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Finance and Management
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Gudkova , A.A. (2025). Fiscal Response of SMEs: Methodology for Assessment and Practical Application (Case Study of Perm Krai). Finance and Management, 3, 33–60. https://doi.org/10.25136/2409-7802.2025.3.75414
Fiscal Response of SMEs: Methodology for Assessment and Practical Application (Case Study of Perm Krai)
DOI: 10.25136/2409-7802.2025.3.75414EDN: MJQUHXReceived: 08/05/2025Published: 08/12/2025Abstract: The fiscal response of SMEs is a key indicator for evaluating the effectiveness of government support and assessing its impact on a region's economic development. Defined as the ratio between the volume of budget investments in the SME sector and the resulting tax revenues, this metric allows for an assessment of the direct efficiency of public expenditures. Importantly, it quantifies how many rubles of tax revenue are generated per ruble of budget investment. Analysis of fiscal response helps identify the relationship between financial support volumes and growth in tax revenues, facilitating more informed allocation of budget resources and optimization of government support measures. The study employs comparative analysis and synthesis of existing approaches to evaluating SME support effectiveness, develops a coefficient for assessing expenditure efficiency, and conducts empirical analysis through collection and examination of budgetary and tax reporting data to evaluate the structure of government support and its impact on fiscal response. A comparative analysis method is also used to match support volumes with tax revenues. The research proposes a quantitative metric—the "SME Fiscal Response Coefficient"—as a tool for evaluating support effectiveness, with calculations based on data from Perm Krai for the period 2019–2024. Evaluating fiscal response requires a comprehensive approach that considers multiple factors influencing SME tax revenues, including expenditures on SME support programs and initiatives, tax expenditures resulting from incentives, and costs associated with maintaining support infrastructure. The study uses tax revenues from SMEs as the primary outcome measure of government support effectiveness. Investigating fiscal response not only assesses the efficiency of existing support measures but also identifies potential improvements, optimizes the structure of government assistance, and develops more effective mechanisms to stimulate SME development. These efforts contribute to increased tax revenues and sustainable economic growth in the region. The methodology and findings provide policymakers with actionable insights for refining SME support programs and maximizing their economic impact. Keywords: fiscal response, SME, government support, expenditure efficiency, tax revenues, Perm Krai, budget expenditures, regional economy, performance evaluation, tax incentivesThis article is automatically translated. You can find original text of the article here. Introduction Small and medium–sized enterprises (hereinafter referred to as SMEs) are a factor in the development of market relations and play a significant role in the socio-economic development of countries, as SMEs perform a number of important functions, namely, create additional jobs, increase investment activity, contribute to GDP and GRP, contribute to the formation of a competitive environment, free pricing and It replenishes budgets of various levels through the payment of taxes. Every year, small business generates over 50% of GDP in developed countries such as China, the United States, and the countries of Europe I, II. However, the high level of participation of SMEs in the economies of developed countries is due to several factors. First, the process of deindustrialization has led to the growth of the service sector, which is dominated by small firms. Secondly, there are significant differences in the definition of criteria for classifying companies as small and medium-sized businesses. For example, the maximum number of employees who qualify an enterprise as an average is 1,000 in China, 500 in the United States, while in Russia this threshold is only 250 employees I-III. Such differences in the number of employees in the criteria for classifying SMEs make it difficult to objectively compare the real contribution of SMEs from different States. The use of unified international standards would make it possible to adjust the assessment of the role of Russian SMEs. According to a number of researchers, if a unified approach were applied, the Russian share of SMEs in GDP would increase from the current 27% to the level of 30-40%. Nevertheless, despite the potential increase in the indicator, it is not able to radically change the situation and confirm the leading role of SMEs in the national economy. Small business opportunities in Russia are not being fully exploited, so at the moment the indicators in the Russian Federation are significantly lower. As of mid-2025, over 6.6 million small and medium-sized enterprises are registered in the Russian Federation, and the number of their employees is more than 15 million people III. The share of small and medium-sized enterprises in the gross domestic product of the Russian Federation in 2024 is 21.7%IV. In order to maintain and improve current indicators and solve the problem of insufficient impact on the country's development of such a segment of the economy as small and medium-sized businesses, government authorities implement state support measures in the format of implementing state programs through co-financing from federal and regional budgets. State support for SMEs is a multifaceted set of measures covering a wide range of tools: from administrative assistance and financial incentives to property support, consulting services, tax benefits and measures aimed at expanding the sales market for products and services of SMEs. Financing of SME development and support programs is provided from four sources (federal, regional, local and extra-budgetary budgets), with the main share coming from the federal budget. In the context of the federal budget deficit for the last 3 years in a row, the issue of efficient use of funds has become particularly relevant, since the allocation of additional financial resources to support and develop SMEs does not always lead to a proportional increase in the contribution of the SME sector to the country's economy, employment growth and increased tax revenues. This fact highlights the need to develop a new indicator for assessing the effectiveness of support, reflecting the contribution of SMEs to the sustainable development of the regions. Given the differences in the level of development of small and medium-sized enterprises across the regions of Russia, it is necessary to conduct a comprehensive analysis of the costs of implementing support measures and compare them with the economic effect in the form of tax revenues to the budget of the region. The purpose of this article is to develop and test a methodology for calculating the SME fiscal response coefficient using the example of the Perm Region, which can become a unified and rational tool for comprehensive assessment, development programs, implementation of measures to support and manage the SME sector in the region's economy. Materials and methods. The following methods were used in the course of the study: - theoretical analysis, including a comparison and generalization of methodological approaches to assessing the effectiveness of SME support presented in the scientific literature; - development of a coefficient for evaluating the effectiveness of SME support costs; - an empirical analysis based on the collection, systematization and analysis of budget and tax reporting data, which makes it possible to assess the structure of government support and its impact on tax revenues from SMEs, as well as identify factors contributing to an increased fiscal response; - proportional distribution method (or proportional breakdown method). The proportional distribution method is a kind of indirect method, when the total indicator (the total amount of personal income tax and income tax) is divided into parts in proportion to the known shares obtained from another source (data provided in the news portal); - a comparative analysis method that allows comparing the volume of government support for SMEs and tax revenues from this sector of the economy in different time periods and identifying the dynamics of the fiscal response. Literature review The current system for assessing the effectiveness of state support for small and medium-sized businesses is characterized by fragmentation, focusing mainly on monitoring individual indicators and activities. This approach certainly allows us to solve tactical tasks, but it limits the ability to form a holistic view of the impact of support on the SME sector and, as a result, makes it difficult to optimize and redirect resources. In development programs and project passports, an increase in the number of people employed in the SME sector has traditionally been the main criterion for effectiveness. However, a more objective assessment of efficiency allows for an approach that takes into account tax revenues reflecting the contribution of SMEs to the region's economy. An analysis of the literature shows a lack of empirical studies evaluating the effectiveness of government spending on business development, as measured by the fiscal effect – an increase in tax revenues to the budget. Therefore, the development of new methodological approaches for assessing the effectiveness of government policy in the field of SME support is becoming an urgent task. To date, the scientific community has been divided into 5 groups, each of which uses different approaches to assessing the effectiveness of SME support and its level of development. Representatives of the first group (Zhukova I.A., Ladygin V.V., Savchishkina E.P., Grazhdankin V.A., Lukyanova T.V., Orlova L.A., Romanenko E.V., Popov S.A., Buev V.V., Migin S.V., Shestoperov O.M., Smirnov N.V., Nemets A.V., Kremin A.E., Bykova N.V., Chivirev I.V., Ogneva D.M., Baranov D.N.) evaluate efficiency through the level of entrepreneurship development in the region's economy, using methods based on the calculation of integral indices [1-16]. The advantage of this approach is the ability to combine various indicators and metrics into a single numerical indicator, which simplifies monitoring the state of the sector and allows for comparative analysis with other regions. However, this approach may not take into account the influence of external factors and the specifics of individual enterprises. The second group, represented by Yakovlev A.A., Freinkman L.M., Ershova N.V., Agalyan A.A., Prokhorenkov P.A., Reger T.V., Okhrimenko, A.V., Gachegov M.A., Skopin S.A., as well as foreign researchers (Li, Rama, E. Autio and G. Rannikko), prefers preference for modern assessment approaches based on the use of technical software for statistical (correlation and regression) analysis, taking into account the elimination of systematic differences between the compared groups [17-22]. The key characteristics of enterprises that have received support are compared with similar indicators of firms from the control group that are not covered by support. The advantages include the ability to identify causal relationships between various factors and the effectiveness of SME support. However, it should be noted that such approaches can be sensitive to the quality of the source data and require significant computing resources. Separately, we will highlight the evaluation model using the mathematical apparatus of fuzzy set theory, fuzzy logic and a fuzzy inference system proposed by Andreev S.V. This model of fuzzy evaluation of the effectiveness of regional financial support, characterized by ease of use and suitability for automation, provides an adequate assessment of the impact of support on the activities of SMEs, which is confirmed by empirical data in the author's work [23]. The third group, including Vasilyeva M.V., Orlov M.V., Toreev V.B., Voronovskaya O.E., Kuzmina A.I., Sullivan R.O., Kosheleva N.A. and Yaroshenko T.P., in their works considered measuring the effectiveness of budget expenditures based on achieving the targets set in government programs [24-28]. This approach certainly increases the transparency and controllability of budget spending, as the results are linked to predefined and measurable indicators. However, its significant limitation is that it does not always take into account indirect effects that occur beyond the planned results, and, most importantly, it does not allow assessing the real impact of government support itself on long-term socio-economic development, limiting itself to stating whether or not the goals defined in strategic documents have been achieved. The fourth group: Belyaev A.N., Derman D.O., Tsygankov D.B. consider the level of administrative pressure on the SME sector, the effectiveness of organizing the coordination work of authorities using the survey method (D.J. Story) [29-30]. This approach should take into account the high risk of errors in data collection and interpretation of the results obtained, related to the subjectivity of assessments and possible bias of respondents. The key advantage of this approach is the ability to identify non-financial factors affecting SME development, such as administrative barriers and the quality of public administration. However, it should be borne in mind that survey methods are subjective and can only reflect the perception of entrepreneurs, not the real situation, and that the analysis of administrative pressure does not directly assess the economic effectiveness of government support. Using the survey method, Shikhverdiev A. P., Vishnyakov A. A., and Oganezova N. A. analyze the effectiveness of government support mechanisms for SMEs in Arctic conditions. Their research reveals both internal constraints and external obstacles hindering the development of this sector, and offers tools for improving the entrepreneurial ecosystem [31]. The same group includes the methodologies developed by Srhoj et al., which focus on determining the degree of importance of grants for new SMEs and developing criteria for selecting SMEs in the allocation of state support funds. The impact of grant programs on the success of new SMEs is assessed using a rating assessment, enterprise reporting, and employee surveys) [32]. This approach makes it possible to identify the SME entities that will demonstrate the best results after receiving grant support, and to record real changes in the success rates of companies due to participation in support programs (increased profits, turnover and number of employees, increased tax payments). The methodology makes it possible to determine the effectiveness of individual support measures and evaluate the results of the activities of SMEs. However, a significant limitation is the difficulty of establishing a causal relationship between grant support and the observed changes, since the results of SME activities are influenced by many other factors unrelated to participation in the program. Moreover, the methodology is limited to evaluating a specific grant support measure and does not take into account the full range of support measures provided to SMEs in the region, which does not allow for a holistic view of the effectiveness of regional policies to support small and medium-sized enterprises. Kolodnyaya G.V. suggests evaluating the effectiveness of SME support by analyzing the activities of development institutions and organizations providing information, marketing, legal, educational and consulting support, as well as product certification services and assistance in entering foreign markets. The author argues that a key factor in increasing the competitiveness of the SME sector has been the revision of the state support policy, which has shifted the focus from direct financial injections to stimulating development. Such a transition is recognized as a more effective approach to long-term development [33]. The fifth group: American authors Adaman F., Devine P., Fuller T., Moran P. propose to constantly monitor and evaluate the effectiveness of all budget expenditures [34-35]. The tool allows you to use a significant set of indicators-factors and a complex rating mechanism. A similar evaluation system exists in Russia (results-based budgeting). The assessment of the effectiveness of the use of budgetary funds goes beyond