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Inventory Shocks and the Great Moderation

Author

Listed:
  • James Morley

    () (University of New South Wales)

  • Aarti Singh

    () (University of Sydney)

Abstract

Why did the volatility of U.S. real GDP decline by more than the volatility of final sales with the Great Moderation in the mid-1980s? One explanation is that firms shifted their inventory behavior towards a greater emphasis on production smoothing. We investigate the role of inventories in the Great Moderation by estimating an unobserved components model that identifies inventory and sales shocks and their propagation in the aggregate data. Our estimates provide no support for increased production smoothing. Instead, smaller transitory inventory shocks are responsible for the excess volatility reduction in output compared to sales. These shocks behave like informational errors related to production that must be set in advance and their reduction also helps explain the changed forecasting role of inventories since the mid-1980s. Our findings provide an optimistic prognosis for a continuation of the Great Moderation, despite the dramatic movements in output during the recent economic crisis.

Suggested Citation

  • James Morley & Aarti Singh, 2015. "Inventory Shocks and the Great Moderation," Discussion Papers 2012-42B, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2012-42b
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2012-42.pdf
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    References listed on IDEAS

    as
    1. West, Kenneth D, 1986. "A Variance Bounds Test of the Linear Quadratic Inventory Model," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 374-401, April.
    2. Tara M. Sinclair, 2009. "The Relationships between Permanent and Transitory Movements in U.S. Output and the Unemployment Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 529-542, March.
    3. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    4. Herrera, Ana Mari­a & Murtazashvili, Irina & Pesavento, Elena, 2008. "The comovement in inventories and in sales: Higher and higher," Economics Letters, Elsevier, vol. 99(1), pages 155-158, April.
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    Cited by:

    1. Yunjong Eo & James Morley, 2015. "Likelihood‐ratio‐based confidence sets for the timing of structural breaks," Quantitative Economics, Econometric Society, vol. 6(2), pages 463-497, July.
    2. Arpita Chatterjee & James Morley & Aarti Singh, 2017. "Full Information Estimation of Household Income Risk and Consumption Insurance," Discussion Papers 2017-07, School of Economics, The University of New South Wales.
    3. Chatterjee, Arpita & Morley, James & Singh, Aarti, 2017. "Likelihood-Based Estimates of Household Consumption Insurance," Working Papers 2017-04, University of Sydney, School of Economics, revised Apr 2018.
    4. Kenneth D. West, 2017. "Hansen and Sargent's Recursive Models of Dynamic Linear Economies: A Review Essay," Journal of Economic Literature, American Economic Association, vol. 55(1), pages 173-181, March.
    5. repec:eee:ecmode:v:66:y:2017:i:c:p:163-170 is not listed on IDEAS

    More about this item

    Keywords

    Great Moderation; inventories; production smoothing; unobserved components model;

    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
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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