China's digital shadows: unveiling the economic toll of cybercrime

China's rapid digitalization presents both opportunities and vulnerabilities. While it benefits from technological advancement and a large internet user base, it also faces significant challenges from cybercrime, which impacts economic stability and growth. This study examines the complex effects of cybercrime on China's economic growth, focusing on the interplay between digital progress and vulnerability to cyber threats. Prior research highlights the negative impacts of cybercrime on financial losses, supply chains, and consumer trust, while investments in cybersecurity can mitigate these effects and drive innovation. This study investigates how cybercrime affects economic growth across China's provinces from 2005 to 2022, utilizing a comprehensive empirical model incorporating provincial and annual fixed effects to quantify the negative impact and explore regional disparities. The study improves upon previous research by incorporating regional nuances and employing the generalized method of moments (GMM) methodology to manage dynamic panel data and address endogeneity concerns, offering a more robust framework for understanding the varied impacts of cybercrime across different regions and time.

Existing literature predominantly shows a negative correlation between cybercrime and economic growth, with cybercrime eroding resources through diminished consumer confidence and corporate investment, and increased cybersecurity costs diverting funds from productive investments. However, some argue that cybersecurity spending can positively impact the economy by stimulating the information security sector. The literature also acknowledges the significant roles of labor and capital inputs, technological innovation, educational investment, and internet penetration in economic growth, highlighting the synergistic effect of these factors and the importance of addressing the digital divide. This study integrates these diverse perspectives to provide a cohesive narrative, exploring the complexities of cybersecurity investments and the interplay of various factors influencing economic growth.

The study employs an expanded Cobb-Douglas production function to investigate the effects of cybercrime on economic growth. The model incorporates variables such as labor input, capital input, technological innovation, education investment, and internet penetration. Initially, a logarithmic transformation is applied to normalize the variance-covariance matrix. A series of control variables are added to refine the analytical precision. The Hausman test is used to justify the inclusion of both provincial and annual fixed effects. Two hypotheses are formulated: (1) Cybercrime negatively impacts economic growth, and (2) The impact of cybercrime varies significantly across regions. The study utilizes data from various sources, including the National Bureau of Statistics Data Center, Provincial Statistical Yearbooks, and annual work reports from People's Procuratorates. The study employs correlation analysis, followed by a fixed-effects model. To address potential endogeneity concerns, a robustness test is conducted using the generalized method of moments (GMM) estimator for dynamic panel data. A regional heterogeneity test further disaggregates the data into three subsets corresponding to China's eastern, central, and western regions to analyze regional variations in cybercrime's impact.

Correlation analysis shows a negative relationship between cybercrime and economic growth, with positive correlations between economic growth and labor input, capital input, technological innovation, education investment, and internet penetration. The fixed-effects model (Model 3 in Table 3) shows that a 1% increase in cybercrime correlates with a 0.019% decrease in economic growth. This negative impact is robust across multiple model specifications. The GMM estimation (Table 4) confirms the negative and statistically significant effect of cybercrime on economic growth. The regional heterogeneity test (Table 5) reveals that the negative impact of cybercrime is most pronounced in the eastern region (-0.034%), followed by the central (-0.017%) and western (-0.011%) regions, highlighting regional disparities in vulnerability and resilience.

The findings confirm both hypotheses: cybercrime negatively impacts China's economic growth, and this impact varies across regions. The negative correlation is consistent with existing literature highlighting direct financial losses, increased cybersecurity spending, reduced consumer trust, and business disruptions. The regional variations reflect differing levels of digital infrastructure development and economic structures. The eastern region's greater vulnerability may be due to its advanced digital economy and higher concentration of valuable targets for cybercriminals. The study's comprehensive analysis provides a macroeconomic perspective, complementing existing microeconomic studies focusing on specific sectors or businesses. The results emphasize the need for targeted interventions to mitigate the negative effects of cybercrime and promote sustainable economic growth.

This study demonstrates a significant negative impact of cybercrime on China's economic growth, with regional variations. The findings support the need for region-specific cybersecurity policies, public-private partnerships, increased cybersecurity awareness, and updated legal frameworks. Future research should investigate intra-regional variations, the evolution of cybersecurity measures, biases in cybercrime reporting, and socio-economic influences on cybercrime.

The study's regional aggregation might mask intra-regional variations. The analysis does not dynamically track evolving cybersecurity measures. Reported cybercrime incidents may be subject to biases due to variations in detection and reporting practices. Socio-economic and cultural influences on cybercrime prevalence and impact are not fully explored.