A Study on the Impact of Digital Financial Literacy on Household Entrepreneurship—Evidence from China

Abstract

With the rapid development of digital finance, digital financial literacy is becoming increasingly important. This study examines the impact of digital financial literacy on household entrepreneurship and finds that it significantly promotes the occurrence of household entrepreneurship. To address potential endogeneity concerns, the study employs an instrumental variable approach, and the results remain robust after a series of checks. Heterogeneity tests reveal that the effect of digital financial literacy on household entrepreneurship is particularly pronounced in rural areas, underdeveloped regions, and lower-tier cities. Further analysis indicates that digital financial literacy also enhances household entrepreneurial investment levels, with a more significant impact on survival entrepreneurship investments. In mechanism tests, the study shows that access to formal finance partially mediates the relationship between digital financial literacy and household entrepreneurship. Additionally, our research also found that digital financial literacy can promote entrepreneurship among marginalized groups, such as women and individuals with lower levels of education. Our findings offer valuable insights for policymakers aiming to foster sustainable and inclusive development. In line with the United Nations’ 2030 Agenda for Sustainable Development, entrepreneurship is recognized as a key driver for achieving sustainable economic growth. Our study emphasizes the importance of promoting entrepreneurship by enhancing digital financial literacy among residents in underdeveloped areas, which is crucial for fostering inclusive growth, creating jobs, and reducing regional disparities, all of which contribute to long-term sustainable development.

1. Introduction

In 2020, the seventy-fifth session of the United Nations General Assembly emphasized the important role of entrepreneurship in sustainable development. Entrepreneurship contributes to job creation, promotes inclusive economic growth and innovation, and improves social conditions to address economic and relief issues within the context of the 2030 Agenda for Sustainable Development [1]. In previous studies, entrepreneurship is of significant importance in stimulating market vitality, optimizing industrial structures, and facilitating economic transformation [2]. Many countries consider encouraging entrepreneurship as an important way to solve unemployment issues [3], create job opportunities, and reduce poverty [4], as well as promoting regional economic development. Additionally, entrepreneurship is also believed to promote social sustainable development by addressing social issues, such as educational inequality and the uneven distribution of medical resources [5]. Entrepreneurial behavior is influenced by many factors, and the issue of insufficient funds is one of the important factors that constrain entrepreneurial behavior [6]. The ability to access financial services is an important factor in solving funding issues, and thus promoting entrepreneurial behavior and improving entrepreneurial performance [7,8]. Obtaining financial support is a key element for entrepreneurs to break through financial constraints and succeed in their ventures [9]. Bianchi [10] found that the level of financial development has a positive effect on the number of entrepreneurs. Furthermore, the development of information technology and the use of internet technology are also considered important drivers of entrepreneurship. Janson and Wrycza [11], using data from Poland, found that information technology promotes entrepreneurial activity, and the development of information technology not only promotes the occurrence of entrepreneurial activities but also has a positive effect on the successful operation of businesses. Ying Tan [12] found that internet usage has a significant and positive impact on entrepreneurship. In recent years, the rapid development of digital technology and its combination with financial services has led to a surge in complex and new financial instruments, including digital wallets and cryptocurrencies [13]. With the rapid development of digital finance, the popularity of digital payments, mobile banking, and credit cards is increasing, and more and more new types of financial services can only be obtained through digital channels [14]. The current financial technology environment requires financial consumers to have sufficient knowledge and ability to use digital financial services.

In past research, financial literacy has been considered a key factor in accessing financial services and promoting the occurrence of entrepreneurship [15]. With the development of financial technology, financial literacy needs to be redefined [16]. In the current environment where financial technology and digital technology are rapidly becoming widespread, financial consumers require sufficient knowledge and capabilities to obtain digital financial services [17]. The concept of digital financial literacy represents an upgrade of financial literacy in the digital age; digital financial literacy is a key factor in efficiently accessing financial services in the digital era [18]. Improvements in digital financial literacy help households and individuals more quickly and easily obtain the latest financial products and services in a digital environment. The proliferation of digital finance has brought more financing sources to entrepreneurial groups [19]. Potential entrepreneurs with higher digital financial literacy imply stronger abilities to use digital finance, fewer financial constraints, and easier access to financial support, and financial support has a promoting effect on entrepreneurial decisions [20]. This leads to the main question of this study: Does digital financial literacy have a promoting effect on household entrepreneurship? Based on this, what is the mechanism by which digital financial literacy promotes the occurrence of household entrepreneurship? How does digital financial literacy affect household entrepreneurial investment? Furthermore, what is the heterogeneity between urban and rural households in terms of entrepreneurial decisions and investment due to digital financial literacy? What is the heterogeneity between households in different regions in terms of entrepreneurial decisions and investment due to digital financial literacy? What is the heterogeneity in the impact of digital financial literacy on entrepreneurial decisions and investment among households in cities of different sizes? To address these questions, this study adopts a micro perspective and examines the impact of digital financial literacy on household entrepreneurship and household entrepreneurial investment through theoretical and empirical analysis. Although existing literature has explored the impact of financial literacy or digital financial knowledge on household entrepreneurship, the novel concept of digital financial literacy in the digital age warrants further investigation. However, no study has yet examined the influence of digital financial literacy as a comprehensive indicator on household entrepreneurship. The significance of this research lies in enriching the theoretical framework of digital financial literacy in the digital age while offering a new perspective on achieving sustainable development through the promotion of entrepreneurship. The structure of this paper is as follows: The first part introduces the research background and highlights the value of the study. The second part reviews existing literature on digital finance, digital financial literacy, and entrepreneurship, and proposes hypotheses to provide a foundation for subsequent research. The third part explains the data sources and the construction of variables, followed by a detailed description of the research methodology. The fourth part presents the empirical results, including endogeneity analysis, robustness tests, heterogeneity analysis, and mediation mechanism tests. The fifth part discusses the results, reiterating the significance of this study and its contribution to sustainability. The sixth part provides a summary of the paper and outlines prospects for future research.

