Dependence of the regional investment multiplier on the degree of the regional economy sectoral diversification (on the example of the regions of the Central Federal District)

Eremin Vladimir Vladimirovich PhD in Economics Leading Scientific Associate, Center for Monitoring and Assessment of Economic Security of the Institute of Economic Policy and Economic Security Problems, Department of Economic Security and Risk Management, Faculty of Economics and Business, Financial University under the Government of the Russian Federation 125009, Russia, g. Moscow, ul. Tverskaya, 22B, str. 3 villy9@rambler.ru Other publications by this author

Introduction

The period from 2022 to the present for the Russian economy is characterized by the fact that its development is facing quite unprecedented and diverse sanctions pressure. The diversity of this pressure lies in the fact that it is designed to:

1. To make it difficult for Russian manufacturers to access modern technologies, materials, components and finished products. The purpose of this influence is to reduce the economic activity of Russian businesses and to reduce the supply of products on the domestic market of the Russian Federation.

2. To make it difficult to export Russian products, making it difficult to move them across the border of the Russian Federation. The goal is to reduce sales markets and, as a result, the incomes of Russian manufacturers.

3. Make it difficult to pay for Russian imports. The goal is to reduce the supply of imports necessary for Russian producers and consumers from not only unfriendly, but also friendly to Russia states.

4. Make it difficult to receive payments for Russian exports. The goal is to reduce the incomes of Russian producers, destabilize the currency and, as a result, the financial market of the Russian Federation ^[1].

The breadth of the imposed sanctions has recently led to the exhaustion of new options for sanctions pressure on the Russian Federation. Nevertheless, the exhaustion of these options is compensated by the tightening of existing sanctions, the search for and suppression of ways used by Russia to circumvent them.

It should be noted that the sanctions pressure did not show the significant effectiveness initially attributed to it, both as a result of the anti-sanctions actions of the Russian Government and as a result of the general complication of the global economy, which reduces the effectiveness of sanctions compared to the 20th century.^[2]

In many ways, the purpose of such sanctions pressure is the formation of hotbeds of social tension in the Russian economy by creating a shortage of both consumer and investment products and, ultimately, reducing the commodity content of income received by Russians ^[3],[4]. Therefore, despite the certain current effectiveness of the Russian anti-sanctions policy, it needs to increase this effectiveness. In particular, this is evidenced by high inflation rates ^[5] and an increase in the key rate by the Bank of Russia, as a reaction to this inflation that poses risks to the development of the Russian economy ^[6].

The scope of increasing the effectiveness of countering sanctions pressure is clear – increasing domestic production and product supply in the economy of the Russian Federation ^[7]. But the clarity of this path does not mean that it is simple (especially against the background of a high key rate). Since the increase in supply is faced not only with the complexity and sometimes the impossibility of replacing foreign technologies with Russian ones, but also with a certain limitation of Russian resources. A striking example of such a limitation is the personnel shortage ^[8]. In an environment where resource constraints are exacerbated by difficult external economic conditions, new, non-trivial tools are needed to improve investment efficiency. In this paper, it is proposed to base such a tool on the action of the investment multiplier.

Investment multiplier as a tool to increase the efficiency of investments in the regional economy

The possibility of using the investment multiplier as a tool to increase the efficiency of these investments in the regional economy becomes obvious, based on the very definition of this term. The investment multiplier is an indicator that characterizes the ratio of the increase in the volume of gross regional product to the increase in the investments that formed this volume ^[9]. According to the approach used in the vast majority of studies, if, for example, the value of the investment multiplier in a region's economy is 1.66, then every 100 rubles of investment in the development of such a regional economy will increase the gross product of the analyzed region (GRP) by 166 rubles ^[10]. Obviously, the multiplier's reinforcing effect increases the return on investment in the form of GRP growth. How is this reinforcing effect formed?

Investments in the development of the regional economy, as a rule, form the resource potential of the region, defined as a set of combinations of resources that can be used within the framework of regional production ^[11]. Individuals and legal entities involved in the process of this formation receive a monetary reward for their participation. Legal entities – revenue for goods supplied and services rendered. Individuals who are employees of legal entities receive remuneration for their work. Part of the funds received is saved, and tax payments are made from another part. The remaining funds are spent on consumption. Individuals purchase food, household appliances, clothing, etc. Legal entities purchase raw materials, equipment, and pay utility bills. That is, the income they receive partially becomes the income of their own supplier groups, which, in turn, transfer part of these funds to their suppliers, etc. This is how income distribution chains are formed, in which expenses serve as a link. Within these chains, incomes are growing for all their participants, which enhances the overall increase in the regional economy's income from investments compared to the increase in this income planned as part of an investment project without taking into account the multiplier effect. It should be noted that the presence of multiplicative income transfer chains was revealed back in the 19th century ^{[12, pp. 62-63]}.

