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Identification of dynamic economic models from reduced form VECM structures: an application of covariance restrictions

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  • Robert H. Rasche

Abstract

This analysis is a straightforward implementation of both long-run and short-run identifying or overidentifying restrictions on a vector error correction model in the "structural VAR" framework. The framework utilizes covariance restrictions, long-run multiplier restrictions, error correction coefficient restrictions, and restrictions on slope coefficients of the stimultaneous interactions in the "economic model." The framework is general enough to incorporate restrictions on impact multipliers. Two examples are provided. The first example is a dynamic M2 demand specification with a comparison to previous results that are constructed using restrictions on distributed lag coefficients to achieve identification. The second example illustrates the identification of equilibrium short-term and long-term interest responses of money demand using error-correction coefficient restrictions when the individual coefficients are underidentified in the cointegrating vectors in the presence of stationary interest rate spreads.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2000-011.

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Date of creation: 2001
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Handle: RePEc:fip:fedlwp:2000-011

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Keywords: Econometric models ; Demand for money;

References

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  1. Bernanke, Ben S., 1986. "Alternative explanations of the money-income correlation," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 49-99, January.
  2. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  3. Flint Brayton & Eileen Mauskopf & David Reifschneider & Peter Tinsley & John Williams, 1997. "The role of expectations in the FRB/US macroeconomic model," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Apr, pages 227-245.
  4. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
  5. repec:sae:niesru:v:145:y::i:1:p:43-63 is not listed on IDEAS
  6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  7. Gali, Jordi, 1992. "How Well Does the IS-LM Model Fit Postwar U.S. Data," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 709-38, May.
  8. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
  9. Boswijk, H. Peter, 1995. "Efficient inference on cointegration parameters in structural error correction models," Journal of Econometrics, Elsevier, vol. 69(1), pages 133-158, September.
  10. Hallman, Jeffrey J & Porter, Richard D & Small, David H, 1991. "Is the Price Level Tied to the M2 Monetary Aggregate in the Long Run?," American Economic Review, American Economic Association, vol. 81(4), pages 841-58, September.
  11. Robert H. Rasche, 1990. "Demand functions for measures of U.S. money and debt," Proceedings, Board of Governors of the Federal Reserve System (U.S.), pages 113-172.
  12. David H. Small & Richard D. Porter, 1989. "Understanding the behavior of M2 and V2," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Apr, pages 244-254.
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