Home  Journals  Regional Economics: Theory and Practice  11(542) - 2025 November

Forecasting regional economic security indicators based on econometric time series models

Received: 23 July 2025

Accepted: 25 August 2025

Available online: 27 November 2025

Subject Heading: ECONOMIC-MATHEMATICAL MODELING

JEL Classification: C01, С32, C51, C87

Pages: 128-146

https://doi.org/10.24891/pjnvtn

Subject. This article discusses the issue of improving the accuracy of predictive models.
Objectives. The article aims to assess the correctness of using time series for determining the prospects of development of regional economic systems.
Methods. For the study, we used mathematical analysis tools.
Results. The article presents the author-built time series predictive models to assess the level of economic security of the Republic of Dagestan. The confidence interval for some indicators of economic security turned out to be too wide, indicating a high level of uncertainty in the presented forecast.
Conclusions. Time series models describe the changes in indicators characterizing the economic security of the region well enough and can be used when developing regional economic development plans in the medium term. Improving the accuracy and adequacy of predictive models requires the use of longer time series of the initial indicators.

Keywords: economic security of region, time series forecasting, ARIMA model, Brown’s model, model identification, gretl

References:

1. Andrukovich P.F. [Notes on the principles of construction of economic indicators forecast models (on example forecast system ProRosEc)]. Ekonomika i matematicheskie metody, 2020, vol. 56, no. 2, pp. 66–76. (In Russ.) DOI: 10.31857/S042473880009230-2 EDN: MWIIVQ
2. Kuryshev N.I. [The problem of measuring the quantity of output in the input–output model by W. Leontief in modeling the trends in economic reproduction of nations and regions]. Regional'naya ekonomika: teoriya i praktika, 2021, vol. 19, iss. 8, pp. 1568–1592. (In Russ.) EDN: 10.24891/re.19.8.1568 EDN: HEKUQZ
3. Polyakova M.A., Golovko E.A., Kirichenko A.O. [Integration of mathematical models into the public administration system and prospects for their application]. Prikladnye ekonomicheskie issledovaniya, 2024, no. S2, pp. 25–32. (In Russ.) DOI: 10.47576/2949-1908.2024.85.58.003 EDN: QCTXFO
4. Gavrilets Yu.N., Kudrov A.V., Tarakanova I.V. [Statistical analysis and modeling of regional economy and science relationship]. Ekonomika i matematicheskie metody, 2022, vol. 58, no. 4, pp. 56–70. (In Russ.) DOI: 10.31857/S042473880023019-9 EDN: QQUSQS
5. Gavrilets Yu.N., Tarakanova I.V. [Experience of statistical and entropy analysis of relationships between the information and production sectors of the regional economy of Russia]. Ekonomika i matematicheskie metody, 2023, vol. 59, no. 4, pp. 71–85. (In Russ.) EDN: 10.31857/S042473880028218-8 EDN: BKPSOQ
6. Komzolov A.A., Kirichenko T.V., Nazarova Yu.A. et al. [Methods for analyzing deliberate and emergent energy security strategy of Russia]. Vestnik Moskovskogo universiteta. Seriya 6. Ekonomika, 2023, no. 1, pp. 110–134. (In Russ.) DOI: 10.55959/msu0130-0105-6-58-1-6 EDN: DOQPSX
7. Ismikhanov Z.N. [Identifiable regression models of the relationship between agricultural development indicators of the regions]. Regional'naya ekonomika: teoriya i praktika, 2020, vol. 18, vol. 7, pp. 1357–1373. (In Russ.) DOI: 10.24891/re.18.7.1357 EDN: ZAHSUA
8. Afanas'ev M.Yu., Gusev A.A. [Forecasting estimates of the economic complexity of Russian regions]. Regional'naya ekonomika: teoriya i praktika, 2024, vol. 22, iss. 3, pp. 545–567. (In Russ.) EDN: 10.24891/re.22.3.545 EDN: HEUYNE
9. Kaneva M.A., Untura G.A. [Regional growth rates dependence on healthcare spending: Threshold regression estimation]. Regional'naya ekonomika: teoriya i praktika, 2022, vol. 20, iss. 2, pp. 355–381. (In Russ.) DOI: 10.24891/re.20.2.355 EDN: XEJUUQ
10. Skrypnik D.V. [The economic modeling development. An econometric aspect]. Ekonomika i matematicheskie metody, 2022, vol. 58, no. 2, pp. 32–42. (In Russ.) EDN: 10.31857/S042473880020013-3 EDN: VNRNRW
11. Kаsimova T.M. [Panel data models as a tool for analysis and forecasting of economic indicators of Russian Regions]. Fundamental'nye issledovaniya, 2020, no. 3, pp. 48–53. (In Russ.) DOI: 10.17513/fr.42698 EDN: OYIRIH
12. Magomedgadzhiev Sh.M., Ibiev M.I. [Assessment of trends and forecasting indicators of innovative-technological development of the Republic of Dagestan]. Fundamental'nye issledovaniya, 2020, no. 7, pp. 48–53. (In Russ.) DOI: 10.17513/fr.42804 EDN: VPVVZJ
13. Adamadziev K.R., Akhmedov A.S. [Analysis of trends in the dynamics of three key social indicators of the economy of the Russian Federation (according to data for 2005–2022)]. Nauchnoe obozrenie: teoriya i praktika, 2024, vol. 14, iss. 7, pp. 1379–1392. (In Russ.) EDN: 10.35679/2226-0226-2024-14-7-1379-1392 EDN: EKKPCW
14. Ramazanov R.R. [Agent modeling in research and forecasting of socio-economic systems and processes]. Ekonomika i matematicheskie metody, 2021, vol. 57, no. 1, pp. 19–32. (In Russ.) EDN: 10.31857/S042473880010550-4 EDN: RNUUSO
15. Skrobotov A.A. [Time series forecasting under structural breaks]. Prikladnaya ekonometrika, 2024, no. 4, pp. 120–139. (In Russ.) DOI: 10.22394/1993-7601-2024-76-120-139 EDN: FBZYHW
16. Garafutdinov R.V. [Influence of some ARFIMA model parameters on the accuracy of financial time series forecasting]. Prikladnaya ekonometrika, 2021, no. 2, pp. 85–100. (In Russ.) EDN: 10.22394/1993-7601-2021-62-85-100 EDN: GZHIKL
17. Orlova I.V. [Using free software for econometric modeling]. Fundamental'nye issledovaniya, 2023, no. 1, pp. 81–89. (In Russ.) DOI: 10.17513/fr.43424 EDN: SPFXIG

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