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A Mathematical Model and Programme Support for Determination of the Values of the Marginal Reserve Requirement as Instrument of Monetary Policy

Author

Listed:
  • Darko Pongrac

    (Croatian National Bank, Zagreb)

  • Kristina Soric

    (Faculty of Economics, Zagreb)

  • Visnja Vojvodic Rosenzweig

    (Faculty of Economics, Zagreb)

Abstract

This paper studies the problem of interdependence between central bank and commercial bank goals. The basic central bank task is to achieve and to maintain price stability. Croatian external debt has been increasing for years and so the activities of the Croatian National Bank are designed to correct this situation. In order to stop the further increase of the external debt, the Croatian National Bank uses several monetary policy instruments, among which is the marginal reserve requirement. On the other hand, the goal of commercial banks is to maximise profits. Banks take loans from abroad at a lower interest rate and invest this money in Croatia at a higher interest rate, thus fulfilling their goal. In order to obtain the desired effects of the marginal reserve requirement, its optimal percentage value should be determined. This problem is modelled as a bi-level mixed 0-1 programming problem. The objective of the leader (Croatian National Bank) is to minimize the increase in household loans by setting different percentages of the reserve requirements for loans extended to households and for those granted to enterprises. The objective of the followers (banks) is to maximize profits. In order to solve this NP-hard problem a heuristic is proposed. In order to verify the model, the paper ends with simulations and the presentation of computational results.

Suggested Citation

  • Darko Pongrac & Kristina Soric & Visnja Vojvodic Rosenzweig, 2007. "A Mathematical Model and Programme Support for Determination of the Values of the Marginal Reserve Requirement as Instrument of Monetary Policy," Financial Theory and Practice, Institute of Public Finance, vol. 31(3), pages 249-278.
    • Handle: RePEc:ipf:finteo:v:31:y:2007:i:3:p:249-278
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    References listed on IDEAS

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    1. Buyang Cao & Fred Glover, 1997. "Tabu Search and Ejection Chains---Application to a Node Weighted Version of the Cardinality-Constrained TSP," Management Science, INFORMS, vol. 43(7), pages 908-921, July.
    2. Ellison, Martin & Valla, Natacha, 2001. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Journal of Monetary Economics, Elsevier, vol. 48(1), pages 153-171, August.
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    More about this item

    Keywords

    monetary policy instruments; commercial banks credit activity; marginal reserve requirement; bi-level mixed 0-1 programming problem; NP-hard problem; heuristic;
    All these keywords.

    JEL classification:

    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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