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Stackelberg Model and Public-Private Partnerships in the Natural Resources Sector of Russia

  • Sergey LavlinskiiEmail author
  • Artem Panin
  • Aleksandr V. Plyasunov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11548)

Abstract

A comparative analysis is conducted of the efficiency of different partnership models in the natural resources sector of Russia. The first one is a classic public-private partnership (PPP) model used in developed countries, whereby a private company builds an object of public property and transfers it to the government either immediately after the construction or after a certain period of operation of the object. The second model represents for the government a costly alternative of the former and is used in Russia in underdeveloped regions. This model assumes that the government supports the investor in infrastructure development and, in part, in the implementation of mandatory environmental protection measures and can also provide tax incentives. In practical terms, this work aims to look into possible ways of transforming the current Russian PPP model towards the classic forms of partnership. To conduct the comparative analysis of the PPP models, Stackelberg models are formulated and original iterative algorithms are developed for solving the corresponding bilevel Boolean programming problems based on probabilistic local search. The properties of the equilibrium solutions are studied using real data for the Transbaikal krai. Based on the modeling results, the different partnership models are compared to find out the conditions under which the private investor would choose to invest in publicly owned industrial infrastructure facilities in Russia.

Keywords

Stackelberg game Bilevel mathematical programming problems Mineral resources development program Probabilistic local search algorithm 

Notes

Acknowledgements

This work was financially supported by the Russian Science Foundation (project No. 16-18-00073).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sergey Lavlinskii
    • 1
    • 2
    • 3
    Email author
  • Artem Panin
    • 1
    • 2
  • Aleksandr V. Plyasunov
    • 1
    • 2
  1. 1.Sobolev Institute of MathematicsNovosibirskRussia
  2. 2.Novosibirsk State UniversityNovosibirskRussia
  3. 3.Zabaikalsky State UniversityChitaRussia

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