Technology Adoption and Learning-by-Doing: The Case of Bt Cotton Adoption in China

Guang Tian, Xiaoxue Du, Fangbin Qiao and Andres Trujillo-Barrera
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Guang Tian: Department of Agricultural and Applied Economics, University of Wisconsin-Madison, Madison, WI 53705, USA
Xiaoxue Du: Department of Agricultural Economics and Rural Sociology, University of Idaho, Moscow, ID 83843, USA
Fangbin Qiao: China Economics and Management Academy, Central University of Finance and Economics, Beijing 100081, China

JRFM, 2021, vol. 14, issue 11, 1-13

Abstract: Although the benefits of genetically modified (GM) crops have been well documented, how do farmers manage the risk of new technology in the early stages of technology adoption has received less attention. We compare the total factor productivity (TFP) of cotton to other major crops (wheat, rice, and corn) in China between 1990 and 2015, showing that the TFP growth of cotton production is significantly different from all other crops. In particular, the TFP of cotton production increased rapidly in the early 1990s then declined slightly around 2000 and rose again. This pattern coincides with the adoption of Bt cotton process in China. To further investigate the decline of TFP in the early stages of Bt cotton adoption, using aggregate provincial-level data, we implement a TFP decomposition and show that the productivity of GM technology is higher, whereas the technical efficiency of GM technology is lower than that of traditional technologies. Especially, Bt cotton exhibited lower technical efficiency because farmers did not reduce the use of pesticide when they first started to adopt Bt cotton. In addition, we illustrate the occurrence of a learning process as GM technology diffuses throughout China: after farmers gain knowledge of Bt cotton, pesticide use declines and technical efficiency improves.

Keywords: genetically modified crops; technical efficiency; total factor productivity; Bt cotton; risk management (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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