the traditional cost-benefit criteria and should take into account not only the ratio of the results achieved and the resources spent on the implementation of the strategic goals of the political system, but also ensuring state interests. This means that the effectiveness of budget expenditures should be considered in the context of broader political and strategic goals, and not only in terms of economic efficiency. This approach makes it possible to allocate budget resources depending on the achievement of the goals and priorities of socio-economic policy and to make changes to the long-term financial allocation plan for a three-year period in each subject of the Russian Federation. Both in Russia and abroad, scientific thought is aimed at developing and improving methods that allow an objective assessment of the impact of government support on the development of SMEs and their contribution to the economy. Researchers are increasingly coming to the conclusion that it is necessary to use comprehensive methods that take into account the direct and indirect effects of government support, as well as social and environmental aspects. There is a growing interest in using microeconomic data to more accurately assess the impact of government support, and quantitative methods are also being actively used. At the same time, there are differences in the focus of research: foreign studies often focus on assessing the impact of individual state support tools on specific performance indicators of SMEs. Historically, this has been due to a more developed system for collecting and processing statistical data on SME activities, as well as increased access to this data for researchers abroad. In Russia, access to such information has been limited for a long time, but the situation is changing: since December 2020, the Federal Tax Service of Russia has been maintaining a register of recipients of SME support, making this data publicly available. Current trends in scientific thought in Russia and abroad in the field of methods for evaluating the effectiveness of government support for SMEs have much in common, but there are also significant differences related to the level of economic development, the availability of data, and the degree of interaction between science and practice. It is worth noting that the selection of a research methodology and the choice of an algorithm for evaluating effectiveness significantly affects the final results and their interpretation: if the authors use the most complex econometric methods, the results can be considered more reliable. The authors of such studies conclude that government support has a positive impact and contributes to the development of SME recipients of support. It is advisable to emphasize that newer approaches to performance assessment include the use of sophisticated models, which has become possible due to the development of digital technologies for the creation, processing and analysis of large amounts of data. The problem with assessing the effectiveness of budget expenditures to support MSMEs is that there is a wide variety of points of view when determining performance indicators, but there is no single criterion to identify the budgetary effect of support. At the same time, performance indicators can be subordinated not only to objective factors, but also to subjective factors. Objective data include quantitative data, such as the number of supported SMEs, employment growth, tax revenues, and other measurable indicators. However, along with these factors, there are subjective components that influence the perception of the results of the SME support and development policy. Examples of subjective factors include: assessment of effectiveness based on personal impressions (surveys of SMEs); public perception of the degree of transparency in spending; assessment of administrative pressure and regulation of the SME sector by the state. The variety of approaches used is due to the constant development and adaptation of forms and types of support caused by the changing economic situation, crisis phenomena, the emergence of new trends and other significant influencing factors. An analysis of domestic and foreign studies has revealed that a significant part of the work is devoted to assessing the level of development of SMEs using quantitative indicators and index methods. Another part of the research focuses on clarifying the concept of "effectiveness of budget expenditures to support SMEs" and analyzing the impact of budget expenditures within the framework of current quantitative performance indicators included in government programs. However, it should be noted that most of these approaches do not take into account the budget effect, i.e. the impact of the support provided on the increase in tax revenues and the formation of the revenue base of the budget. This limits the possibility of a comprehensive assessment of the effectiveness of government support and requires the development of new methodological approaches that take into account the fiscal returns on investments in SMEs. Thus, there is a need to clarify the theoretical and methodological foundations for assessing the effectiveness of budget expenditures to support SMEs, including the development of an indicator that takes into account both support costs and income received from the SME sector. Construction of the coefficient "Fiscal response of SMEs" To calculate the "fiscal response of SMEs" coefficient, it is proposed to use both publicly available data and information that requires a request to government authorities and the Federal Tax Service (FTS) in order to obtain a more complete and objective assessment of the effectiveness of SME support. This will make it possible to take into account all the key factors affecting the development of the sector and draw informed conclusions. However, when evaluating the effectiveness, the researcher may not have access to all the data described in the algorithm for calculating the SME Fiscal return coefficient shown in Fig. 1.
Figure 1 – Algorithm for calculating the coefficient "Fiscal response of SMEs" When estimating the cost of supporting SMEs, the costs of implementing the State SME Development Program (RPR) and regional projects and activities (RRP) are taken into account. Tax expenses (NR) include the amount of tax arrears due to the application of preferential rates in the region (USN, PSN, corporate income tax, corporate property tax, transport tax, incentive benefits (PIP) and other benefits). To calculate the total cost of supporting SMEs, it is necessary to take into account the cost of the support infrastructure. These include the costs of financing the following institutions: innovation funds; regional venture funds; information and consulting agencies; guarantee funds; microfinance funds; centers for innovative development and cluster initiatives; regional centers for innovation and technology transfer; business incubators; technology parks; export centers; SME support agencies and other organizations. In case of incomplete data on tax expenditures and/or support infrastructure expenditures, use the available information. When assessing income from the SME sector, taxes coming from both the application of special tax regimes and budgets of all three levels are taken into account. In particular, the federal budget receives personal income tax, corporate income tax, VAT and excise taxes; regional taxes include corporate property tax and transport tax; local taxes and fees: land and tourist taxes and trade levy. Taxes paid only by SMEs are used in the calculation. In case of incompleteness of data on tax receipts, the available information should be used. Interpretation of the SME Fiscal Response Coefficient (FOM). If the FOM is > 1: Each ruble invested in support of SMEs brings more than one ruble in the form of tax revenues to the budget. This indicates the high efficiency of government support, contributing to the growth of tax revenues and overall economic development. If FOM - inefficiency of individual support measures. Support tools do not bring the expected results; - mismatch of support areas to business needs. It is possible that the industries or areas of activity that have the greatest potential for growth and tax revenues are not