China's agricultural exports, while large in volume, lack strength due to a persistent trade deficit. The transition from quantity- to quality-driven exports is hindered by challenges in agricultural quality upgrading. Geographical Indications (GIs), as intellectual property rights specifying product origin and quality, offer a potential solution. The 2007 China-EU '10+10' pilot project for mutual GI recognition provided a unique opportunity to study the impact of such agreements on export quality. This study explores whether mutual GI recognition enhances the quality of China's agricultural exports, investigates the underlying mechanisms (supply-side and demand-side effects), and examines whether these effects vary across different export markets, products, and firms. The research addresses a gap in the literature by focusing on bilateral mutual GI recognition, considering both supply and demand-side factors, and examining the experience of Chinese firms, a largely under-researched area.

Existing literature explores the quality of agricultural exports, often using methods like unit value, backcasting, and nested logit models. Studies have identified various factors influencing export quality, including trade measures (SPS measures, positive lists), economic factors (FDI, institutional environment), and regional quality reputations. Research on GIs and export trade is also relevant, with some studies showing GIs can increase export prices and market access, while others suggest potential cost increases. However, there's limited research on bilateral GI recognition's impact on developing country firms' export quality and the demand-side effects in the importing country. This study aims to address these gaps.

The study employs a multi-time point difference-in-differences (DID) model using Chinese customs export data from 2000 to 2016. Export product quality is measured using a method similar to Khandelwal et al. (2013) and Shi (2014), regressing the logarithm of quantity on the logarithm of price to obtain a quality index. The model includes a policy variable representing mutual GI recognition, control variables (SPS measures, openness, per capita income, exchange rate, GI endowment difference), and firm, product, and destination country fixed effects. A propensity score matching (PSM) method is used to address potential selection bias. Several robustness checks are performed, including replacing the dependent variable, sample tail reduction, modifying the PSM matching method, and a placebo test. A two-stage least squares (2SLS) approach addresses potential endogeneity. Heterogeneity tests examine differences across countries with high vs. low GI endowments, firm size, and product categories (labor-intensive vs. resource-intensive). Finally, a mediation analysis explores the mechanisms through which mutual GI recognition affects export quality, considering specialization agglomeration, cost-saving, domestic demand upgrading, and product recognition effects.

The empirical results strongly support the hypothesis that mutual GI recognition between China and the EU significantly improves the quality of China's agricultural exports. This finding is robust across various robustness checks and addresses potential endogeneity concerns. Heterogeneity analysis reveals that the positive effect is more pronounced in: 1. Countries with high GI endowments: Consumers in these countries are more familiar with and value GIs. 2. Large and medium-sized firms: These firms have more resources to invest in quality improvement and meet higher standards. 3. Labor-intensive products: These products are easier to upgrade compared to resource-intensive products. The mechanism analysis demonstrates that mutual GI recognition improves export quality through both supply-side and demand-side channels. Supply-side effects include: 1. Specialization agglomeration: Mutual recognition leads to standardized production, economies of scale, and knowledge spillovers. 2. Cost-saving: Reduced information and trade costs due to streamlined processes. Demand-side effects include: 1. Domestic demand upgrading: Increased demand for higher-quality products within China stimulates quality improvement for exports. 2. Product recognition: Mutual recognition enhances product reputation, reduces consumer risk, and increases willingness to pay a premium.

The findings confirm the effectiveness of bilateral GI recognition in upgrading the quality of agricultural exports. The significant positive impact highlights the importance of international cooperation in improving export competitiveness. The mechanism analysis clarifies the interplay of supply and demand factors, demonstrating that both production efficiency and market demand play critical roles. The heterogeneity analysis suggests targeted policies focusing on specific product categories, firm sizes, and export destinations can maximize the benefits of GI agreements. The results contribute to the literature on quality upgrading, GI protection, and international trade, particularly in the context of developing economies.

This study provides strong evidence supporting the positive impact of mutual GI recognition on the quality of China's agricultural exports. The findings highlight the importance of both supply-side improvements (specialization, cost reduction) and demand-side factors (domestic demand, product recognition). Future research could explore the long-term impacts of GI agreements, compare the effectiveness of different GI recognition models, and analyze the role of institutional factors in shaping the outcomes.

The study's timeframe (2000-2016) might limit the generalizability of findings to longer-term trends. The focus on China-EU trade might not fully represent the broader impacts of GI recognition in other contexts. While the study accounts for several potential biases, unobservable factors might still influence the results. The reliance on secondary data sources may constrain the granular level of analysis.