced.

4.2.2. Heterogeneity Testing

In addition to the vastness of China, regional differences, uneven distribution of factor endowments, a wide range of historical development experiences, economic foundation, and human environment differences result in differences among regions; thus, economic development capability shows a “high in the east and low in the west” trend. Consequently, we further explored the regional disparities between the digital economy and high-quality economic development. Unlike previous studies, this study performed regression studies primarily by classifying the eastern, central, western, and northeastern regions, as shown in

Table 6. The influence of digital economy development degree in different regions on high-quality economic development.

Variables	Eastern	Central	Western	Northeastern
Digital	0.167 ***	0.045	0.185 ***	0.449 ***
	(8.838)	(0.793)	(3.766)	(4.219)
Constant	0.253 ***	0.454 ***	0.372 ***	0.338 ***
	(4.918)	(15.350)	(8.743)	(4.774)
Control variable/time effect	YES	YES	YES	YES
Observed	180	180	180	180
R-squared	0.558	0.942	0.683	0.880

Note: Robustness standard error is included in parentheses; *** p < 0.01.

.

Table 6 estimates the effects of high-quality economic development on the digital economy in various regions. Across regions, the impact varies. The digital economy only dramatically affects the center regions’ high-quality economic development. However, in eastern, western, and northeastern regions, it is significantly positive in promoting high-quality economic development, as indicated by the regression coefficients of 0.167, 0.185, and 0.4449, respectively. The western and northeast regions present more obvious digital economy development than the eastern and central regions, with moderate economic development. The reason for the above results may be that digital economy-related infrastructure in the eastern region is relatively complete; there is a foundation for integrating the digital economy into the real economy, and there are fewer hurdles to economic transformation. However, implementing the digital economy in the central regions certainly impacts traditional industry development. A lack of experience at an early stage has led to some enterprises still waiting and watching. Enterprises that have undergone digital transformation are still undergoing a high input of production factors, and it is yet unclear how this will affect high-quality economic development. In the western and northeastern regions, traditional industries have long dominated economic development. As the digital economy provides solutions to traditional problems, it can quickly be incorporated into the economic reform and play an effective role. According to the above analysis, it evident that digital economy development is not only intrinsically linked to high-quality economic development but also gives economically underdeveloped areas a fresh growth orientation.

4.2.3. Mechanism Testing

In the previous part, we examined the relationship between the digital economy and high-quality economic development, finding that the former could remarkably and positively impact the latter. As discussed in the mechanism analysis part, the impact of the digital economy’s supply and demand on the economy creates high-quality growth. In the following section, we examine this.

The digital economy’s supply effect is highly affected: capital and labor significantly affect production; capital flow and employment decisions are more affected by policy orientation, production, and operation directions, future income expectations, and economic development trends. Moreover, digital economy development helps to facilitate the transformation of the labor force from the low end to the high end and promotes the upgrading of economic and social financial agglomerations, which can be taken as capital accumulation and flow [90,91]. The digital economy, as an emerging field, in the process of integrating with the traditional economy, still needs talents who have a solid capability of conducting cross-border integration or research and development (R&D) [92]. Consequently, the financial agglomeration index [93] and R&D personnel are selected as indicators to measure the digital economy’s supply effect. The relationship between the digital economy’s supply effect and high-quality economic development is presented in

Table 7. The impact of the digital economy from the supply side on high-quality economic development.

Variables	Financial Agglomeration	HQED	R&D Personnel	HQED
Digital	10.380 ***		0.042 *
	(11.839)		(1.749)
Financial agglomeration		0.011 ***
		(5.711)
R&D personnel				0.307 ***
				(4.796)
Constant	−1.420 **	0.422 ***	0.073 **	0.400 ***
	(−2.160)	(15.783)	(2.048)	(14.189)
Control variable/time/regional effect	YES	YES	YES	YES
Observed	180	180	180	180
R-squared	0.558	0.942	0.683	0.880

Note: Robustness standard error is included in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1.

