Supply Chain Shocks and Retail Resilience: The Dynamics of Global Value Chains and Inventories
Keywords:
business, economics, supply chains, inventories, semiparametric, Time Series, supply shocksAbstract
We examine the role and relationship of global value chains and inventories by delving into the dynamic effects of upstream manufacturing shocks on downstream retailer performance. Motivated by the pivotal role inventories play in firm demand management, our research employs a novel two-step methodology involving a reduced-form semiparametric smooth coefficient model, and a structural vector autoregressive model. The findings, based on monthly data spanning from January 1999 to December 2021, reveal a profound, and enduring impact of manufacturing supply chain shocks on the retail sector. Following a unit supply chain shock, downstream retailers experience a substantial and lasting increase in inventory accumulation, accompanied by a short-term decline, and subsequent stabilization in sales. Moreover, post-shock, retailers experience a permanent decrease in output, underscoring the far-reaching, and persistent consequences of disruptions in upstream supply chain agents on downstream retail operations.
References
Abramovitz, M. (1950). Inventories and business cycles, with special reference to manufacturers’ inventories (No. abra50-1). National Bureau of Economic Research.
Bils, M., & Kahn, J.A. (2000). What inventory behavior tells us about business cycles. American Economic Review, 90(3), 458–481.
Bivin, D.G. (1986). Inventories and interest rates: A critique of the buffer stock model. The American Economic Review, 76(1), 168–176.
Blanchard, O.J. (1983). The production and inventory behavior of the American automobile industry. Journal of Political Economy, 91(3), 365–400.
Blinder, A.S., Lovell, M.C., & Summers, L.H. (1981). Retail inventory behavior and business fluctuations. Brookings Papers on Economic Activity, 1981(2), 443–520.
Bray, R.L., & Mendelson, H. (2013). Disentangling production smoothing from the bullwhip effect. SSRN.
Crouzet, N., & Oh, H. (2016). What do inventories tell us about news-driven business cycles? Journal of Monetary Economics, 79, 49–66.
Granger, C.W., & Lee, T.H. (1989). Investigation of production, sales and inventory relationships using multicointegration and non‐symmetric error correction models. Journal of Applied Econometrics, 4(S1), S145–S159.
Görtz, C., Gunn, C., & Lubik, T.A. (2022). Is there news in inventories? Journal of Monetary Economics, 126, 87–104.
Görtz, C., & Gunn, C.M. (2018). Taking stock of TFP news shocks: The inventory comovement puzzle (Tech. Rep.).
Hastie, T., & Tibshirani, R. (1993). Varying-coefficient models. Journal of the Royal Statistical Society: Series B (Methodological), 55(4), 757–779.
Holt, C.C. (1960). Planning production, inventories, and workforce.
Inoue, H., & Todo, Y. (2019). Firm-level propagation of shocks through supply-chain networks. Nature Sustainability, 2(9), 841–847.
Jones, C.S., & Tuzel, S. (2013). Inventory investment and the cost of capital. Journal of Financial Economics, 107(3), 557–579.
Kesavan, S., Kushwaha, T., & Gaur, V. (2016). Do high and low inventory turnover retailers respond differently to demand shocks? Manufacturing & Service Operations Management, 18(2), 198–215.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. American Economic Review, 99(3), 1053–1069.
Lee, H.L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102.
Li, Q., Huang, C.J., Li, D., & Fu, T.-T. (2002). Semiparametric smooth coefficient models. Journal of Business & Economic Statistics, 20(3), 412–422.
Lovell, M. (1961). Manufacturers’ inventories, sales expectations, and the acceleration principle. Econometrica: Journal of the Econometric Society, 29(3), 293–314.
Metters, R. (1997). Quantifying the bullwhip effect in supply chains. Journal of Operations Management, 15(2), 89–100.
Niranjan, T.T., Wagner, S.M., & Aggarwal, V. (2011). Measuring information distortion in real-world supply chains. International Journal of Production Research, 49(11), 3343–3362.
Pettit, T.J., Fiksel, J., & Croxton, K.L. (2010). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, 31(1), 1–21.
Ramey, V.A., & West, K.D. (1999). Inventories. Handbook of Macroeconomics, 1, 863–923.
Scholten, K., & Schilder, S. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal, 20(4), 471–484.
Tukamuhabwa, B.R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: Definition, review and theoretical foundations for further study. International Journal of Production Research, 53(18), 5592–5623.
Wen, Y. (2011). Input and output inventory dynamics. American Economic Journal: Macroeconomics, 3(4), 181–212.
West, K.D. (1993). Inventory models. Cambridge, Mass., USA: National Bureau of Economic Research.
Wieland, A., & Durach, C.F. (2021). Two perspectives on supply chain resilience. Journal of Business Logistics, 42(3), 315–322.
Williams, C.J.M. (2022). The evolution of inventory dynamics in a post-crisis economy. Economics Bulletin, 42(4).
Wu, J.C., & Xia, F.D. (2016). Measuring the macroeconomic impact of monetary policy at the zero lower bound. Journal of Money, Credit and Banking, 48(2–3), 253–291.