چکیده
1. مقدمه
2. تحلیل های نظری و توسعه فرضیه ها
3. طرح تحقیق
4. نتایج تجربی
5. تست های استحکام
6. تجزیه و تحلیل بیشتر
7. نتیجه گیری و پیامدها
اعلامیه منافع رقابتی
مراجع
Abstract
1. Introduction
2. Theoretical analyses and development of hypotheses
3. Research design
4. Empirical results
5. Robustness tests
6. Further analysis
7. Conclusions and implications
Declaration of competing interest
References
چکیده
استفاده از فناوری کلان داده ها در مدیریت مالیات جهانی به طور فزاینده ای گسترده می شود. چین در سالهای اخیر فناوریهای پیشرفتهتری را برای حاکمیت مالیاتی با استفاده از سیستمهای کلان داده پیادهسازی کرده است. با جمعآوری دادهها از طریق خراش وب در اولین زمانهای اجرای مدیریت مالیات کلان داده در استانهای مختلف چین، ما رابطه بین اداره مالیات دادههای کلان و اعتبار بانکی شرکتها را در بازارهای نوظهور بررسی میکنیم. نتایج ما نشان میدهد که اداره مالیات دادههای کلان توانایی شرکتها را برای دریافت وامهای بانکی افزایش میدهد. آزمونهای مکانیزم نشان میدهد که اداره مالیات دادههای کلان کیفیت افشای اطلاعات شرکتی را بهبود میبخشد و دسترسی به وامهای اعتباری بانکی را تسهیل میکند. ما متوجه شدیم که اداره مالیات کلان دادهها محیط تامین مالی شرکت را بهبود میبخشد و کارایی تخصیص منابع را در بازار اعتبار افزایش میدهد.
Abstract
The application of big data technology to global tax management is becoming increasingly widespread. China has been implementing increasingly mature technologies for tax governance using big data systems in recent years. By collecting data through web scraping on the earliest implementation times of big data tax administration in various provinces of China, we explore the relationship between big data tax administration and corporate bank credit in emerging markets. Our results show that big data tax administration enhances firms’ ability to obtain bank loans. Mechanism tests indicate that big data tax administration improves the quality of corporate information disclosure, facilitating access to bank credit loans. We find that big data tax administration improves the corporate financing environment, enhancing the efficiency of resource allocation in the credit market.
Introduction
The digital economy has expanded rapidly around the world. Driven by continuous upgrades in Internet functionality and the widespread application of big data, significant changes are occurring in governments, corporate business models and in people’s daily lives (Chen and Srinivasan, 2024). Taxation departments provide a good example of such changes, as big data technology is expanding the traditional auditing model. “Big data tax administration” combines big data with tax auditing; it involves acquiring big data from Internet platforms and integrating and comparing multiple sources of data (Bassey et al., 2022). Its implementation, which has become a new trend in national tax governance, reflects the modernization of national governance capabilities and systems within the tax system and significantly enhances the efficiency of governments’ tax collection (Canares, 2016). A key question is whether, looking beyond strict tax enforcement, modernized tax governance can guide firms to improve the quality of their information disclosure, thereby enhancing the efficiency of resource allocation in capital markets? Examining this question yields insights relevant to governments worldwide who are implementing governance based on big data technology.
Bank loans are an important financial resource and whether they are allocated in a timely and appropriate manner is an important issue from both theoretical and practical perspectives. An extensive body of research discusses the various factors that influence firm credit, including corporate characteristics and the policy environment. However, few studies explore whether innovations and modernizations within the tax governance system can improve the financing environment for firms. Studying the effects and mechanisms of big data tax administration on corporate bank credit enhances the understanding of the social effects of modernized governance and provides empirical evidence for the motivational impact of “tax administration with data” on firms.
Conclusions and implications
The widespread adoption and application of the Internet and big data have reduced the cost of information flow, and the multi-party storage and sharing of big data has gradually become a new form of social capital. The use of big data by tax authorities not only improves the capabilities and efficiency of tax collection but also promotes the rational allocation of financial capital at the national level and facilitates enterprise financing. We investigate the effects of big data tax administration on corporate credit and find that implementing big data tax administration (1) has a positive impact on corporate bank credit; (2) improves the quality of corporate information, thereby promoting corporate credit and (3) has a more pronounced effect on enterprises with stronger (vs. weaker) financial constraints. The conclusions of our study are beneficial because they enhance academic understanding of the economic consequences of big data tax administration, and also have practical significance for tax authorities actively seeking external forces to improve tax collection procedures. Based on our theoretical and empirical analyses, we put forward the following policy recommendations.
First, the government should enhance cooperation between tax authorities and third-party online platforms, synchronously strengthening tax administration under the “delegation, management and service” framework. We show that by enhancing information collecting capabilities, big data tax administration improves the quality of corporate information disclosure, thereby optimizing corporate financing efficiency. In the context of the digital transformation of enterprises and the increasing application of big data in society, tax inspection departments should make full use of the data at the societal level, engaging in cooperation with online platforms and online assessment agencies. By utilizing the correlation between multi-party data and the data provided by enterprises, tax inspection departments can strengthen their verification of corporate information. This will help eliminate the corporate practices of inflating projects and manipulating information disclosure, and encourage and guide firms to improve their information quality.