. Models (1) and (3) indicate that the development of the digital economy remarkably and positively impacts financial agglomeration and the number of R&D personnel, with regression coefficients of 10.38 and 0.042, respectively. Research indicates that digital economy development can facilitate the flow of capital into financial agglomerations, meanwhile promoting traditional talents to transform into high-end talents. The financial agglomeration index, the situation of R&D personnel, and the level of high-quality economic development are regressed in models (2) and (4). The results indicate that the financial agglomeration index and the situation of the R&D personnel have a considerable and positive impact on the high-quality economic development level. Hence, it can effectively promote industry transformation and development, stimulate enterprise innovation, and achieve high-quality economic development by addressing the two important production factors: capital and labor.

The second aspect is its demand effects. The digital economy’s development can increase an enterprise’s vitality as well as expand its production scale, and it also has a positive effect on the registration of new enterprises [94]. Enterprises are one of the pillars of national economic development, and their continuous expansion can ensure long-term economic growth and promote high-quality growth. Based on the previous provincial panel data, we conducted a regression analysis to assess how the digital economy impacts the number of corporate legal entities under different ownership. In

Table 8. The impact of digital economy from the demand side on high-quality economic development.

PanelA:
Variables	State-Owned Enterprises Holding Legal Entities	Collective Enterprise Holding Legal Entities	Private Holding Enterprise Legal Entities	Foreign-Invested Enterprises Legal Entities
Digital	0.882 **	1.143 ***	0.716	1.233 **
	(2.396)	(3.559)	(0.699)	(2.321)
Constant	9.680 ***	9.975 ***	12.732 ***	8.700 ***
	(23.422)	(25.899)	(20.944)	(13.796)
Control variable/time/ regional effect	YES	YES	YES	YES
R-squared	0.988	0.991	0.985	0.995
Panel B:
Variables	Deve	Deve	Deve	Deve
State-owned enterprises holding legal entities	0.026 **
	(2.162)
Collective enterprise holding legal entities		0.019 *
		(1.833)
Private holding enterprise legal entities			0.017 **
			(2.103)
Foreign-invested enterprises legal entities				0.012 *
				(1.823)
Constant	0.267 **	0.329 ***	0.306 ***	0.417 ***
	(2.103)	(2.897)	(2.659)	(6.116)
Control variable/time/regional effect	YES	YES	YES	YES
R-squared	0.982	0.982	0.982	0.981

Note: Robustness standard error is included in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. The number of legal entities of state-owned enterprises, collective enterprises, private enterprises, and foreign-invested enterprises are estimated in the form of log values. Source: National Bureau of Statistics in China.

, Panel A’s regression findings demonstrate that, as the development level of the digital economy rises, the number of legal personnel of state-owned enterprises, collective enterprises, and foreign-invested enterprises increases significantly, with regression coefficients of 0.882, 1.143, and 1.233, respectively. In spite of this, the development of the digital economy has not remarkably affected the development of privately held businesses. As a result of technological progress, enterprises are transformed and upgraded, which is a process of continuously eliminating and recreating. Privately held businesses are more closely linked to market demand, with faster liquidity and changing rates.

Consequently, the digital economy accelerates the rate of elimination and regeneration of enterprises, so its impact is not significant in the short term. Panel B regresses the number of legal persons of different types and the level of high-quality economic development. Hence, an apparent positive correlation can be found between the number of legal persons of various types and the level of high-quality economic development. Furthermore, the digital economy can increase consumer demand, expand enterprises, and promote sustainable development. Enterprises can provide better services during upgrading [95], promoting high-quality economic development.

