ASSESSMENT OF THE LEVEL OF SOCIO-ECONOMIC DEVELOPMENT OF REGIONS AND THEIR INSURANCE MARKETS BASED ON THE INDEX METHOD (RUSSIA) Текст научной статьи по специальности «Экономика и бизнес»

I Journal of Siberian Federal University. Humanities & Social Sciences 2023 16(9): 1600-1615

EDN: JQMUVP УДК 368.01

Assessment of the Level of Socio-Economic Development of Regions and Their Insurance Markets Based on the Index Method (Russia)

Evgenia L. Prokopjeva*3, Svetlana Saksonovab and Zhanna V. Pisarenkoc

aSiberian Federal University Krasnoyarsk, Russian Federation b University of Latvia Riga, Latvia

€St. Petersburg State University St. Petersburg, Russian Federation

Received 17.11.2022, received in revised form13.06.2023, accepted 15.06.2023

Abstract. The insurance market is one of the driving forces in the socio-economic development of the country. Therefore, the study of the level of development of the insurance market becomes an urgent problem both for countries with a stagnating economy and with a rapidly growing one. This is particularly true for countries with a transitive economy, as being unstable and subject to increased risks. The intentional development of the insurance market in these countries will increase financial stability and ensure the growth of their economies, thereby reducing the risks of the global economy. The article proposes a rating model that takes into account the key indicators of socio-economic development of regions, and indicators characterizing the level of development of the insurance market. It is based on the use of indices within the framework of the methodology used by the United Nations to evaluate countries using the integral indicator of "Human Development Index (HDI)". The proposed model allows to quantify the level of development of specific regions and their insurance markets. The rating assessment model makes it possible to compare the level of socio-economic development of countries (regions) with the level of development of the insurance market and, therefore, to identify countries (regions) that have problems in the development of the insurance market. This assessment is the basis for the development of a set of measures that contribute to the development of regions and their insurance markets at the state and state-by-state levels as well.

Keywords: insurance market, insurance premiums, socio-economic development, depth of the insurance market, insurance density, level of payments, rating model, human development index, private indexes, integral index.

© Siberian Federal University. All rights reserved

* Corresponding author E-mail address: [email protected]; [email protected]; [email protected]

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Research area: economy.

Citation: Prokopjeva E. L., Saksonova S., Pisarenko Zh. V. Assessment of the level of socio-economic development of regions and their insurance markets based on the index method (Russia). In: J. Sib. Fed. Univ. Humanit. soc. sci., 2023, 16(9), 1600-1615. EDN: JQMUVP

Оценка уровня социально-экономического развития регионов и их страховых рынков на основе индексного метода (на примере России)

Е. Л. Прокопьеваа, С. Саксоноваб, Ж. В. Писаренков

"Сибирский федеральный университет Российская Федерация, Красноярск бУниверситет Латвии Латвия, Рига

вСанкт-Петербургский государственный университет Российская Федерация, Санкт-Петербург

Аннотация. Страховой рынок является одной из движущих сил в социально-экономическом развитии страны. Поэтому исследование уровня развития страхового рынка становится актуальной проблемой как для стран со стагнирующей экономикой, так и с быстро растущей. Особенно это актуально для стран с транзитивной экономикой как нестабильной и подверженной повышенным рискам. Целенаправленное развитие страхового рынка в этих странах позволит повысить финансовую устойчивость и обеспечить рост их экономики, тем самым создавая условия для снижения рисков глобальной экономики. В статье предложена рейтинговая модель, в которой учтены ключевые показатели социально-экономического развития регионов, и показатели, характеризующие уровень развития страхового рынка. Она основана на использовании индексов в рамках методики, используемой Организацией объединенных наций для оценки стран с помощью интегрального показателя «Индекс человеческого развития (ИЧР)». Предлагаемая модель позволяет количественно оценить уровень развития конкретных регионов и их страховых рынков. Модель рейтинговой оценки позволяет сопоставить уровень социально-экономического развития стран (регионов) с уровнем развития страхового рынка и на основе этого выявить страны (регионы), имеющие проблемы в развитии страхования страхового рынка. Эта оценка является основой для разработки комплекса мер, способствующих развитию регионов и страховых рынков на государственном и межгосударственном уровнях.

Ключевые слова: страховой рынок, страховые премии, социально-экономическое развитие, глубина страхового рынка, плотность страхования, уровень выплат, рейтинговая модель, индекс человеческого развития, частные индексы, интегральный индекс.

Научная специальность: 08.00.00 - экономические науки.

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Цитирование: Прокопьева Е. Л., Саксонова С., Писаренко Ж. В. Оценка уровня социально-экономического развития регионов и их страховых рынков на основе индексного метода (на примере России). Журн. Сиб. федер. ун-та. Гуманитарные науки, 2023, 16(9), 1600-1615. EDN: JQMUVP

Introduction

In modern economy the processes of globalization are intensifying, on the one hand, and the tendencies of regionalization are increasing, on the other hand. This is what makes it necessary to study regional problems of sustainable economic growth on a global scale and at the national level.