More modern studies determine that the value of the investment multiplier can be not only positive, but also negative ^[13]. An increase in investments in a sector of the region's economy with a negative multiplier value will lead to a decrease in the gross regional product. In other words, the investment multiplier can not only enhance, but also weaken the effectiveness of investments in the regional economy. This state of affairs not only complicates the use of the multiplier as the desired investment effect booster, but also raises questions about the factors influencing the value of the regional investment multiplier. Because by influencing these factors, it is possible to control the multiplier value, and as a result, to influence the level of effectiveness of regional investment projects for the formation of the region's resource potential, expressed in the dynamics of GRP. This approach will make it possible to turn the investment multiplier into a full-fledged management tool for the regional economy.

At the same time, a certain scientific problem lies in the fact that existing scientific research in the analyzed area is mostly aimed at calculating the value of the investment multiplier. Matrix or scalar methods are used for this purpose. Matrix methods are more informative because they allow us to obtain the value of the investment multiplier for several sectors of the economy at once ^[14],[15]. Scalar methods are less informative, as they allow us to obtain a single multiplier value for the analyzed economy, or an industry from its composition ^[16],[17]. Nevertheless, neither matrix nor scalar methods for calculating multiplier values are primarily aimed at studying the structure of multiplicative processes and the factors influencing them. The lack of information about such factors makes it impossible to control the value of the investment multiplier by purposefully influencing it. Consequently, it does not allow multiplicative management of investment efficiency and GRP dynamics. The presented work aims to identify the relationship between the structure of the regional economy and the value of the regional investment multiplier. The presence of this connection will make it possible to control the multiplier value, changing the structure of investments in the formation of the resource potential of the regional economy and, as a result, changing the sectoral structure of this economy.

The impact of the degree of sectoral diversification of the regional economy on the value of the regional investment multiplier

This article is devoted to determining the impact on the value of the investment multiplier from such a factor as the degree of sectoral diversification of the regional economy. At the same time, by sectoral economic diversification we mean the presence in the structure of the region's economy of a diverse and wide range of industries producing a wide and diverse range of goods. By industry concentration, we mean the dependence of the region's economy on an extremely narrow set of industries producing a narrow range of goods.

To assess the impact of the degree of sectoral diversification of the regional economy, data from two regional economies of the Central Federal District (CFD) were taken. The interest in studying this particular federal district lies in the fact that, despite the presence in its composition of the economy of the Moscow agglomeration, which is one of the top 10 urban economies in the world in terms of GRP, the Central Federal District does not rank first in terms of GRP per capita, second only to the Ural and Northwestern Federal Districts. not much ahead of the Far Eastern Federal District – see the data in Table 1.

Table 1 – GRP per capita by federal districts of the Russian Federation, 2022

Source: compiled by the author according to ^[18]

It should also be noted that, according to Rosstat data, the specific GRP of the Central Federal District regions (with the exception of the Moscow city economy) is lower than the specific GRP of most regions of the Northwestern, Ural and Far Eastern Federal Districts. In other words, proximity to an extremely developed and economically large-scale urban agglomeration does not give the regions of the Central Federal District economic advantages.

This state of affairs, in our opinion, indicates that the economy of the Central Federal District and its constituent regions has the potential to increase efficiency and further grow, which requires additional research on the factors affecting this economy. One of these factors is investigated in this paper.

In order to select regional economies for further analysis, we rank the economies of the regions of the Central Federal District by GRP level – Table 2.

Table 2 – GRP per capita by region of the Central Federal District, 2022

Source: compiled by the author according to ^[18]

Let's take the economy of Moscow and the Moscow region beyond the boundaries of the analysis because:

- Moscow's economy is abnormal in size not only within the Central Federal District, but also within Russia;

- the close ties between the Moscow region and Moscow distort the economic indicators of the Moscow region. For example, this is due to the fact that a significant part of the residents of the Moscow region travel to Moscow for work as part of the pendulum migration, but spend their earned money mainly in the Moscow region.

Since two regions are outside the boundaries of the analysis, dashes are placed in table 2 opposite their numbers. Let's select two of the remaining regions for comparative analysis. These are the Ryazan Region, as the average of the analyzed regions in terms of GRP, and the Ivanovo Region, as the region with the lowest GRP value among the analyzed regions.

The degree of sectoral diversification (concentration) of the region's economy is estimated using the Herfindahl-Hirschman (HHI) indices calculated using the formula (1):

HHI, (4.11)

where n is the number of the type of economic activity in the economy of the analyzed region.;

m is the number of economic activities in the economy of the analyzed region.;

d is the share of goods shipped, works performed, and services rendered in the economy of the analyzed region for the mth type of economic activity.

The initial data for calculating the HHI index for the economy of the Ryazan region and the values of the desired index obtained from this calculation are presented in Table 3. The selective approach to presenting these data is explained by their significant volume.

Table 3 – Production structure (%) and the value of the Herfindahl-Hirschman index for the economy of the Ryazan Region (2005-2021)

Source: compiled by the author according to ^[19]

Similar data for the economy of the Ivanovo region are presented in Table 4.

