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Macroeconomic regime change and the size of supply chain disruption and energy supply shocks

Author

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  • De Santis, Roberto A.
  • Tornese, Tommaso

Abstract

The COVID-19 pandemic and Russia’s invasion of Ukraine have complicated macroeconomic forecasting and policymaking due to unprecedented disruptions in supply chains and energy markets, suggesting a new macroeconomic regime. However, we are unable to reject the null hypothesis of no structural break in March 2020. We then examine whether these shocks have increased post-COVID-19. Their sizes were initially elevated, but then have been gradually returning to pre-pandemic levels. The linear and nonlinear models reveal that supply chain disruptions cause persistent increases in expected inflation and headline goods prices, while energy supply shocks have a transitory inflation effect. The nonlinear model shows that real GDP is adversely affected by supply shocks in low growth periods. JEL Classification: C32, E32

Suggested Citation

  • De Santis, Roberto A. & Tornese, Tommaso, 2025. "Macroeconomic regime change and the size of supply chain disruption and energy supply shocks," Working Paper Series 3120, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20253120
    Note: 185689
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    Citations

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    Cited by:

    1. Esteban Jaimovich & Vincenzo Merella, 2026. "Air or Sea? Quality-Driven Sorting in International Trade," Working Papers 388, Red Nacional de Investigadores en Economía (RedNIE).
    2. Bonato, Matteo & Gupta, Rangan & Pierdzioch, Christian, 2026. "Do shortages forecast aggregate and sectoral U.S. stock market realized variance? Evidence from a century of data," Journal of Empirical Finance, Elsevier, vol. 86(C).
    3. Ko Adachi & Yoshiyuki Kurachi & Masato Okamoto & Tomohiro Sugo & Akitoshi Toyoda, 2026. "Supply Constraints and Inflation Dynamics," Bank of Japan Working Paper Series 26-E-3, Bank of Japan.
    4. Caporin, Massimiliano & Gupta, Rangan & Subramaniam, Sowmya & Torrent, Hudson S., 2026. "Supply Constraints and Conditional Distribution Predictability of Inflation and its Volatility: A Nonparametric Mixed-Frequency Causality-in-Quantiles Approach," Research in Economics, Elsevier, vol. 80(2).

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    JEL classification:

    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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