supported; - delayed support effect, if it takes more time to realize the effect of support measures; - The weak economic stability of the region is due to its high dependence on crisis-prone industries. Mono-specialized regions, due to their structure, are particularly vulnerable to economic shocks, and even an effective SME support system is not always able to offset the negative effects of sectoral crises on tax revenues; - other factors affecting tax revenues. For example, the general economic conditions in the region, the demographic situation, and the investment climate. If support does not pay off, it is necessary to conduct a detailed analysis of the reasons, including an assessment of the impact of support on other socio-economic indicators, and take corrective measures to increase efficiency and/or reallocate resources. It is also worth noting that tax revenues from the SME sector are influenced by many factors, not just government support. In particular, the general economic situation in the region and the country, changes in tax legislation, demographic trends, the investment climate, the level of infrastructure development and the competitive environment can have a significant impact on the incomes of SMEs and, consequently, on their tax deductions. Therefore, when assessing the effectiveness of government support, it is necessary to take into account the influence of these external factors and conduct a comprehensive analysis, including various indicators. With accurate data on tax revenues from the SME sector and the total cost of supporting it, regional authorities will be able not only to assess current efficiency, but also to predict the economic impact of various scenarios for the development of the sector, as well as optimize the allocation of budget resources to maximize returns. In this case, the subject of the federation will be able to choose which program should be supported. The proposed formula for the coefficient "Fiscal response of SMEs" (Fig. 1) makes it possible to assess the effectiveness of using budgetary resources and determine how justified the costs of supporting SMEs are in terms of replenishing the consolidated budget of the region. Moreover, the analysis of this coefficient in dynamics makes it possible to identify trends – an increase or decrease in tax returns from each ruble invested in SMEs – which opens up the possibility for timely adjustment and optimization of support measures. The FOM coefficient can be used as a management tool to solve a number of tasks.: - evaluation of the effectiveness of various measures to support SMEs: The FOM allows you to compare different types of support and identify the most effective ones.; - making informed decisions about the allocation of budget funds: the FOM allows you to direct resources to those programs and tools that provide the greatest return in the form of tax revenues; - Monitoring and adjusting the SME support policy: The FOM allows you to track the dynamics of the effectiveness of support measures and make the necessary changes in a timely manner.; - increase transparency and controllability: The use of the FOM makes the decision-making process on SME support more transparent and controlled, as the effectiveness of programs is assessed on the basis of objective data. Calculation of the FOM coefficient using the example of the Perm Region The choice of the study period is due to the fact that the implementation of the National Project "Small and medium-sized entrepreneurship and support for individual Entrepreneurial Initiative" began in 2019, that is, government support increased during this period, as the development of entrepreneurship has become one of the key strategic goals. This period also makes it possible to assess the dynamics of the activities of SMEs and, consequently, the government's contribution to the development of entrepreneurship in the region. According to the presented algorithm, the first calculation block includes an estimate of the cost of supporting SMEs.: - expenses for the State SME Development Program (RPr); - expenses for the implementation of regional project activities; - tax expenses (HP - lost tax revenues due to the application of tax benefits); - the cost of maintaining the support infrastructure (RINFR). Initially, we will collect data on government support expenditures for SMEs in the Perm Region by year. Table 1 shows data on the volumes and sources of financial support for the Small and medium-sized Business Development subprogram in the Perm Region. Table 1 – Volumes and sources of financial support for the program "Development of small and medium-sized enterprises" in the Perm Region in 2019-2024, million rubles
Source: compiled by the author on the basis of data V, VI. Significant changes are taking place in the financing structure. The share of the federal budget is decreasing (especially pronounced in 2022-2023), which indicates a change in the priorities of the federal center or insufficient activity of regional authorities in attracting federal funds. At the same time, the share of the regional budget is increasing, which indicates the strengthening of the region's role in supporting SMEs. Extra-budgetary sources also show volatility, which is probably related to changes in investment activity and the availability of credit resources. The lack of funding from local budgets throughout the analyzed period raises questions about the participation of municipalities in supporting SMEs and the implementation of the principle of subsidiarity in this area. It is worth noting that similar trends are observed in almost every constituent entity of the Russian Federation, except for subsidized regions. Further, Table 2 shows the costs of implementing regional policy and implementing regional projects in the field of development and support of small and medium-sized enterprises in the region. Table 2 – Volumes and sources of financial support for the implementation of regional policy and the implementation of regional projects in the field of small and medium-sized business development in the Perm Region in 2019-2024, mln. rubles'
Source: compiled by the author on the basis of data V, VI. In most events, the main share of financing is provided by the regional budget. This highlights the importance of regional policy in supporting SMEs and indicates the willingness of regional authorities to invest in the development of this sector of the economy. The participation of the federal budget is limited and is not permanent for all events. Federal funding is mainly directed towards the project "Creating conditions for an easy start", namely subsidies from the Perm Entrepreneurship Development Fund non-profit organization (providing a range of services to citizens who want to do business) and financial support in the form of grants to SMEs that are social entrepreneurs or young entrepreneurs under 25 years of age. Table 3 below shows the costs of measures to ensure the availability of financial resources for SMEs and the provision of subsidies for the development and support of small and medium-sized enterprises in the region. Table 3 –Volumes and sources of financial support for measures to increase the availability of financial resources for SMEs and the provision of subsidies for the development and support of small and medium-sized businesses in the Perm Region in 2019-2024, million rubles
Source: compiled by the author on the basis of data V, VI. According to Table 3, we note that the priority of measures to ensure the availability of financial resources, funded mainly from the regional budget and extra-budgetary sources, has been identified. There has been a steady increase in funding for these activities, while other support measures are implemented sporadically and depend on federal programs. The general trend is an increase in financial support for SMEs aimed at ensuring the availability of financial resources. The following expenses are presented in table 4: subsidies to the non-profit organization Perm Entrepreneurship Development Fund; subsidies to JSC Corporation for the Development of Small and Medium-Sized Enterprises of the Perm Territory; contributions to the authorized capital of JSC Corporation for the Development of Small and Medium-Sized Enterprises of the Perm Territory.
