We examine how patent disclosures influence technology classification decisions by patent examiners and how firms strategically tailor these disclosures to affect classification outcomes. Using a novel machine learning approach, we construct a measure of “greenwashing” in patent disclosures by comparing the likelihood of receiving a green technology classification based on the textual content of the claims section (which serves as a succinct, standardized articulation of the invention’s key features and legal scope) versus the detailed description section (which provides a detailed, technical explanation of the invention). Analyzing U.S. patent applications from 2011 to 2022, we find that examiners place greater weight on the claims section, especially when they are busier. This reliance creates opportunities for firms to strategically craft claims to increase the chances of receiving a green classification, even when the detailed descriptions suggest that the underlying technology is less fundamentally green. Firms are more likely to engage in such greenwashing behavior following negative environmental incidents, when incentives to appear environmentally friendly are stronger. These effects are amplified when examiners are particularly busy (and thus less able to scrutinize claims), when firms employ more sophisticated patent lawyers, and when there is heightened media attention to the firm-specific environmental incident. We also find that greenwashed patents are less likely to be cited by subsequent innovations, suggesting that misclassification likely undermines their relevance and technological impact. Overall, our findings highlight an unintended consequence of emphasizing claims over detailed descriptions to reduce information processing costs: this practice facilitates strategic manipulation, or greenwashing, in patent disclosures.
