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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 2/2026. Economics and Management.

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Alexey I. Boldiasov

Market analyst, PromKhimResurs-D LLC, Dzerzhinsk, Russia

ORCID: 0000-0002-7307-900X

 

OPTIMAL SAFETY STOCK CALCULATING IN THE NON-FERROUS METALS WHOLESALE TRADE

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The work is devoted to the development of models of optimal insurance inventory for trading enterprises specializing in the wholesale of non-ferrous metals. The approaches to optimizing the insurance stock in the literature have been identified: heuristic; level of service; robust optimization; the “Newsvendor” model and its variations; multi-criteria and targeted optimization; cost minimization; loss minimization; use of digital tools. The insurance inventory in the industry is the minimum amount of inventory that guarantees the required level of service during the time before the replenishment of commodity resources or the organization of transit delivery to the customer with an unknown discrete, integer distribution of demand (order volume). Two models based on the universal estimation of probability bounds by Chebyshev and Cantelli inequalities, respectively, and a distributed robust optimization model based on a linear programming problem with a constraint on moments and an upper bound on a random variable are proposed. Empirical research based on real data shows that with a service level of 0,90 and 0,95, the difference in results between the compared models is only 1–2 tons, which makes a more conservative solution preferable, since it is universal for any distribution. In the example under consideration, with a service level of 0,99 corresponding to the minimum probability of shortage, models based on probabilistic inequalities can obtain an insurance stock of 70 to 100 tons, while a model based on a linear programming problem recommends keeping an insurance stock equal to the maximum value of demand (order volume). In this case, the solution is a compromise between the high opportunity costs of storing insurance inventory and the loss of robustness to ignorance of distribution due to the introduction of an upper limit on demand (order volume).

Keywords: wholesale trade, non-ferrous metals, insurance stock, service level, robust optimization, Chebyshev inequality, Cantelli inequality, linear programming.

