Abstract
The study is about territories rankings based on the application of statistical methodology for the purposes of characterizing the condition of territory (socio-economic, political, and ecological at a specific date and for the purposes of evaluation of changes of this condition over time. A proposed system of indicators allows building a comprehensive quantitative assessment (rating) of a particular territory. The author provides a generic algorithm for ranking. Also results of approbation of this algorithm on the example of the Russian Federation are shown. Scientific novelty and practical value of the research are reflected. The directions and challenges of the further development of research are presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arkhangelskaya, L. Yu. (2015). Assessment of the socio-political attractiveness of regions as an effective instrument of regional management. In R. M. Nureyev, M. L. Alpidovskaya, & D. E. Sorokin (Eds.), coll. Development of modern Russia: Problems of reproduction and creation. Moscow: Financial University, 2015 Electronic Edition.
Arkhangelskaya L. Y. (2017). Methodology of statistical evaluation of territories development level as subsystem of monitoring state-regional governance interaction. In Global economy in the twenty-first century dialectics of confrontation and solidarity, Chapter 4.3 (pp. 273–284).
Sulakshin, S. S. (2014). Man and the State: Development and management; A collection of works (Vol. 1). Moscow: Science and Politics.
Bratersky M. V. (2011). Economic instruments of foreign policy and political risks (pp. 152–208). Moscow: Higher School of Economics. 2010.
Kogay E. A. (2012) Promotion of the region image in communications space. In Article in coll. XII International Scientific Conference on the Problems of Economy and Society Development (Vol. 3, pp. 222–228). Moscow: Ed. House of the HSE.
Bocharov, M. A. (2014). Russia in figures. The ratings of the regions based on the results of socio-economic development in 2013. Issue 1/Series “Publication for the Decision-Makers.”-m., “White algae”.
Sahlin, V. N., & Arkhangelskaya, L. Y. (2016). Political statistics in Russia: Formation and development. Vestnik of the Financial University. Humanities, 3(23), 33–42.
Lipina, S. A., Agapova, E. V., & Lipina, A. V. (2018). Development of green economy in Russia: Opportunities and prospects. Moscow: LENAND.
Stiglitz, D., Sen, A., Fitoussi, J.-P. (2016). Mis-measuring our lives: Why GDP doesn’t add up: The report by the Commission on the Measurement of Economic Performance and Social Progress Russ. Ed.: translation of I. Kushnareva; science editor T. Drobyshevskaya. Moscow: Ed. House of Gaidar Institution.
Tikunov, A. V. Integral indicators of spatial patterns of world countries development. Moscow: Book House “LIBROKOM”.
Akhrimenko, A. S. (2012). The method of basic development models of Russia’s regions efficiency estimation. In Article in coll. XII International Scientific Conference on the Problems of Development of Economy and Society (Vol. 2, pp. 312–322) Moscow: Ed. House of the HSE.
The UN Report on Human Development. (2011). http://hdr.undp.org/HDR_2011.
Kobzeva S. V. (2010). World systems for monitoring crises and conflicts: A methodological review. Systemic monitoring of global and regional risks/Resp. Ed. YES. Khalturina, A. V. Korotaev, Yu. V. Zinkin (pp. 30–60). Moscow: Publishing House LCI.
Gasparyan, O. T., Kamalova, R. U., & Kocheshkova E. A., et al. (2014). Development indices of the states of the world: Reference book. In Nisnevich, Yu. A. (Ed.), Nat. Issled. University Higher School of Economics. Moscow: Izd. House of the Higher School of Economics.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendices
Appendix 1
Economic indicators (i = 1) [6], pp. 11–12, [7]
Indicator | Calculation form | |
|---|---|---|
Positive/negative | Gross indicator, c.u. | Per capita, c.u./pers.; nat. c.u./pers. |
GRP (1.1) | Trillion rub | |
Net balance financial result (profit) +/(loss)−(1.2)) | Trillion rub | |
Agricultural production (1.3) | Billion rub | |
Production of livestock and poultry for slaughter (live weight) (1.4) | Million. t | |
Milk production (1.5) | Million. t | |
Investments in fixed capital (1.6) | Trillion rub | |
Foreign investment (1.7) | Billion USD | |
The number of economic entities on 01.01. 2xxx g. (1.8) | Thous. u. | |
The number of individual entrepreneurs on 01.01.2 xxx (1.9) | Thous. u. | Per 1000 people |
Transportation of cargoes by railway public transport (small entrepreneurship subjects excluded) (1.10) | Billion. t | Per 1000 people |
Loading cargo at railway public transport (1.11) | Billion. t | |
Income of taxes, fees and other mandatory payments to the budget of the Russian Federation (1.12) | Trillion rub | |
Appendix 2
Indicators of social development of the territories (i = 2) [6], pp. 12–13, [7].