The insurance market is currently the most important driving force of the social and economic development of countries and regions, as well as a protective mechanism in the face of global risks. Therefore, the study of the level of its development, taking into account regional peculiarities, as well as quantitative and qualitative assessment, seems utterly relevant.

The authors take position on the fact that the assessment of the level of socio-economic development of regions and their insurance markets is quite relevant for countries with economies in transition. This is contingent on the evidence that these countries are characterized, on the one hand, by uneven development of various regions and, on the other hand, by the high development potential of both the regions themselves and their insurance markets, as well as the instability of the economy as a whole. The group of countries with economies in transition is quite numerous - this includes the states of Central and Eastern Europe, as well as the CIS countries - about 28 countries in total. The instability of the economic development in these countries affects the stability of the global financial system and economy. Therefore, considering the assessment of the level of socioeconomic development of regions and their insurance markets with the help of the rating model proposed by the authors, it is very important to identify problem regions, the degree of disproportions in their development and, thereafter, to systematize the problems to be solved and further to conduct a comprehensive analysis in order to work out a system of measures that promote the development of

regions and insurance markets at the state and state-by-state levels.

The purpose of the article is to propose a model for assessing the level of socio-economic development of regions and their insurance markets in countries with transitive economies, as well as measures aimed at improving the indicators of the insurance markets.

The practical significance of the article consists in the possibility of using the proposed model by means of the example of any regional insurance markets in order to improve their interaction and to increase their role in the economy development. The proposed model itself is of general importance for assessing the development of the insurance market; its application is presented on the example of Russia.

The structure of the insurance market of the region and the level of its development are determined by the specifics of the functioning and development of a particular region. This specificity is shaped by the geographical location of the region, its climatic or demographic features, the presence or absence of natural resources, national characteristics, which together constitute the socio-economic development of the region.

The proposed model for assessing the level of socio-economic development of regions and their insurance markets succeeds in solving this problem. From the authors' perspective it could be used not only for intra-country regions, but also for regions as associations of several countries.

1. Literature Review

Various aspects of the problem under study are presented quite widely in the academic literature.

It is worth taking note of the works describing the problems of sustainable development of economic systems, and, the relationship between the indicators of the insurance market and the economic growth indicators in particular; as well as the importance of insur-

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ance as an investment tool in the economy of any country, for example, (Lee H. S.et al., 2018) and (Njegomir and Stojic, (2010) and, in the economy of transition countries (Bayar et al., 2021), in particular.

Insurance acts as an institution of financial and social protection, and insurance companies (especially for long-term life insurance) are the most important and socially responsible investors, accounting for about 8-12 % of the total investments of developed countries in the economy (Prokopjeva et al., 2020), which, in turn, serves as a significant factor in economic growth (Sholoiko, 2018).

A number of authors have given evidence on the following research:

• there is a direct correlation between economic growth indicators and insurance market development indicators both in national economies (Kuznetsova and Pisarenko, 2016) and in regional integration complexes (Be-lozyorov and Pisarenko, 2014);

• different types of grouped countries have different degrees of dependence between economic growth indicators and insurance market development indicators (Lee C.-C. et al., 2013), which is determined by historical, economic, spatial, geographical, regional (Prokopjeva, 2019) and geopolitical characteristics (Prokopjeva et al., 2020);

• close relationship between the indicators of economic development and growth of the countries under consideration and their insurance markets is ambiguous, due to the fact that the active growth of insurance is observed in countries with a high density and a significant proportion of the young population (Mdanat et al., 2019), as well as in countries with economies in transition (Kozarevic et al., 2013);

• reasons for similarities and differences in the studied relationships are diverse and determined by differences in the functioning of socio-economic systems (geographical, legislative, political, social, etc.) (PavicKramaric and Galetic, 2013), as well as the accepted model of insurance regulation (Mohyuldin, 2017) and regulation of applied innovative technologies (Porrini, 2017), (Rupeika-Apoga and Thalass-inos, 2020);

• growth of the insurance market corresponds to the overall economic growth (Saksonova and Koleda, 2017), provided that investment activity is intensified (Saksonova, 2014) and risks are assessed (Oana and Daniela, 2016);

• life insurance shows a closer relationship with macroeconomic indicators compared to other segments of the insurance market (David Cummins and Rubio-Misas, 2021);

• various authors investigate various aspects of the development of insurance markets related to new trends in their development. Thus, a group of authors (Altarhouni et al.,

2021) have been studying the role of insurance market development in environmental degradation, which is a new aspect of insurance research;

• interesting studies such as "Digital Technologies and Insurance Market in Russia" are devoted to various modern trends related to innovations in the insurance market that contribute to its development; the author of the given research concludes that digital technologies determine a new technological trend in the classical behavior of policyholders due to the heuristic choice of insurance services based on the use of digital technologies (Prosvetova,

2022). The use of digital technologies by insurance companies within the country aspect was investigated by Comanac et al., 2016. Thus, the aforementionedresearchers and these ones as well (Laidroo et al., 2021) conclude that business models using Fin Tech contribute to the development of the financial and the insurance sectors. The authors (Salkovska et al., 2018) and (Batraga et al., 2018) believe that there are universal methods that influence the behavior of both consumers and companies providing services to them to develop companies in a variety of economic sectors, including, for example, the trading sector;

• finally, providing the research on insurance markets, the scientistssuggestvarious models, for example, the dynamic panel threshold model, which determines the relationship between life insurance and economic growth (dynamic panel threshold model) (Lee C.-C. et al., 2013). The article of (Han L. et al., 2010) examines the relationship between insurance de-

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velopment and economic growth using GMM models on a set of dynamic panel data for 77 countries for the period of 1994-2005.