JEL: L81, L61, M21

EDN: BJPJVS

DOI: https://doi.org/10.52180/2073-6487_2026_2_99_123

References

  1. Bulatov S.V. Improvement of the efficiency of duplicates at a motor transport enterprise if an insurance reserve is available // Bulletin of Bryansk state technical university. 2021. No. 9 (106). Pp. 43–48. (In Russ.). EDN: ABRJSL. DOI: 10.30987/1999-8775-2021-9-43-48.
  2. Zemskov A.V., Ljan Ja., Klykov M.S. Optimization of safety stocks of material and technical products in transport construction organizations // Scientific, technical and economic cooperation of Asia-Pacific countries in the 21st century. 2014. No. 1. Pp. 127–129. (In Russ.). EDN: SGSRDH.
  3. Kacovich D.M., Najdis O.A. Improving the inventory management system through the implementation of dynamic standardization // Logistics. 2023. No. 7-8 (200-201). Pp. 20–25. (In Russ.). EDN: EUAMJG. DOI: 10.54959/22197222_2023_07_08_20.
  4. Miksyuk S.F., Ankuda E.V. Inventory management in procurement logistics in corporate information system: a conceptual approach // Belarusian Economic Journal. 2020. No. 1 (90). Pp. 138–147. (In Russ.). EDN: ZLLSJO.
  5. Skvoroda E.V. Model of formation of insurance stock of material resources of enterprises of chemical industry // Proceedings of BSTU. Series 5: Economics and Management. 2018. No. 2 (214). Pp. 69–73. (In Russ.). EDN: YPTTZB.
  6. Solomakha G.M., Tulueva V.A., Khizhnyak S.V. Deterministic models of inventory management in a manufacturing enterprise with changing characteristics of demand, supply and storage // Herald of Tver State University. Series: Applied Mathematics. 2025. No. 1. Pp. 51–66. (In Russ.). EDN: WYWNCY. DOI: 10.26456/vtpmk729.
  7. Chendilova E.B. Method of calculating safety stock of finished goods in the mining industry // Russian Journal of Industrial Economics. 2013. No. 2. Pp. 83–88. (In Russ.). EDN: QJFATP.
  8. Elyashevich I.P. Harmonic analysis in inventory management in logistics and supply chains // Lomonosov Economics Journal. 2023. Vol 58. No. 4. Pp. 223–246. (In Russ.). EDN: RHDDZV. DOI: 10.55959/MSU0130-0105-6-58-4-10.
  9. Amirjabbari B., Bhuiyan N. Determining Supply Chain Safety Stock Level and Location // Journal of Industrial Engineering and Management. 2014. Vol. 7. No. 1. Pp. 42–71. DOI:10.3926/jiem.543.
  10. Arrow K., Harris T., Marschak J. Optimal Inventory Policy. 1951. Econometrica. Vol. 19. No. 3. Pp. 250–272. DOI: 10.2307/1906813.
  11. Apollonio N. Cantelli’s Bounds for Generalized Tail Inequalities // Axioms, 2025. Vol. 14. No. 43. Pp. 1–18. DOI: 10.3390/axioms14010043.
  12. Barros L., Cortez P., Sameiro-Carvalho M. A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process // Operations Research Perspectives. 2021. No. 8. Pp. 1–25. DOI: 10.1016/j.orp.2021.100192.
  13. Bazyar A., Taghizade G. A Multi-objective Multi-item Capacitated Lot-sizing Model with Safety Stock and Shortage Costs based on Just-in-time Approach // Global Journal of Economic and Finance Research. 2025. Vol. 2. No. 4. Pp. 171–180. DOI: 10.55677/GJEFR/01-2025-Vol02E4.
  14. Chen B. Data-Driven Inventory Control with Shifting Demand // Production and Operations Management. 2021. Vol. 30. No. 5. Pp. 1–38. DOI: 10.1111/poms.13326.
  15. Cinfrignini A., Petturiti D., Stabile G. Newsvendor problem with discrete demand and constrained first moment under ambiguity // Decisions in Economics and Finance. 2024. No. August. Pp. 1–34. DOI: 10.1007/s10203-024-00477-7.
  16. Díaz D., Marta R., Ortega G., Ponce H. A Machine Learning Approach for Modeling Safety Stock Optimization Equation in the Cosmetics and Beauty Industry // Advances in Computational Intelligence. 2021. MICAI 2021. Lecture Notes in Computer Science. Vol. 13067. Springer, Cham. Pp. 173–186. DOI: 10.1007/978-3-030-89817-5_13.
  17. Farahinejad K., Gholamian M. Optimizing the Safety Stock with Guaranteed Service Model in Reverse Logistics Considering Internal and External Returns // International Journal of Supply and Operations Management. 2019. Vol. 6. No. 3. Pp. 188–199. DOI: 10.22034/2019.3.1.
  18. Fleuren T., Merzifonluoglu Y., Hendriks M., Sotirov R. Integrated production and safety stock planning in high-tech manufacturing: a comparative study at ASML // Flexible Services and Manufacturing Journal. 2025. No. November. Pp. 1–44. DOI: 10.1007/s10696-025-09634-5.
  19. Ghosh S., Mukhoti S. Non-parametric generalised newsvendor model // Annals of Operations Research. 2021. No. 321. Pp. 241–266. DOI: 10.1007/s10479-022-05112-5.
  20. Gijsbrechts J., Boute R., Mieghem J., Zhang D. Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems // Manufacturing & Service Operations Management. 2021. Vol. 24. No. 3. Pp. 1349–1368. DOI: 10.1287/msom.2021.106.
  21. Gotoh J., Takano Y. Newsvendor solutions via conditional value-at-risk minimization // European Journal of Operational Research. 2006. No. 179. Pp. 80–96. DOI: 10.1016/j.ejor.2006.03.022.
  22. Kelle P. On the safety stock problem for random delivery processes // European Journal of Operational Research. 1984. Vol. 17. No. 2. Pp. 191–200.
  23. Kim D., Farmaciawaty D., Nizar A. Strategic Safety Stock Level for High Import Dependence Manufacturing Supply Chain for Enhanced Force Majeure Preparedness // Eduvest – Journal of Universal Studies. 2025. Vol. 5. No. 7. Pp. 9080–9097. DOI: 10.59188/eduvest.v5i7.51630.
  24. Khokhar M., Zia S., Khan S., Saleem S., Siddiqui A., Abbas M. Decision Support System for Safety Stock and Safety Time Buffers in Multi-Item Single-Stage Industrial Supply Chains // International Journal of Information Systems and Social Change. 2023. Vol. 14. No. 1. Pp. 1–13. DOI: 10.4018/IJISSC.324933.
  25. Mercadier M., Strobel F. A one-sided Vysochanskii-Petunin inequality with financial applications // European Journal of Operational Research. 2021. Vol. 295. No. 1. Pp. 374–377. DOI: 10.1016/j.ejor.2021.02.041.
  26. Modares A., Farimani N., Emroozi V. Developing a Newsvendor Model based on the Relative Competence of Suppliers and Probable Group Decision-making // Industrial Management Journal. 2022. Vol. 14. No. 1. Pp. 115–142. DOI: 10.22059/IMJ.2022.331988.1007872.
  27. Moncayo-Martínez L., Reséndiz-Flores E., Mercado D., Sánchez-Ramírez C. Placing Safety Stock in Logistic Networks under Guaranteed-Service Time Inventory Models: An Application to the Automotive Industry // Journal of Applied Research and Technology. 2014. Vol. 12. No. 3. Pp. 538–550. DOI: 10.1016/s1665-6423(14)71633-5.
  28. Nurbandini R., Sadirsan E. Optimization of Re-Order Point (ROP) and Safety Stock (SS) for RON 92 Fuel (Pertamax) Using the Economic Order Quantity (EOQ) Method at Pertashop Ulak Bandung, Muara Enim Regency // Journal of Management and Energy Business. 2025. Vol. 5. No. 1. Pp. 79–87. DOI: 10.54595/jmeb.v5i1.105.
  29. Panas E., Ninni V. The Distribution of London Metal Exchange Prices: A Test of the Fractal Market Hypothesis // European Research Studies. 2010. Vol. 13. No. 2. Pp. 193–210. DOI: 10.35808/ersj/284.
  30. Prékopa A. The discrete moment problem and linear programming // Discrete Applied Mathematics. 1990. Vol. 27. No. 3. Pp. 235–254. DOI: 10.1016/0166-218X(90)90068-N.
  31. Scarf H. A min-max solution of an inventory problem. In: Studies in the Mathematical Theory of Inventory and Production // Stanford University Press*, California, 1958. Pp. 201–209. DOI: 10.1057/9781137024381_3.
  32. Watkins C., McAleer M. Pricing of non-ferrous metals futures on the London Metal Exchange // Applied Financial Economics. 2006. Vol. 16. No. 12. Pp. 853–880. DOI: 10.1080/09603100600756514.
  33. Zhang J., Xie W., Sarin S. Robust Multi-Product Newsvendor Model With Substitution Under Cardinality-Constrained Uncertainty Set // European Journal of Operational Research. 2020. Vol. 293. No. 1. Pp. 1–58. DOI: 10.1016/j.ejor.2020.12.023.