2. Literature Review and Hypothesis Proposition

2.1. Research on Digital Finance and Digital Financial Literacy

Financial services provided through mobile phones, computers, and credit cards linked to digital payment systems are known as digital finance. Digital finance is an innovative development of financial services in the digital age, reshaping the banking industry. The rapid development and widespread adoption of digital finance have provided support for achieving financial inclusion [21]. Digital finance can improve the opportunities for a large number of financially excluded populations to access finance, allowing them to obtain formal financial services through digital devices such as mobile phones [22]. The development of digital finance can help more disadvantaged groups, such as rural and impoverished communities, to access financial services [23]. Additionally, the ability to use digital finance at the micro-level individual has a positive effect on financial inclusion [24].

In 2018, the Organisation for Economic Co-operation and Development (OECD) first introduced the concept of digital financial literacy, emphasizing that enhancing the public’s digital financial literacy should become an important task in financial education [25]. Subsequently, Morgan et al. [26] constructed an overall framework for measuring digital financial literacy, proposing four dimensions of digital financial literacy: cognition of digital financial products and services, cognition of digital financial risks, ability to control digital financial risks, and consumer awareness and ability to protect rights. In 2021, the Alliance for Financial Inclusion summarized the development and policy information of digital finance in multiple countries and provided a summary of the definition of digital financial literacy: Digital financial literacy is a multi-dimensional concept that includes financial knowledge as well as financial and digital literacy skills, representing consumers’ knowledge, skills, confidence, and ability to fully, effectively, and safely use digital financial products and services to make optimal economic decisions for maximum benefit [27]. Kass-Hanna et al. [28] consider digital financial literacy as a key factor in financial inclusiveness and security, and have constructed a conceptual framework of digital literacy, financial literacy, and digital financial literacy, measuring it across five dimensions: basic knowledge and skills, awareness, practice, decision-making, and self-protection.

Existing research has found that the improvement of digital literacy and financial literacy is highly correlated with the increase in formal and informal lending and that digital literacy and financial literacy can promote life insurance, health insurance, and emergency risk management behaviors. In heterogeneity tests, scholars believe that the impact of digital literacy and financial literacy is greater in rural areas, the poor, and women compared to urban areas, the wealthy, and men [16]. Setiawan [29] measured digital financial literacy across four dimensions: digital financial knowledge, risk awareness, practical experience with digital finance, and digital financial skills. The study, using Indonesia as an example, found that digital financial literacy positively affects current consumption behavior and future expenditure behavior, as well as influencing future savings and expenditure plans. Rahayu R [30] found that the digital financial literacy of the millennial generation not only influences consumer and savings behavior but also positively affects investment behavior. An individual’s experience, knowledge, and attitude toward digital financial platforms and products can minimize behavioral biases and financial errors, leading to rational, secure, profitable, and informed financial decisions [31]. Digital financial literacy broadens the avenues for credit and savings, providing mainstream financial services to disadvantaged groups and those with less information. Youngjoo Choung [32], in her study using online survey data on the link between digital financial literacy and the financial health of Korean adults, discovered that improved financial knowledge and the ability to prevent digital fraud positively impact financial health.

2.2. Digital Financial Literacy and Household Entrepreneurship

The impact of digital financial literacy on entrepreneurship is primarily reflected in the level of financial knowledge and financial literacy. For instance, Oseifuah et al. [33] found that in their assessment of the financial literacy level of young entrepreneurs in the Vhembe district of Limpopo province, South Africa, the financial literacy level of young entrepreneurs was higher than the average. Entrepreneurs with higher financial literacy and greater use of financial tools have better loan repayment capabilities and a higher likelihood of entrepreneurial survival [34]. Financial knowledge in asset management can optimize entrepreneurial behavior [35]. Financial literacy not only promotes the occurrence of entrepreneurship but also significantly enhances entrepreneurial performance, that is, the higher the financial literacy, the higher the entrepreneurial returns [36].

Another crucial aspect of digital financial literacy is the ability to use digital financial products and services, which is essential for obtaining financial services such as commercial insurance and bank loans. Scholars have examined, from both macro and micro perspectives, that the development of digital finance and residents’ use of digital finance can significantly promote entrepreneurship [37]. Beck et al. [38], in their study focusing on Kenya, discovered that the use of mobile payments can enhance entrepreneurial performance by improving entrepreneurs’ execution capabilities, reducing the probability of encountering information asymmetry and decreasing the likelihood of funds being stolen. Digital financial capabilities are found to be positively correlated with household entrepreneurial decisions [39] and entrepreneurial performance [40].

