Knowledge creates value: the role of financial literacy in entrepreneurial behavior

The study examines whether and how financial literacy shapes household entrepreneurial behavior in China. Motivated by human capital theory and modern entrepreneurship theory, the authors posit that financial literacy—as scarce human capital—enhances opportunity identification, decision-making quality, access to networks, and risk-taking, thereby fostering entrepreneurship. The research addresses three core questions: (1) Does financial literacy have immediate (current), long-term (lagged), and dynamic (change over time) effects on households’ participation in entrepreneurship and on initiative-driven entrepreneurship? (2) Do these effects differ by urban versus rural residence and by gender? (3) Through which mechanisms—income, social networks, and risk attitudes—does financial literacy influence entrepreneurship, and does financial education strengthen this relationship? The study is important given global policy efforts to promote entrepreneurship and the mixed evidence on determinants of entrepreneurial activity. It contributes by focusing on financial literacy’s role at the household level, exploring temporal effects, testing mechanisms, and documenting heterogeneity.

The paper reviews determinants of financial literacy and entrepreneurial behavior. For financial literacy, micro-level factors such as gender (men typically score higher), age (hump-shaped), education (positively related), health, and experience matter; macro-level influences include parental education and behavior, neighborhood effects, school- and community-based education, and the broader financial and social environment. Evidence on financial education’s effectiveness is mixed but includes studies showing positive impacts. With rapid digitization, digital finance engagement is linked to financial literacy, and a research agenda on digital financial literacy is emerging. For entrepreneurial behavior, macro-determinants include economic development, institutions, taxation, leadership turnover, property rights, banking regulation, culture, and information environments; micro-determinants include liquidity/credit constraints, social networks, trust, training, work experience, health, education, identity, wealth, and risk preferences. Research gaps remain regarding financial literacy’s direct role in fostering household entrepreneurship, which this study addresses.

Data: The study uses China Household Finance Survey (CHFS) microdata from 2015 and 2017. Samples with missing values are excluded. Province fixed effects are included in baseline models. Measures of financial literacy: (1) Literacy1: count of correct answers (0–3) to three standard questions (interest rate calculation, inflation, venture capital). In 2015, 28.67% answered the interest question correctly (23.16% wrong; 48.17% no answer), 16.39% correctly understood inflation (37.84% wrong; 45.76% no answer), and 51.94% correctly answered the venture capital item (4.58% wrong; 43.48% no answer). (2) Literacy2: factor score from factor analysis on six dummies distinguishing wrong vs. nonresponse for each question (KMO supports factor analysis). Factors with eigenvalue >1 are retained. Outcomes: Household entrepreneurial behavior at the family level. Entrepre1 (current participation in self-employed business; 1/0). Entrepre2 (initiative entrepreneurship; 1 if motives include “want to be the boss/earn more/be more flexible and free,” else 0). Dynamic change measures 2015–2017: Entrepre1′ and Entrepre2′ coded as −1, 0, 1 based on changes. Controls (2015): Gender, age and age squared, health, marital status, education, risk preference (RL), risk neutrality (RN), risk aversion (RA), parental CPC membership (CPC, proxy for parental network), family size (FS), assets (log), numbers of children <16 (NC) and elderly >60 (NE), homeownership (House), number unhealthy (NU). Asset used in some specifications; province fixed effects included in current-effect models. Empirical models: (i) Current effect: Probit(Entrepre=1) on contemporaneous financial literacy and controls (2015). (ii) Long-term effect: Probit(Entrepre in 2017=1) on financial literacy measured in 2015 and controls (2015). (iii) Dynamic effect: ordered Probit of Entrepre′ (−1,0,1) on 2015 financial literacy and controls. Endogeneity concerns (reverse causality; measurement error from guessing) are addressed via IV two-stage regressions using the highest parental education as the instrument for financial literacy (argued exogenous to children’s later entrepreneurial decisions; parental network is controlled). Tests include first-stage F, Durbin–Wu–Hausman/DWH. Mechanism analyses: (1) Income channel: regress total household income (log) and income rank (top 50% vs. bottom 50%) on financial literacy using OLS/Probit with IV to test whether literacy raises income and rank. (2) Social network channel: proxy networks by log cash and non-cash gift expenditures, revenues, and their sum associated with the Spring Festival, other holidays, weddings, and funerals (Expenditure, Revenue, Sum) in 2015; estimate effects of financial literacy with IV. (3) Risk attitude channel: model RL, RN, RA (Probit) and a composite Risk index (values 1–3) on financial literacy with IV. Robustness checks: Replace financial literacy with individual question dummies (e.g., Dum1 interest calculation; Dum3 inflation; Dum5 venture capital, where Dum5 is consistently significant) and with an attention proxy (Attention to financial/economic information). Heterogeneity: split samples by rural/urban and by gender; test coefficient differences via Fisher’s permutation tests with bootstrap (1,000 resamples). Further analysis: Financial education (Learn=1 if took econ/finance coursework) as a determinant of financial literacy (OLS and PSM: nearest neighbor, radius, kernel matching) and as moderator via interaction terms Literacy×Learn in entrepreneurship regressions.