* Stanford University (США) признан нежелательной организацией в России.

Manuscript submission date: 09.02.2026

Manuscript acceptance date: 02.04.2026

 

For citation:

Boldiasov A.I. Optimal safety stock calculating in the non-ferrous metals wholesale trade // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2026. № 2. Pp. 99-123. (In Russ.). https://doi.org/10.52180/2073-6487_2026_2_99_123 EDN: BJPJVS

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 2/2026. Economics and Management.

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Anastasiia A. Dryndak

Cand. Sci. (Econ.), Associate Professor of the Department of Enterprise Economics, Donetsk State University, Donetsk, Russia

ORCID: 0000-0003-1461-6140

 

DEVELOPMENT OF THE AGRO-INDUSTRIAL COMPLEX OF THE DONETSK PEOPLE’S REPUBLIC IN THE FACE OF EXTERNAL CHALLENGES AND INTERNAL CONSTRAINTS

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The study revealed contradictory dynamics in the development of agro-industrial complex of the Donetsk People’s Republic. On the one hand, a significant progress has been made in crop production and certain areas of animal husbandry, on the other hand, systemic problems persist that hinder the realization of production potential. The key challenges include: high depreciation of machinery, technological dependence on imports, structural imbalances between export-oriented and import-substituting industries, as well as external risks. A set of measures has been developed to modernize the agro-industrial complex, including technological renewal of production and infrastructure, development of the research base, restructuring of industries and improvement of investment policy. Special attention is paid to the need to develop the processing industry and increase the share of high-value-added products.

Keywords: agro-industrial complex, DPR, sustainable development, crop production, animal husbandry, food security, export potential.

JEL: Q13, Q18, R11

EDN: XLLIJJ

DOI: https://doi.org/10.52180/2073-6487_2026_2_83_98

References

  1. The economy of the Donetsk People’s Republic: state, problems, solutions: a collective monograph / collective of authors of Institute of Economic Research; under the scientific editorship of A.V. Polovyan; Institute of Economic Research. Donetsk. 2024. (In Russ.).
  2. The economy of the Donetsk People’s Republic: state, problems, solutions: a scientific report / edited by A.V. Polovyan, R.N. Lepa, N.V. Shemyakina. Donetsk: State Institution «Institute of Economic Research», 2021. (In Russ.).
  3. Economic security in the sphere of management: legal aspects: a monograph / collective of authors of Institute of Economic Research; under the scientific editorship of N.L. Shelukhin. Donetsk. 2024. (In Russ.).
  4. Strelina E.N., Aliev A.R. Methodological foundations of the application of a project-oriented approach in agriculture // Bulletin of Donetsk National University. Series B. Economics and law. 2025. No. 4. Pp. 389–399. (In Russ.). EDN: EPALGF.
  5. Dryndak A.A. Strategic approaches to ensuring food security in conditions of uncertainty // Socio-economic and Humanitarian Journal. 2024. № 1 (31). Pp. 283–295. (In Russ.). EDN: NXQXFH.
  6. Kadomtseva M.E. System of indicators of sustainable development of the national agro-industrial complex // Studies on Russian Economic Development. 2024. No. 1 (202). Pp. 144–156. (In Russ.). DOI: 10.47711/0868-6351-202-144-156.
  7. Polyanskaya N.M., Kolesnyak A.A. Conceptual approaches to the study of the food supply system in the region // Socioeconomic and Humanitarian Journal. 2023. No. 1. Pp. 14–23. (In Russ.). DOI: 10.36718/2500-1825-2023-1-14-23.
  8. Donets L.I., Yakovenko Ya.A. Assessment of the consumer market of the Donetsk People’s Republic // Vestnik of Donetsk National University. Series B. Economics and Law. 2020. No. 4. Pp. 97–105. (In Russ.). EDN: TZPOZN.

