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Spatial-autoregressive model for the two groups of related regions (eastern and western parts of Russia)

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  • Demidova, Olga

    (Higher School of Economics, Moscow, Russia)

Abstract

The present study suggest a generalization of the spatial autoregressive model for the case when considered regions are split into two different groups, which have a mutual influence on each other. The weighing matrix in this model is split into four parts and four spatial coefficients are estimated. The proposed model is applied for the analysis of three macroeconomic indicators using the data for Russian regions, previously divided into western and eastern. Our analysis revealed: 1) a positive spatial correlation of the main macroeconomic indicators for the western regions, 2) both positive and negative externalities for the eastern regions and 3) the asymmetric influence of eastern and western regions on each other. Usually «impulses» from the western regions have a positive effect on the eastern regions, but the «impulses» from the eastern regions usually do not affect the western regions.

Suggested Citation

  • Demidova, Olga, 2014. "Spatial-autoregressive model for the two groups of related regions (eastern and western parts of Russia)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 19-35.
    • Handle: RePEc:ris:apltrx:0235
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    Cited by:

    1. Olga Demidova & Elizat Kamalova, 2021. "Spatial Econometric Modeling of Economic Growth in Russian Regions: Do Institutions Matter? [Пространственно-Эконометрическое Моделирование Экономического Роста Российских Регионов: Имеют Ли Значен," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 34-59, April.
    2. Vakulenko, Elena, 2015. "Analysis of the relationship between regional labour markets in Russia using Okun’s model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 28-48.
    3. Demidova, O. & Timofeeva, E., 2021. "Spatial aspects of wage curve estimation in Russia," Journal of the New Economic Association, New Economic Association, vol. 51(3), pages 69-101.
    4. Демидова Ольга Анатольевна & Иванов Денис Сергеевич, 2016. "Модели Экономического Роста С Неоднородными Пространственными Эффектами (На Примере Российских Регионов)," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(1), pages 52-75.
    5. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    6. E. A. Kolomak & A. I. Sherubneva, 2023. "Spatial Structure and Factors of Economic Development of Asian Russia," Regional Research of Russia, Springer, vol. 13(3), pages 375-385, September.
    7. Semerikova, Elena, 2014. "Unemployment in East and West Germany: Spatial panel data analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 107-132.
    8. V. A. Rusanovskiy & V. A. Markov, 2016. "Influence of the spatial factor on the regional differentiation of unemployment in the Russian economy," Studies on Russian Economic Development, Springer, vol. 27(5), pages 593-604, September.
    9. Alexander Myasnikov, 2018. "Analysis of the Determinants of Total Factor Productivity in Russian Regions," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1168-1180.
    10. Petrov, Mikhail & Serkov, Leonid & Kozhov, Konstantin, 2021. "Analysis of the spatial features of regional power consumption in the Russian Federation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 5-27.

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    More about this item

    Keywords

    spatial lags; spatial effects; East and West; Russian regions;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • P50 - Political Economy and Comparative Economic Systems - - Comparative Economic Systems - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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