The Chinese government's emphasis on improving investment efficiency highlights the critical role of investment in firm success and economic growth. Inefficient investment, encompassing both underinvestment (missing positive NPV projects) and overinvestment (pursuing negative NPV projects), stems from market imperfections (financing constraints), information asymmetry, and agency costs. Existing research examines institutional factors and managerial/shareholder behavior as determinants of investment efficiency. This study investigates the impact of digital finance, a rapidly developing financial model, on mitigating inefficient investment. Digital finance, integrating technology and finance, potentially addresses these issues by enhancing access to financial services, reducing information asymmetry, and improving corporate governance. The study proposes a theoretical framework based on 'resource effects' (improved access to financial resources) and 'governance effects' (reduced agency problems and information asymmetry) to analyze digital finance's impact.

Prior research on firm investment efficiency focuses on two main perspectives. The first emphasizes external institutional factors such as policy environments, political resources, and regional institutional development in mitigating inefficient investment. The second highlights the roles of firm managers and shareholders, employing theories like upper echelons theory and information asymmetry theory. Studies consistently demonstrate the link between financing constraints, information asymmetry, agency costs, and inefficient investment. This study builds upon this foundation by examining the unique role of digital finance in addressing these factors.

The study uses a sample of non-financial firms listed in Shanghai and Shenzhen A-shares from 2008 to 2019. Data preprocessing involved excluding firms with asset-liability ratios outside the range of 0-1, ST, ST*, and PT firms, and those with missing data. Continuous variables were winsorized at the 1% and 99% levels. The final sample included 19,780 observations. Inefficient investment (INVEFF) was measured using a regression model adapted from Biddle et al. (2009), where the absolute value of the residuals represents the degree of inefficiency. Digital finance (DWF) was measured using a municipal-level Digital Inclusive Finance Index from Peking University and Ant Financial Services Group, encompassing coverage breadth, use depth, and digitization of inclusive finance. Control variables included firm size, financial leverage, firm performance (ROA), ownership concentration, board size, number of firm committees, state ownership, listing age, cash ratio, stock returns, and percentage of fixed assets. The main hypothesis was tested using a regression model (Equation 2), controlling for industry and year fixed effects. Endogeneity was addressed using the Heckman two-stage model and instrumental variables (internet penetration). Additional analyses examined the impact on overinvestment and underinvestment separately, the effects of different dimensions of digital finance, and heterogeneity based on regional institutional development and firm nature.

The benchmark regression results consistently demonstrate that digital finance significantly mitigates firm inefficient investment (Table 3). This finding remains robust after addressing endogeneity concerns using Heckman two-stage model and instrumental variable approaches (Tables 4 and 5). The economic significance is substantial: a one standard deviation increase in digital finance reduces firm inefficient investment by 8.47%. Further analyses reveal that digital finance's mitigating effect is more pronounced in non-state firms and in regions with higher levels of institutional development (Table 10). The impact is more significant on overinvestment compared to underinvestment (Table 11). All three sub-dimensions of digital finance (coverage breadth, use depth, and digitization) contribute to reducing inefficient investment. Mechanism analysis (Table 9) confirms that the mitigating effect operates through both resource and governance channels: digital finance alleviates financing constraints, reduces agency costs, and mitigates information asymmetry. Robustness checks, including excluding firms listed on the Growth Enterprise Market (GEM) and controlling for industry trend effects, support the findings (Tables 7 and 8).

The findings confirm the significant positive impact of digital finance on firm investment efficiency, particularly for non-state firms in well-developed institutional environments. This addresses a gap in the existing literature by demonstrating the dual resource and governance effects of digital finance. The results highlight the importance of digital finance in improving resource allocation and corporate governance, offering insights for firms and policymakers. The more pronounced impact on overinvestment suggests that digital finance may be particularly effective in curbing excessive risk-taking and improving capital allocation decisions.

This study provides strong evidence supporting the positive impact of digital finance on mitigating inefficient investment. The findings highlight the importance of both resource and governance effects. Future research could explore the role of specific digital finance platforms, investigate the long-term impact of digital finance on investment efficiency, and examine the influence of regulatory policies on the relationship between digital finance and investment behavior. Further exploration of cross-country comparisons might shed light on the generalizability of these findings.

The study focuses on China, limiting the generalizability of the findings to other contexts with different institutional settings and levels of digital financial development. The use of a specific digital finance index might also limit the generalizability to other indices or measures. The study period is also specific, and future trends may differ. Finally, unobserved heterogeneity could remain despite the use of fixed effects.