Manuscript submission date: 14.02.2026

Manuscript acceptance date: 02.04.2026

 

For citation:

Dryndak A.A. Development of the agro-industrial complex of the Donetsk People's Republic in the face of external challenges and internal consrtaints // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2026. № 2. Pp. 83-98. (In Russ.). https://doi.org/10.52180/2073-6487_2026_2_83_98 EDN: XLLIJJ 

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 1/2026. Economics and Management.

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Ksenia Yu. Yadrishchenskaya

Postgraduate Student at Lomonosov Moscow State University, Moscow, Russia

ORCID: 0009-0009-8009-1216

 

THE ROLE OF LEISURE IN ASSESSING INDIVIDUAL WELL-BEING OF WORKING-AGE INDIVIDUALS

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This study introduces a novel methodology for assessing well-being, based on analyzing leisure time allocation among working-age individuals. The research constructs a latent well-being variable using measures of human capital (health and education) and material conditions (income). Applying a MIMIC model to the Sample Observation of Daily Time Use by the Population data (N = 52,177), we demonstrate a robust relationship between the latent well-being variable and leisure time allocation decisions. Our analysis classifies lei- sure activities into those positively, negatively, and nonlinearly associated with well-being levels, also revealing gender-based differences in well-being determinants during both workdays and weekends. The findings can be utilized in developing measures aimed at enhancing the quality of life and well-being of the population.

Keywords: time use, time allocation, well-being, leisure.