- Financial literacy significantly and positively predicts household entrepreneurship participation and initiative entrepreneurship in the current period (Probit), in the long term (2015 literacy predicting 2017 outcomes), and dynamically (ordered Probit on changes 2015–2017). For example, in long-term models (Table 6), coefficients on Literacy1 for Entrepre1 and Entrepre2 are 0.007 (p<0.05) and 0.009 (p<0.1), and on Literacy2 are 0.010 (p<0.01) and 0.007 (p<0.1), respectively. - Addressing endogeneity with IV (parental education) via two-stage regressions yields consistent positive effects (DWH tests support endogeneity; strong first-stage F statistics reported), corroborating baseline results. - Robustness: Using alternative proxies, the venture capital literacy dummy (Dum5) shows significant positive associations across current, long-term, and dynamic specifications; an attention-to-finance proxy (Attention) is also positively associated with entrepreneurial outcomes. - Heterogeneity (rural vs. urban): Financial literacy’s effect on participation in entrepreneurship is more pronounced in urban households, while its effect on initiative entrepreneurship is stronger in rural households (inter-group coefficient differences statistically significant by permutation tests; Table 10). - Heterogeneity (gender): Effects on participation are stronger among men, while effects on initiative entrepreneurship are stronger among women (significant male–female coefficient differences; Table 11). - Mechanisms validated: • Income channel: Financial literacy significantly increases total household income and the probability of being in the top 50% income rank (e.g., positive significant coefficients for Literacy1 and Literacy2; strong IV results; Table 12). • Social network channel: Financial literacy significantly raises gift-related expenditures, revenues, and their sum, indicating broader social networks (significant in OLS and IV; Table 13). • Risk attitude channel: Financial literacy increases risk preference and risk neutrality and reduces risk aversion; the composite Risk index increases with literacy. IV estimates confirm these patterns (Table 14). - Financial education: Learn is strongly and positively associated with higher financial literacy (OLS and PSM ATT estimates significant; Tables 15–16). Interactions Literacy×Learn are positive and significant across current and dynamic entrepreneurship models, indicating that financial education amplifies the impact of financial literacy on entrepreneurial behavior (Table 17).

The findings directly address the research questions: financial literacy operates as a key form of human capital that not only correlates with but also appears to causally enhance household entrepreneurship, with effects that are immediate, persistent, and dynamically improving. The validated mechanisms show that literacy supports entrepreneurship by raising household resources (income), widening access to information and support (social networks), and shifting risk attitudes toward greater risk tolerance—all central to opportunity identification and venture initiation. Heterogeneous impacts by location and gender highlight contextual constraints and different motivating factors: in urban areas, deeper markets and resources translate literacy into higher participation, whereas in rural areas, literacy more strongly fuels initiative among those already engaged. Among men, literacy more strongly spurs entry into entrepreneurship; among women, it strengthens proactive, opportunity-driven motives once engaged. Financial education both builds literacy and magnifies its entrepreneurial returns, suggesting complementarities between knowledge acquisition and application. These insights enrich human capital and entrepreneurship theories by detailing how specific capabilities (financial knowledge) translate into entrepreneurial action via identifiable channels and contexts, and they inform policy on where and how to target literacy and education to catalyze entrepreneurship.

Using CHFS 2015 and 2017 data and Probit/ordered Probit models with IV strategies, the study shows that financial literacy exerts significant current, long-term, and dynamic positive effects on household entrepreneurship participation and initiative entrepreneurship. Mechanism analyses reveal income, social network, and risk attitude channels. Heterogeneity analyses demonstrate stronger effects on participation in urban areas and among men, and stronger effects on initiative entrepreneurship in rural areas and among women. Financial education raises financial literacy and strengthens its impact on entrepreneurship. The study contributes to human capital and entrepreneurship theories by identifying literacy’s multi-channel influence and temporal persistence at the household level and offers guidance for policy targeting and program design.

- Data limitations: analyses rely on CHFS cross-sections from 2015 and 2017; longer panels would improve causal inference and track dynamics over time. - Omitted contextual variables: limited measures of cultural diversity at finer market-segment levels constrain exploration of cultural effects on entrepreneurship. - Measurement limitations: relatively simple questionnaires may not fully capture the complexity of entrepreneurial behavior and financial literacy (including digital dimensions). - Despite IV strategies, residual endogeneity or unobserved factors may remain; parental education may proxy networks/resources despite controls. Future work should integrate richer instruments, longitudinal designs, and digital financial literacy measures to strengthen identification and scope.