TY - JOUR
T1 - The Learning Process and Technological Change in Wind Power
T2 - Evidence from China's CDM Wind Projects
AU - Tang, Tian
AU - Popp, David
N1 - Publisher Copyright:
© 2015 by the Association for Public Policy Analysis and Management
PY - 2016/12/1
Y1 - 2016/12/1
N2 - The Clean Development Mechanism (CDM) is a project-based carbon trade mechanism that subsidizes the users of climate-friendly technologies and encourages technology transfer. The CDM has provided financial support for a large share of Chinese wind projects since 2002. Using pooled cross-sectional data of 486 registered CDM wind projects in China from 2002 to 2009, we examine the determinants of technological change in wind power from a learning perspective. We use a spatial error model to estimate the effects of different channels of learning—learning through R&D in wind turbine manufacturing, learning from a firm's previous wind project experience, spillovers from industry-wide project experience, and learning through the network interaction between project developer and turbine manufacturer—on technological change, measured as reductions in projected costs or as increased capacity factor across CDM wind projects. While we find that a project developer's previous experience matters, interactions between a wind project developer and its partner foreign turbine manufacturer lead to the largest cost reductions and capacity factor improvement. We also find that spillovers from industry-wide experience only exist for wind farm installation. The evidence of industry-wide spillovers and the joint learning within partnerships between project developers and foreign turbine manufacturers supports the subsidies to users of wind technologies, and policy regimes that promote international collaboration and technology transfer.
AB - The Clean Development Mechanism (CDM) is a project-based carbon trade mechanism that subsidizes the users of climate-friendly technologies and encourages technology transfer. The CDM has provided financial support for a large share of Chinese wind projects since 2002. Using pooled cross-sectional data of 486 registered CDM wind projects in China from 2002 to 2009, we examine the determinants of technological change in wind power from a learning perspective. We use a spatial error model to estimate the effects of different channels of learning—learning through R&D in wind turbine manufacturing, learning from a firm's previous wind project experience, spillovers from industry-wide project experience, and learning through the network interaction between project developer and turbine manufacturer—on technological change, measured as reductions in projected costs or as increased capacity factor across CDM wind projects. While we find that a project developer's previous experience matters, interactions between a wind project developer and its partner foreign turbine manufacturer lead to the largest cost reductions and capacity factor improvement. We also find that spillovers from industry-wide experience only exist for wind farm installation. The evidence of industry-wide spillovers and the joint learning within partnerships between project developers and foreign turbine manufacturers supports the subsidies to users of wind technologies, and policy regimes that promote international collaboration and technology transfer.
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U2 - 10.1002/pam.21879
DO - 10.1002/pam.21879
M3 - Article
AN - SCOPUS:84949845154
SN - 0276-8739
VL - 35
SP - 195
EP - 222
JO - Journal of Policy Analysis and Management
JF - Journal of Policy Analysis and Management
IS - 1
ER -