A new use of importance sampling to reduce computational burden in simulation estimation

Quantitative Marketing and Economics

Volumn 7, Issue 4, 2009, Pages 343-376

  Ackerberg, Daniel A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Importance sampling; Monte Carlo study; Simulation estimators

Indexed keywords

EID: 70349740753     PISSN: 15707156     EISSN: 1573711X     Source Type: Journal    
DOI: 10.1007/s11129-009-9074-z     Document Type: Article

References (43)

1. Ackerberg, D. (2001). A new use of importance sampling to reduce computational burden in simulation estimation. NBER working paper #T273
2. Ackerberg, D. (2003). Advertising, learning, and consumer choice in experience. Good markets: A structural empirical examination. International Economic Review, 44, 1007-1040.
3. Aguirregabiria, V., & Mira, P. (2002). Swapping the nested fixed point algorithm: A class of estimators for discrete Markov decision models. Econometrica 70, 1519-1543.
4. Aguirregabiria, V., & Mira, P. (2007). Sequential estimation of dynamic discrete games. Econometrica 75, 1-53.
5. Bajari, P. (1998a). Econometrics of the first price auction with asymmetric bidders. Mimeo, Stanford Univ.
6. Bajari, P. (1998b). Econometrics of sealed bid auctions. In 1998 Proceedings of the Business and Economic Statistics Section of the American Statistical Association (pp. 41-49).
7. Bajari, P., Benkard, C. L., & Levin, J. (2007a). Estimating dynamic models of imperfect competition. Econometrica 75, 1331-1370.
8. Bajari, P., Fox, J., & Ryan, S. (2007b). Linear regression estimation of discrete choice models with nonparametric random coefficient distributions. American Economic Review, 97, 459-463.
9. Bajari, P., Chernozhukov, V., Hong, H., & Nekipelov, D. (2008). Nonparametric and semiparametric analysis of a dynamic game model. Unpublished working paper.
10. Bajari, P., Fox, J., Kim, K., & Ryan, S. (2009a). Discrete choice models with a nonparametric distribution of random coefficient. Mimeo, U. of MN.
11. Bajari, P., Hong, H., & Ryan, S. (2009b). Identification and estimation of discrete games of complete information. Econometrica, in press.
12. Berry, S. T. (1992). Estimation of a model of entry in the airline industry. Econometrica, 60, 889-917.
13. Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica, 63, 841-890.
14. Crawford, G., & Shum, M. (2005). Uncertainty and learning in pharmaceutical demand. Econometrica, 73, 1135-1174.
15. Davis, P. (2006). Estimation of quantity games in the presence of indivisibilities and heterogeous firms. Journal of Econometrics, 134, 187-214.
16. Erdem, T., & Keane, M. (1996). Decision making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing Science, 15, 1-20.
17. Gasmi, F., Laffont, J-J, & Vuong, Q. (1991). Econometric analysis of collusive behavior in a soft drink industry. Journal of Economics and Management Strategy, 1, 277-311.
18. Geweke, J. (1989). Efficient simulation from the multivariate normal distribution subject to linear inequality constraints and the evaluation of constraint probabilities. Econometrica, 57, 1317-1339.
19. Goettler, R., & Clay, K. (2009). Tariff choice with consumer learning and switching costs. Mimeo, Chicago GSB.
20. Gourieroux, C., & Monfort, A. (1991). Simulation based inference in models with heterogeneity. Annales d'Economie et de Statistique, 20/21, 69-107.
21. Hansen, L. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50, 1029-1064.
22. Hartmann, W. (2006). Intertemporal effects of consumption and their implications for demand elasticity estimates. Quantitative Marketing and Economics, 4, 325-349.
23. Hendel, I., & Nevo, A. (2006). Measuring the implications of sales and consumer inventory behavior. Econometrica, 74, 1137-1173.
24. Hotz, V. J., & Miller, R. A. (1993). Conditional choice probabilities and the estimation of dynamic models. Review of Economic Studies 60, 497-529.
25. Hotz, V. J., Miller, R. A., Sanders, S., & Smith, J. (1994). A simulation estimator for dynamic models of discrete choice. Review of Economic Studies 61, 265-289.
26. Imai, S., Jain, N., & Ching, A. (2009). Bayesian estimation of dynamic discrete choice models. Econometrica, in press.
27. Jofre-Bonet, M., & Pesendorfer, M. (2003). Estimation of a dynamic auction game. Econometrica 71, 1443-1489.
28. Judd, K., & Su, C. (2008). Constrained optimization approaches to estimation of structural models. Mimeo, Stanford.
29. Keane, M., & Wolpin, K. (1994). The solution and estimation of discrete choice dynamic programming models by simulation and interpolation. Review of Economics and Statistics, 76, 648-72.
30. Keane, M., & Wolpin, K. (2000). Estimating the effect of welfare on the education, employment, fertility and marraige decisions of women. Mimeo, UPenn.
31. Keane, M., & Wolpin, K. (2001). The effect of parental transfers and borrowing constraints on educational attainment. International Economic Review, 42, 1051-1103.
32. Lerman, S., & Manski, C. (1981). On the use of simulated frequencies to approximate choice probabilities. In C. Manski & D. McFadden (Eds.) Structural analysis of discrete data with econometric applications. (pp. 305-319). Cambridge: MIT.
33. Maskin, E., & Riley, J. (1996). Existence of equilibrium in sealed, high bid auctions. Mimeo.
34. McFadden, D. (1989) A method of simulated moments for estimation of discrete response models without numerical integration. Econometrica, 57(5), 995-1026.
35. Kloek, T., & Van Dijk, H. (1978): Bayesian estimation of equation system parameters: An application of integration by Monte-Carlo. Econometrica, 46, 1-20.
36. Norets, A. (2009) Inference in dynamic discrete choice models with serially correlated unobserved state variables. Econometrica, in press.
37. Pakes, A., Ostrovsky, M., & Berry, S. (2007). Simple estimators for the parameters of discrete dynamic games, with entry/exit examples. RAND Journal of Economics 38, 373-399.
38. Pakes, A., & Pollard, D. (1989). Simulation and the asymptotics of optimization estimators. Econometrica, 57, 1027-1057.
39. Pantano, J. (2008). Labor market stigma in a forward looking model of criminal behavior. Mimeo, Washington U, St. Louis.
40. Pesendorfer, M., & Schmidt-Dengler, P. (2008). Asymptotic least squares estimators For dynamic games. Review of Economic Studies, 75, 901-928.
41. Rust, J. (1987). Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher. Econometrica, 55, 999-1033.
42. Rust, J. (1997). Using randomization to break the curse of dimensionality. Econometrica, 65, 487-516.
43. Train, K. (2003). Discrete choice methods with simulation. Cambridge: Cambridge University Press.