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A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation

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Author Info
Daniel A. Ackerberg

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Abstract

Method of Simulated Moments (MSM) estimators introduced by McFadden (1989)and Pakes and Pollard (1989) are of great use to applied economists. They are relatively easy to use even for estimating very complicated economic models. One simply needs to generate simulated data according to the model and choose parameters that make moments of this simulated data as close as possible to moments of the true data. This paper uses importance sampling techniques to address a significant computational caveat regarding these MSM estimators - that often one's economic model is hard to solve. Examples include complicated equilibrium models and dynamic programming problems. We show that importance sampling can reduce he number of times a particular model needs to be solved in an estimation procedure, significantly decreasing computational burden.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0273.

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Date of creation: Jul 2001
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Handle: RePEc:nbr:nberte:0273

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C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions

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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.:
  1. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September. [Downloadable!] (restricted)
    Other versions:
  2. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-72, November. [Downloadable!] (restricted)
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  3. Lee, L.F., 1992. "Asymptotic Bias in Maximum Simulated Likelihood Estimation of Discrete Choice Models," Papers 93-03, Michigan - Center for Research on Economic & Social Theory.
  4. Berkovec, James & Stern, Steven, 1991. "Job Exit Behavior of Older Men," Econometrica, Econometric Society, vol. 59(1), pages 189-210, January. [Downloadable!] (restricted)
  5. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July. [Downloadable!] (restricted)
  6. John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
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  7. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September. [Downloadable!] (restricted)
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  8. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November. [Downloadable!] (restricted)
  9. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134. [Downloadable!] (restricted)
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  10. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 437-483, June. [Downloadable!]
  11. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January. [Downloadable!] (restricted)
  12. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240. [Downloadable!] (restricted)
  13. repec:cup:etheor:v:11:y:1995:i:3:p:437-83 is not listed on IDEAS
  14. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35. [Downloadable!] (restricted)
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  15. Keane, Michael P & Wolpin, Kenneth I, 2001. "The Effect of Parental Transfers and Borrowing Constraints on Educational Attainment," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1051-1103, November.
  16. Davis, Peter, 2006. "Estimation of quantity games in the presence of indivisibilities and heterogeneous firms," Journal of Econometrics, Elsevier, vol. 134(1), pages 187-214, September. [Downloadable!] (restricted)
  17. Stern, Steven, 1994. "Two Dynamic Discrete Choice Estimation Problems and Simulation Method Solutions," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 695-702, November. [Downloadable!] (restricted)
  18. V A Hajivassiliou & DL McFadden, 1997. "The Method of Simulated Scores for the Estimation of LDV Models," STICERD - Econometrics Paper Series /1997/328, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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  19. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September. [Downloadable!] (restricted)
  20. Berry, Steven T, 1992. "Estimation of a Model of Entry in the Airline Industry," Econometrica, Econometric Society, vol. 60(4), pages 889-917, July. [Downloadable!] (restricted)
  21. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August. [Downloadable!] (restricted)
    Other versions:
Full references

Cited by:
(explanations, 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.)

  1. Matteo Richiardi, 2004. "The Promises and Perils of Agent-Based Computational Economics," Computational Economics 0401001, EconWPA. [Downloadable!]
    Other versions:
  2. Justin G. Trogdon, 2005. "Demand for and Regulation of Cardiac Services," HEW 0502001, EconWPA. [Downloadable!]
  3. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics, Springer, vol. 7(4), pages 343-376, December. [Downloadable!] (restricted)
  4. Wesley Hartmann & V. Viard, 2008. "Do frequency reward programs create switching costs? A dynamic structural analysis of demand in a reward program," Quantitative Marketing and Economics, Springer, vol. 6(2), pages 109-137, June. [Downloadable!] (restricted)
  5. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics, Springer, vol. 4(4), pages 325-349, December. [Downloadable!] (restricted)
  6. Hartmann, Wesley R. & Nair, Harikesh S., 2007. "Retail Competition and the Dynamics of Consumer Demand for Tied Goods," Research Papers 1990, Stanford University, Graduate School of Business. [Downloadable!]
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