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The Use of Monetary Aggregate to Target Nominal GDP

  • Martin Feldstein
  • James H. Stock

This paper studies the possibility of using the broad monetary aggregate M2 to target the quarterly rate of growth of nominal GDP. Our findings indicate that the Federal Reserve could probably guide M2 in a way that reduces not only the long-term average rate of inflation but also the variance of the annual rate of growth of nominal GDP. An optimal M2 rule, derived from a simple VAR, reduces the mean ten-year standard deviation of annual GDP growth by over 20 percent. Although there is uncertainty about this value because of both parameter uncertainty and stochastic shocks to the economy, we estimate that the probability that the annual variance would be reduced over a ten year period exceeds 85 percent. A much simpler policy based on a single equation linking M2 and GDP is shown to be almost as successful in reducing this annual GDP variance. Additional statistical tests indicate that M2 is a useful predictor of nominal GDP. Moreover, a battery of recently developed tests for parameter stability fails to reject the hypothesis that the M2 - GDP link is stable, but the MI - GDP and monetary base - GDP relations are found to be highly unstable. This evidence contradicts those who have argued that the M2 - GDP relation is so unstable in the short run that it cannot be used to reduce the variance of nominal GDP growth.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 4304.

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Date of creation: Mar 1993
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Publication status: published as Monetary Policy, N. Gregory Mankiw, ed., pp.7-70, (Chicago: University of Chicago Press: 1994).
Handle: RePEc:nbr:nberwo:4304
Note: EFG ME
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  1. Ploberger, Werner & Krämer;, Walter, 1990. "The Local Power of the CUSUM and CUSUM of Squares Tests," Econometric Theory, Cambridge University Press, vol. 6(03), pages 335-347, September.
  2. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
  3. David F. Hendry & Neil R. Ericsson, 1990. "Modeling the demand for narrow money in the United Kingdom and the United States," International Finance Discussion Papers 383, Board of Governors of the Federal Reserve System (U.S.).
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  9. R.A. Pecchenino & Robert H. Rasche, 1990. "P* Type Models: Evaluation and Forecasts," NBER Working Papers 3406, National Bureau of Economic Research, Inc.
  10. Christopher A. Sims, 1982. "Policy Analysis with Econometric Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 13(1), pages 107-164.
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  12. Arturo Estrella & Gikas A. Hardouvelis, 1989. "The term structure as a predictor of real economic activity," Research Paper 8907, Federal Reserve Bank of New York.
  13. Christiano, Lawrence J, 1992. "Searching for a Break in GNP," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 237-50, July.
  14. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  15. Ljungqvist, Lars & Park, Myungsoo & Stock, James H. & Watson, Mark W., 1988. "The convergence of multivariate unit root distributions to their asymptotic limits : The case of money-income causality," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 489-502.
  16. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-85, March.
  17. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-52, September.
  18. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(01), pages 1-21, March.
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