Vol. 12 No. 2 (2026)
June 2026

Articles

Global supply chain disruptions and United States industries: Winners and losers

Published 2026-06-30

  • Marcin Pietrzak

Marcin Pietrzak
Institute of Economics, Polish Academy of Sciences

Abstract

Objective: The article aims to examine how pressure in the global supply chains affects United States industry-level equity returns and volatility, showing which sectors are winners and losers under high- versus low-pressure regimes.

Research Design & Methods: I adopted a quantitative design, modelling 49 U.S. industry-portfolio returns from January 1998 to June 2024 using a two-regime Markov-Switching autoregressive model with transition probabilities that are a function of the global supply chain pressure index (GSCPI).

Findings: Heightened pressure cleaves the cross-section: commodity and capital goods industries enjoy higher long-run returns, while defensives outperform only in tranquil periods, so the regime shift turns winners into losers and vice-versa. Moving into the high-pressure state also amplifies volatility across most sectors and pushes roughly half of them into negative territory, revealing a stark volatility-growth trade-off.

Implications & Recommendations: Regularly tracking supply-chain pressure allows investors and policymakers to anticipate shifts in sector-level risk-return profiles and to adopt broad, resilience-enhancing strategies to smooth market volatility and sustain economic stability.

Contribution & Value Added: The article introduces a regime-switching model linking global supply-chain disruptions to the U.S. sectoral equity dynamics, uncovering asymmetric effects on returns and volatility that linear models overlook.

Keywords

global supply chains, equity market, volatility, autoregressive model, Markov-switching model

(PDF) Save

Author Biography

Marcin Pietrzak

Assistant Professor at the Institute of Economics, Polish Academy of Sciences. His research interests include financial economics, time series econometrics and financial markets.