While previous studies have examined the relationship between financial knowledge or digital financial knowledge and entrepreneurship, this study extends the existing research by constructing a comprehensive indicator of digital financial literacy and analyzing its impact on household entrepreneurship. This holistic approach allows for a more nuanced understanding of how digital financial literacy shapes not only the likelihood of entrepreneurship but also the level of entrepreneurial investment. From previous studies, we can observe that financial literacy and the use of digital financial skills can positively impact household entrepreneurship. Residents with higher levels of digital financial literacy tend to have more comprehensive financial knowledge and more advanced skills in utilizing digital finance. Therefore, we have reason to propose the following hypothesis:

H1. 

The improvement of digital financial literacy can significantly increase the likelihood of household entrepreneurship occurring.

H2. 

Households with higher digital financial literacy have higher levels of entrepreneurial investment.

The connection between H1 and H2 lies in the dual role of digital financial literacy—not only does it facilitate the initiation of entrepreneurial activities (H1), but it also enhances the depth of household commitment and resource allocation to entrepreneurial ventures (H2). The ability to leverage digital financial tools empowers households to scale their businesses, access additional financial resources, and reduce financial risk, ultimately fostering greater entrepreneurial investment.

2.3. The Mediating Mechanism of Digital Financial Literacy on Household Entrepreneurship

Potential entrepreneurs often face the issue of initial funding constraints [41], and a lack of liquidity can restrict entrepreneurial activities [42]. Whether a household can obtain external financial resources is a critical factor in deciding to start a business, with formal and informal finance being the usual channels for securing external funding. However, most small and medium-sized enterprises (SMEs) have limited collateral, lack sufficient operating records, and face severe information asymmetry, making it difficult to obtain support from formal financial institutions. The underdeveloped financial system in China exacerbates these issues, leaving many families constrained by limited access to formal financial services. This financial constraint significantly hinders entrepreneurial activities.

Residents with higher digital financial literacy are more likely to access both formal and informal financial services [16]. Families with higher levels of digital financial literacy tend to possess greater financial knowledge, enabling them to better understand the nature, characteristics, and risks of financial products. This allows them to navigate financial markets more effectively and make informed decisions. The rapid advancement of financial technology and digital platforms enables individuals and families to access banks, insurance companies, and other financial institutions through mobile devices anytime and anywhere. By utilizing these digital tools, individuals can alleviate the information asymmetry that often limits access to financial services.

Moreover, individuals with higher digital financial literacy have enhanced skills in using digital financial products, such as online banking, digital lending, and mobile payment platforms, enabling them to access more convenient and diverse forms of formal finance. This access to formal finance can alleviate liquidity constraints, facilitating entrepreneurship among potential entrepreneurial families.

The role of digital financial literacy in facilitating access to formal financial resources directly supports the progression from H1 and H2 to H3. While H1 posits that digital financial literacy increases the likelihood of household entrepreneurship, and H2 suggests that households with higher digital financial literacy invest more in entrepreneurial ventures, H3 highlights the mechanism through which this occurs—by enhancing access to formal financial services. This progression reflects how improved digital financial literacy not only drives entrepreneurial intent but also mitigates key barriers, such as liquidity constraints, through the facilitation of formal financial resources.

Thus, this study proposes the following hypothesis:

H3. 

Digital financial literacy can promote the occurrence of household entrepreneurship by facilitating the acquisition of formal finance by families.

3. Date and Methodology

3.1. Data Processing

The data for this study come from the China Household Finance Survey (CHFS). In light of the data’s applicability and availability, this paper utilizes the survey data from CHFS 2019. The China Household Finance Survey (CHFS) is a nationwide sampling survey project conducted by the Survey and Research Center for China Household Finance at Southwestern University of Finance and Economics. It aims to collect micro-level information related to household finance, including demographic characteristics and employment, assets and liabilities, income and consumption, social security and insurance, as well as subjective attitudes, providing a comprehensive and detailed portrayal of household economic and financial behavior. The latest publicly available CHFS data from the fifth round of the 2019 survey covers 29 provinces (autonomous regions and municipalities directly under the Central Government), 343 districts and counties, and 1360 village (residential) committees, with a sample size of 34,643 households, making the data representative at both the national and provincial levels.

Since individuals aged 80 and above typically do not engage in entrepreneurship, this study excludes samples from this age group to avoid potential bias in the analysis. This paper excludes samples with severe missing values and samples where the head of household is over 80 years old. Finally, 27,267 samples were left for study.

3.2. Measuring Digital Financial Literacy

The core explanatory variable of this paper is digital financial literacy: based on the availability of data, refer to Prasad et al. [18], Lyons and Kass-Hanna [28], and Setiawan M [29]. This study comprises the following five dimensions to build a comprehensive indicators of digital financial literacy: financial knowledge, financial skills, digital financial skills, digital platform use and risk awareness.

Financial Knowledge: According to the CHFS questionnaire, the setting is based on the calculation of questions about interest rates and inflation. Van Rooij et al. [43] believe that the financial knowledge level of people who choose not to know or refuse to answer is lower than that of people who answer incorrectly. Respondents who directly answered questions about interest rate calculations were assigned a value of “1”, while those who refused to answer were assigned a value of “0”, creating a variable indicating whether the respondent directly addressed interest rate questions. Additionally, a dummy variable was created based on the correctness of the interest rate calculation, with correct answers assigned a value of “1” and incorrect answers assigned a value of “0”. Using the same method, dummy variables were constructed for whether respondents directly addressed inflation calculation questions and whether they correctly answered inflation calculation questions. In total, four dummy variables were developed to measure financial knowledge levels.

