Industrial policy is often discussed through high-level narratives and flagship initiatives, yet its implementation—particularly at the subnational level—remains opaque. We leverage large language models (LLMs) to systematically analyze over three million government documents from 2000 to 2022, extracting structured policy information to decode China’s industrial policy at various levels of government. Combining these newly constructed granular industrial policy data with micro-level firm data, we document four sets of facts on China’s industrial policies, including the economic and political rationality of the choice of the target sectors, the dynamics of the policy tools, the diffusion and similarity of policies, and the effects on firm entry and productivity.
This article discusses how reducing frictions across Chinese provinces could significantly improve aggregate output, lower spatial inequality, and discourage population concentration in large cities.
This paper presents evidence that firms’ export and import decisions within the same foreign market are complementary, due to bilateral economies of scope that allow substantial cost savings when engaging in both activities. By quantifying these savings through a structural model, we show that bilateral economies of scope significantly enhance firms’ participation in international trade and amplify the effects of trade liberalization, offering new insights for policymakers and researchers.
We investigate whether high-speed rail (HSR) connectivity influences electric vehicle (EV) adoption, using a quasi-natural experiment from China’s HSR expansion and several identification strategies. Our findings consistently show that, by alleviating range anxiety, the expansion of HSR can account for up to one third of the increase in EV market share and EV sales in China during our sample period from 2010 to 2023, with effects particularly pronounced in cities served by faster HSR lines. These results suggest that transportation infrastructure can play a complementary role in accelerating the transition to electric mobility.
The interplay between trade liberalization and demographic behavior illuminates the challenges of reconciling career and family. This paper examines how gender-specific trade liberalization influences fertility, leveraging a Bartik-style shift-share instrumental variable strategy that incorporates female skill intensity into input tariff exposure. We find that input-trade liberalization significantly reduces fertility, particularly among highly educated women, private sector employees, and first-time mothers—groups experiencing the steepest career-family trade-offs. Mechanism analysis shows that enhanced labor market prospects raise the opportunity cost of childbearing, delaying or reducing family formation. These findings underscore the socioeconomic implications of trade policy for demographic trends.