Computing the Distributions of Economic Models via Simulation
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 $L_1$ 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 investigate
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||04 Jul 2006|
|Date of revision:|
|Contact details of provider:|| Web page: http://comp-econ.org/|
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hansen, Bruce E., 2005. "Exact Mean Integrated Squared Error Of Higher Order Kernel Estimators," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1031-1057, December.
- Esteban Rossi-Hansberg & Mark L. J. Wright, 2007.
"Establishment Size Dynamics in the Aggregate Economy,"
American Economic Review,
American Economic Association, vol. 97(5), pages 1639-1666, December.
- Esteban Rossi-Hansberg & Mark L. J. Wright, 2006. "Establishment size dynamics in the aggregate economy," Staff Report 382, Federal Reserve Bank of Minneapolis.
- Deaton, A. & Laroque, G., 1989.
"On The Behavior Of Commodity Prices,"
145, Princeton, Woodrow Wilson School - Public and International Affairs.
- Johnson, Paul A., 2005.
"A continuous state space approach to "Convergence by Parts","
Elsevier, vol. 86(3), pages 317-321, March.
- Johnson, Paul, 2003. "A Continuous State Space Approach to “Convergence by Parts”," Vassar College Department of Economics Working Paper Series 54, Vassar College Department of Economics.
- Elerian, O. & Chib, S. & Shephard, N., 1998.
"Likelihood INference for Discretely Observed Non-linear Diffusions,"
146, Economics Group, Nuffield College, University of Oxford.
- Elerain, Ola & Chib, Siddhartha & Shephard, Neil, 2001. "Likelihood Inference for Discretely Observed Nonlinear Diffusions," Econometrica, Econometric Society, vol. 69(4), pages 959-93, July.
- Neil Shephard & Ola Elerian & Siddhartha Chib, 1998. "Likelihood inference for discretely observed non-linear diffusions," Economics Series Working Papers 1998-W10, University of Oxford, Department of Economics.
- Ola Elerian & Siddhartha Chib & Neil Shephard, 2000. "Likelihood inference for discretely observed non-linear diffusions," OFRC Working Papers Series 2000mf02, Oxford Financial Research Centre.
- Giorgio Valente & Lucio Sarno, 2004.
"Comparing the accuracy of density forecasts from competing models,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 23(8), pages 541-557.
- Sarno, Lucio & Valente, Giorgio, 2002. "Comparing the Accuracy of Density Forecasts from Competing Models," Computing in Economics and Finance 2002 223, Society for Computational Economics.
- Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
- Nishimura, Kazuo & Stachurski, John, 2005. "Stability of stochastic optimal growth models: a new approach," Journal of Economic Theory, Elsevier, vol. 122(1), pages 100-118, May.
- A. S. Hurn & K. A. Lindsay & V. L. Martin, 2003. "On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 45-63, 01.
- Nishimura, Kazuo & Rudnicki, Ryszard & Stachurski, John, 2006. "Stochastic optimal growth with nonconvexities," Journal of Mathematical Economics, Elsevier, vol. 42(1), pages 74-96, February.
When requesting a correction, please mention this item's handle: RePEc:sce:scecfa:185. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.