Financial Skills: For financial skills, four dummy variables were generated to indicate ownership of financial products, stock accounts, bonds, and financial derivatives. Ownership of financial products was assigned a value of “1”, while non-ownership was assigned a value of “0”, creating a dummy variable for financial product ownership. Similarly, dummy variables were created for stock account ownership, bond ownership, and financial derivative ownership following the same approach.

Digital Financial Skills: Three dummy variables are generated based on digital lending (whether there is online lending in the questionnaire) and digital financial wealth management products (not purchased offline from traditional financial institutions), and the income from digital financial wealth management products is also included in the index.

Digital Platform Usage: Composed of a dummy variable based on the question “whether to use a smartphone”.

Risk Awareness: It is based on whether the answer is positive to the question “Do you have a certain amount of money for what kind of risky investment”. A positive answer is considered to have risk awareness and is assigned a value of “1”, while refusing to answer or not knowing is considered to have no risk awareness and is assigned a value of “0”.

This paper conducted a factor analysis on the aforementioned 14 variables. Before conducting the factor analysis, these 14 variables were first standardized. The KMO value is greater than 0.6, which is suitable for factor analysis. Finally, iterative factor analysis was performed on the fourteen variables, and the comprehensive score of residents’ digital financial literacy was calculated, which serves as an index to measure digital financial literacy, DFL (

Table 1. Construction of digital financial literacy variable.

Variable	Dimensions	Indicators
DFL	Financial Knowledge	Whether to answer questions about calculating inflation
		Whether to correctly answer questions about calculating inflation
		Whether to answer questions about calculating interest rates
		Whether to correctly answer questions about calculating interest rates
	Financial Skills	Whether to have financial wealth management products
		Whether to have a stock account
		Whether to have bonds
		Whether to have financial derivatives
	Digital Financial Usage Skills	Whether to have digital wealth management products (purchased through digital platforms)
		Digital Financial Product Earnings
		Whether to have digital lending
		Whether they have an online payment account
	Digital Financial Usage Skills	Whether to positively answer the choice of investment at what level of risk

).

3.3. Dependent Variable

Entrepreneurship is a new career choice and represents a change and innovation in the original mode of production or management. In this paper, the dependent variable of household entrepreneurship refers to families participating in industrial and commercial production and business projects. It is identified through the questionnaire with the question “Last year, did your household engage in industrial and commercial business projects?” Those who answer “yes” are considered entrepreneurial families, generating a dummy variable “1”; those who answer “no” or refuse to answer are considered non-entrepreneurial families, generating a dummy variable “0”.

Entrepreneurial investment can reflect the household’s input into entrepreneurship, which is also one of the dependent variables studied in this paper. Based on the sample’s response to “How much investment did your household make in the industrial and commercial business projects?”, logarithmic processing is performed as a measure of the household’s entrepreneurial investment.

In addition, according to different entrepreneurial motivations, entrepreneurship can be classified into “passive entrepreneurship”, “active entrepreneurship”, and “value-oriented entrepreneurship”. “Passive entrepreneurship”, also known as subsistence entrepreneurship, refers to entrepreneurship undertaken for survival when no other options are available. “Active entrepreneurship” refers to entrepreneurship chosen to seize business opportunities or pursue higher income; “Value-oriented entrepreneurship” refers to entrepreneurship undertaken to pursue personal social value and contribute to society. Based on the response to “What is the main reason your household engaged in industry and commerce?”, entrepreneurship is classified as follows: those who answer “cannot find other job opportunities” are identified as passive entrepreneurship; those who answer “engaging in industry and commerce can earn more”, “ideal hobbies/want to be boss”, “more flexible and free”, or “inherit the household business” are identified as active entrepreneurship; those who answer “social responsibility, solving social employment” are identified as value-oriented entrepreneurship.

3.4. Control Variables

In this study, control variables are selected from the individual level of the household head, the household level, and the regional macro level. The construction of both household head’s personal control variables and household control variables is based on data from CHFS 2019, while regional control variables are constructed according to statistical yearbooks of various cities in China. Control variables are measured as follows:

Control variables of the Household Head:

Age of the Household Head: Age and the square of age divided by 100.

Gender of the Household Head: Male = 1, Female = 0.

Education Level: Total years of education received.

Party Membership: Member = 1, Non-member = 0.

Marital Status: Married = 1, Not married = 0.

Household Control Variables:

Household Size: Total population of the household.

Household Burden: The proportion of elderly and children in the total household population.

Total Household Income: Logarithm of the total income.

Total Household Assets: Logarithm of the total assets.

Regional Control Variables:

Economic Development Level of the City where the Household Head Resides: Measured by the logarithm of the per capita GDP of the city.

Industrial Structure Level of the City: The sum of the first and second industries’ output as a ratio to the total GDP.

Financial Development Level: The ratio of the year-end balance of deposits and loans to the total GDP.

Government Intervention Level in the City: The ratio of government fiscal expenditure to the total GDP.

By including these control variables, the study aims to account for various factors that could influence the relationship between digital financial literacy and entrepreneurship, ensuring a more nuanced and accurate analysis.

3.5. Methods

The Ordinary Least Squares (OLS) method is simple, easy to use, and computationally efficient, making it suitable for most common regression studies. OLS directly estimates regression coefficients, providing clear model interpretations. Therefore, this paper employs the method of ordinary least squares to investigate the relationship between digital financial literacy and household entrepreneurship and uses instrumental variables to address potential endogeneity issues. Moreover, household entrepreneurial investment is only present for families that participate in entrepreneurship, resulting in a large number of zero values. The Tobit model can effectively handle samples with significant left-censoring data; therefore, this paper utilizes the Tobit model to study the impact of digital financial literacy on household entrepreneurial investment.