There are other studies offering models for evaluating the work of insurance industry enterprises, but they evaluate their activities from the point of view of the integration of national insurance markets without connection with the socio-economic development of the regions.

2. Methodology and discussion

The model for assessing a socio-economic development of regions and their insurance markets implies their ranking by certain indicators or a complex of them, and therefore, it is actually a rating model based on the calculation of indices. The essence of the model is a comparative assessment of factors related to regional insurance markets, based on the methodology applied by the UN to assess countries using the integral indicator of "Human Development Index (HDI)"1.

Considering each of the listed indicators, three partial indices have been calculated respectively (formula 1):

(1)

Dr . - the actual value of the indicator; D -

fact ' min

the value of the indicator taken as the minimum; D - the value of the indicator taken as

' max

the maximum.

The authors have proposed an index evaluation model similar in algorithm to the UN methodology, but with an expanded list of indicators reflecting the socio-economic development of regions and the insurance markets.

Fig. 1 shows an algorithm that includes the following stages of index calculation within the framework of the proposed model (Fig. 1).

The indicators of socio-economic development shown in the diagram are calculated per capita and selected because, according to the authors, they are the most important (key) in assessing the development of the region, informative and can be obtained for any region.

These indicators reflect both the level and quality of life of the population in the region (social potential) and the level of development of the regional economy as a whole (economic potential).

Further, on the basis of the listed seven indicators, partial indices of I1-I7 have been calculated in reliance on the statistical data considering the formulas similar to the formula 1: I - GRP index per capita (formula 2):

h =

GRPfact - GRPmin

GRPmirir,

I - life expectancy index (formula 3):

b =■

IJE Xç^Q^ L E Xfj

LExmin„

(2)

(3)

1 Human Development Index. [electronic resource]. https://ru.wikipedia.org/wiki/HHaeKC_He^oBeqecKoro_ pa3BHTHS#MeTOa,_Hcno^L3yeMLiH_gaa_BLiHHC^eHHS_HHP

The remaining private indices of the socio-economic development of the regionhave been calculated in the same way: I3 - index of income per capita; I4 - index of investments in fixed assets; I5 - housing security index; I6 - employment index; I7 - the index of qualification of employees.

The calculation data are shown in Table 1.

On the basis of private indices, the authors have determined the integral index of the socioeconomic development of the region according to the geometric mean formula (formula 4):

/ = y/i x I2 x /3 x /4 x /5 x I6 x I7

(4)

Further, the key indicators of the development of regional insurance markets have been identified in order to compare them further with the level of socio-economic development of the regions of Russia. The initial data for calculations (indicators of insurance premiums, payments, etc.) are taken from the website of the Bank of Russia.

Making use of these indicators, the authors have calculated the private insurance market indices of (J1-J4), having applied formulas similar to the formulas 2 and 3:

- insurance premium index per capita;

- index of the number of contracts per capita;

- insurance premium index in GRP;

- index of the level of insurance payments.

The calculation data are shown in Table 2.

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Selection of key indicators of socio-economic development of the subject of the Russian Federation: gross regional product per capita; life expectancy; average income per capita; investment in fixed assets per capita: indicators of housing provision; the ratio of the employed in the economy to the total population; the share of highly skilled workers within the total number of employees

1

Calculation ofprivate indices of socio-economic development of the regions of the Russian Federation, allowing to quantify the proximity of the considered regional entity to the entity that has die highest level of socio-economic development

r

Selection of key indicators for the development of regional insurance markets:

the amount of insurance premiums and payments per capita; the number of insurance contracts taken out per capita; the share of insurance premiums within die gross regional product; die level of payments (the ratio of insurance premiums and payments)

1

Calculation ofprivate indices of the development of insurance markets in the regions of the Russian Federation, allowing to assess the proximity of the considered regional entity to the entity that has the highest level of development of the regional insurance market

Calculation of two integral indices: the index of socio-economic development of regions; the index of development of the insurance market

Assembling regions into 9 groups based on a comparative analysis of the rating of socio-economic development of the region and the rating on the level of insurance development, which makes it possible to see the position of the region on the level of development of the insurance market and its compliance with the level of socioeconomic development

Fig. 1. Algorithm for assessing the socio-economic development of regions and their insurance markets

Source: Compiled by the authors

Table 1. Private indices of socio-economic development of Russian regions in 2020

