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Empirical estimation of spatial competition between grocery retail chains in Moscow and St. Petersburg

Author

Listed:
  • Elizaveta Gaivoronskaia

    (HSE University St. Petersburg, Russian Federation)

  • Dmitrii Tereshchenko

    (HSE University St. Petersburg, Russian Federation)

Abstract

This paper presents an empirical analysis of spatial competition among major retail chains in the grocery markets of Moscow and St. Petersburg. Using an ordered probit model and spatial data, the determinants of entry and exit decisions in local markets are examined. The results reveal the predominance of the motive to avoid cannibalization: the probability of entry is negatively related to the number of a chain's own stores in the market. On the other hand, an increase in the number of competitors' stores is positively related to the probability of entry. The study also confirms the significance of spatial effects and the heterogeneity of behavior across chain formats.

Suggested Citation

  • Elizaveta Gaivoronskaia & Dmitrii Tereshchenko, 2026. "Empirical estimation of spatial competition between grocery retail chains in Moscow and St. Petersburg," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 81, pages 93-116.
    • Handle: RePEc:ris:apltrx:022383
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    Keywords

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    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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