4. Results

4.1. Relationship Between DFL and Households’ Choice to Engage in Entrepreneurship

Firstly, this study investigates the impact of digital financial literacy on household entrepreneurial decisions. To ensure the robustness of the regression results, control variables at the individual, household, and regional levels are gradually added to the regression analysis. In

Table 2. The relationship between digital financial literacy and household entrepreneurship.

Variable	(1) ENT	(2) ENT	(3) ENT
DFL	0.0912 ***	0.0500 ***	0.0542 ***
	(0.00571)	(0.00598)	(0.00597)
Age	0.00242 **	0.00774 ***	0.00747 ***
	(0.00117)	(0.00116)	(0.00116)
Age2/100	−0.00129	−0.00479 ***	−0.00469 ***
	(0.00102)	(0.00105)	(0.00105)
The gender of the household head	0.0224 ***	0.0209 ***	0.0168 ***
	(0.00451)	(0.00452)	(0.00452)
Whether they are a member of the Party	−0.0215 ***	−0.0270 ***	−0.0284 ***
	(0.00535)	(0.00526)	(0.00524)
Whether they are married	0.0408 ***	0.00141	0.00001
	(0.00485)	(0.00518)	(0.00517)
The Educational Level of the Household Head	−0.00357 ***	−0.00556 ***	−0.00515 ***
	(0.000577)	(0.000606)	(0.000608)
Household Burden		−0.0319 ***	−0.0297 ***
		(0.00650)	(0.00648)
Household Assets (Logarithm)		0.0342 ***	0.0379 ***
		(0.00126)	(0.00133)
Household Income (Logarithm)		−0.00755 ***	−0.00616 ***
		(0.00191)	(0.00193)
Household Size		0.0210 ***	0.0189 ***
		(0.00162)	(0.00164)
Household Head’s City Per Capita GDP (Logarithm)			−0.0305 ***
			(0.00597)
Industrial Structure			−0.135 ***
			(0.0377)
Level of Financial Development			0.00656 ***
			(0.00112)
Degree of Government Intervention			−0.196 ***
			(0.0298)
Constant	0.278 ***	0.0250	0.481 ***
	(0.0335)	(0.0374)	(0.0684)
N R-square	27,267	27,267	27,267
	0.048	0.080	0.085

** denotes significance at the 5% level, and *** denotes significance at the 1% level.

, The first column includes only individual control variables, the second column adds both individual and household-level control variables, and the third column further includes regional-level control variables. The regression results show that the impact of digital financial literacy on entrepreneurial choice is significant at the 1% level in all three stages, indicating that the likelihood of a household choosing to start a business increases with the improvement of the household head’s digital financial literacy. Thus, hypothesis H1 is verified.

Regarding the control variables, the impact of age and the square of age on entrepreneurship is positive for the former and negative for the latter. The relationship between age and entrepreneurial behavior is inversely U-shaped, meaning that as age increases, the likelihood of a household choosing to start a business first increases and then decreases. Households with a party-member as the head are less likely to choose entrepreneurship, possibly because the strong political identity of party member households restrains their risk preference; households with a male head are more willing to choose entrepreneurship, possibly because males have a more aggressive attitude towards risk.

At the household level, control variables show that there is a positive relationship between the decision to start a business and the size of the household and the level of household assets. The impact of household income and household burden on entrepreneurial decisions is significantly negative, possibly because families with higher incomes lack the motivation to engage in entrepreneurship. Looking at the macro-level influencing factors, the higher the financial development level of the area where the household is located, the greater the likelihood of choosing to start a business, possibly because in areas with higher financial development levels, households’ financing needs for starting businesses are more easily met. In addition, the impact of government intervention on household entrepreneurial decisions is negative.

4.2. Endogeneity Analysis

This paper controls for various factors at different levels that may affect household entrepreneurship as much as possible, but there may still be omitted variables that have not been taken into account, and there may also be issues such as reverse causality. Entrepreneurs may also use financial tools to a greater extent during the entrepreneurial process, thereby improving their computational skills and digital financial knowledge. To alleviate these influences as much as possible, this study categorizes the sample into five age groups: 18–30 years old, 30–40 years old, 40–50 years old, 50–60 years old, and over 60 years old. The average digital financial literacy of households within the same community and age range, excluding the sample itself, is used as an instrumental variable. The average digital financial literacy of other families in the same community has a certain impact on the level of the household head’s digital financial literacy, meeting the relevance requirement, but this average value does not directly affect the entrepreneurial choices of the surveyed households. The Hausman test result rejects the exogeneity of the explanatory variable at the 5% level, thus it is deemed necessary to introduce an instrumental variable. In the weak instrumental variable test, the F-value of 314 is greater than 10, rejecting the hypotheses of a weak instrumental variable. The first and second columns of

Table 3. Instrumental variables estimations.

Variable	(1) First-Stage Regression DFL	(2) Second-Stage Regression ENT
Instrumental variables	0.263 ***
	(0.009)
DFL		0.049 *
		(0.033)
Control variables	Yes	Yes
N	27,267	27,267
R-square	0.376	0.088

* denotes significance at the 10% level, and *** denotes significance at the 1% level.

show the results of the two-stage regression with the instrumental variable. The impact of the instrumental variable on digital financial literacy in the first stage is significantly positive at the 1% level, proving a positive correlation between the two. The results using the instrumental variable shown in the second column indicate that the impact of digital financial literacy on household entrepreneurship remains positively correlated, with the coefficient value decreasing from 5.42% to 4.9%.

