Re-Evaluating the Knowledge Production Function for the Regions of the Russian Federation
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Re-Evaluating the Knowledge Production Function for the Regions of the Russian Federation Jens K. Perret1
Received: 20 March 2016 / Accepted: 9 March 2017 © Springer Science+Business Media New York 2017
Abstract The present study picks up on the aspect of knowledge generation—a key part of every national innovation system—in the context of the Russian Federation. Following Fritsch and Slavtchev (2006), a knowledge production function can be used to account for the efficiency of an innovation system. In detail, this study implements a panel quantile regression estimation approach and thus presents a novel approach in studying national innovation system and, more specifically, their efficiency. In particular, a non-linear knowledge production function is estimated to quantify for a possible non-linear impact of knowledge inputs on domestically—sing patents from the Russian Patent Office—and internationally—using patents from the European Patent Office—oriented knowledge output. Using regional data, it is shown that a non-linear impact of the inputs especially on Russian domestic patents can be found. The results offer new insights into the structure of the Russian innovation system as a threshold is identified where the innovation system switches from increasing returns of researcher input to decreasing returns. This implies that only smaller research systems work efficiently, and starting from a size of approximately 900 researchers, their efficiency steadily decreases. Keywords Russian federation · Knowledge · Knowledge production function · Knowledge generation · Quantile regression · Regional economics
Jens K. Perret
[email protected] 1
International School of Management, Im MediaPark 5c, 50670 Cologne, Germany
J Knowl Econ
Introduction In 1992, Lundvall introduced the concept of the national innovation system (NIS) into economic literature providing a comprehensive frame of reference to analyze the innovation dynamics in economies. According to the OECD’s 1999 report on national innovation systems, regional innovation systems are the essential building blocks of any NIS. The analysis of an NIS is therefore inherently of a regional nature. At the core of every NIS, two concepts are of central importance: the generation and the diffusion of innovations and ergo knowledge; on the one hand, inside the system itself and on the other across the system’s borders. This concept is illustrated fittingly in OECD (1999). The present study picks up on the aspect of knowledge generation in the context of the Russian Federation (RF).1 Over the last two decades, the RF experienced a transition from a Soviet centrally planned economy to a market economy,2 However, it can still not be considered a fully developed knowledge society comparable to Western European economies where the terms of knowledge society or knowledge economy can be interchanged with the term NIS. Komkov et al. (2005) provides a first report on Russia’s transition to a knowledge society. In this context, the Russian Federation is an interesting subje
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