JEL: I31, J18, J22

EDN: YBMXBH

DOI: https://doi.org/10.52180/2073-6487_2026_1_109_132

References

  1. Kalabikhina I. E., Shamsutdinova V. Sh. Twice Poor: Who is in Time and Money Shortage // Journal of Social Policy Studies. 2023. No. 21 (4). Pp. 629–646. (In Russ.). DOI: 10.17323/727-0634-2023-21-4-629-646.
  2. Álvarez B., Miles-Touya D. Time Allocation and Women’s Life Satisfaction: Evidence from Spain // Social Indicators Research. 2016. Vol. 129. Pp. 1207–1230. DOI: 10.1007/s11205-015-1159-3.
  3. Aguiar M., Hurst Measuring Trends in Leisure: The Allocation of Time over Five Decades // The Quarterly Journal of Economics. 2007. Vol. 122. No. 3. Pp. 969–1006. http://www.jstor.org/stable/25098866.
  4. Bashkirova K. Determinants of health of Russia’s population based on daily time allocation data // Population and Economics. 2024. Vol. 8. No. 2. Pp. 1–18. DOI: 10.3897/popecon.8.e116960.
  5. Berset M., et al. Work Characteristics as Predictors of Physiological Recovery on Weekends // Scandinavian Journal of Work, Environment & Health. 2009. Vol. 35. No. 3. Pp. 188–192. http://www.jstor.org/stable/40967776.
  6. Böhnke P. First European Quality of Life Survey: Life satisfaction, happiness and sense of belonging. Social Science Research Centre (WZB). Berlin. 2005. https://www.eurofound.europa.eu/en/publications/2005/first-european-quality-life-survey-lifesatisfaction-happiness-and-sense-0.
  7. Chang C., et al. Comparing multiple statistical software for multiple-indicator, multiplecause modeling: an application of gender disparity in adult cognitive functioning using MIDUS II dataset // BMC Medical Research Methodology. 2020. Vol. 20. No. 275. DOI: 10.1186/s12874-020-01150-4.
  8. Dahm P.C., et al. Work-family conflict and self-discrepant time allocation at work // Journal of Applied Psychology. 2015. Vol. 100. No. 3. Pp. 767–792. DOI: 10.1037/a0038542.
  9. Fritz C., et al. The Weekend Matters: Relationships between Stress Recovery and Affective Experiences // Journal of Organizational Behavior. 2010. Vol. 31. No. 8. Pp. 1137–1162. http://www.jstor.org/stable/41683967.
  10. Gershuny J. Time-Use Surveys and the Measurement of National Well-Being. Swansea: Centre for Time Use Research, University of Oxford. 2011.
  11. Gimenez-Nadal J.I., Sevilla A. Trends in time allocation: A cross-country analysis // European Economic Review. 2012. Vol. 56. No. 6. Pp. 1338–1359. DOI: 10.1016/j.euroecorev.2012.02.011.
  12. Jöreskog K. G., Goldberger A. S. Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable // Journal of the American Statistical Association. 1975. Vol. 70. No. 351a. Pp. 631–639. DOI: 10.1080/01621459.1975.10482485.
  13. Kalil A., et al. Education gradients in parental time investment and subjective wellbeing // Review of Economics of the Household. 2024. Vol. 23. Pp. 661–706. DOI: 10.1007/s11150-024-09734-5.
  14. Kasser T., Sheldon K.M. Time Affluence as a Path toward Personal Happiness and Ethical Business Practice: Empirical Evidence from Four Studies // Journal of Business Ethics. 2009. Vol. 84 (2). Pp. 243–255. DOI: 10.1007/s10551-008-9696-1.
  15. Kekäläinen T., et al. Cross-Sectional and Longitudinal Associations between Leisure Time Physical Activity, Mental Well-Being and Subjective Health in Middle Adulthood // Applied Research in Quality of Life. 2020. Vol. 15. Pp. 1099–1116. DOI: 10.1007/s11482-019-09721-4.
  16. Knabe A., et al. Dissatisfied with Life but Having a Good Day: Time-use and Well-being of the Unemployed // The Economic Journal. 2010. Vol. 120. Pp. 867–889. DOI: 10.1111/j.1468-0297.2009.02347.x.
  17. Krueger A., et al. National Time Accounting: The Currency of Life. Measuring the Subjective Well-Being of Nations: National Accounts of Time Use and Well-Being // National Bureau of Economic Research. 2009.
  18. Kwarciński T., Ulman P., Wdowin J. Measuring Subjective Well-being Capability: A Multi-Country Empirical Analysis in Europe // Applied Research in Quality of Life. 2024. DOI: 10.1007/s11482-024-10334-9.
  19. Livingston, Jackson-Nevels B., Reddy V. Social, Cultural, and Economic Determinants of Well-Being // Encyclopedia. 2022. Vol. 2. Pp. 1183–1199. DOI: 10.3390/encyclopedia2030079.
  20. Martinez Mendiola A., Cortina C. Leisure time and parenting in Europe: a more difficult equation for mothers? // Family Relations. 2024. Vol. 73. No. 4. Pp. 2823–2845. DOI: 10.1111/fare.13017.
  21. Martinetti E.C. A multidimensional assessment of well-being based on sen’s functioning approach // Rivista Internazionale di Scienze Sociali. 2000. Vol. 108. No. 2. Pp. 207–239. http://www.jstor.org/stable/41634742.
  22. Merz J. Time and Economic Well–Being—A Panel Analysis of Desired versus Actual Working Hours // Review of Income and Wealth. 2002. Vol. 48. Pp. 317–346. DOI: 10.1111/1475-4991.00057.
  23. Nikolaev B. Does Higher Education Increase Hedonic and Eudaimonic Happiness? // Journal of Happiness Studies. 2018. Vol. 19. Pp. 483–504. DOI: 10.1007/s10902-016-9833-y.
  24. Nilsson A., Hellryd E., Kjell O. Doing well-being: Self-reported activities are related to subjective well-being // PLOS ONE. 2022. Vol. 17. No. e0270503. DOI: 10.1371/journal.pone.0270503.
  25. How’s Life?: Measuring Well-being // Paris: OECD Publishing. 2011. DOI: 10.1787/9789264121164-en.
  26. Okun M., et al. The Social Activity/Subjective Well-Being Relation: A Quantitative Synthesis // Research on Aging. 1984. Vol. 6. No. 1. Pp. 45–65. DOI: 10.1177/0164027584006001003.
  27. Orehek E., Inagaki T. On the Benefits of Giving Social Support: When, Why, and How Support Providers Gain by Caring for Others // Current Directions in Psychological Science. 2017. Vol. 26. Pp. 109–113.
  28. Rosseel Y. lavaan: An R Package for Structural Equation Modeling // Journal of Statistical Software. 2012. Vol. 48. No. 2. Pp. 1–36. DOI: 10.18637/jss.v048.i02.
  29. Ruggeri K., et al. Well-Being Is More Than Happiness and Life Satisfaction: A Multidimensional Analysis of 21 Countries // Health and Quality of Life Outcomes. 2020. Vol. 18. Pp. 192. DOI: 10.1186/s12955-020-01423-y.
  30. Rutskiy V. et al. Modeling the Well-Being of the Population and Its Factors Using the Well-Being Index // Networks and Systems in Cybernetics (CSOC 2023). Cham: Springer. 2023. Pp. 55. DOI: 10.1007/978-3-031-35317-8_55.
  31. Shao Q. Does less working time improve life satisfaction? Evidence from European Social Survey // Health Economics Review. 2022. Vol. 12. No. 50. DOI: 10.1186/s13561-022-00396-6.
  32. Stiglitz J., Sen A., Fitoussi J.-P. Report by the Commission on the Measurement of Economic Performance and Social Progress. 2009.
  33. Stutzer A., Frey B. S. Recent Developments in the Economics of Happiness: A Selective Overview // IZA Discussion Papers. 2012. No. 7078. Institute for the Study of Labor (IZA), Bonn.
  34. Suleiman A.O., et al. Worker perspectives on the impact of non-standard workdays on worker and family well-being: A qualitative study // BMC Public Health. 2021. Vol. 21. No. 2230. DOI: 10.1186/s12889-021-12265-8.
  35. Wajcman J., Bittman M. The Rush Hour: The Character of Leisure Time and Gender Equity // Social Forces. 2000. Vol. 79. DOI: 10.2307/2675568.
  36. Wang P., et al. The Impact of Residents’ Leisure Time Allocation Mode on Individual Subjective Well-being: The Case of China // Applied Research in Quality of Life. 2022. Vol. 17. Pp. 1831–1866. DOI: 10.1007/s11482-021-10003-1.
  37. Weston G., et al. Work hours, weekend working, nonstandard work schedules and sleep quantity and quality: findings from the UK household longitudinal study // BMC Public Health. 2024. Vol. 24. No. 309. DOI: 10.1186/s12889-024-17762-0.
  38. World Bank. World Development Report 1980. New York: Oxford University 1980.
  39. Yamaguchi S., Oshima H. Analysis of the Relationship Between Residential Environment and Multifaceted Well-Being // International Journal of Community Well-Being. 2024. Vol. 7. Pp. 467–489. DOI: 10.1007/s42413-024-00219-y.
  40. Zwierzchowski J., Panek T. Measurement of Subjective Well-Being Under Capability Approach in Poland // Polish Sociological Review. 2020. Vol. 210. Pp. 157–178. DOI: 10.26412/psr210.02.

