IDEAS home Printed from https://ideas.repec.org/a/aiy/jnjaer/v23y2024i3p721-750.html
   My bibliography  Save this article

Modeling of Functional Relationships of Regional Economic Systems Based on Small Samples Based on Bayesian Intelligent Measurements

Author

Listed:
  • Roman A. Zhukov
  • Svetlana V. Prokopchina
  • Maria A. Plinskaya
  • Maria A. Zhelunitsina

Abstract

Regional economies, which are economic subsystems of a socio-ecological-economic system, are characterized by rapidly changing conditions affecting their functioning. Therefore, traditional approaches based on long-term trends and the construction of appropriate models are not enough for modeling and need to be over updated, including through combination with other approaches that take into account the volatility of conditions. Open sources datasets are fraught with uncertainty (different sources may have different values for the same indicator). So, some indicators are being constantly adjusted: changes are introduced into datasets from the previous periods; evaluation periods are not sufficient for model construction that would be methodologically valid from the point of view of mathematical statistics, Additionally, the results of functioning depend on influencing factors as well as measurement results. These problems lead to the need to resort to probabilistic estimates and the incompleteness and fuzziness dataset, as well as to obtain samples of sufficient volume from low-power data. The purpose of the study is to model the relationship between the volume of gross domestic product and the factors characterizing the functioning of the economic subsystem of the regions, under the conditions of uncertainty and limited data in a given period of time. The case study is constructed on The Tula region dataset. The working hypothesis is that it is possible to construct a methodologically correct econometric models using the dataset of a specific region of the Russian Federation over a certain period of time. We applied the methods of econometric modeling and the methodology of Bayesian intelligent measurements, as well as the methodology for generating a sufficient amount of data on small samples. For the Tula region and dataset for 2022, nonlinear models for the GDP by region volumes (14 sections of the NACE) were built. This made it possible to test the presented methodology based on a combination of econometric and Bayesian approaches to modeling the complex systems functioning, with conclusions having both theoretical and practical value for the region's sustainable development.

Suggested Citation

  • Roman A. Zhukov & Svetlana V. Prokopchina & Maria A. Plinskaya & Maria A. Zhelunitsina, 2024. "Modeling of Functional Relationships of Regional Economic Systems Based on Small Samples Based on Bayesian Intelligent Measurements," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(3), pages 721-750.
    • Handle: RePEc:aiy:jnjaer:v:23:y:2024:i:3:p:721-750
    DOI: https://doi.org/10.15826/vestnik.2024.23.3.029
    as