Table 4 –Volumes and sources of financial support for subsidies and contributions to the authorized capital of infrastructure support agencies for the provision of a range of services for SMEs in the Perm Region in 2019-2024, million rubles
Source: compiled by the author on the basis of data V, VI. According to the data in Table 4, it is possible to state the heterogeneity of support. The Perm Entrepreneurship Development Fund is mainly funded to provide information and consulting services, while the Corporation for the Development of Small and Medium-Sized Enterprises of the Perm Region receives significant contributions to the authorized capital only in certain years (2021 and 2024), which indicates the implementation of certain large-scale projects. The main financial support can be considered the financing of microloans, which is implemented on the basis of contributions to the authorized capital of JSC Microfinance Company of Perm Krai. At the same time, federal funding remains limited, and the participation of local and extra-budgetary sources also varies depending on the specific agency. It should be noted that the active involvement of extra-budgetary sources of financing for support programs and infrastructure organizations for the development of SMEs would reduce the burden on the budget and increase the total amount of funds allocated to support SMEs. The next step is to analyze the shortfall in tax revenues (tax expenditures) – the lost budget revenues that arise due to the application of tax benefits and preferences in the region. The following benefits apply to SMEs in the Perm Region: - benefits under the simplified taxation system; - income tax benefits; - corporate property tax benefits. Table 5 shows data on the volume of tax revenues falling short to the consolidated budget of the Perm Region. Table 5 – The volume of shortfall in budget revenues of the Perm Region related to the application of reduced tax rates for certain categories of SMEs in 2019-2024, million rubles
Source: compiled by the author on the basis of data VII-IX. Further, according to the calculation algorithm, it is necessary to consider the costs of maintaining organizations that provide support and tools for the development of SMEs in the region. Within the framework of this study, it was not possible to separate the costs of maintaining organizations that support and develop SMEs in the Perm Region from the costs of program activities. It should be noted that the state authorities of the subject of the federation, by virtue of their powers, have the ability to collect complete information necessary to implement the proposed algorithm for evaluating effectiveness. Now let's move on to the second block of the algorithm – the assessment of tax revenues from SMEs: - tax revenues from SMEs applying special tax regimes (NTss); - tax revenues from SMEs received by the federal budget: personal income tax, corporate income tax, VAT, excise taxes (NPFs); - tax revenues from SMEs received by the regional budget: property tax and transport tax (NPrb); - tax revenues from SMEs received by the local budget: land and tourist taxes, trade levy (NPmb). There is no separation of tax revenues from SMEs and other organizations in the open tax reporting of the Federal Tax Service (FTS), which makes it difficult to assess the direct contribution of the SME sector to the formation of the revenue side of the budget. Therefore, in order to test the methodology, it was decided to take into account tax revenues from SMEs applying special tax regimes, the average value of corporate income tax, as well as the average value of personal income tax. It is important to note that when analyzing the contribution of the SME sector to the budget system, it is necessary to take into account taxes received by the consolidated budget of the constituent entity of the Russian Federation, since financing of SME support is carried out from budgets of all levels. Tax data received by the consolidated budget of the region takes into account all levels of the budget system, as well as extra-budgetary funds (the compulsory medical insurance fund and the social insurance fund). This allows us to get a more complete picture of the economic efficiency of government support for the SME sector. Table 6 provides information on accrued and received taxes to the consolidated budget of the Perm Region. Table 6 – Accrued and received taxes to the consolidated budget of the Perm Region in the period 2019-2024, million rubles
Source: compiled by the author on the basis of data VII-XII. Due to the lack of separation of tax revenues from SMEs in the open consolidated tax reporting of the Federal Tax Service, an indirect method based on data published in regional media with reference to information from tax authorities was used to assess the contribution of SMEs to the formation of budget revenues. The total amount of personal income tax and income tax received by the budget of the Perm Region was divided in proportion to the shares indicated in the Perm XIII news portal. It is recorded that 1/3 for personal income tax and 15% for income tax falls on the SME sector. Despite the limitations of this approach, it provided a rough estimate of the contribution of the SME sector, which is necessary for further analysis. Next, the algorithm needs to assess the contribution of the SME sector to regional and local budget revenues, but such data is not publicly available. Due to the lack of open data on the contribution of SMEs to regional and local budgets, data from the Agency for the Development of Small and Medium-Sized Enterprises in the Perm Region were used for the assessment, according to which 75% of SMEs use the STS XIV. Such a preferential system exempts from paying income tax, personal income tax, VAT and property tax. Consequently, it can be concluded that SMEs make an insignificant contribution to budget revenues from these taxes, using available data on income from special regimes, income tax and personal income tax to assess them. So, an analysis of the costs of supporting SMEs and an analysis of tax revenues from SMEs has been carried out. Table 7 shows the final data. Table 7 –Comparison of SME support costs and tax revenues from the SME sector in the Perm Region in 2019-2024, million rubles
Source: compiled by the author based on data from VII-XIV. The analysis of the data in the table, carried out to identify the relationship between the costs of supporting SMEs and tax revenues from this sector, as well as to implement an algorithm for comparing these costs and revenues, allows us to assess the effectiveness of government support and identify areas for optimization. The identified problems in the system of state support are proposed to be solved using the FOM coefficient. The main problems include: - Instability of SME support costs. The pronounced volatility in the articles "Lost tax revenues due to the application of preferential tax rates in the region" and "Financing of the state program" indicates the lack of a clear strategy and a systematic approach. To solve this problem, it is proposed to develop a long-term SME support strategy with clear goals and indicators, providing predictable financing of key areas. Using the FOM will help determine the optimal level of financing for various support programs, creating a more predictable environment for SME development. - An increase in tax benefits that does not lead to a proportional increase in income. A significant increase in "Lost Tax Revenues" in 2022, not accompanied by a similar increase in total revenues from the SME sector, indicates the potential for improving the effectiveness of tax incentives. To achieve proportional growth, it is necessary to conduct a detailed analysis of tax benefits, review the conditions for their provision, focusing on stimulating priority activities and strengthening control over their use. The FOM will make it possible to assess the impact of tax incentives on budget revenues and, as a result, optimize their structure by directing support to the most profitable types of activities for the budget. Table 8 presents data on the growth rates of SME support costs and tax revenues from the SME sector in order to identify a general economic trend. Table 8 –Growth rates of SME support costs and tax revenues from the SME sector in the Perm Region in 2019-2024, million rubles and %
An analysis of the growth rates of SME support costs and tax revenues from the SME sector (2020-2024) reveals multidirectional dynamics. The decline in the income of the SME sector in 2020, coupled with an increase in support costs, indicates a crisis in the economy. The subsequent significant increase in income in 2021 (37%) with an increase in support costs (39%) indicates the effectiveness of government support measures. A sharp increase in support costs in 2022 (148%) with a slight increase in income (3%) indicates the need to review the areas of government support. The reduction in support costs in 2023 (-12%) and 2024 (-55%), while maintaining positive income growth (+21% and +20%, respectively), indicates a reduction in the dependence of the SME sector on government support and the possibility of reducing funding for large-scale support measures. Let's move on to the final stage of the assessment – the calculation of the coefficient "Fiscal response of SMEs", reflecting the ratio between budget revenues received from the SME sector and the costs of its support. Let's compare the data using the formula presented in the algorithm (divide the total amount of tax revenue from SMEs by the total cost of its support). The results are presented in table 9. Table 9 –The coefficient of "Fiscal response of small and medium-sized businesses" in the Perm Region in 2019-2024.