Manuscript submission date: 28.07.2025

Manuscript acceptance date: 24.02.2026

 

For citation:

Yadrishchenskaya K.Yu. The role of leisure in assessing individual well-being of working-age individuals // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2026. № 1. Pp. 109-132. (In Russ.). https://doi.org/10.52180/2073-6487_2026_1_109_132 EDN: YBMXBH

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 2/2026. Economics and Management.

.xmlJATS XML

Evgeny M. Buchwald

Dr. Sci. (Econ.), Professor, Chief Researcher, Center for Federal Relations and Regional Development, Institute of Economics of the RAS, Moscow, Russia

ORCID: 0000-0001-9892-5930

 

Olga N. Valentik

Researcher, Center for Federal Relations and Regional Development, Institute of Economics of the RAS, Moscow, Russia

ORCID: 0000-0003-0529-0855

 

THE FORMATION OF ANCHOR POINTS OF SPATIAL DEVELOPMENT OF THE RUSSIAN FEDERATION ECONOMY AT THE PRESENT STAGE: PRIORITIES, PROBLEMS AND WAYS OF THEIR PRACTICAL SOLUTION

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The adoption at the end of 2024 of a new version of the Spatial Development Strategy of the Russian Federation for the period up to 2030 and with a forecast up to 2036 confirmed the fact that spatial strategizing remains a necessary component for the strategic management of economic and social processes in the country. At the same time, there has been established a position that the success of such a strategy-building practice in this case is determined not only by its legal and regulatory framework, but also by its reliance on a holistic system of spatial development and regulatory institutions, many of which (even with some historical analogies) can be considered innovative for our practice of state and municipal governance. In this sense, a significant advantage of the Strategy-2024 for development of local self-government and its implementation plan should be indicated as their emphasis on solving specific institutional and managerial tasks in the spatial development sphere, as well as on establishing pathways for achieving these challenges, particularly through the creation of growth “anchors” and innovative development of the Russian economy. The article emphasizes the need to prepare and adopt a new Strategy for the development of Russian local self-government and outlines the fundamental innovations that should be enshrined in this strategic planning document. This includes maintaining the status of Russian local self-government as an institution of civil society and ensuring the direct participation of the population in its implementation.

Keywords: strategic planning, spatial strategizing, growth anchors, small and medium-sized settlements, municipalities.

