Almost by definition, radical innovations create a need to revise existing
classification systems. In this paper, we argue that classification system
changes and patent reclassification are common and reveal interesting
information about technological evolution. To support our argument, we present
three sets of findings regarding classification volatility in the U.S. patent
classification system. First, we study the evolution of the number of distinct
classes. Reconstructed time series based on the current classification scheme
are very different from historical data. This suggests that using the current
classification to analyze the past produces a distorted view of the evolution
of the system. Second, we study the relative sizes of classes. The size
distribution is exponential so classes are of quite different sizes, but the
largest classes are not necessarily the oldest. To explain this pattern with a
simple stochastic growth model, we introduce the assumption that classes have a
regular chance to be split. Third, we study reclassification. The share of
patents that are in a different class now than they were at birth can be quite
high. Reclassification mostly occurs across classes belonging to the same
1-digit NBER category, but not always. We also document that reclassified
patents tend to be more cited than non-reclassified ones, even after
controlling for grant year and class of origin