To alleviate the issue of sample selection bias, this study uses propensity score matching (PSM) for testing. The entire sample is divided into a treatment group and a control group based on the mean value of digital financial literacy. Those with a score greater than the mean are assigned to the treatment group (coded as “1”), and those with a score less than the mean are assigned to the control group (coded as “0”). Three different matching methods—nearest neighbor matching, radius matching, and kernel matching—are used. The average treatment effect on the treated (ATT) is calculated based on the matched samples, and the results are presented in

Table 4. PSM testing.

Matching Method	ENT
	ATT	t Value	Standard Error
Nearest Neighbor Matching	0.1629 ***	2.32	0.005
Kernel Matching	0.1628 ***	2.29	0.005
Radius Matching	0.1629 ***	3.77	0.006

*** denotes significance at the 1% level.

below. The results from all three matching methods show statistically significant matching. These findings suggest that digital financial literacy significantly increases the likelihood of households choosing entrepreneurship.

4.3. Robustness Test

To further ensure the reliability of the results rather than randomness, this paper employs three methods for robustness checks. First, the model is replaced for testing, changing the original OLS regression to a Probit model, which is still applicable to this study since its dependent variable is a binary variable of 0 and 1. The regression results after replacement are shown in the first column of

Table 5. Robustness test.

Variable	(1) Probit	(2) The Sample After Excluding the Municipalities Directly Under the Central Government	(3) The Sample After Tail Trimming
	ENT	ENT	ENT
DFL	0.0644 ***	0.0521 ***	0.0657 ***
	(0.0267)	(0.00582)	(0.00633)
Control variables	yes	yes	yes
N	27,267	26,131	25,433
R-square		0.085	0.093

*** denotes significance at the 1% level.

. Second, because the economic development level of municipalities directly under the Central Government is relatively high, and there is a significant difference in the level of individual digital financial literacy and the choice of household entrepreneurship, samples from the four municipalities directly under the Central Government, Beijing, Shanghai, Tianjin, and Chongqing are excluded before regression analysis. The third column of Table 5 shows the results after removing the samples of municipalities directly under the Central Government, and it can be seen that after removing these samples, the impact of the household head’s digital financial literacy level on entrepreneurial choice remains significant. Finally, a trimming process of one percent at both the top and bottom is performed on digital financial literacy to avoid the impact of extreme values, as shown in the second column of Table 5, the results remain significant. From the above results, it can be seen that whether it is to delete samples or exclude extreme values, or to change the measurement model, the final regression results are significantly positive; therefore, the basic regression results are relatively robust.

4.4. Heterogeneity Test

Given the significant economic disparities between urban and rural areas in China, there are considerable differences in household economic behaviors among urban and rural residents. The entrepreneurial behaviors of households with rural household registration and those with urban household registration also exhibit certain differences. Therefore, this paper distinguishes between urban and rural household registrations based on the responses to “type of household registration” and “type of household registration before unification” in the questionnaire, and generates dummy variables accordingly. The interaction term between rural household registration and digital financial literacy is added to the regression. The results, as shown in the first column of

Table 6. Heterogeneity test.

Variable	(1) 2SLS ENT	(2) 2SLS ENT	(3) 2SLS ENT
DFL	0.00908 *	0.0470 ***	0.0277 ***
	(0.00688)	(0.00763)	(0.00704)
DFL × Dummy Variable for Rural Household Registration	0.111 ***
	(0.00953)
Dummy Variable for Rural Household Registration	0.0347 ***
	(0.00484)
DFL × Dummy Variable for Central Region		0.0305 **
		(0.0119)
Dummy Variable for Central Region		0.00638
		(0.00558)
DFL × Dummy Variable for Western Region		0.0253 **
		(0.0112)
Dummy Variable for Western Region		−0.00579
		(0.00507)
DFL × Dummy Variable for Northeast Region		0.00300
		(0.0148)
Dummy Variable for Northeast Region		−0.0165 ***
		(0.00616)
DFL × Dummy Variable for Second-tier Cities			0.00519
			(0.0111)
Dummy Variable for Second-tier Cities			−0.00294
			(0.00600)
DFL × Dummy Variable for Tier-3 Cities and Lower			0.0679 ***
			(0.00884)
Dummy Variable for Tier-3 Cities and Lower			−0.0169 ***
			(0.00625)
Controls	Yes	Yes	Yes
Observations	27,267	27,267	27,267
R-squared	0.097	0.089	0.089

* denotes significance at the 10% level, ** denotes significance at the 5% level, and *** denotes significance at the 1% level.

, indicate that the coefficient of the interaction term is in the same direction as digital financial literacy in the baseline regression, with rural household registration playing a positive role in promoting entrepreneurship through digital financial literacy. It can be observed that compared to urban households, the level of digital financial literacy of rural household heads has a greater promoting effect on entrepreneurship. The reason may be that the financial development level and the level of digital infrastructure in rural areas are lower than in urban areas; thus, the impact of the digital financial literacy of the household head on promoting entrepreneurship is more pronounced.