The obtained values of the coefficient "Fiscal response of SMEs" demonstrate volatile dynamics in the period from 2019 to 2024. A higher value at the beginning of the study period (2019 - 7.48) indicates a high return on investment in the SME sector. The decrease in the coefficient in 2020-2022 reflects the impact of external macroeconomic factors such as the pandemic and sanctions pressure. After the implementation of regional projects to increase the number of SMEs, enhanced financial support measures, and the introduction of tax incentives (reduced tax rates for STS for priority activities; preferential corporate property tax rates; preferential income tax rates). The subsequent growth in 2023 (2.87) signals a gradual recovery and adaptation of the SME sector to the new economic conditions. The volatility of the coefficient values highlights the need for constant monitoring and adaptation of government support measures to ensure its maximum effectiveness. The calculation of the developed coefficient "Fiscal response of SMEs" allows us to further assess the sluggishness of support for small and medium-sized enterprises and adjust support programs. The study revealed that the greatest expenses for supporting the SME sector are lost tax revenues due to the application of preferential tax rates in the region. Despite the fact that the growth rate of expenditures on the development of the SME sector outstrips the growth rate of income from their development, the economic effect has been positive for all 6 years. Of the measures taken by the regional authorities to develop the SME sector, most of the financing is spent on the implementation of tax benefits (lost budget revenues). It is important to note that, despite fluctuations in costs, the total amount of income from the SME sector has grown steadily throughout the period, which may indicate the sustainability of the SME sector, regardless of support measures aimed at stimulating economic growth. By 2024, the "Fiscal Response" coefficient reached 7.63, indicating that for every ruble of public investment in support of SMEs in the Perm Region, 7.63 rubles of tax revenue from this sector accounted. The costs that can be reduced without prejudice to the FOM are those that do not have a significant impact on the economic activity of SMEs in the region or have low efficiency. Examples include inefficient tax incentives, excessive administrative costs for the maintenance of support institutions, or activities that do not contribute to business development. By 2025, the Perm Region has implemented a number of measures to transform the costs of supporting SMEs, including infrastructure maintenance. The SME Development Agency has been reintegrated into the structure of the Ministry of Economic Development and Investment, which aims to consolidate resources and expertise for an integrated and coordinated approach to business development. Also, as part of the review of the cost structure, it was decided to abandon financial support on a subsidiary basis, which included subsidies to social and young entrepreneurs, as well as reimbursement of part of the costs of entrepreneurial projects. Although these expenses amounted to more than 300 million rubles, they covered less than 1% of the SMEs in the Perm Region. The released funds are planned to be redirected to other support measures. The SME Fiscal Response Coefficient (FOM) is a tool for evaluating the effectiveness of government policy to support small and medium–sized businesses. He can solve the problem of unjustified allocation of budget funds based on data analysis, rather than on political motives. The analysis of various support measures (grants, subsidies, benefits) helps to identify the most effective incentives for SME development and increase tax revenues, which leads to cost optimization and resource redistribution. The coefficient can be useful for government agencies, development institutions, entrepreneurs, and researchers, helping them develop and implement effective policies, evaluate support effectiveness, understand available opportunities, and conduct research. Increasing the FOM requires an integrated approach, including: analyzing the effectiveness of measures to support SMEs, reviewing the cost structure, optimizing tax benefits, strengthening control over the targeted use of funds and attracting extra-budgetary funding. It is important to remember that this is a long-term task that requires constant monitoring and strategy adjustments. The introduction of the FOM helps to increase the efficiency of using budget funds, increase tax revenues from SMEs, accelerate the development of the sector and create jobs. The proposed coefficient makes it possible to compare the effectiveness of SME support policies in different regions, leveling their differences. Based on data on expenditures and tax revenues from SMEs, a ratio can be calculated that allows regions to be objectively ranked and ratings of the effectiveness of investments in the SME sector to be compiled, which encourages the exchange of best practices and informed decision-making. Thus, the FOM ensures transparency of public administration, allows making informed decisions to stimulate the growth of SMEs and increase their contribution to the economy. Conclusion Thus, the article proposes an algorithm for calculating the fiscal response coefficient of small and medium-sized enterprises, which includes an estimate of the cost of supporting SMEs and income (tax revenues). The coefficient shows the overall economic effect of these investments, provides a comprehensive understanding of the relationships, the magnitude of the impact and the economic payback, which is necessary to make informed decisions to support SMEs. The developed algorithm has been tested on data from the Perm Region over the past 6 years. An analysis of support costs and tax revenues has shown that the growth rate of expenditures on the development of the SME sector outstrips the growth rate of income from their development. At the same time, there has been a positive economic effect for all 6 years. Of the measures taken by the regional authorities to develop the SME sector, most of the financing is spent on the implementation of tax benefits (lost budget revenues). It is important to note that, despite fluctuations in costs, the total amount of income from the SME sector has grown steadily throughout the period, which may indicate the sustainability of the SME sector, regardless of support measures aimed at stimulating economic growth. By 2024, the "Fiscal Response" coefficient reached 7.63, showing that every ruble of public investment in support of SMEs in the Perm Region provided a return of 7.63 rubles of tax revenue from this