Indicator | Calculation form | |
|---|---|---|
Positive/negative | Gross indicator, c.u. | Per capita, c.u./capita.; nat. c.u./capita. |
Commissioning of residential space (2.1) | Million. M2 | Per capita |
–/Total mortality (2.2) | Thous. people | Per 1000 people of population |
–/Child mortality under the age of 1 year (2.3) | Thous. people | 1000 people born |
Construction of outpatient clinics (2.4) | Visits per shift | Per capita |
Construction of hospitals (2.5) | Beds | Per 100,000 people of population |
Construction of schools (2.6) | Students. Places | Per 100,000 people of population |
Construction of kindergartens (2.7) | Places | Per 1000 people of population |
Average monthly nominal wages (2.8) | Rub. | Per capita of employed population |
Average money income per capita (per month) (2.9) | Thous. rub. | Thous. Rub/person—the month |
(–)/Number of recorded crimes (2.10) | The number of crimes | /1000 people |
(–)/Unemployed | Thous. people | Per 100 people of population |
The average length of education for population aged from 6 to 24 years | Years | |
Expectancy of length of education for population aged 6 to 24 years (2.13) | Years | |
The average life expectancy for the generation born in the current year (2.14) | Years | |
Appendix 3
Indicators of political development of the territories (i = 3) [2]
Indicator | Calculation form | |
|---|---|---|
Positive/negative | Gross indicator | Per capita, c.u./capita.; nat. c.u./capita. |
The number of the electorate (3.1) | Thous. people | |
The number of parties and public organizations (3.2) | Thous. org. | Per 10 thous. man |
(–)/Number of political conflicts (3.3) | Confl. | Per 1000 people |
Number of polling stations (3.4) | U. | Per 10,000 people |
The number of candidates in elections (3.5) | People | Per 10,000 people |
The number of armed conflicts in the territory (3.6) | Confl. | Per 10,000 people |
The number of victims of armed conflicts (3.7) | People | Per 10,000 people |
The type of political power (3.8) | Point score | |
(–)/Number of victims of political conflicts (3.9) | Per 1000 people | |
Attribute groups according religion (3.10) and national composition of the electorate (3.11) | Thous. people % | Frequency distribution |
Appendix 4
Environmental indicators of territories (i = 4) [8,9,10]
Indicator | Calculation form | |
|---|---|---|
Positive/negative | Gross indicator | Per capita, c.u./capita.; nat. c.u./capita. |
Environmental capacity (±) (4.1) | Area (km2)/GRP GRP-gross regional product | |
Natural resource productivity (±) (4.2) | GRP/km2 | |
Instant environmental capacity(±) (4.3) | Level of resources/need for res. 1 person | |
Area (4.4) | Thous. km2 | |
Population density (4.5) | People/km2 | |
Provision of drinking water to the population l/year per person (4.6) | Thous l | Per capita |
Air pollution on the types of contaminants (±) (4.7) | Million t/m3 | Per capita, kg/person |
Soil pollution degree on 1 km2 (±) (4.8) | Million km2 | Per capita |
The number of anthropogenic disasters by type (–) (4.9) | Disasters | Per 10,000 people of population |
Power supply per production unit by types of energy sources (energy supply) (ΜW-h/km2) (4.10) | MKW-hour | Per capita |
Agricultural area, thous. hectares (4.11) | Thousand hectares | Per capita |
The degree of water pollution of the territory by type (±) (4.12) | Million. M3 | Per capita |
Subsoil assets by type (4.13) | NAT. U | Per capita |
Forest area (4.14) | Million. hectares | Per capita |
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Arkhangelskaya, L.Y., Sitnikova, O.Y., Vachrameeva, M.V. (2019). Quantitative Measurement of Territories’ Ratings. In: Popkova, E. (eds) Ubiquitous Computing and the Internet of Things: Prerequisites for the Development of ICT. Studies in Computational Intelligence, vol 826. Springer, Cham. https://doi.org/10.1007/978-3-030-13397-9_55
Download citation
DOI: https://doi.org/10.1007/978-3-030-13397-9_55
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-13396-2
Online ISBN: 978-3-030-13397-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)