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(S,s) insights into the role of inventories in business cycles and high frequency fluctuations

Author

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  • Julia Thomas

    (Ohio State University)

  • Aubhik Khan

    (Ohio State University)

Abstract

We develop an equilibrium model to explain salient business cycle patterns involving aggregate production, sales and inventory investment alongside a distinct set of patterns at high frequencies. Our firms face idiosyncratic productivity shocks and fixed costs of ordering inputs, leading them to order infrequently and accumulate inventories. Thus, the model’s aggregate state vector includes a time-varying distribution of firms over productivities and inventories. Disciplined by data on aggregate inventories and firm-level sales and output, our model reproduces key patterns in the data at business cycle frequencies: Inventory investment is procyclical and positively correlated with final sales, GDP varies more than sales, and the inventory-to-sales ratio is countercyclical. These successes are robust to a wide range of micro-level parameters governing firms’ order costs and relative productivities, while those parameters are key to the model’s high-frequency performance. When order costs are more predictable and shifts in relative productivities are transitory, the model also performs well in key high frequency respects: The relative volatility of inventory investment rises sharply, and sales and inventory investment are negatively correlated, while both series maintain positive correlations with GDP. Despite these distinctions, our model predicts that aggregate fluctuations are surprisingly unaffected by inventories even at high frequencies.

Suggested Citation

  • Julia Thomas & Aubhik Khan, 2016. "(S,s) insights into the role of inventories in business cycles and high frequency fluctuations," 2016 Meeting Papers 662, Society for Economic Dynamics.
  • Handle: RePEc:red:sed016:662
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    References listed on IDEAS

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    1. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
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    3. Diego A. Comin & Thomas Philippon, 2006. "The Rise in Firm-Level Volatility: Causes and Consequences," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 167-228, National Bureau of Economic Research, Inc.
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    5. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    6. Aubhik Khan & Julia K. Thomas, 2007. "Inventories and the Business Cycle: An Equilibrium Analysis of ( S , s ) Policies," American Economic Review, American Economic Association, vol. 97(4), pages 1165-1188, September.
    7. Aubhik Khan & Julia K. Thomas, 2008. "Idiosyncratic Shocks and the Role of Nonconvexities in Plant and Aggregate Investment Dynamics," Econometrica, Econometric Society, vol. 76(2), pages 395-436, March.
    8. Sarte, Pierre-Daniel & Schwartzman, Felipe & Lubik, Thomas A., 2015. "What inventory behavior tells us about how business cycles have changed," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 264-283.
    9. Alan S. Blinder, 1981. "Retail Inventory Behavior and Business Fluctuations," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 12(2), pages 443-520.
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    Cited by:

    1. Julio L. Ortiz, 2022. "Spread Too Thin: The Impact of Lean Inventories," International Finance Discussion Papers 1342, Board of Governors of the Federal Reserve System (U.S.).

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