This paper empirically evaluates the impact of a Government-Initiated Non-Profit Ecommerce Platform (GNEP) on specialty agricultural sales, focusing specifically on Pu’er tea in China. Using a difference-in-differences methodology and a comprehensive panel dataset that covers over 90% of local tea farmers, we uncover a marked substitution effect. The implementation of GNEP leads to an average decline of 11.22% in offline household sales, while online sales see an uptick of 16.88%. Further analysis confirms a universal channel shift from offline to online sales, irrespective of both production levels and tea quality. Contrary to expectations, the overall tea sales volume remains largely stable post-launch. Additionally, premium-quality teas experience a 2.42% price boost online, while regular teas show a 0.40% decrease compared to offline prices. Mechanism analyses further indicate that the increase in online sales is driven primarily by the intensive margin instead of the extensive margin. Although the platform does not significantly expand the number of farmers engaging in online sales, it succeeds in offering a cost-effective avenue for diversifying product offerings and achieving higher prices for premium-quality products. Our study illuminates the transformative role of e-commerce platforms in rural economic development and provides essential insights for policymakers and practitioners.

While previous research has delved into the relationship between political uncertainty and the aggregate cross-border flows of capital, there remains a notable gap in our understanding of how political uncertainty affects firm ownership structure within foreign direct investment (FDI) projects, specifically concerning the intensive margin. In this study, we commence by introducing a stylized model, wherein a risk-averse foreign investor teaming up with a local producer is concerned about the political risk associated with the provision of public goods by the local government. Our analysis demonstrates that the foreign investor, acting as a residual claimant, allocates a greater proportion of revenues to the local partner when local policy conditions are more uncertain. This strategic decision indirectly locks in local government commitment to the international joint venture, thereby mitigating the negative influence of political uncertainty. Subsequently, we test our theoretical framework by employing a unique dataset that encompasses city-level political turnovers and firm-level incentive structures in the context of China. The results unveil robust evidence substantiating that uncertainty arising from local political turnover significantly affects the revenue-sharing agreements between foreign investors and their local partners within the international joint production.

This paper examines the impact of the carbon emissions trading scheme (ETS) on directed technological change in the context of Chinese pilot schemes. We focus on firms’ heterogeneity in driving innovation and explore policy variations across pilots. Using a matched difference-in-differences design with a zero-inflated Poisson model, we find that the low-carbon innovation is driven by firms at the intensive margin. On average, a firm files 0.16 additional low-carbon patents annually at the intensive margin. In addition, when looking across pilots, the effect on low-carbon innovation is significant in two pilots, Beijing and Shanghai. We further find that, when looking at firms with different productivity levels measured by output per worker, the pilot ETS encourages low-carbon innovation at the intensive margin but reduces entry into low-carbon innovation at the extensive margin for the more productive firms. Our results suggest that innovation inertia matters, and future policies should encourage smaller firms covered by ETS to start innovation in low-carbon technologies.

We study the consequences of market uncertainty on international trade. An increase in foreign market uncertainty dampens China's aggregate exports on both the extensive and intensive margins. The adverse effects are more pronounced in industries facing tighter financial constraints than in others. We propose a dynamic trade model to explain the facts. Greater uncertainty depresses a firm's expected value of exporting and borrowing capacity, leading to fewer exporters and a smaller average size of exports. Under calibrated parameters, the uncertainty shock accounts for a sizable fraction of China's trade collapse in the 2008 financial crisis and the recent trade war.