JEL: R12, R58

EDN: HGZYCH

DOI: https://doi.org/10.52180/2073-6487_2026_2_66_82  

References

  1. Babashkin V.V. Retrospects of “unpromising” villages // Peasant research. 2018. Vol. 3. No. 3. Pp. 186–194. (In Russ.).
  2. Buchwald E.M., Valentik O.N., Kolchugina A.V. Small and medium-sized towns in the Strategy of Spatial Development of the Russian Federation: Report. Moscow: Institute of Economics of the RAS. 2019. (In Russ.).
  3. Buchwald E.M., Valentik O.N. Corrections in the spatial development strategy: are there serious movements forward? // Regional economy. South of Russia. 2023. Vol. 11. No. 1. Pp. 31–42. (In Russ.). DOI: 10.15688/re.volsu.2023.1.3.
  4. Domnina I.N. Geostrategic Territories in Strategic Plans for the Transformation of the Spatial Model of the Russian Economy // Bulletin of the Institute of Economics of the Russian Academy of Sciences. 2025. No. 5. Pp. 65–80. (In Russ.). DOI: 10.52180/2073-6487_2025_5_65_80.
  5. Ivanov O.B., Buchwald E.M. Spatial development strategy: new visions and old problems // ETAP: economic theory, analysis, practice. 2022. No. 5. Pp. 7–26. (In Russ.). DOI: 10.24412/2071-6435-2022-5-7-26.
  6. Korolenko A.V. Spatial transformations of Russian territories: trends and regional differences in settlement // Problems of territory development. 2023. Vol. 27. No. 1. Pp. 47–75. (In Russ.). DOI: 10.15838/ptd.2023.1.123.4.
  7. Marquart E., Kiseleva N.N., Sosnin D.P. The system of anchor settlements as a mechanism for managing spatial development: theoretical and practical aspects // Power. 2022. No. 2. Pp. 95–111. (In Russ.).
  8. Peshkova V.V. The problem of liquidation of “unpromising” villages in the 1960s and 1980s and its consequences // History and social studies. 2021. No. 18. Pp. 95–99. (In Russ.).
  9. Fedorovskaya A.A., Tkachenko D.A. Key settlements on the territory of the Russian Federation. In the collection: Construction and architecture. Rostov-on-Don. 2023. Pp. 62–63. (In Russ.).

Manuscript submission date: 14.11.2025

Manuscript acceptance date: 02.04.2026

 

For citation:

Buchwald E.M., Valentik O.N. The formation of anchor points of spatial development of the Russian Federation economy at the present stage: priorities, problems and ways of their practical solution // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2026. № 2. Pp. 66-82. (In Russ.). https://doi.org/10.52180/2073-6487_2026_2_66_82 EDN: HGZYCH

 

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 1/2026. Economics and Management.

.xmlJATS XML

Shamil M. Gimbatov

Cand. Sci. (Econ.), Leading Researcher, Institute of Socioeconomic Research, Dagestan Federal Research Center of the RAS, Makhachkala, Russia

ORCID: 0000-0002-8302-3544

 

Zaur U. Medzhidov

Cand. Sci. (Econ.), Researcher, Institute of Socioeconomic Research, Dagestan Federal Research Center of the RAS, Makhachkala, Russia

ORCID: 0000-0002-6008-1661

 

Dmitry N. Kobzarenko

Dr. Sci. (Eng.), Leading Researcher, Institute of Socioeconomic Research, Dagestan Federal Research Center of the RAS, Makhachkala, Russia

ORCID: 0000-0002-0963-7935

 

Amina Sh. Gimbatova

student, Dagestan State Medical University of the Ministry of Health of the Russian Federation, Makhachkala, Russia

 

TYPOLOGY OF SOCIO-ECONOMIC BEHAVIOR OF THE REPUBLIC OF DAGESTAN POPULATION

Размер файла87-108
 Размер файла   377.93 KB Размер файла Full text

The purpose of the study is to identify the population groups in the Republic of Dagestan according to the peculiarities of socio-economic behavior and life support strategies. The study was conducted using machine learning methods based on multidimensional data analysis algorithms. Using the cluster analysis on Rosstat’s Household Budget Survey data for 2016–2023, five population types with different behavioral patterns were identified. Among them, the dominant model stands out (42% of the population), in which the economic stability of households located mainly in rural areas is achieved not through the labor market and social transfers, but through the resources of the extended household and subsistence production. The natural income in this group exceeds the national level by 3,5 times. This cluster is organically supplemented by underage household members of the above group, which makes up 62% of the sample. A separate group of the rural population is consisted of rural pensioners, whose well-being relies mainly on federal support, in contrast to urban pensioners, whose incomes depend mainly on regional sources. These two groups are not very numerous (3,8 and 4,5% of the sample, respectively). About 30% of the sample includes the active urban population. The results of the study indicate the low effectiveness of standard social policy instruments (monetary benefits to individuals) for a significant part of the region’s population and the need to move to the development of rural infrastructure, as well as the development of targeted socio-demographic policy, taking into account the identified regional specifics.