Regions of Russia I I I h I I I

The Russian Federation total 0,222 0,364 0,279 0,177 0,627 0,398 0,356

Central Federal District 0,306 0,440 0,454 0,200 0,689 0,495 0,582

Belgorod Region 0,209 0,419 0,236 0,133 0,927 0,452 0,238

Bryansk Region 0,083 0,299 0,176 0,029 0,845 0,298 0,034

Vladimir Region 0,110 0,272 0,131 0,053 0,819 0,401 0,123

Voronezh Region 0,127 0,383 0,231 0,170 0,860 0,328 0,226

Ivanovo Region 0,046 0,270 0,138 0,000 0,679 0,355 0,092

KalugaRegion 0,176 0,302 0,222 0,132 0,870 0,441 0,176

KostromaRegion 0,077 0,302 0,130 0,006 0,736 0,281 0,230

KurskRegion 0,135 0,297 0,188 0,176 0,870 0,361 0,337

Lipetsk Region 0,157 0,364 0,238 0,185 0,933 0,405 0,280

Moscow Oblast 0,233 0,397 0,458 0,187 1,000 0,592 0,674

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Continuation of Table 1

Regions of Russia I I I I I I

Oryol Region 0,095 0,315 0,142 0,072 0,793 0,151 0,218

RyazanRegion 0,109 0,356 0,154 0,046 0,959 0,214 0,111

SmolenskRegion 0,100 0,273 0,162 0,068 0,788 0,301 0,192

TambovRegion 0,091 0,378 0,173 0,154 0,870 0,221 0,280

TverRegion 0,105 0,232 0,159 0,057 0,964 0,421 0,061

TulaRegion 0,141 0,293 0,179 0,156 0,793 0,405 0,383

YaroslavlRegion 0,150 0,338 0,181 0,064 0,741 0,351 0,096

Moscow 0,625 0,682 0,860 0,355 0,269 0,659 1,000

North-Western Federal District 0,269 0,389 0,319 0,200 0,720 0,472 0,398

RepublicofKarelia 0,169 0,246 0,214 0,076 0,679 0,251 0,165

KomiRepublic 0,323 0,236 0,281 0,191 0,746 0,375 0,092

ArkhangelskRegion 0,282 0,301 0,286 0,243 0,736 0,258 0,226

VologdaRegion 0,175 0,268 0,176 0,248 0,876 0,294 0,103

KaliningradRegion 0,164 0,378 0,184 0,122 0,762 0,485 0,218

Leningrad Region 0,227 0,383 0,235 0,354 0,803 0,418 0,284

MurmanskRegion 0,303 0,264 0,414 0,363 0,585 0,559 0,379

Novgorod Region 0,138 0,186 0,141 0,070 0,953 0,341 0,069

PskovRegion 0,075 0,195 0,134 0,029 0,907 0,281 0,042

Saint-Petersburg 0,357 0,552 0,458 0,170 0,622 0,632 0,659

SouthernFederalDistrict 0,113 0,389 0,199 0,080 0,580 0,301 0,180

Republic of Adygea 0,063 0,397 0,188 0,103 0,658 0,077 0,253

Republic of Kalmykia 0,080 0,459 0,029 0,040 0,570 0,258 0,375

Republic of Crimea 0,044 0,325 0,086 0,126 0,244 0,241 0,241

Krasnodarskiy Kray 0,137 0,401 0,286 0,075 0,674 0,348 0,042

Astrakhan Region 0,200 0,397 0,126 0,107 0,534 0,321 0,322

Volgograd Region 0,106 0,411 0,113 0,079 0,560 0,274 0,257

Rostov Region 0,108 0,387 0,212 0,056 0,601 0,294 0,203

Sevastopol 0,071 0,377 0,204 0,110 0,756 0,361 0,552

North Caucasus Federal District 0,038 0,573 0,117 0,045 0,394 0,227 0,253

Republic of Dagestan 0,038 0,728 0,162 0,065 0,285 0,151 0,226

Republicoflngushetia 0,000 1,000 0,0005 0,018 0,067 0,207 0,180

Kabardino-Balkarian Republic 0,023 0,562 0,073 0,024 0,342 0,348 0,222

Karachay-Cherkess Republic 0,023 0,546 0,034 0,020 0,383 0,013 0,287

Republic of North Ossetia-Alania 0,045 0,517 0,118 0,017 0,777 0,037 0,548

ChechenRepublic 0,008 0,525 0,113 0,035 0,306 0,298 0,241

