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Oil Price Shocks, Inventories, And Macroeconomic Dynamics


  • Herrera, Ana María


This paper investigates the time delay in the transmission of oil price shocks using disaggregated manufacturing data on inventories and sales. VAR estimates indicate that industry-level inventories and sales respond faster to an oil price shock than aggregate gross domestic product, especially in industries that are energy-intensive. In response to an unexpected oil price increase, sales drop and inventories are accumulated. This leads to future reductions in production. We estimate a modified linear–quadratic inventory model to inquire whether the patterns observed in the VAR impulse responses are consistent with rational behavior by the firms. Estimation results suggest that three mechanisms play a role in the industry-level dynamics. First, oil prices act as a negative demand shock. Second, the shock catches manufacturers by surprise, resulting in higher-than-anticipated inventories. Third, because of their desire to smooth production, manufacturers deviate from the target level of inventories and spread the decline in production over various quarters; hence the delay in the response of aggregate output.

Suggested Citation

  • Herrera, Ana María, 2018. "Oil Price Shocks, Inventories, And Macroeconomic Dynamics," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 620-639, April.
  • Handle: RePEc:cup:macdyn:v:22:y:2018:i:03:p:620-639_00

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    Cited by:

    1. Hilde C. Bj�rnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    2. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    3. Lutz Kilian & Robert J. Vigfusson, 2009. "Pitfalls in estimating asymmetric effects of energy price shocks," International Finance Discussion Papers 970, Board of Governors of the Federal Reserve System (U.S.).
    4. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
    5. Zhang, Xi-Xi & Liu, Lu, 2020. "The time-varying causal relationship between oil price and unemployment: Evidence from the U.S. and China (EGY 118745)," Energy, Elsevier, vol. 212(C).
    6. Wen, Danyan & Liu, Li & Ma, Chaoqun & Wang, Yudong, 2020. "Extreme risk spillovers between crude oil prices and the U.S. exchange rate: Evidence from oil-exporting and oil-importing countries," Energy, Elsevier, vol. 212(C).
    7. Mohamad B. Karaki, 2020. "Monetary shocks and job flows: evidence from disaggregated data," Empirical Economics, Springer, vol. 58(6), pages 2911-2936, June.
    8. Marc Gronwald, 2009. "Investigating the U.S. Oil-Macroeconomy Nexus using Rolling Impulse Responses," CESifo Working Paper Series 2702, CESifo.
    9. Zeina Alsalman, 2021. "Does the source of oil supply shock matter in explaining the behavior of U.S. consumer spending and sentiment?," Empirical Economics, Springer, vol. 61(3), pages 1491-1518, September.

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