Can knowledge reclassification accelerate technological innovation?

Technological knowledge evolves not only through the generation of new ideas, but also through the reinterpretation of existing ones. Reinterpretations lead to changes in the classification of knowledge, that is, reclassification. This study investigates the relationship between reclassification and the rate of technological change both empirically and analytically. Drawing on patent data as a proxy for technological knowledge, I discuss two empirical patterns: (i) more recent patents are more likely to get reclassified and (ii) larger technological classes acquire proportionally more reclassified patents. These patterns are then used to formulate an analytical model of knowledge accumulation, which can be solved exactly to describe the relationship between reclassification and growth rates in detail and to make further predictions about related knowledge quantities. These predictions are supported across all major technology domains, implying a strong link between reclassification and the pace of technological advancement. In sum, the model allows for a better understanding of both the magnitude and shape of technological growth patterns. More generally, it connects various seemingly unrelated knowledge quantities, providing a basis for knowledge-intrinsic explanations of growth patterns.