References

  1. Acemoglu, D., Carvalho, V.M., Özdaglar, A., & Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977-2016. https://doi.org/10.3982/ECTA9623 DOI: https://doi.org/10.3982/ECTA9623
  2. Ascari, G., Bonam, D., & Smadu, A. (2024). Global supply chain pressures, inflation, and implications for monetary policy. Journal of International Money and Finance, 142, 103029. https://doi.org/10.1016/j.jimonfin.2024.103029 DOI: https://doi.org/10.1016/j.jimonfin.2024.103029
  3. Baldwin, R., & Freeman, R. (2020). Trade conflict in the age of Covid-19. VoxEU.org. Retrieved from https://cepr.org/voxeu/columns/trade-conflict-age-covid-19 on May 22, 2020.
  4. Barrot, J.N., & Sauvagnat, J. (2016). Input Specificity and the Propagation of Idiosyncratic Shocks in Production Networks, The Quarterly Journal of Economics, 131(3), August 2016, 1543-1592. https://doi.org/10.1093/qje/qjw018 DOI: https://doi.org/10.1093/qje/qjw018
  5. Benigno, G., di Giovanni, J., Groen, J.J.J., & Noble, A.I. (2022). The GSCPI: A new barometer of global supply chain pressures (Staff Report No. 1017). Federal Reserve Bank of New York. Retrieved from https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr1017.pdf on May 22, 2020. DOI: https://doi.org/10.2139/ssrn.4114973
  6. Bouri, E., Cepni, O., Gupta, R., & Liu, R. (2025). Supply chain constraints and the predictability of the conditional distribution of international stock market returns and volatility. Economics Letters, 247, 112176. https://doi.org/10.1016/j.econlet.2025.112176 DOI: https://doi.org/10.1016/j.econlet.2025.112176
  7. Carvalho, V.M., Nirei, M., Saito, Y.U., & Tahbaz-Salehi, A. (2021). Supply Chain Disruptions: Evidence from the Great East Japan Earthquake. The Quarterly Journal of Economics, 136(2), 1255-1321. https://doi.org/10.1093/qje/qjaa044 DOI: https://doi.org/10.1093/qje/qjaa044
  8. Cohen, L., & Frazzini, A. (2008). Economic links and predictable returns. The Journal of Finance, 63(4), 1977-2011. https://doi.org/10.1111/j.1540-6261.2008.01379.x DOI: https://doi.org/10.1111/j.1540-6261.2008.01379.x
  9. Filardo, A.J. (1994). Business-cycle phases and their transitional dynamics. Journal of Business & Economic Statistics, 12(3), 299-308. https://doi.org/10.1080/07350015.1994.10524545 DOI: https://doi.org/10.1080/07350015.1994.10524545
  10. French, K.R. (2025, May 7). 49 Industry Portfolios. Dartmouth College. Retrieved from https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html on May 5, 2025.
  11. Ginn, W. (2024). Global supply chain disruptions and financial conditions. Economics Letters, 239, 111739. https://doi.org/10.1016/j.econlet.2024.111739 DOI: https://doi.org/10.1016/j.econlet.2024.111739
  12. Gofman, M., Segal, G., & Wu, Y. (2020). Production networks and stock returns: The role of vertical creative destruction. The Review of Financial Studies, 33(12), 5856-5905. https://doi.org/10.1093/rfs/hhaa034 DOI: https://doi.org/10.1093/rfs/hhaa034
  13. Gozgor, G., Khalfaoui, R., & Yarovaya, L. (2023). Global supply chain pressure and commodity markets: Evidence from multiple wavelet and quantile connectedness analyses. Finance Research Letters, 54, 103791. https://doi.org/10.1016/j.frl.2023.103791 DOI: https://doi.org/10.1016/j.frl.2023.103791
  14. Hamilton, J.D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. https://doi.org/10.2307/1912559 DOI: https://doi.org/10.2307/1912559
  15. Hendricks, K.B., Jacobs, B.W., & Singhal, V.R. (2020). Stock market reaction to supply chain disruptions from the Great East Japan Earthquake. Manufacturing & Service Operations Management, 22(4), 683-699. https://doi.org/10.1287/msom.2019.0777 DOI: https://doi.org/10.1287/msom.2019.0777
  16. Hendricks, K.B., & Singhal, V.R. (2003). The effect of supply chain glitches on shareholder wealth. Journal of Operations Management, 21(5), 501-522. https://doi.org/10.1016/j.jom.2003.02.003 DOI: https://doi.org/10.1016/j.jom.2003.02.003
  17. Hendricks, K.B., & Singhal, V.R. (2005a). Association between supply chain glitches and operating performance. Management Science, 51(5), 695-711. https://doi.org/10.1287/mnsc.1040.0353 DOI: https://doi.org/10.1287/mnsc.1040.0353
  18. Hendricks, K.B., & Singhal, V.R. (2005b). An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm. Production and Operations Management, 14(1), 35-52. https://doi.org/10.1111/j.1937-5956.2005.tb00008.x DOI: https://doi.org/10.1111/j.1937-5956.2005.tb00008.x
  19. Herskovic, B. (2018). Networks in production: Asset pricing implications. The Journal of Finance, 73(4), 1785-1818. https://doi.org/10.1111/jofi.12684 DOI: https://doi.org/10.1111/jofi.12684
  20. Hupka, Y. (2022). Leverage and the global supply chain. Finance Research Letters, 50, 103269. https://doi.org/10.1016/j.frl.2022.103269 DOI: https://doi.org/10.1016/j.frl.2022.103269
  21. Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E: Logistics and Transportation Review, 136, 101922. https://doi.org/10.1016/j.tre.2020.101922 DOI: https://doi.org/10.1016/j.tre.2020.101922
  22. Kim, C.J., & Nelson, C.R. (2017). State-space models with regime switching: classical and Gibbs-sampling approaches with applications. MIT Press.
  23. Riaz, A., Ullah, A., & Muhammad, B. (2025). The impact of global supply chain pressure on the stock market: A sectoral view. Humanities and Social Sciences Communications, volume 12, Article 284. https://doi.org/10.1057/s41599-025-04634-0 DOI: https://doi.org/10.1057/s41599-025-04634-0
  24. Smirnyagin, V., & Tsyvinski, A. (2022). Macroeconomic and asset pricing effects of supply chain disasters (NBER Working Paper No. 30503). National Bureau of Economic Research. https://doi.org/10.3386/w30503 DOI: https://doi.org/10.3386/w30503
  25. Tillmann, P. (2024). The asymmetric effect of supply chain pressure on inflation. Economics Letters, 235, 111540. https://doi.org/10.1016/j.econlet.2024.111540 DOI: https://doi.org/10.1016/j.econlet.2024.111540

Downloads

Download data is not yet available.

Similar Articles

1-10 of 181

You may also start an advanced similarity search for this article.