Furthermore, there are significant regional differences in China’s economic development level. Therefore, dummy variables for the eastern, central, western, and northeastern regions are generated based on the household’s location. Interaction terms are created by multiplying the dummy variables for being in the central, western, and northeastern regions with digital financial literacy, and these interaction terms are added to the model for regression. The second column of Table 6 shows that using the eastern region’s household samples as the control group, the enhancing effect of digital financial literacy on the likelihood of choosing entrepreneurship is greater in the central and western regions. However, in the northeastern region, the coefficient of the interaction term is not significant, and the impact effect on household entrepreneurship is significantly negative. The reason may be that the eastern region has a more developed level of economic development, digital technology, and financial development. The central and western regions have a lower degree of digital technology exposure and financial development compared to the eastern region; thus, the level of digital financial literacy of the household head plays a more important role. The northeastern region has always had issues with a single economic structure and a poor business environment, with low private economic activity, which may explain why the northeastern region has an inhibitory effect on household entrepreneurship.

In addition, the macro environment, openness, and business environment of cities of different levels also vary greatly, leading to differences in individual economic behaviors. The third column of Table 6, based on different levels within the same city, with first-tier cities/new first-tier cities as the reference group, adds interaction terms between second-tier cities, third-tier cities, and digital financial literacy. The results show that, compared to first-tier and new first-tier cities, the impact of individual digital financial literacy on household entrepreneurship is greater in third-tier cities. The reason should be similar to the urban–rural heterogeneity and regional heterogeneity; third-tier cities have a lower level of economic development, and their digital infrastructure and financial development levels are not as advanced as those in first-tier cities; thus, the promoting effect brought by an individual’s level of digital financial literacy is greater.

4.5. The Relationship Between Digital Financial Literacy and a Household’s Entrepreneurial Investment

This paper investigates the relationship between digital financial literacy and the level of a household’s entrepreneurial investment. After the inclusion of instrumental variables, the results of the IV-Tobit model are shown in

Table 7. Impact of DFL on a household’s entrepreneurial investment.

Variable	(1) Ent IV-Tobit Entrepreneurial Investment	(2) Subsistence Entrepreneurship Household Samples IV-Tobit Entrepreneurial Investment	(3) Opportunity Entrepreneurship Samples IV-Tobit Entrepreneurial Investment	(4) Value-Driven Entrepreneurship Samples IV-Tobit Entrepreneurial Investment
DFL	1.141 ***	0.158 *	0.718 ***	0.793
	(0.1204)	(0.351)	(0.131)	(0.689)
Control variables	yes	yes	yes	yes
N	27,267	27,267	27,267	27,267
R-square	0.097	0.086	0.091	0.093

* denotes significance at the 10% level, and *** denotes significance at the 1% level.

, Column 1, indicating that the level of digital financial literacy can significantly enhance the increase in entrepreneurial investment. The results in the second and third columns of Table 7 indicate that the impact of digital financial literacy on both subsistence entrepreneurship and value entrepreneurship is significantly positive. However, digital financial literacy does not have a promoting effect on a household’s value-oriented entrepreneurial investment. Specifically, we hypothesize that value-driven entrepreneurship Investment, which is often driven by personal passion or social goals, may not rely as heavily on financial knowledge or digital financial tools compared to survival or opportunity-driven entrepreneurship investment.

4.6. The Mechanism Test of Digital Financial Literacy on Household Entrepreneurship

A mechanism study was conducted on the impact of digital financial literacy on household entrepreneurship, thereby verifying the hypotheses presented earlier. First, this study verified the formal financial channels. According to the theory presented earlier, entrepreneurial households often face financial constraints, and obtaining loans from institutions such as banks or credit unions can effectively alleviate this issue, thereby increasing the likelihood of households choosing to start a business. Therefore, this paper explores the impact of digital financial literacy on household entrepreneurship from the perspective of formal financial channels. Based on the sample households’ responses to the questions “Do you have a bank loan?” and “Do you have a bank revolving loan?”, this study measures whether they have received support from formal finance. If a sample household has a bank loan, it is coded as “1”; if not, it is coded as “0”.

Based on the research conclusions from the preceding text, the impact of digital financial literacy on the choice of entrepreneurship is significantly positive. Then, by constructing a mediation effect model for regression analysis, the results are shown in

Table 8. Mediation mechanism test.

Variable	(1) Ent	(2) Formal Finance
DFI	0.0537 ***	0.0101 ***
	(0.00557)	(0.00311)
Formal financial	0.504 ***
	(0.0143)
Controls	Yes	Yes
N	27,267	27,267
R-square	0.136	0.017

*** denotes significance at the 1% level.

. The first column is the result after adding the mediator variable to the baseline regression model, and the second column shows the impact of digital financial literacy on obtaining formal finance. It can be seen that the regression coefficients are significant at the one percent level, indicating the presence of partial mediation effects. Additionally, based on the original analysis, we conducted a mediation effect test using the Bootstrap method to further validate the robustness of the underlying mechanism. After 1000 resampling iterations, the confidence interval of the indirect effect did not include 0; thus, we conclude that formal finance acts as a mediator in the relationship between digital financial literacy and household entrepreneurship.

Therefore, it can be concluded that digital financial literacy can promote household entrepreneurship by improving access to formal finance.

