Production Function Based on Input–Output and Growth Rate Indicators as a Tool for Assessment of Innovation Climate in Russian Regions

Liudmila Samoilova () and Dmitry Rodionov
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Liudmila Samoilova: Saint Petersburg Institute (Branch), All-Russian State University of Justice, 199178 Saint Petersburg, Russia
Dmitry Rodionov: Institute of Industrial Management, Economics and Trade, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia

Economies, 2022, vol. 10, issue 12, 1-28

Abstract: Assessment of the innovation climate in Russian regions is a priority. Given the uneven socio-economic development of the federation subjects, it is essential to determine their readiness for the transition to an innovative course. However, due to the high degree of differentiation in the socio-economic development of Russian regions, when using methods based solely on tracking indicators, there is a decrease in the objectivity of the assessment. This is caused by a significant spread in the values of the indicators, which provokes the distortion of the final calculations. To avoid the subjectivization of calculations, it is appropriate to supplement them with the construction of functional dependencies. In this regard, the purpose of the study was to substantiate hypotheses about the possibility of using the production function to assess regions’ innovation climate. The process of evaluating the innovative climate of meso-territories is implemented using the methods of statistical analysis: absolute and relative statistical values, indices, interquartile range, time series, and regression analysis. As a result of building production function models in volumetric and temporal records, arguments are formulated regarding its use to characterize innovative conditions. In the study, an additional character of the production function was established; it is possible to use it, but with several assumptions. The obstacles to innovative transformations in the Russian regions are formulated based on the calculations. The scientific contribution of the authors comes down to substantiating the expediency of combining heterogeneous methods of analysis in identifying innovative conditions in Russian regions; it is proposed to combine both a generally recognized tool for these purposes—indicative analysis and a less common one—a production function.

Keywords: innovation economy; innovation climate; differentiation of innovation in meso environments; assessment; production function (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2022
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