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Producer Price Inflation Connectedness and Input-Output Networks

Author

Listed:
  • N. Melisa Bilgin

    (Koç University)

  • Kamil Yilmaz

    (Koç University)

Abstract

We analyze the transmission of producer price in inflation shocks across the U.S. manufacturing industries from 1947 to 2018 using the Diebold-Yilmaz Connectedness Index framework, which fully utilizes the information in generalized variance decompositions from vector autoregressions. The results show that the system-wide connectedness of the input-output network Granger-causes the producer price inflation connectedness across industries. The input-output network and the inflation connectedness nexus is stronger during periods of major supply-side shocks, such as the global oil and metal price hikes, and weaker during periods of aggregate demand shocks, such as the Volcker disinflation of 1981-84 and the Great Recession of 2008. These findings are consistent with Acemoglu et al. (2016)'s conjecture that supply shocks are transmitted downstream, whereas demand shocks are transmitted upstream. Finally, preliminary results show that Trump tariffs caused an increase in the system-wide inflation connectedness in the first half of 2018, due to shocks mostly transmitted from tariff-targeted industries, namely, basic metals, fabricated metals and machinery.

Suggested Citation

  • N. Melisa Bilgin & Kamil Yilmaz, 2018. "Producer Price Inflation Connectedness and Input-Output Networks," Koç University-TUSIAD Economic Research Forum Working Papers 1813, Koc University-TUSIAD Economic Research Forum.
    • Handle: RePEc:koc:wpaper:1813
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    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1813.pdf
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    References listed on IDEAS

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    Cited by:

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    2. You, Kefei & Raju Chinthalapati, V.L. & Mishra, Tapas & Patra, Ramakanta, 2024. "International trade network and stock market connectedness: Evidence from eleven major economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    3. David I. Okorie, 2021. "A network analysis of electricity demand and the cryptocurrency markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3093-3108, April.
    4. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2023. "The impact of the COVID-19 pandemic and Russia-Ukraine war on multiscale spillovers in green finance markets: Evidence from lower and higher order moments," International Review of Financial Analysis, Elsevier, vol. 89(C).
    5. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).

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    More about this item

    Keywords

    Input-output networks; Inflation; Connectedness; Supply-side shocks; Commodity prices; Business cycles; Vector autoregression; Variance decomposition.;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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