5. Conclusions and Suggestions

Based on China’s provincial panel data from 2014 to 2019, we analyzed the data using the fixed-effect model, and the conclusions reached support the research conclusions of Huang Qunhui et al. [30,31,32,33], suggesting that the degree of digital economy plays a positive role in promoting high-quality economic development. In addition, this research also accomplished the following: First, from a theoretical perspective, it deepened research into Nax’s “Vicious Circle of Poverty” theory. Digital economy can improve production efficiency by improving the quality of the supply system, improving supply efficiency, increasing supply profit, and breaking the “Vicious Circle of Poverty” in terms of supply. The digital economy can also improve the purchasing power by increasing the purchasing desires and the aggregate demand of the society, breaking the “Vicious Circle of Poverty” in terms of demand. The digital economy can break through the “Malthusian trap” through supply driving demand and demand driving supply, and can provide a theoretical perspective for the subsequent research on the “Vicious Circle of Poverty” theory of Nax. Second, viewed through the lens of internal mechanism, the digital economy mainly promotes high-quality economic development through its supply and demand effect. From the standpoint of supply effect, the development of the digital economy can stimulate the concentration of capital and the increase in R&D personnel to increase the supply system’s quality, efficiency, and profitability, thus promoting high-quality economic development. From the standpoint of the demand effect, the digital economy can encourage consumer demand to raise overall social demand to encourage the growth of businesses and scale to achieve a level of high-quality economic development. Third, based on the heterogeneity analysis of different geographical locations, it was found that the western and northeastern regions, which are economically underdeveloped regions, have greater potential for high-quality economic development, which provides theoretical support for narrowing the wealth gap between countries and reconstructing the economic structure.

The paper offers some suggestions as follows.

It is crucial to promote the development of the economy and utilize its long-term advantages for high-quality economic development. To enable the economy to achieve high-quality development, new digital infrastructure must be built faster in underdeveloped areas. Furthermore, this accelerates the expansion of new space in the digital economy field. To date, digital products and demand supported by 4G technology are moving closer to being full, and a new wave of economic activity requires new technologies to be the driving force. As the generation of 5G technology develops, the digital economy will become the foundation for future industrial Internet development. This will lead to “industry + 5G”. Last, it is crucial to encourage the digital economy’s integration with the physical economy and create new economic development domains and models.

In addition, regionally speaking, the development of the digital economy has a more significant impact on economically underdeveloped areas. Because the digital economy developed late in these regions, the policy should consider the local economic development level, the ecological environment, and the human environment when providing policy direction and technical assistance. To achieve this, it is essential to deepen the development of the digital economy in economically underdeveloped areas and promote the development of digital industrialization by improving the construction of digital economy infrastructure. The focus should be on industrial digitalization development, blurring the boundaries of industrial development, and encouraging the digitization and transformation of traditional industries. For example, from the perspective of agriculture, we should employ digital technology to raise the added value of farm products and enhance the storage and logistics to expand the marketing scope. In industry, we should increase the supply and use of digital equipment, accelerating the research and development of industrial applications to promote the transformation of industrial manufacturing to intelligent manufacturing. In tertiary industries, we should utilize the benefits of the digital economy to their fullest and efficiently integrate and optimize information and data to build and improve a new service industry model.

Finally, with the development of the digital economy as the focal point, it is possible to make the most of the supply and demand consequences of the digital economy. In one way, the digital economy’s development facilitates the adaptation and flexibility of supply structures to changes in demand. There are still deficiencies in market mechanisms that should be made up by high-quality economic development and stimulate innovation through the digital economy. In order to achieve this, government departments should continue to develop strategic measures and promotion mechanisms that encourage digital economy development, stimulate the enthusiasm of enterprises by providing policy, provide financial and technical support to expand the space for digital economy development, continuously optimize the business environment, provide convenience for the flow of talent and labor, and coordinate the development of the digital economy. In another way, the legal system, policies, and regulations need to be improved because the digital economy is a new field. Since it is difficult for government departments to monitor this area, enterprises that invest in technological innovation and industrial development should take on specific social responsibilities. It is the responsibility of leading enterprises to expand production scale and comprehensive development while encouraging small and medium-sized enterprises to overcome technical barriers and create an ecological environment where the entire industry and industrial cluster can collaborate to achieve sustainable economic growth and high-quality development.