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Computing the Distributions of Economic Models Via Simulation Author info | Abstract | Publisher info | Download info | Related research | Statistics John Stachurski () (Department of Economics, University of Melbourne)
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This paper studies a Monte Carlo algorithm for computing distributions of state variables when the underlying model is a Markov process. It is shown that the L1 error of the estimator always converges to zero with probability one, and often at a parametric rate. A related technique for computing stationary distributions is also investigated.
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Paper provided by Kyoto University, Institute of Economic Research in its series Working Papers with number
615.
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Length: 34pages
Date of creation: Apr 2006Date of revision:
Handle: RePEc:kyo:wpaper:615Contact details of provider: Postal: Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501 Phone: +81-75-753-7102 Fax: +81-75-753-7193 Email: Web page: http://www.kier.kyoto-u.ac.jp/eng/index.html More information through EDIRC
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Keywords: Distributions Markov processes simulation. Other versions of this item:
Find related papers by JEL classification: C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
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António Antunes & Tiago Cavalcanti & Anne Villamil, 2006.
"Computing General Equilibrium Models with Occupational Choice and Financial Frictions ,"
SCAPE Policy Research Working Paper Series
0611, National University of Singapore, Department of Economics, SCAPE.
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