    Download full text from publisher

    File URL: https://journalaer.ru//fileadmin/user_upload/site_15934/2024/07_ZHukov_Prokopcina_Plinskaja_ZHelunicina.pdf
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.15826/vestnik.2024.23.3.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Szafranek, Karol & Szafrański, Grzegorz & Leszczyńska-Paczesna, Agnieszka, 2024. "Inflation returns. Revisiting the role of external and domestic shocks with Bayesian structural VAR," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 789-810.
    2. Isaiah Andrews & James H. Stock & Liyang Sun, 2019. "Weak Instruments in Instrumental Variables Regression: Theory and Practice," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 727-753, August.
    3. Roman A. Zhukov & Maria A. Plinskaya & Evgeny V. Manokhin, 2023. "Assessment of the Regions Functioning Based on Production Functions with the Above Cost Factors," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(3), pages 657682-6576.
    4. Huning, Thilo R. & Wahl, Fabian, 2021. "The fetters of inheritance? Equal partition and regional economic development," European Economic Review, Elsevier, vol. 136(C).
    5. Valery Makarov & Sergey Ayvazyan & Mikhail Afanasyev & Albert Bakhtizin & Ashkhen Nanavyan, 2016. "Modeling the Development of Regional Economy and an Innovation Space Efficiency," Foresight-Russia Форсайт, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 10(3 (eng)), pages 76-90.
    6. Di Noia, Antonio & Mastrantonio, Gianluca & Jona Lasinio, Giovanna, 2024. "Bayesian size-and-shape regression modelling," Statistics & Probability Letters, Elsevier, vol. 204(C).
    7. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    8. J. Paul Elhorst, 2022. "The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 249-267, December.
    9. Salles, Thiago Taglialegna & Nogueira, Denismar Alves & Beijo, Luiz Alberto & Silva, Liniker Fernandes da, 2019. "Bayesian approach and extreme value theory in economic analysis of forestry projects," Forest Policy and Economics, Elsevier, vol. 105(C), pages 64-71.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cohle, Zachary & Ortega, Alberto, 2023. "The effect of the opioid crisis on patenting," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 493-521.
    2. Vu, Trung V., 2021. "Do genetically fragmented societies respond less to global warming? Diversity and climate change policies," Energy Economics, Elsevier, vol. 104(C).
    3. Carlo Ciccarelli & Torben Dall Schmidt, 2022. "The impact of history on regional development," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 219-225, December.
    4. Schnorpfeil, Philip & Weber, Michael & Hackethal, Andreas, 2023. "Households' response to the wealth effects of inflation," SAFE Working Paper Series 400, Leibniz Institute for Financial Research SAFE.
    5. Bartels, Charlotte & Jäger, Simon & Obergruber, Natalie, 2020. "Long-Term Effects of Equal Sharing: Evidence from Inheritance Rules for Land," IZA Discussion Papers 13665, Institute of Labor Economics (IZA).
    6. Guedes, Ricardo & Iachan, Felipe S. & Sant’Anna, Marcelo, 2023. "Housing supply in the presence of informality," Regional Science and Urban Economics, Elsevier, vol. 99(C).
    7. Penney, Jeffrey & Lehrer, Steven F. & Bernal, Gloria L. & Reyes, Luis Carlos, 2023. "Do opportunities for low-income students at top colleges promote academic success? Evidence from Colombia's Ser Pilo Paga program," CLEF Working Paper Series 64, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    8. Gay, Victor & Gobbi, Paula E. & Goñi, Marc, 2024. "The Customary Atlas of Ancien Régime France," Explorations in Economic History, Elsevier, vol. 93(C).
    9. Bensch, Gunther & Gotz, Gunnar & Peters, Jörg, 2020. "Effects of rural electrification on employment: A comment on Dinkelman (2011)," Ruhr Economic Papers 840, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    10. Bai, Yiyi & Okullo, Samuel J., 2023. "Drivers and pass-through of the EU ETS price: Evidence from the power sector," Energy Economics, Elsevier, vol. 123(C).
    11. Yukun Ma, 2023. "Identification-robust inference for the LATE with high-dimensional covariates," Papers 2302.09756, arXiv.org, revised Nov 2023.
    12. Xavier Gabaix & Ralph S. J. Koijen, 2024. "Granular Instrumental Variables," Journal of Political Economy, University of Chicago Press, vol. 132(7), pages 2274-2303.
    13. Vu, Trung V., 2020. "Economic complexity and health outcomes: A global perspective," Social Science & Medicine, Elsevier, vol. 265(C).
    14. Gandhi, Sahil & Green, Richard K. & Patranabis, Shaonlee, 2022. "Insecure property rights and the housing market: Explaining India’s housing vacancy paradox," Journal of Urban Economics, Elsevier, vol. 131(C).
    15. Michelle Yin & Garima Siwach & Dajun Lin, 2023. "Vocational Rehabilitation Services and Labor Market Outcomes for Transition‐Age Youth with Disabilities in Maine," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(1), pages 166-197, January.
    16. Silvia Moler‐Zapata & Richard Grieve & Anirban Basu & Stephen O’Neill, 2023. "How does a local instrumental variable method perform across settings with instruments of differing strengths? A simulation study and an evaluation of emergency surgery," Health Economics, John Wiley & Sons, Ltd., vol. 32(9), pages 2113-2126, September.
    17. Angrist, Joshua & Kolesár, Michal, 2024. "One instrument to rule them all: The bias and coverage of just-ID IV," Journal of Econometrics, Elsevier, vol. 240(2).
    18. Agust n S. B n trix & Hayley Pallan & Ugo Panizza, 2022. "The Elusive Link Between FDI and Economic Growth," Trinity Economics Papers tep0722, Trinity College Dublin, Department of Economics.
    19. Chila, Vilma & Devarakonda, Shivaram, 2024. "The effects of firm-specific incentives (stock options) on mobility and employee entrepreneurship," Journal of Business Venturing, Elsevier, vol. 39(3).
    20. Ovuakporie, Oghogho Destina & Pillai, Kishore Gopalakrishna & Wang, Chengang & Wei, Yingqi, 2021. "Differential moderating effects of strategic and operational reconfiguration on the relationship between open innovation practices and innovation performance," Research Policy, Elsevier, vol. 50(1).

    More about this item

    Keywords

    gross domestic product by region; production function; socio-ecological-economic system; model; Bayesian intellectual measurements; small sample;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • P25 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Urban, Rural, and Regional Economics
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aiy:jnjaer:v:23:y:2024:i:3:p:721-750. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Natalia Starodubets (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.