StavropolTerritory 0,066 0,448 0,117 0,050 0,544 0,324 0,234

Volga Federal District 0,148 0,339 0,175 0,102 0,679 0,355 0,249

Republic of Bashkortostan 0,134 0,320 0,209 0,079 0,642 0,261 0,215

Republic of Mari-El 0,068 0,337 0,064 0,002 0,699 0,331 0,169

Republic o fMordovia 0,083 0,403 0,047 0,053 0,741 0,445 0,272

Republic of Tatarstan 0,253 0,471 0,286 0,239 0,679 0,482 0,387

Udmurt Republic 0,148 0,330 0,127 0,055 0,461 0,418 0,004

Chuvash Republic 0,059 0,371 0,054 0,027 0,720 0,338 0,207

PermRegion 0,190 0,237 0,210 0,139 0,539 0,244 0,061

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Continuation of Table 1

Regions of Russia I I I I I I

KirovRegion 0,065 0,340 0,105 0,034 0,679 0,318 0,241

Nizhny Novgorod Region 0,160 0,300 0,258 0,101 0,705 0,482 0,291

Orenburg Region 0,186 0,282 0,118 0,132 0,663 0,268 0,215

PenzaRegion 0,087 0,382 0,096 0,059 0,845 0,268 0,272

SamaraRegion 0,171 0,328 0,192 0,099 0,684 0,438 0,444

SaratovRegion 0,083 0,347 0,092 0,059 0,813 0,268 0,165

UlyanovskRegion 0,086 0,340 0,107 0,039 0,772 0,281 0,180

UralFederalDistrict 0,410 0,313 0,303 0,373 0,606 0,441 0,310

KurganRegion 0,060 0,226 0,071 0,020 0,617 0,043 0,061

SverdlovskRegion 0,195 0,268 0,337 0,126 0,642 0,341 0,261

TyumenRegion 0,993 0,409 0,475 1,000 0,518 0,602 0,444

ChelyabinskRegion 0,133 0,285 0,132 0,091 0,658 0,498 0,257

Siberian Federal District 0,173 0,224 0,159 0,125 0,565 0,334 0,192

RepublicofAltai 0,055 0,172 0,055 0,114 0,373 0,184 0,184

RepublicofTyva 0,043 0,000 0,000 0,030 0,000 0,000 0,444

RepublicofKhakassia 0,148 0,220 0,091 0,051 0,585 0,227 0,077

AltaiTerritory 0,056 0,255 0,110 0,022 0,544 0,274 0,042

KrasnoyarskTerritory 0,351 0,227 0,227 0,209 0,580 0,435 0,272

IrkutskRegion 0,222 0,125 0,146 0,212 0,570 0,321 0,153

KemerovoRegion 0,120 0,140 0,124 0,139 0,580 0,271 0,084

NovosibirskRegion 0,159 0,296 0,209 0,096 0,601 0,368 0,372

OmskRegion 0,112 0,300 0,155 0,096 0,580 0,401 0,184

TomskRegion 0,191 0,334 0,177 0,097 0,554 0,348 0,188

Far Eastern Federal District 0,259 0,167 0,320 0,292 0,492 0,418 0,264

RepublicofBuryatia 0,064 0,202 0,130 0,065 0,394 0,154 0,268

RepublicofSakha (Yakutia) 0,087 0,343 0,432 0,671 0,466 0,528 0,000

Trans - Baikal Territory 0,494 0,083 0,137 0,082 0,378 0,308 0,487

Kamchatka Region 0,331 0,190 0,540 0,213 0,606 0,666 0,487

Primorsky Krai 0,184 0,188 0,304 0,107 0,482 0,401 0,195

KhabarovskTerritory 0,205 0,157 0,372 0,160 0,513 0,482 0,429

Amur Region 0,166 0,069 0,250 0,740 0,591 0,415 0,088

Magadan Region 0,609 0,132 0,730 0,409 0,777 0,722 0,544

Sakhalin Region 1,000 0,171 0,635 0,824 0,668 0,592 0,222

Jewish Autonomous Region 0,093 0,032 0,150 0,112 0,497 0,284 0,034

Chukotka Autonomous Okrug 0,777 0,033 1,000 0,908 0,492 1,000 0,410

Calculated according to Federal State Statistics Service. [electronic resource]. URL: https://rosstat.gov.ru.

Table 2. Private indices of development of insurance markets of Russian regions in 2020

