Guo Kou is a student in the Class of 2026 at DKU, majoring in Social Sciences with a focus on the Political Economy Track in Economics. Awarded the CSCC Student Initiated Research or Creative Project Grant for the 2023-2024 academic year, Guo is investigating the effects of High-Tech Enterprise (HNTE) Certification on Chinese businesses’ export and import activities. Under the guidance of Faculty Supervisor Jiahua Yue, Guo’s research project, “The Impact of High-Tech Enterprise Certification on Export and Import”, aims to provide empirical data on how this certification influences trade operations and competitiveness within international markets. In our conversation with Guo, we will delve into the inspiration driving his project, discuss his journey through the research process, and examine how his findings might deepen our knowledge of international trade and economics.
Hi Guo, could you tell us what initially drew you to the topic of High-Tech Enterprise Certification and its impact on exports and imports?
My interest in High-Tech Enterprise (HNTE) Certification stems from my longstanding focus on China’s international trade policies and enterprise competitiveness. HNTE Certification, as a policy tool, aims to promote technological innovation and international market expansion through tax incentives and subsidies. By studying its impact on exports and imports, I hope to uncover its effectiveness and provide practical insights for both business leaders and policymakers. This research seeks to bridge knowledge gaps and support global strategies for Chinese enterprises.
Could you elaborate on the specific statistical methods or models that have been most crucial in your research, and why you chose them?
The Difference-in-Differences (DID) method has been the most critical approach in my research. I use it to compare enterprise trade data before and after certification to identify causal relationships between policy intervention and trade performance. Additionally, panel data regression models help account for time and firm-level heterogeneity. These methods are essential for controlling confounding variables and providing a dynamic understanding of policy impact.
As you have delved into the data analysis, how have you navigated the challenges of data reliability and validity, particularly given the complex nature of international trade data? Also, how have your initial hypotheses evolved, and what have been the most intriguing insights you’ve uncovered so far?
To address data reliability and validity issues, I implemented a multi-step cleaning process and cross-validated the data sources. Interviews with industry executives offered valuable qualitative insights, helping me contextualize the quantitative findings. Initially, I hypothesized that certification would primarily boost export volume. However, the data revealed an intriguing trend: certified enterprises not only increased their export volume but also diversified their market distribution, which exceeded my expectations.
What role do you think qualitative insights from enterprise executives will play in your research conclusions?
Insights from enterprise executives play a crucial role in complementing quantitative data. For example, they provide firsthand accounts of how the certification has influenced their R&D investments and international branding efforts. These qualitative insights offer deeper context to the numerical data, enhancing the practical relevance and depth of my research conclusions.
What experiences have you found most rewarding while working on this project, and how have they shaped your view on international trade?
The most rewarding part of this project has been extracting meaningful insights from both data and interviews and translating them into actionable policy recommendations. This process has deepened my understanding of the complex interactions between policy, innovation, and international trade. It has given me a new perspective on the dynamic nature of trade and the importance of well-designed policies in shaping global competitiveness.
What skills do you think students develop through this kind of research, and how do these skills prepare them for future challenges?
This type of research helps students develop critical thinking, data analysis, and communication skills. Working with complex datasets taught me how to approach problems systematically, while engaging with executives improved my interdisciplinary communication abilities. These skills are not only valuable for academic research but also prepare students to tackle challenges in policymaking and business.
