International trade has become the fastest growing driver of global carbon emissions, with large quantities of emissions embodied in exports from emerging economies. International trade with emerging economies poses a dilemma for climate and trade policy: to the extent emerging markets have comparative advantages in manufacturing, such trade is economically efficient and desirable. However, if carbon-intensive manufacturing in emerging countries such as China entails drastically more CO2 emissions than making the same product elsewhere, then trade increases global CO2 emissions.

Using the bidding prices of participants in China's national wind project concession programs from 2003 to 2007, this paper built up a learning curve model to estimate the joint learning from learning-by-doing and learning-by-searching, with a novel knowledge stock metric based on technology adoption in China through both domestic technology development and international technology transfer. The paper describes, for the first time, the evolution of the price of wind power in China, and provides estimates of how technology adoption, experience building wind farm projects, wind turbine manufacturing localization, and wind farm economies of scale have influenced the price of wind power.