Regions of Russia J J2 J3

The Russian Federation total 0,182 0,178 0,433 0,213

Central Federal District 0,389 0,392 0,721 0,165

BelgorodRegion 0,076 0,096 0,183 0,255

BryanskRegion 0,064 0,102 0,304 0,250

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Continuation of Table 2

Regions of Russia J J2 J

VladimirRegion 0,087 0,102 0,344 0,130

VoronezhRegion 0,097 0,099 0,349 0,214

IvanovoRegion 0,077 0,075 0,494 0,130

KalugaRegion 0,090 0,110 0,253 0,272

KostromaRegion 0,065 0,117 0,324 0,280

KurskRegion 0,066 0,085 0,224 0,165

LipetskRegion 0,084 0,080 0,256 0,156

MoscowOblast 0,145 0,118 0,331 0,000

OryolRegion 0,061 0,091 0,264 0,218

RyazanRegion 0,086 0,120 0,342 0,238

SmolenskRegion 0,089 0,119 0,374 0,288

TambovRegion 0,055 0,078 0,246 0,211

TverRegion 0,074 0,120 0,300 0,273

TulaRegion 0,094 0,082 0,312 0,245

YaroslavlRegion 0,097 0,095 0,308 0,260

Moscow 1,000 1,000 0,999 0,173

North-Western Federal District 0,221 0,148 0,450 0,299

Republic of Karelia 0,090 0,108 0,261 0,292

Komi Republic 0,113 0,104 0,188 0,197

Arkhangelsk Region 0,112 0,449 0,211 0,218

VologdaRegion 0,116 0,114 0,329 0,150

KaliningradRegion 0,104 0,084 0,312 0,249

LeningradRegion 0,058 0,052 0,127 0,140

MurmanskRegion 0,147 0,082 0,265 0,167

NovgorodRegion 0,082 0,098 0,276 0,114

PskovRegion 0,063 0,108 0,319 0,267

Saint-Petersburg 0,420 0,169 0,683 0,339

Southern Federal District 0,067 0,081 0,261 0,335

Republic of Adygea 0,029 0,034 0,165 0,502

Republic of Kalmykia 0,025 0,033 0,121 0,376

Republic of Crimea 0,021 0,066 0,144 0,204

KrasnodarskiyKray 0,083 0,084 0,284 0,377

AstrakhanRegion 0,090 0,090 0,227 0,212

VolgogradRegion 0,072 0,077 0,292 0,297

RostovRegion 0,071 0,100 0,286 0,335

Sevastopol 0,006 0,014 0,032 0,626

North Caucasus Federal District 0,026 0,027 0,192 0,621

RepublicofDagestan 0,007 0,011 0,057 1,524

Republicoflngushetia 0,000 0,001 0,034 2,964

Kabardino-BalkarianRepublic 0,019 0,027 0,170 0,472

Karachay-CherkessRepublic 0,018 0,018 0,162 0,946

Republic of North Ossetia-Alania 0,016 0,024 0,112 1,288

ChechenRepublic 0,004 0,005 0,062 0,810

StavropolTerritory 0,072 0,063 0,387 0,374

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Continuation of Table 2

Regions of Russia J J2 J3

Volga Federal District 0,098 0,101 0,314 0,210

RepublicofBashkortostan 0,088 0,075 0,304 0,225

RepublicofMariEl 0,068 0,084 0,361 0,167

RepublicofMordovia 0,061 0,082 0,289 0,279

RepublicofTatarstan 0,136 0,137 0,286 0,188

UdmurtRepublic 0,086 0,101 0,277 0,199

ChuvashRepublic 0,075 0,094 0,428 0,119

PermRegion 0,114 0,086 0,302 0,155

KirovRegion 0,092 0,144 0,501 0,029

NizhnyNovgorodRegion 0,101 0,104 0,306 0,375

OrenburgRegion 0,078 0,081 0,208 0,251

PenzaRegion 0,068 0,096 0,310 0,162

SamaraRegion 0,133 0,121 0,385 0,194

SaratovRegion 0,068 0,086 0,319 0,234

UlyanovskRegion 0,087 0,086 0,401 0,203

UralFederalDistrict 0,147 0,115 0,200 0,192

KurganRegion 0,052 0,086 0,297 0,380

SverdlovskRegion 0,121 0,111 0,316 0,257

TyumenRegion 0,241 0,123 0,139 0,110

ChelyabinskRegion 0,099 0,118 0,345 0,281

Siberian Federal District 0,087 0,109 0,248 0,288

RepublicofAltai 0,020 0,038 0,126 0,394

RepublicofTyva 0,029 0,024 0,201 0,287

RepublicofKhakassia 0,048 0,084 0,150 0,418

AltaiTerritory 0,049 0,067 0,291 0,263

KrasnoyarskTerritory 0,095 0,138 0,143 0,281

IrkutskRegion 0,096 0,102 0,222 0,301

KemerovoRegion 0,088 0,083 0,329 0,165

NovosibirskRegion 0,125 0,179 0,383 0,387

OmskRegion 0,079 0,094 0,308 0,323

TomskRegion 0,100 0,102 0,264 0,166

Far Eastern Federal District 0,092 0,098 0,185 0,366

RepublicofBuryatia 0,052 0,048 0,287 0,242

RepublicofSakha (Yakutia) 0,085 0,129 0,088 0,018

Trans - Baikal Territory 0,043 0,063 0,195 0,364

Kamchatka Region 0,106 0,066 0,172 0,332

Primorsky Krai 0,108 0,097 0,293 0,629

KhabarovskTerritory 0,128 0,139 0,321 0,446

Amur Region 0,098 0,112 0,288 0,066

Magadan Region 0,147 0,143 0,132 0,056

Sakhalin Region 0,126 0,101 0,061 0,299

Jewish Autonomous Region 0,034 0,060 0,150 0,941

Chukotka Autonomous Okrug 0,025 0,021 0,000 0,276

Calculated according to Official website of the Bank of Russia. [electronic resource]. URL: cbr.ru/statistics/insurance/

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Further, the integral index of the insurance market development has been calculated(for-mula 5):

Having calculated the two integral indices, the authors have provided a comparative analysis of the integral indices upon the regions of Russia (Federal Districts and Subjects of the Russian Federation). All regions have been rated according to the values of the integral indices. The ranking data are shown in Table 3.

Further, a rating correlation of the socioeconomic development of the region and of the insurance development of this very region has been carried out.

The authors have proposed to sort out the rating values of the insurance markets of the regions into three groups:

Group 1 - high level - rating 1-27;

Group 2 - average level - rating 28-54;

Group 3 - low level - rating 55-80.

