The evolving boundary of green technology
Nicol\`o Barbieri, Kerstin H\"otte, Peter Persoon

TL;DR
This paper investigates biases in green patent statistics caused by classification updates, regional adoption delays, and quality thresholds, revealing that green innovation is accelerating and shifting towards Asia.
Contribution
It identifies and quantifies three key biases affecting green patent data, providing new insights into the true trends and geographic shifts in green innovation.
Findings
Green patent counts increase by 9.2% with updated classifications.
Regional biases cause 10% of green patents from late-adopting countries to be overlooked.
Green innovation is accelerating and increasingly centered in Asia.
Abstract
Green patents are a key indicator to track technological efforts aimed at fighting climate change. Using an original dataset that merges different Patstat releases, we identify three mechanisms that may bias green patent statistics, potentially leading to contradictory findings. First, patent reclassifications due to updates in (green) classification codes result in an 9.2\% increase in the number of green patents when using the most recent classification structure. Second, delays in the adoption of the Cooperative Patent Classification (CPC) system introduce regional biases, as approximately 10\% of green patents from late-adopting countries remain undetected in less recent versions of the database. Third, we provide evidence that quality thresholds used to identify high-value inventions significantly shape observed trends in green patenting. Analyzing these mechanisms, our paper…
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Taxonomy
TopicsSustainable Industrial Ecology
