Experience curve analyses for green hydrogen technology development

Given the rapid increase in government support for green hydrogen technology development, it is important to incorporate research development and demonstration (RD&D) spending into the estimation of the learning rate for electrolysis technologies. Thus, we develop a two-factor experience curve model with spillovers and economies of scale that allows us to estimate learning rates for both alkaline and PEM (polymer electrolyte membrane) electrolysis technologies using both global- and country-level data from OECD countries. Our research strategy allows us to mitigate estimation or omitted variable bias from ignoring technology-push measures, unobserved country-specific characteristics, and knowledge spillovers. Using a global dataset over 2003–2020, we estimate global learning-by-doing rates of 17.5 %-46.8 % and global learning-by-researching rate of 9 %–42.3 % for electrolysis technologies after incorporating learning parameter estimates into the well-established progress equation. When we allow for spillovers, we find a linear relationship between PEM technology and alkaline technology improvements. Based on our OECD panel dataset, which incorporate more observations, we estimate learning-by-doing rates of 0.6 %–9.4 % and learning-by-researching rates of 4.0 %–19.9 %. In addition, country-level PEM electrolysis cost is reduced by about 28 % for the sample period 2004–2021 because of global experience spillover effects. Therefore, our empirical findings suggest that the role of technology push measures remains critical for promoting and achieving cost improvements for electrolysis technologies. Furthermore, the absorptive capacity of a country should be improved to maximise the spillover of global learning.