Further, the authors propose to divide each of the three groups into three more groups, depending on the degree to which the development of the insurance market corresponds to the level of socio-economic development:

1) the level of development of the insurance market corresponds to the level of socioeconomic development of the region. It is assumed that the deviations of the two ratings are no more than 10 points;

2) the level of development of the insurance market is higher than the level of development of the socio-economic development of the region by more than 10 rating points;

3) the level of development of the insurance market is lower than the level of socioeconomic development of the region by more than 10 rating points.

If the ratings of the development of the socio-economic sphere of the region or the insurance market have relatively low values, then, despite their compliance, we could also talk about the weak development of the insurance market, as well as the socio-economic sphere itself. Table 4 gives the generalized statistics of the distribution of the regions by Federal Districts.

Analyzing the position of regions in Table 4, it could be seen that the highest level of development of insurance markets is observed among the subjects of the Central and Volga Federal Districts. The lowest indicators of the insurance market development and its efficiency are observed in most regions of the North Caucasus and Far Eastern Federal Districts.

The general conclusion is that, despite the differentiated conditions of the socio-economic development of the regions of Russia, the level of development of insurance markets in most regions is equally low. Most of the ratings of insurance markets of the regions are significantly lower than the ratings of these regions in terms of the socio-economic development.

3. Conclusion and recommendations

The evaluation of the model provides the authors with an opportunity to draw the following summary:

1. The proposed model gives a quantitative description of the insurance market of

Table 3. Ratings of Russian regions by integral indices of socioeconomic development and insurance market development

Regions of Russia Indicators of socio-economic development Indicators of insurance development

