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Adjustment Is Much Slower Than You Think

  • Ricardo J. Caballero
  • Eduardo M.R.A. Engel

    ()

    (Dept. of Economics, Yale University)

In most instances, the dynamic response of monetary and other policies to shocks is infrequent and lumpy. The same holds for the microeconomic response of some of the most important economic variables, such as investment, labor demand, and prices. We show that the standard practice of estimating the speed of adjustment of such variables with partial-adjustment ARMA procedures substantially overestimates this speed. For example, for the target federal funds rate, we find that the actual response to shocks is less than half as fast as the estimated response. For investment, labor demand and prices, the speed of adjustment inferred from aggregates of a small number of agents is likely to be close to instantaneous. While aggregating across microeconomic units reduces the bias (the limit of which is illustrated by Rotemberg's widely used linear aggregate characterization of Calvo's model of sticky prices), in some instances convergence is extremely slow. For example, even after aggregating investment across all establishments in U.S. manufacturing, the estimate of its speed of adjustment to shocks is biased upward by more than 80 percent. While the bias is not as extreme for labor demand and prices, it still remains significant at high levels of aggregation. Because the bias rises with disaggregation, findings of microeconomic adjustment that is substantially faster than aggregate adjustment are generally suspect.

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Paper provided by Economic Growth Center, Yale University in its series Working Papers with number 865.

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Length: 30 pages
Date of creation: Jul 2003
Date of revision:
Handle: RePEc:egc:wpaper:865
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  1. Marvin Goodfriend, 1987. "Interest rate smoothing and price level trend-stationarity," Working Paper 87-03, Federal Reserve Bank of Richmond.
  2. Woodford, Michael, 2000. "Optimal Monetary Policy Inertia," Seminar Papers 666, Stockholm University, Institute for International Economic Studies.
  3. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
  4. Caballero, Ricardo J., 1999. "Aggregate investment," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 12, pages 813-862 Elsevier.
  5. 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.
  6. 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.).
  7. Thomas J. Sargent, 1978. "Estimation of dynamic labor demand schedules under rational expectations," Staff Report 27, Federal Reserve Bank of Minneapolis.
  8. 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.
  9. 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.
  10. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  11. 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.
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