Structural Similarity and the Persistence of DEA Benchmarks in Regional Innovation Systems

Regional innovation policy requires well-founded choices of regions for comparative learning. This study examines whether similarity in economic structure helps identify persistent innovation benchmarks across 85 Russian territories in 2019–2021. Employment shares describe economic structure, while data envelopment analysis (DEA) relates innovation expenditure to innovative output in the following year. Structurally selected benchmarks are compared with alternative approaches, including random reference sets. We distinguish ratio retention (a sustained advantage in innovative output relative to expenditure) from projection participation (the possibility of contributing to the same recipient’s later optimal DEA projection). The latter criterion is exploratory. In the main specification, ratio retention occurs in 78.3% of initially selected peer–recipient pairs, while both conditions hold in 55.1% (joint retention). Structural selection shows no clear persistence advantage over random reference sets. Sustained relative performance therefore does not ensure continued DEA reference status. For regional authorities, the framework supports the periodic reassessment of comparison regions and the selection of cases for closer investigation of innovation performance. It does not establish the effects of policy transfer. Broad sector categories, nominal monetary indicators and a single subsequent evaluation window limit generalization.