Table 4 – Production structure (%) and the value of the Herfindahl-Hirschman index for the economy of the Ivanovo Region (2005-2021)

Source: compiled by the author according to ^[19]

A comparison of the HHI of the analyzed economies allows us to conclude that the degree of concentration of the economy of the Ivanovo region is higher than the degree of concentration of the economy of the Ryazan region.

The value of the investment multiplier for the economies of the analyzed regions is calculated using formula (2), presented and tested in ^[11].

, (2)

where M is the value of the investment multiplier;

o is the amount of specific outflows from income transmission chains (the sum of the specific propensity to save and the specific amount of tax payments);

a is the value of the investment accelerator (the number of additional investment units to meet the additional demand unit).

The presented investment multiplier formula is derived based on modeling the internal structure of the multiplicative process distribution within the regional economy. The initial data for calculating the multiplier of the Ryazan region and the results obtained are presented in Table 5.

Table 5 – Initial data for the calculation and magnitude of the multiplier of the Ryazan region (selected)

Source: compiled by the author according to ^[19]

Similar data for the economy of the Ivanovo region are presented in table 6.

Table 6 – Initial data for the calculation and magnitude of the multiplier of the Ryazan region (selected).

Source: compiled by the author according to ^[19]

Based on data on the investment multiplier values (Tables 3.4) and the Herfindahl-Hirschman index (Tables 5.6), we will compile econometric models of the dependence of the investment multiplier values of the analyzed regions on the degree of sectoral diversification of the analyzed regional economies. The basis of calculations is the model (3)

, (3)

where M is the value of the regional investment multiplier;

b is a coefficient characterizing the influence of the degree of diversification of the regional economy on the value of the regional multiplier;

HHI is the value of the Herfindahl-Hirschman index for the region's economy.

Modeling using formula (3), performed for the economies of the analyzed regions, allowed us to obtain the following result – Table 7.

Table 7 shows the value of coefficient b and the statistical significance of model (3) for the economies of the analyzed regions.

Source: compiled by the author according to Tables 3-6

Thus, for the economy of the Ryazan region, the following equation (5) is obtained for the dependence of the investment multiplier of the analyzed region on the degree of diversification of the regional economy:

, (5)

For the economy of the Ivanovo region, this equation will look like this:

, (6)

The equations obtained for the analyzed regions are statistically significant.

According to the results of the presented data, the Ryazan region, in comparison with the Ivanovo region, has:

- a large value of the investment multiplier;

- lower values of the Herfindahl-Hirschman index (hence a more diversified economy).

The conducted modeling allows us to conclude that these values are related to each other. At the same time, according to equations (5) and (6), a higher degree of diversification of the regional economy has a stronger impact on the value of the regional investment multiplier. Thus, for the more diversified Ryazan economy, the coefficient b of equation (5) is 10.5919, whereas for equation (6) it is 7.0609. That is, as the degree of sectoral diversification increases, this diversification has a stronger positive impact on the value of the regional investment multiplier. A decrease in industry diversification will reduce this impact and, as a result, the value of the regional multiplier, which is confirmed by the analyzed regional data.

It should be noted that the presented calculations show that there is no need for variability in the tools used for regions with different levels of GRP per capita. Since this toolkit is the same for regions that differ significantly from each other in terms of specific GRP. The proposed approach differs from existing scientific publications in that it is not devoted to a simple calculation of the value of the regional investment multiplier with a statement of its significance in statics or dynamics. The presented approach is aimed at forming levers of influence on the value of the investment multiplier, which requires an analysis of the factors influencing this value.

Conclusions.

The modeling carried out in the work made it possible to determine the degree of sectoral diversification of the regional economy as a factor influencing the value of the regional investment multiplier. By changing the structure of investments in the formation of the resource potential of the region, it is possible to influence the degree of sectoral diversification of the regional economy. In turn, this will have an impact on the value of the regional multiplier.

Given that the multiplier value characterizes the number of units of GRP growth per unit of investment, managing this value allows you to manage the effectiveness of investments in the formation of the resource potential of the regional economy, increasing and, if necessary, reducing this efficiency. In turn, this justifies the practical applicability of the results obtained. In practice, having plans for specific investments in the formation of a region's resource potential with specific amounts and their sectoral distribution, management decision makers can calculate exactly how the planned distribution of the investment structure will change the sectoral structure of the economy of the analyzed region. Knowing the change in the structure of the economy and its impact on the multiplier value, it is possible to calculate the planned change in the GRP of the region. Having several options for the sectoral distribution of investments in the formation of the resource potential of the region, management decision makers can choose the option that has the best impact on the multiplier and, as a result, GRP. The proposed approach creates the basis for the formation of a regional policy to optimize the allocation of investments in the formation of the resource potential of the region. At the same time, this policy should be checked for compliance with existing resource constraints.

It should be noted that this approach to improving investment efficiency and stimulating GRP growth has not been widely adopted in practice. Therefore, the proposed approach is a kind of reserve for increasing the efficiency of investments in the formation of the resource potential of the region. A reserve capable of contributing to countering the sanctions pressure on the economy of the Russian Federation.