Integral index I Rating of the region Integral index J Rating of the region

1 2 3 4 5

The Russian Federation total 0,3216 - 0,2339 -

Central Federal District 0,4231 1 0,3670 1

Belgorod Region 0,3097 13 0,1359 51

Bryansk Region 0,1410 68 0,1493 34

Vladimir Region 0,1885 49 0,1413 46

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Continuation of Table 3

1 2 3 4 5

Voronezh Region 0,2758 23 0,1633 20

Ivanovo Region 0,1833 53 0,1389 48

Kaluga Region 0,2701 25 0,1616 23

Kostroma Region 0,1366 69 0,1624 21

Kursk Region 0,2815 20 0,1199 63

Lipetsk Region 0,3084 14 0,1278 56

MoscowOblast 0,4393 7 0,1782 12

Oryol Region 0,1869 50 0,1336 54

Ryazan Region 0,1806 54 0,1699 14

Smolensk Region 0,2017 45 0,1837 9

Tambov Region 0,2423 31 0,1220 61

Tver Region 0,1774 58 0,1642 19

Tula Region 0,2820 19 0,1558 29

Yaroslavl Region 0,2036 44 0,1646 18

Moscow 0,5838 2 0,6444 1

North-Western Federal District 0,3675 3 0,2576 2

RepublicofKarelia 0,2115 41 0,1653 16

KomiRepublic 0,2700 26 0,1443 42

Arkhangelsk Region 0,3062 16 0,2193 5

Vologda Region 0,2462 30 0,1596 27

Kaliningrad Region 0,2728 24 0,1614 24

Leningrad Region 0,3535 12 0,0855 70

Murmansk Region 0,3946 8 0,1519 31

Novgorod Region 0,1780 56 0,1262 57

Pskov Region 0,1294 72 0,1553 30

SaintPetersburg 0,4541 6 0,3579 2

Southern Federal District 0,2160 7 0,1478 7

RepublicofAdygea 0,1803 55 0,0949 68

RepublicofKalmykia 0,1568 63 0,0784 76

Republic of Crimea 0,1554 64 0,0800 73

KrasnodarskiyKray 0,1972 46 0,1655 15

Astrakhan Region 0,2488 29 0,1406 47

Volgograd Region 0,2053 43 0,1483 35

Rostov Region 0,2095 42 0,1618 22

Sevastopol 0,2648 27 0,0355 80

North Caucasus Federal District 0,1593 8 0,0959 8

RepublicofDagestan 0,1614 62 0,0496 79

RepublicofIngushetia 0,0526 82 0,0034 82

Kabardino-BalkarianRepublic 0,1293 73 0,0801 72

Karachay-CherkessRepublic 0,0742 82 0,0841 71

Republic of North Ossetia-Alania 0,1333 70 0,0864 69

ChechenRepublic 0,1210 74 0,0303 81

StavropolTerritory 0,1839 52 0,1599 25

Volga Federal District 0,2454 5 0,1597 4

RepublicofBashkortostan 0,2206 38 0,1460 38

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Continuation of Table 3

1 2 3 4 5

RepublicofMariEl 0,1046 78 0,1361 50

RepublicofMordovia 0,1851 51 0,1414 44

RepublicofTatarstan 0,3744 10 0,1781 13

UdmurtRepublic 0,1140 75 0,1480 36

ChuvashRepublic 0,1482 66 0,1375 49

Perm Region 0,1947 48 0,1464 37

Kirov Region 0,1702 60 0,1181 64

NizhnyNovgorod Region 0,2762 22 0,1862 8

Orenburg Region 0,2272 36 0,1346 52

Penza Region 0,1968 47 0,1342 53

Samara Region 0,2821 18 0,1863 7

Saratov Region 0,1779 57 0,1445 41

Ulyanovsk Region 0,1734 59 0,1571 28

Ural Federal District 0,3829 2 0,1595 5

Kurgan Region 0,0846 79 0,1500 33

Sverdlovsk Region 0,2774 21 0,1815 11

Tyumen Region 0,5961 1 0,1459 39

Chelyabinsk Region 0,2340 35 0,1835 10

Siberian Federal District 0,2236 6 0,1616 3

RepublicofAltai 0,1331 71 0,0785 75

RepublicofTyva 0,0829 80 0,0799 74

RepublicofKhakassia 0,1477 67 0,1261 58

AltaiTerritory 0,1117 77 0,1261 59

KrasnoyarskTerritory 0,3074 15 0,1512 32

Irkutsk Region 0,2187 39 0,1598 26

Kemerovo Region 0,1685 61 0,1414 45

Novosibirsk Region 0,2586 28 0,2396 3

Omsk Region 0,2156 40 0,1648 17

Tomsk Region 0,2350 34 0,1454 40

Far Eastern Federal District 0,3004 4 0,1570 6

RepublicofBuryatia 0,1508 65 0,1145 66

RepublicofSakha (Yakutia) 0,3591 11 0,0642 77

Trans - BaikalTerritory 0,2215 37 0,1176 65

Kamchatka Region 0,3916 9 0,1416 43

PrimorskyKrai 0,2373 33 0,2094 6

Khabarovsk Territory 0,2968 17 0,2248 4

Amur Region 0,2400 32 0,1203 62

Magadan Region 0,4955 4 0,1117 67

Sakhalin Region 0,5006 3 0,1236 60

Jewish Autonomous Region 0,1137 76 0,1308 55

Chukotka Autonomous Okrug 0,4647 5 0,0528 78

Calculated according to Federal State Statistics Service. [electronic resource].URL: https://rosstat.gov.ru; Официальный сайт Банка России. [Электронный ресурс]. URL: cbr.ru/statistics/insurance/

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Table 4. Cross reference between the development of insurance markets and socio-economic development by Federal Districts

Federal Districts (FD) The number of regions where the level of development of the Insurance market is higher than the level of socio-economic development of the region The number of regions where the level of development of the Insurance market corresponds to the development of the socio-economic sphere The number of regions where the level of development of the Insurance market is below the level of socio-economic development Totals (corresponding to the total number of regions in the district)

Central FD 6 8 4 18

Northwest FD 3 4 3 10

South FD 2 2 4 8

North Caucasian FD 2 4 1 7

Privolzhsky FD 8 5 1 14

Uralsky FD 2 1 1 4

Siberian FD 5 4 1 10

Far Eastern FD 3 1 7 11

the Russian Federation total 31 29 22 82

Source: Compiled by the authors.

the region in a two-dimensional comparison. Based on the definition of ratings of insurance markets and ratings of socio-economic development of regions, it is possible to compare: a) regions with each other according to the level of development of insurance markets; b) the level of development of the insurance market of a particular region with the level of its socioeconomic development.

2. The advantage of this model is the use of formalized and objective criteria (indicators) for assessing regions and insurance markets. Therefore, the model is universal and could be applied to any country with a transitive economy.

3. The proposed model is open to supplement the list of indicators. Depending on the specifics and conditions of development of a particular country, the list of indicators used both to assess the rating of the region and to assess the rating of the insurance market might vary.

4. Other countries with transitive economies also have problems of uneven development of insurance markets. Therefore, this model could be applied to any country with an administrative-territorial division, and allows to analyze the degree of this disparity.

5. Ensuring that the level of development of insurance markets corresponds to the general level of economic development is a global

problem that hinders the active functioning of the global insurance market and the inefficient distribution of insurance capital. The proposed model makes it possible to assess the regional insurance market, to identify problem regions, and, based on the results obtained, to develop a regional insurance policy aimed at solving the identified problems.

Due to the results obtained, the following recommendations could be made to increase the economic potential of regional insurance markets in order to reduce discrepancies between the level of development of the economy and insurance markets.

1. To develop the level of insurance culture of the population, thereby forming the demand for voluntary insurance services.

2. To encourage the introduction of state and regional insurance support programs, for example, in agricultural insurance, housing insurance, environmental risk insurance and other types of insurance that are significant on a regional and global scale.

3. To increase the transparency of pricing in insurance activities and to limit the share of remuneration to intermediaries through legislative or regulatory measures. This recommendation could stimulate demand for insurance services. Currently, this is hindered by the

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inflated cost of insurance services, which is observed in many countries with economies in transition.

4. To improve the professionalism of specialists in the field of insurance by developing insurance education and scientific potential in countries and regions.

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5. Stimulate competition in insurance markets and improve the quality of insurance services, especially at the stage of loss settlement. The growth of competition will help accelerate the integration of countries with a transition economy into the global insurance community.

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