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Network structure of the economy and the propagation of monetary shocks

Author

Listed:
  • Elena Deryugina

    (Bank of Russia, Russian Federation)

  • Andrey Leonidov

    (Lebedev Physical Institute, Russian Federation)

  • Alexey Ponomarenko

    (Bank of Russia, Russian Federation)

  • Stanislav Radionov

    (Lebedev Physical Institute, Russian Federation)

  • Ekaterina Vasilyeva

    (Lebedev Physical Institute, Russian Federation)

Abstract

We calibrate a network model and monetary shocks based on empirical data from inputoutput tables for the Russian economy. We examine various aspects of the propagation of monetary shocks, such as the dispersion of relative prices and the local peak values of the aggregated price index achieved during the convergence to the new equilibrium. We show that these developments depend significantly on the way new money is injected into the economy.

Suggested Citation

  • Elena Deryugina & Andrey Leonidov & Alexey Ponomarenko & Stanislav Radionov & Ekaterina Vasilyeva, 2024. "Network structure of the economy and the propagation of monetary shocks," Bank of Russia Working Paper Series wps130, Bank of Russia.
    • Handle: RePEc:bkr:wpaper:wps130
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    References listed on IDEAS

    as
    1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    2. Mandel, Antoine & Veetil, Vipin P., 2021. "Monetary dynamics in a network economy," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    3. McLeay, Michael & Radia, Amar & Thomas, Ryland, 2014. "Money creation in the modern economy," Bank of England Quarterly Bulletin, Bank of England, vol. 54(1), pages 14-27.
    4. Michael Weber & Ali Ozdagli, 2016. "Monetary Policy Through Production Networks: Evidence from the Stock Market," 2016 Meeting Papers 148, Society for Economic Dynamics.
    5. Peter Dietsch, 2021. "Money creation, debt, and justice," Politics, Philosophy & Economics, , vol. 20(2), pages 151-179, May.
    6. Eytan Sheshinski & Yoram Weiss, 1977. "Inflation and Costs of Price Adjustment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(2), pages 287-303.
    7. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    8. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    9. Vasco M. Carvalho & Alireza Tahbaz-Salehi, 2019. "Production Networks: A Primer," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 635-663, August.
    10. Michael Weber & Ali Ozdagli, 2016. "Monetary Policy Through Production Networks: Evidence from the Stock Market," 2016 Meeting Papers 148, Society for Economic Dynamics.
    11. Maral Shamloo, 2010. "Price Setting in a Model with Production Chains: Evidence from Sectoral Data," IMF Working Papers 2010/082, International Monetary Fund.
    12. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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    More about this item

    Keywords

    money supply; inflation; Cantillion effects; networks; input-output tables;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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