Innovation indicators in the context of narrative economics

The analysis of innovation systems is a demanding task, which needs to be tackled comprehensively. Their modelling provides an indication of the formal innovative performance while the narrative analysis helps to examine relevant judgments about the rules and institutions that are key to the development of innovations. The study of the complementarity and noncomplementarity of the conclusions obtained using both approaches is likely to contribute to a deeper understanding of the Russian innovation system functioning. The paper aims to analyse how the content and spread of the national innovation system narratives are interrelated with the modelling of the Russian innovation system and the most important indicators of its func tioning. Methodologically, the research takes advantage of the methodological synthesis of nar rative economics and original institutionalism. The research methods include narrative analysis, cointegration analysis of mutual influence between narratives and innovation indicators. The authors identify peculiar features of innovation systems’ modelling, analyse the texts, stories and other sources containing narratives about the Russian innovation system development, and based on this discover the relationship between the spread of certain narratives (the frequen cies of word groups “innovative technologies”, “technology development”, “innovation activities”, “technology implementation”, “scientific schools”, “innovation policy”, “science and technology”) and innovation indicators (share of innovative goods, works, services in the total volume of goods shipped, works performed, services provided; share of expenditure on innovation activi ties in the total volume of goods shipped, works performed, services provided). The analysis also shows cointegration between the frequency of search queries “use of patents” and innovation indicators “number of patent application” and “number of patents issued”. The authors point to a number of limitations related to the innovation system modelling. There are some typical limitations such as availability and reliability of statistical data, methodological heterogeneity of statistics, model specification, etc., as well as some specific ones including a broad, ambiguous definition of the national innovation system, differences in the approaches to defining princi pal determinants, innovations immeasurability, considerations of the system connections and economies of scale, etc. Thus, the findings confirm the need for a narrative study in order to achieve an in-depth understanding of complex economic processes.