sector. In the course of the research, the goal was achieved, which was to propose an algorithm for evaluating the effectiveness of government spending to support small and medium-sized businesses. The rationale for the increase in scientific knowledge introduced by the proposed concept of calculating the coefficient "Fiscal response of SMEs" is as follows: • Integration of fiscal and microeconomic data: The FOM concept combines data on government spending to support SMEs with data on tax revenues from this sector, allowing assessing the effectiveness of government support in terms of fiscal returns. This extends traditional approaches that focus on macroeconomic indicators or individual microeconomic effects. • Comparison and ranking tool: The FOM provides an opportunity to compare the effectiveness of SME support policies in different regions or for different types of support measures, despite their differences in economic conditions or the structure of SMEs. • Stimulating data-based decision-making: The FOM concept facilitates the transition from intuitive or politically motivated decisions to informed decision-making based on the analysis of data on the effectiveness of government support. This increases the transparency and accountability of public administration. • Focus on tax revenue: The FOM focuses on increasing tax revenues from the SME sector, which is an important indicator of its economic development and contribution to the budget. This allows us to evaluate government support not only in terms of social or innovative effects, but also in terms of its financial impact. The results obtained have theoretical and practical value. The theoretical significance of the research lies in the development and testing of an algorithm for evaluating the effectiveness and efficiency of budget expenditures to support SMEs. The practical significance of the study lies in the fact that the proposed algorithm makes it possible to assess the effectiveness of budget expenditures to support SMEs, which is the basis for making informed management decisions in the field of state support for small and medium-sized businesses at the regional level. The SME fiscal response coefficient can become a tool for rating regions on the effectiveness of measures to support small and medium-sized enterprises in terms of their impact on tax revenues to the budget. This will make it possible to compare regions by the effectiveness of their policies and identify best practices for scaling. ______________________ I. Report of the Commissioner for the Protection of the Rights of Entrepreneurs under the President of the Russian Federation / [Electronic resource] // http://doklad.ombudsmanbiz.ru : [website]. – URL: http://doklad.ombudsmanbiz.ru/doklad_2021.html II. A study by the Stolypin Institute of Growth Economics. The sector of small and medium-sized enterprises: Russia and the world. / [Electronic resource] // https://stolypin.institute /: [website]. – URL: https://stolypin.institute/research/our/sektor-malogo-i-srednego-predprinimatelstva-rossiya-i-mir III. Unified Register of small and medium-sized businesses / [Electronic resource] // https://ofd.nalog.ru : [website]. – URL: https://rmsp.nalog.ru/index.html IV. Federal State Statistics Service // EMISS. The share of small and medium-sized enterprises in the gross domestic product. – [Electronic resource]. – URL: https://www.fedstat.ru/indicator/59206 V. Decree of the Government of the Perm Region dated 03.10.2013 N 1325-n (as amended on 01.21.2022) "On Approval of the Perm Region State Program "Economic Policy and Innovative Development" VI. Resolution of the Government of the Perm Region dated 03.10.2013 N 1325-p (as amended on 06.10.2023) "On Approval of the Perm Region State Program "Economic Policy and Innovative Development" VII.Federal Tax Service // Report on form No. 5-NIO for 2019-2024, consolidated as a whole for the Perm Region. – [Electronic resource]. – URL: https://www.nalog.gov.ru/rn59/related_activities/statistics_and_analytics/forms/ VIII. Federal Tax Service // Report on form No. 5-PM for 2019-2024, consolidated as a whole for the Perm Region. – [Electronic resource]. – URL: https://www.nalog.gov.ru/rn59/related_activities/statistics_and_analytics/forms/ IX. Federal Tax Service // Report on form No. 5-USN for 2019-2024, Report on form No. 5-USN for 2024, consolidated as a whole for the Perm Region. –[Electronic resource]. – URL: https://www.nalog.gov.ru/rn59/related_activities/statistics_and_analytics/forms/ X. Federal State Statistics Service // EMISS. Accrual and receipt of taxes, fees and other mandatory payments to the budget system of the Russian Federation [Electronic resource]. – URL: https://www.fedstat.ru/indicator/42547 XI. Report on the tax base and the structure of accruals for the unified imputed income tax for certain types of activities (Form 5-ENVD) [Electronic resource] // Federal Tax Service. URL: https://www.nalog.gov.ru/rn59/related_activities/statistics_and_analytics/forms/ XII. About the report on the tax base and the structure of accruals for personal income tax withheld by tax agents (Form 5-personal income tax) [Electronic resource] // Federal Tax Service. URL: https://www.nalog.gov.ru/rn59/related_activities/statistics_and_analytics/forms/#t00 XIII. Tax revenues from small and medium-sized businesses have increased in the Perm Region [Electronic resource] // Properm.ru - 2023. — December 24. — URL: https://properm.ru/news/2023-12-24/v-permskom-krae-vyrosli-nalogovye-postupleniya-ot-malogo-i-srednego-biznesa-3137954?ysclid=mci570vc3f26582274&utm_source=yandex.ru&utm_medium=organic&utm_campaign=yandex.ru&utm_referrer=yandex.ru XIV. Moscow Institute of Small Business Support in the Perm Region [Electronic resource] / PowerPoint presentation. – 2023. – URL: http://invest .gorodperm.ru/upload/others/2.-Myry-nalogovoj-podderzhki-subektov-predprinimatelskoj-dejatelnosti-v-Permskom-kraje.pdf
The article is published in its final version as approved following the last positive peer review recommending acceptance for publication. It incorporates revisions made by the author in response to prior negative peer review reports that did not recommend publication. All peer review reports, including initial negative reviews, are published in open access alongside the article. All versions of the author’s revisions are archived in the publisher’s repository and may be made available upon reasonable request in accordance with Elsevier’s editorial policies and applicable data availability requirements. References
1. Vilensky, A. V. (2021). On the influence of small and medium-sized entrepreneurship on the development of Russian regions: realities and opportunities. Economics of the Russian Academy of Sciences, 4, 24-38.
