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Missing Aggregate Dynamics: On the Slow Convergence of Lumpy Adjustment Models

The dynamic response of aggregate variables to shocks is one of the central concerns of applied macroeconomics. The main measurement procedure for these dynamics consists of estimmiating an ARMA or VAR (VARs, for short). In non- or semi-structural approaches, the characterization of dynamics stops there. In other, more structural approaches, researcher try to uncover underlying adjustment cost parameters from the estimated VARs. Yet, in others, such as in RBC models, these estimates are used as the benchmark over which the success of the calibration exercise, and the need for further theorizing, is assessed. The main point of this paper is that when the microeconomic adjustment underlying the corresponding aggregates is lumpy, conventional VARs procedures are often inadequate for all of the above practices. In particular, the researcher will conclude that there is less persistence in the response of aggregate variables to aggregate shocks than there really is. Paradoxically, while idiosyncratic productivity and demand shocks smooth away microeconomic non-convexities and are often used as a justification for approximating aggregate dynamics with linear models, their presence exacerbate the bias. Since in practice idiosyncratic uncertainty is many times larger than aggregate uncertainty, we conclude that the problem of missing aggregate dynamics is prevalent in empirical and quantitative macroeconomic research.

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File URL: http://cowles.econ.yale.edu/P/cd/d14a/d1430.pdf
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Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1430.

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Length: 32 pages
Date of creation: Jul 2003
Date of revision: Apr 2008
Handle: RePEc:cwl:cwldpp:1430
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Web page: http://cowles.econ.yale.edu/

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  1. Julio Rotemberg, 1987. "The New Keynesian Microfoundations," NBER Chapters, in: NBER Macroeconomics Annual 1987, Volume 2, pages 69-116 National Bureau of Economic Research, Inc.
  2. Thomas J. Sargent, 1978. "Estimation of dynamic labor demand schedules under rational expectations," Staff Report 27, Federal Reserve Bank of Minneapolis.
  3. Woodford, Michael, 2000. "Optimal Monetary Policy Inertia," Seminar Papers 666, Stockholm University, Institute for International Economic Studies.
  4. Goodfriend, Marvin, 1987. "Interest rate smoothing and price level trend-stationarity," Journal of Monetary Economics, Elsevier, vol. 19(3), pages 335-348, May.
  5. Brian Sack, 1998. "Uncertainty, learning, and gradual monetary policy," Finance and Economics Discussion Series 1998-34, Board of Governors of the Federal Reserve System (U.S.).
  6. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  7. Cabalero, R.J., 1997. "Aggregaete Investment," Working papers 97-20, Massachusetts Institute of Technology (MIT), Department of Economics.
  8. Mark Bils & Peter J. Klenow, 2002. "Some Evidence on the Importance of Sticky Prices," NBER Working Papers 9069, National Bureau of Economic Research, Inc.
  9. Ricardo J. Caballero & Eduardo M.R.A. Engel & John Haltiwanger, 1995. "Aggregate Employment Dynamics: Building From Microeconomic Evidence," NBER Working Papers 5042, National Bureau of Economic Research, Inc.
  10. Majd, Saman & Pindyck, Robert S., 1987. "Time to build, option value, and investment decisions," Journal of Financial Economics, Elsevier, vol. 18(1), pages 7-27, March.
  11. Ricardo J. Caballero & Eduardo M. R. A. Engel & John C. Haltiwanger, 1995. "Plant-Level Adjustment and Aggregate Investment Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(2), pages 1-54.
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