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Generation and testing of pseudo-random numbers to be used in the stochastic simulation of econometric models

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Author Info

  • Calzolari, Giorgio
  • Ciriani, Tito A.
  • Corsi, Paolo

Abstract

Purpose of this paper is the description of the tecniques used to generate pseudo-random numbers, to be added as disturbance terms to the stochastic structural equations of econometric models. These disturbance terms should have the same statistical properties as the residuals obtained, in each equation, during the estimation phase.

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File URL: http://mpra.ub.uni-muenchen.de/24172/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 24172.

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Date of creation: 1976
Date of revision:
Handle: RePEc:pra:mprapa:24172

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Related research

Keywords: Econometric models; random numbers; stochastic simulation;

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References

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  1. Michael K. Evans & Lawrence R. Klein & Mitsuo Saito & Michael D. McCarthy, 1972. "Short-Run Prediction And Long-Run Simulation Of The Wharton Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Vols. 1 and 2, pages 139-200 National Bureau of Economic Research, Inc.
  2. Gary Fromm & Lawrence R. Klein & George R. Schink, 1972. "Short- And Long-Term Simulations With The Brookings Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Vols. 1 and 2, pages 201-310 National Bureau of Economic Research, Inc.
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Cited by:
  1. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1978. "Stochastic simulation of econometric models: installation procedures and user's instructions," MPRA Paper 24173, University Library of Munich, Germany.
  2. Calzolari, Giorgio, 1979. "Stochastic simulation experiments on Model 5 of Bonn University," MPRA Paper 24456, University Library of Munich, Germany.
  3. Calzolari, Giorgio & Corsi, Paolo, 1977. "Stochastic simulation as a validation tool for econometric models," MPRA Paper 21226, University Library of Munich, Germany.
  4. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1979. "Some results on the stochastic simulation of a nonlinear model of the Italian economy," MPRA Paper 22684, University Library of Munich, Germany.

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