2. Zemtsov, S. P., Chepurenko, A. Y., Barinova, V. A., & Krasnoselskikh, A. N. (2020). A new entrepreneurial policy for Russia after the crisis of 2020. Economic Issues, 10, 44-67. 3. Pletnev, D. A., & Nikolaeva, E. V. (2015). Comparative analysis of criteria for classifying enterprises as small and medium enterprises in different countries. Business Strategy, 9, 30-26. 4. Zhukova, I. A., & Savchishkina, E. P. (2012). Methodological recommendations for assessing the effectiveness of state support for small business (based on the example of Shakhty, Rostov region). Modern Management Technologies, 12. 5. Ladygin, V. V. (2014). Improvement of the system of support for small entrepreneurship in the regions of Russia based on the introduction of mechanisms for providing municipal services (Doctoral dissertation). 6. Grazhdankin, V. A. (2009). Formation of infrastructure support institutions for small entrepreneurship in the Altai Territory. Herald of the A.I. Herzen Russian State Pedagogical University, 93, 117-222. 7. Grazhdankin, V. A. (2010). Trends in the development of small entrepreneurship: A case study of the Altai Territory (Candidate dissertation). 8. Lukyanova, T. V. (2003). Organizational and economic support for the professional growth of scientific and pedagogical workers in higher education (Candidate dissertation). 9. Romanenko, E. V. (2009). State support for small entrepreneurship: Features of formation and increasing effectiveness. Siberian Trade and Economic Journal, 8, 30-35. 10. Popov, S. A. (2013). Comprehensive analysis of the effectiveness of management programs for supporting small entrepreneurship. Fundamental Research, 10, 2249-2252. 11. Shestoperov, O. M., & Smirnov, S. V. (2013). On the progress of implementing regulatory impact assessment in the subjects of the Russian Federation: Some results of monitoring. Issues of State and Municipal Administration, 2, 71-90. 12. Nemets, A. V. (2009). Assessment of the effectiveness of support for small entrepreneurship in the system of state regulation (Doctoral dissertation). 13. Kremin, A. E. (2017). Methodology for assessing the effectiveness of state support for small entrepreneurship in the region. Territory Development Problems, 3, 46-61. 14. Bykova, N. V. (2014). A modern approach to assessing the effectiveness of state support for small entrepreneurship. Bulletin of the Leningrad State University named after A.S. Pushkin, 4, 107-115. 15. Chivirev, I. Yu. (2025). Methodological approaches to assessing the effectiveness of state support for small and medium entrepreneurship. Economics and Management, 3, 398-408. http://doi.org/10.35854/1998-1627-2025-3-398-408. 16. Ogneva, D. M., & Baranov, D. N. (2024). Assessment of the effectiveness of state support for the development of small and medium entrepreneurship in the Moscow region. Herald of Moscow University named after S.Yu. Vitte, 1, 56-66. 17. Yakovlev, A. A., Freinkman, L. M., Yershova, N. V., & Agalyan, A. A. (2023). Assessment of the effectiveness of industrial policy instruments in Russia: New approaches. ECO, 2, 60-83. 18. Prokhorenkov, P. A., & Reger, T. V. (2022). Analysis of the effectiveness of state support for small entrepreneurship. Fundamental Research, 6, 40-46. 19. Okhrimenko, A. V., & Gachegov, M. A. (2023). Assessment of the effectiveness of support for small and medium entrepreneurship. Herald of Moscow University. Series 6. Economics, 58, 124-146. https://doi.org/10.55959/MSU0130-0105-6-58-4-6. 20. Skopin, S. A. (2025). Analysis of the effects of state subsidies for small and medium business. International Scientific Journal "Herald of Science", 1, 184-200. 21. Autio, E., & Rannikko, H. (2016). Retaining winners: Can policy boost high-growth entrepreneurship? Research Policy, 45(1), 42-55. 22. Li, Y., & Rama, M. (2015). Firm dynamics, productivity growth, and job creation in developing countries: The role of micro-and small enterprises. The World Bank Research Observer, 30(1), 3-38. 23. Andreev, S. V. (2024). Fuzzy assessment of the effectiveness of financial support for small and medium entrepreneurship entities. Herald of Samara State Economic University, 3, 30-39. 24. Vasilieva, M. V. (2009). Methods for assessing the effectiveness of state funds in conducting effectiveness audits. Economic Analysis: Theory and Practice, 20, 53-58. 25. Orlov, M. V. (2006). Effectiveness of state regulation of entrepreneurial activity (Doctoral dissertation). 26. Toreev, V. B., & Voronovskaya, O. E. (2002). Effectiveness of support programs for small entrepreneurship. Economic Science of Modern Russia, 3, 73-87. 27. Evaluation of programs: methodology and practice (A. I. Kuzmin, R. O'Sullivan, & N. A. Kosheleva, Eds.). (2009). 28. Yaroshenko, T. P. (2011). Methodology for assessing the effectiveness of implementing long-term and departmental target programs. Finance and Credit, 10. 29. Belyaev, A. N., Derman, D. O., & Tsygankov, D. B. (2011). Methodological approaches to meta-evaluation of the quality of regulatory impact assessment conclusions. Designing, Monitoring and Evaluation, 1, 23-51. 30. Storey, D. J. (2000). Six Steps to Heaven: Evaluating the impact of public policies to support small businesses in developed economies. In H. Landstrom & D. L. Sexton (Eds.), Handbook of Entrepreneurship (pp. 176-194). 31. Srhoj, S., Škrinjarić, B., & Radas, S. (2021). Bidding against the odds? The impact evaluation of grants for young micro and small firms during the recession. Small Business Economics, 56, 83-103. 32. Shikhverdieva, A. P., Vishnyakov, A. A., & Oganesova, N. A. (2025). Effectiveness of state support mechanisms for small and medium entrepreneurship in the Arctic (based on the example of the Komi Republic). Arctic and North, 58, 102-116. DOI: https://doi.org/10.37482/issn2221-2698.2025.58.102. 33. Kolodnaya, G. V. (2024). Effectiveness of support for the SME sector in the modern domestic economy. Economics. Taxes. Law, 17, 18-27. DOI: 10.26794/1999-849X-2024-17-5-18-27. 34. Adaman, F., & Devine, P. (2014). Reconsideration of the Theory of Entrepreneurship: A participatory approach. Review of Political Economy, 14(3), 229-355. doi:10.1080/09538250220147877. 35. Fuller, T., & Moran, P. (2016). Small enterprises as complex adaptive systems: A methodological question? Entrepreneurship & Regional Development, 13, 47-63. doi:10.1080/089856201750046801.
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