4.7. The Impact of Digital Financial Literacy on the Household Entrepreneurship of Marginalized Groups

Our study further examines the impact of digital financial literacy on entrepreneurship among marginalized groups. In the previous sections, we have already explored the effect of digital financial literacy on family entrepreneurship among residents in underdeveloped areas, such as rural regions and central and western regions. In this section, we will investigate whether digital financial literacy has a positive impact on family entrepreneurship among women and residents with low educational attainment.

Table 9. The impact of digital financial literacy on marginalized groups.

Variable	(1) Female	(2) Lower_edu
DFI	0.0511 ***	0.0772 ***
	(0.0104)	(0.00946)
Controls	Yes	Yes
Constant	0.387 ***	−0.0440
	(0.122)	(0.106)
N	6434	9187
R-square	0.075	0.073

*** denotes significance at the 1% level.

presents our research results. The second column shows the results of the impact of digital financial literacy on entrepreneurship among women, which is statistically significant at the 1% level. We then excluded samples with more than six years of education for the regression, and the results are shown in the third column. As we can see, digital financial literacy also significantly promotes entrepreneurship among individuals with lower educational attainment, at the 1% significance level.

5. Discussion

Our study, based on data from the 2019 China Household Finance Survey, constructs a comprehensive index of digital financial literacy and empirically examines its impact on household entrepreneurship and household entrepreneurial investment. On this basis, we conducted a detailed analysis of the heterogeneity of the impact in urban and rural areas, regions, and city tiers. Our research found that families with higher digital financial literacy are more likely to engage in entrepreneurship, supporting the hypothesis that digital financial literacy positively affects the household’s choice to start a business. To address potential endogeneity issues, the results still hold after including instrumental variables. To ensure the robustness of the results, this paper uses the replacement empirical model, reduces the tail to remove the extreme values, and removes the three methods for the robustness test, and all values passed the test. In the heterogeneity test distinguishing between urban and rural areas, we found that the enhancement effect of digital financial literacy on rural household entrepreneurship is greater than that on urban families. In the heterogeneity test distinguishing between the eastern, western, central, and northeastern regions, the promotional effect of digital financial literacy on household entrepreneurship in the western and central regions is greater than that in the eastern region (it should be emphasized that in China, the economic development level of the central and western regions lags behind that of the eastern region). In further research, we found that digital financial literacy can also significantly increase the investment of entrepreneurial families in entrepreneurial projects, but it does not affect the investment amount in value-oriented entrepreneurship. In the mechanism test, we found that the improvement of digital financial literacy can indirectly promote household entrepreneurship by promoting household access to formal finance. In further studying the impact of digital financial literacy on marginalized groups, we found that digital financial literacy can also promote the entrepreneurial likelihood of women and individuals with lower levels of education.

Compared with existing research results, our study’s contributions are as follows: First, our study is the first to validate that digital financial literacy has a positive impact on entrepreneurship, supplementing the theoretical research on factors affecting entrepreneurship. Second, our research enriches the study of digital financial literacy; past research on digital financial literacy mainly found its impact on lending, investment, consumption, and income, and our study expands on the role of digital financial literacy. Third, our study finds that the impact of digital financial literacy on household entrepreneurship is heterogeneous; the positive effect of digital financial literacy on entrepreneurship is more pronounced for residents in rural, underdeveloped areas, and underdeveloped cities, which confirms the inclusiveness of digital financial literacy and shows that digital financial literacy is more helpful for disadvantaged groups in starting businesses.

The findings of this study have important implications. Improving individual digital financial literacy can promote the occurrence of household entrepreneurship, and this effect is more pronounced in economically underdeveloped rural areas and the central and western regions. This indicates that in regions with lower economic development and financial infrastructure, the impact of digital financial literacy is greater. In addition to focusing on entrepreneurship skills training, entrepreneurship development, providing entrepreneurial advisory services, creating a conducive entrepreneurial environment, and offering financial support, governments should also prioritize enhancing residents’ digital financial literacy when formulating policies to encourage entrepreneurship. This would stimulate entrepreneurship, create jobs, and promote sustainable economic development. By improving digital financial literacy in underdeveloped areas, governments can drive entrepreneurship in these regions, thereby fostering equitable growth, achieving inclusive development, and reducing regional disparities.

Despite its many contributions, our study also has certain limitations. First, since the Southwest University of Political Science and Law in China has not made the latest China Household Finance Survey data public, our study can only use the 2019 data for research. Additionally, since the concept of digital financial literacy has only been proposed in recent years, there may be limitations in our study’s construction of indicators for digital financial literacy.

In future research, we can explore the additional impacts of digital financial literacy on vulnerable groups such as women and rural residents, including the effects on their income. From the perspective of individual digital financial literacy, we can investigate how to achieve financial inclusion and explore ways to promote sustainable social and economic development.

6. Conclusions

Our study has confirmed the positive effect of digital financial literacy on household entrepreneurship and found that this positive effect is more pronounced in underdeveloped areas, underdeveloped cities, and rural regions. This result emphasizes the important role of digital financial literacy in helping disadvantaged groups start businesses to achieve sustainable development. Our research has also enriched the understanding of digital financial literacy, expanded the theoretical research on factors affecting entrepreneurship, and provided new ideas for countries on how to promote entrepreneurship to achieve sustainable development. In the discussion section of this paper, future research prospects are proposed, including a focus on exploring the help of digital financial literacy for disadvantaged groups. In conclusion, our study results highlight that digital financial literacy can promote economic and social sustainable development through entrepreneurship, and These findings can serve as a foundation for governments’ policies aimed at achieving sustainable development.