Models of Adaptive Targeted Forecasting of Socio-Economic Region Development Indicators

  • Valeriy Vladimirovich DAVNIS Department of Information Technologies and Mathematical Methods in Economics Voronezh State University, Voronezh, Russian Federation
  • Maria Valeryevna DOBRINA Department of Information Technologies and Mathematical Methods in Economics Voronezh State University, Voronezh, Russian Federation
  • Artem Vitalievich CHEKMAREV Department of Information Technologies and Mathematical Methods in Economics Voronezh State University, Voronezh, Russian Federation
  • Viktoria Ivanovana TINYAKOVA Director of the Institute State University of Management, Moscow, Russian Federation

Abstract

The aim of the paper is description of the new approach, which provides the construction of models having the opportunity to reflect in the predicted trajectories of the plans, the expected implementation of which in the future period will lead to changes in the past patterns of socio-economic development of the region. In order to implement this idea, it is proposed to use the adaptive mechanism of targeted adjustment of the forecast model coefficients. Correction is based on the newly received observation data. As a newly arrived observation, a specially formed target value is used, in which the plan is concentrated on changing existing patterns. It is possible to conduct multivariate predictive calculations depending on the variation of target settings, followed by an assessment of the obtained options’ preference according to special criteria.


Results: computational experiments with models built on real data showed that the proposed approach is a fairly effective tool for developing forecasts of the socio-economic development of regions and municipalities.

References

[1] Cowles, A. 1933. Can Stock Market Forecasters Forecast? Econometrica, 1(3): 309-324.
[2] Dipak, B. 2009. Economic Models: Methods, Theory and Applications. Nagasaki University, Japan.
[3] Davnis, V.V. and Tinyakova, V.I. 2005. Prognoznye modeli ekspertnyh predpochtenij [Predictive models of expert preferences]: monograph. Voronezh: Publishing house of Voronezh State University.
[4] Davnis, V.V. and Tinyakova, V.I. 2006. Adaptivnye modeli: analiz i prognoz v ekonomicheskih sistemah [Adaptive models: analysis and forecast in economic systems]: monograph. Voronezh: Publishing house of Voronezh State University.
[5] Davnis, V.V. and Tinyakova, V.I. 2005. Prognoz i adekvatnyj obraz budushchego [Forecast and an adequate image of the future]. Bulletin of the Voronezh State University. Series Economics and Management, 2: 183-190.
[6] Davnis, V.V., Ziroyan, M.A., Komarova, E.V. and Tinyakova, V.I. 2015. Prognoznoe obosnovanie investicionnyh reshenij na finansovyh rynkah [Predictive justification of investment decisions in financial markets]. Moscow.
[7] Davnis, V.V., Dobrina, M.V. and Chekmarev, A.V. 2018. Adaptivno-imitacionnye modeli i ih primenenie v target-imitirovanii celevyh znachenij [Adaptive-simulation models and their application in target-simulation of target values]. Materials of the XIV International Scientific-Practical Conference Economic Forecasting: Models and Methods: 164-169.
[8] Davnis, V.V., Dobrina, M.V. and Chekmarev, A.V. 2018. Osnovy modelirovaniya adaptivno-targetirovannyh prognoznyh traektorij i analiz ih ustojchivosti. [Fundamentals of modeling adaptively targeted forecast trajectories and analysis of their stability]. Scientific Journal Sovremennaya ekonomika: problemy i resheniya. Voronezh State University. 9(105): 17-31.
[9] Dobrina, M.V. and Chekmarev, A.V. 2018. Osnovy adaptivnogo targetirovaniya v prognozirovanii ekonomicheskih processov [The basics of adaptive targeting in forecasting economic processes]. Materials of the XIV International Scientific-Practical Conference Economic Forecasting: Models and Methods, 17-22.
[10] Kendeall, M.G. 1953. The analysis of economic time-series. Part I. Prices. Journal of the Royal Statistical Society. 96: 1-25.
[11] Lukashin, Yu.P. 2003. Adaptivnye metody kratkosrochnogo prognozirovaniya vremennyh ryadov [Adaptive methods of short-term forecasting of time series], Finance and Statistics.
[12] Olexová, C., Štofová, L. 2018. Multi-criteria decision analysis of socio-economic factors of tax evasion. Journal of Applied Economic Sciences, Volume XIII, Winter, 7(61): 1864 – 1873.
[13] Pindyck, R.S. and Rubinfeld, D.L. 1999. Econometric Models and Economic Forecasts. McGraw-Hill, Inc.
[14] Ross, Sh.M. 2003. An Elementary Introduction to Mathematical Finance: Options and other Topics, Cambridge University Press.
[15] Sadovnikova, N.A. and Shmoilova, R.A. 2016. Analiz vremennyh ryadov i prognozirovanie [Analysis of time series and forecasting], MFPU Synergy, 152.
[16] Tsygichko, V.N. 2017. Prognozirovanie social'no-ekonomicheskih processov [Prediction of socio-economic processes], CD Librocom, 240.
Published
2019-06-30
How to Cite
DAVNIS, Valeriy Vladimirovich et al. Models of Adaptive Targeted Forecasting of Socio-Economic Region Development Indicators. Journal of Advanced Research in Law and Economics, [S.l.], v. 10, n. 4, p. 1195-1204, june 2019. ISSN 2068-696X. Available at: <https://journals.aserspublishing.eu/jarle/article/view/4886>. Date accessed: 22 dec. 2024. doi: https://doi.org/10.14505//jarle.v10.4(42).19.