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The paper offers a theoretical analysis of long-run economic growth as an outcome of structural changes. We model the microeconomic behaviour of firms in the final good and capital sectors, and the evolution of classes of workers/consumers. We carefully craft economic behaviour onto empirical evidence, and solve the model numerically. The results illustrate the microeconomic properties of the simulated growth patterns. In particular, we observe and explain the interactions between technological change, firm organization, income distribution, consumption behaviour and growth. We confirm the relevance and interdependence of these structural changes, and underline their microeconomic sources.

Analysts are rapidly developing methods to map publications to SDGs in the face of policy demands. However, as reported by Armitage et al. (2020), a high degree of inconsistency is found when comparing the bibliometric corpora obtained with different approaches. These inconsistencies are not due to minor technical issues, but instead they represent different interpretations of SDGs. Given the variety of understandings regarding the relationship between research and SDGs, we propose that bibliometrics analysts should not assume that there is one single, preferred or consensus way of mapping SDGs to publications. We propose instead that, since different stakeholders have contrasting views about the relationships between science and SDGs, the contribution of bibliometrics should be to provide a plural landscape for stakeholders to explore their own views. We describe here the beta-version of an interactive platform that allows stakeholders to scrutinise in a global map of science the clusters potentially related to SDGs.

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