Russia's Innovation Promotion Policies: Their Evolution, Achievements, Problems and Lessons

Kuzyk, Mikhail; Simachev, Yuri

doi:10.2139/ssrn.2318359

Cited by 1 publication

(2 citation statements)

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“…The ongoing Russian public policy to stimulate firms' development through a substantial variety of instruments for different target groups (e.g. Kuzyk, Simachev (2013)) 5 is characterized by a strong emphasis on sufficiently large and long-operating companies. Such a result is not surprising, especially not for the Russian economy.…”

Section: Discussion and Policy Implicationsmentioning

confidence: 99%

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Assessing the impact of public funding and tax incentives in Russia: Recipient analysis and additionality effects evaluation

Simachev

Kuzyk²,

Zudin³

2017

JRTPE

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of methodologies concerning the assessment of science-technology and innovation policies (Crespi et al. 2011). Objectives of the innovation policy evaluation have become more complex due to the need of recording a substantial amount of different factors and effects, including non-economic ones. The evolution of evaluation techniques develops in several directions (OECD 2012):(1) establishment of frameworks and conditions, formation of the evaluation culture, and -sometimes -the development of assessment legislation; (2) expansion of assessing institutions and their coordination, distribution and improvement of assessment practices; (3) formation of the base and infrastructure for evaluation -determination of standards and methodologies, combining assessment with Key Performance Indicators (KPI), accumulation of policy implementation data, support for the evaluation expert community. The following features of a modern evaluation practice of innovative instruments can be distinguished:(1) regular assessment, cross-country comparison of results; (2) long observation periods (over 10 years), maintenance of extensive detailed statistical databases used for performance evaluations; openness of assessment procedures to capture new effects. (3) the complexity and ambiguity of estimates (e.g. considering substitution effect), presence of significant time lags over output effects (4-6 years), high heterogeneity of the impact of incentive mechanisms; substantial econometric problems; preparation and submission of guidelines on principles and problems of evaluation; (4) openness, publicity of assessment results; practical use of the assessment results for decision-making at government level -the spread of best practices; drawing lessons: in particular, making decisions to stop, clarify or expand various programs, mechanisms and instruments aimed at fostering innovation activity It must be admitted that the Russian public innovation policy evaluation system in comparison with the best foreign examples turns out to be quite imperfect and unbalanced -due to the excessive emphasis on direct results of support and lack of attention to the process of drawing lessons. ASSESSING THE IMPACT OF PUBLIC FUNDING AND TAX INCENTIVES IN RUSSIA: RECIPIENT ANALYSIS AND ADDITIONALITY EFFECTS EVALUATION 1 YURI SIMACHEV , MIKHAIL KUZYK AND NIKOLAY ZUDIN ABSTRACT So far a considerable number of studies have used the concept of additionality as basic evaluation approach but none of them paid attention to additionality effects of the Russian innovation policy yet. In this study we performed a microeconomic evaluation of the industrial firms' public innovation support in Russia focusing on its two key toolbox elements: direct funding and tax incentives. Based on the data from a questionnaire survey of top executives of Russian manufacturing firms from 2015 we identified and evaluated the profiles and the performance of recipients of direct funding and tax incentives. We also assessed the "relative" additionality -the additionality of a concrete ins...

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Section: Discussion and Policy Implicationsmentioning

confidence: 99%

“…The usage of these two instruments for the analysis is quite straightforward as they are traditionally viewed as key elements of the national innovation policy toolbox (e.g. David et al (2000); OECD (2015)) and are well ahead of other instruments in terms of "coverage" and number of firms supported (Kuzyk, Simachev 2013).…”

Section: Objectives Methods and Datamentioning

confidence: 99%