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Simulation-Based Econometric Methods

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  • Andersen, Torben G.

Abstract

The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouri roux and Monfort begin their recent offering, Simulation-Based Econometric Methods, with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960 s, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of the standard linear model, linear simultaneous equations with the associated instrumental variable techniques, and maximum likelihood estimation within the exponential family. During the 1970 s and 1980 s the development of powerful numerical optimization routines led to the exploration of procedures without closed-form solutions for the estimators. During this period the general theory of nonlinear statistical inference was developed, and nonlinear micro models such as limited dependent variable models and nonlinear time series models, e.g., ARCH, were explored. The associated estimation principles included maximum likelihood (beyond the exponential family), pseudo-maximum likelihood, nonlinear least squares, and generalized method of moments. Finally, the third stage considers problems without a tractable analytic criterion function. Such problems almost invariably arise from the need to evaluate high-dimensional integrals. The idea is to circumvent the associated numerical problems by a simulation-based approach. The main requirement is therefore that the model may be simulated given the parameters and the exogenous variables. The approach delivers simulated counterparts to standard estimation procedures and has inspired the development of entirely new procedures based on the principle of indirect inference.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 16 (2000)
Issue (Month): 01 (February)
Pages: 131-138

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Handle: RePEc:cup:etheor:v:16:y:2000:i:01:p:131-138_00

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Cited by:
  1. Peter Fuleky & Eric Zivot, 2010. "Indirect Inference Based on the Score," Working Papers UWEC-2010-08, University of Washington, Department of Economics.
  2. Gouriéroux, Christian & Phillips, Peter C.B. & Yu, Jun, 2010. "Indirect inference for dynamic panel models," Journal of Econometrics, Elsevier, vol. 157(1), pages 68-77, July.
  3. Peter C. B. Phillips & Jun Yu, 2009. "Simulation-Based Estimation of Contingent-Claims Prices," Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3669-3705, September.
  4. Jun YU, 2009. "Econometric Analysis of Continuous Time Models: A Survey of Peter Phillips' Work and Some New Results," Working Papers 21-2009, Singapore Management University, School of Economics.
  5. Neil Shephard & Siem Jan Koopman, 2002. "Testing the assumptions behind the use of importance sampling," Economics Series Working Papers 2002-W17, University of Oxford, Department of Economics.
  6. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
  7. Michael Creel & Dennis Kristensen, 2011. "Indirect likelihood inference," UFAE and IAE Working Papers 874.11, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  8. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
  9. Antonis Demos & Stelios Arvanitis, 2010. "Stochastic Expansions and Moment Approximations for Three Indirect Estimators," DEOS Working Papers 1004, Athens University of Economics and Business.
  10. Gould, Brian W. & Yen, Steven T., 2002. "Food Demand In Mexico: A Quasi-Maximum Likelihood Approach," 2002 Annual meeting, July 28-31, Long Beach, CA 19667, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  11. Chihwa Kao & Lung-fei Lee & Mark M. Pitt, 2001. "Simulated Maximum Likelihood Estimation of the Linear Expenditure System with Binding Non-Negativity Constraints," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 215-235, May.

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