Knowledge subsystems and innovation performance of Brazilian cities (2012–2021): synthetic indicators based on the P2-distance method

This dataset contains a municipal-level panel covering 5,567 Brazilian cities from 2012 to 2021, of which 133 are classified as central cities and 5,434 as peripheral cities, following the urban hierarchy of the REGIC study (Regions of Influence of Cities, IBGE). The dataset includes three synthetic indicators computed annually for each city through the P2-distance (DP2) method: (i) Innovation Performance (DI), aggregating patent counts (INPI), exports and imports of high- and medium-high-technology products (Comex Stat/MDIC), GDP per worker growth (RAIS/MTE), and gross value added growth (IBGE); (ii) Knowledge Capitalization (CAP), aggregating specialization, diversification, and competition indices computed from formal employment records (RAIS/MTE); and (iii) Knowledge Generation (GER), aggregating graduate students, faculty, and research programmes (GEOCAPES/CAPES), education firms and employed population with higher education (RAIS/MTE), and the locational quotient of knowledge-intensive business services (KIBS). The file also provides the linkage of each peripheral city to its central place, the centrality level of central cities (low, medium, high) obtained via K-means clustering, and a geographic contiguity flag indicating whether the peripheral city shares a border with its central place. All indicators were derived exclusively from public domain sources: INPI (https://www.gov.br/inpi/pt-br/central-de-conteudo/estatisticas), Comex Stat/MDIC (https://comexstat.mdic.gov.br/), RAIS/MTE (http://pdet.mte.gov.br/), IBGE — Municipal GDP and REGIC 2018 (https://www.ibge.gov.br/), and GEOCAPES (https://geocapes.capes.gov.br/geocapes/). Data preparation and the construction of the synthetic indicators were performed in R.