Keywords: cluster analysis, machine learning, typology of socio-economic behavior of the population, Republic of Dagestan, households, subsistence farming, social policy.

JEL: G11

EDN: TQEZOD

DOI: https://doi.org/10.52180/2073-6487_2026_1_87_108

Financial support: This research was funded by the Russian Science Foundation (Project No. 25-28-20473).

References

  1. Abdulmanapov P.G. Sociodemographic aspects of self-preservation behavior of women in the Republic of Dagestan // Regional problems of economic transformation. 2022. No. 9. Pp. 65–71. (In Russ.). DOI: 10.26726/1812-7096-2022-9-65-71.
  2. Antonova N.L. Social fears as a factor in self-preservation behavior of the population // Social dynamics of the population and sustainable development: Collection of abstracts of the III All-Russian scientific and practical conference with international participation, Moscow, December 1, 2020 / General ed. A.I. Antonov. Moscow: MAX Press, 2020. Pp. 100–102. (In Russ.).
  3. Gimbatov Sh.M., Kutayev Sh.K., Khadzhalova Kh.M., Abdullayeva Z.Z., Abdulmanapov P.G. Social and Demographic Problems of Formation of the Labor Potential of the North Caucasus // Population. 2023. Vol. 26. No. 1. Pp. 135–146. (In Russ.). DOI: 10.19181/population.2023.26.1.11.
  4. Kazenin K.I., Kozlov V.A. Rejuvenation of Motherhood in Dagestan: Trend or Artifact? (Preliminary Results of a Rural Population Survey) // Demographic Review. 2016. Vol. 3. No. 3. Pp. 121–151. (In Russ.).
  5. Kisilenko A.V., Shapovalova I.S., Kisilenko D.G., Khashaeva S.V., Kovalchuk O.V. Analysis of the results of an expert survey on the factors of self-preservation behavior of the population of the central regions of Russia // Problems of Social Hygiene, Health Care and History of Medicine. 2020. No. 28 (2). Pp. 253–260. (In Russ.). DOI: 10.32687/0869-866X-2020-28-2-253-260.
  6. Korolenko A.V. Models of self-preservation behavior of the population: approaches to study and experience of construction // Economic and social changes: facts, trends, forecast. 2018. Vol. 11. No. 3. Pp. 248–263. (In Russ.). DOI: 10.15838/esc.2018.3.57.16.
  7. Lysenko E., Ragimova O. Culture of life and culture of health // Higher education in Russia. 2008. No. 11. Pp. 139–142. (In Russ.).
  8. Popova L.A., Milaeva T.V., Zorina E.N. Self-preservation behavior of the population: generational aspect // Economic and social changes: facts, trends, forecast. 2021. Vol. 14. No. 5. Pp. 261–276. (In Russ.). DOI: 10.15838/esc.2021.5.77.15.
  9. Rimashevskaya N.M. Social priorities do not change in times of crisis // Population. 2015. No. 2 (68). Pp. 4–8. (In Russ.).
  10. Serezhnikova R.K., Vorotylkina I.M. Formation of a health-preserving culture as a condition for student self-realization // Scientific notes of the Transbaikal State Humanitarian and Pedagogical University named after N.G. Chernyshevsky. 2012. No. 5 (46). Pp. 195–198. (In Russ.).
  11. Simagin Yu.A., Murtuzalieva D.D., Vankina I.N. The impact of municipal-territorial transformations in the regions of Russia on population dynamics // Population. 2023. Vol. 26. No. 1. Pp. 16–28. (In Russ.).
  12. Smirnova Ya.S. Family Forms among the Peoples of the North Caucasus in the 19th – Early 20th Centuries // Soviet Ethnography. 1981. No. 1. Pp. 78–91. (In Russ.).
  13. Kharisov F.F. The role of national culture in the formation of a healthy personality // Science and School. 2004. No. 12. Pp. 18–25. (In Russ.).
  14. Shapovalova I.S. The role of social institutions in the formation of self-preservation behavior of the population of the Central District // Bulletin of the Institute of Sociology. 2020. Vol. 11. No. 1. Pp. 86–112. (In Russ.).

Manuscript submission date: 04.12.2025

Manuscript acceptance date: 24.02.2026

 

For citation:

Gimbatov Sh.M., Medzhidov Z.U., Kobzarenko D.N., Gimbatova A.Sh. Typology of socio-economic behavior of the Republic of Dagestan population // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2026. № 1. Pp. 87-108. (In Russ.). https://doi.org/10.52180/2073-6487_2026_1_87_108 EDN: TQEZOD

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