Synopses & Reviews
Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics.
Review
"This book would be a valuable reference for empirical researchers interested in applying simulation-based methods." JASA
Table of Contents
Part I. Simulation-Based Inference in Econometrics, Methods and Applications: Introduction Melvyn Weeks; 1. Simulation-based inference in econometrics: motivation and methods Steven Stern; Part II. Microeconometric Methods: Introduction Melvyn Weeks; 2. Accelerated Monte Carlo integration: an application to dynamic latent variable models Jean-Francois Richard and Wei Zhang; 3. Some practical issues in maximum simulated likelihood Vassillis A. Hajivassiliou; 4. Bayesian inference for dynamic discrete choice models without the need for dynamic programming John Geweke and Miochael Keane; 6. Bayesian analysis of the multinomial probit model Peter E. Rossi and Robert E. McCulloch; Part III. Time Series Methods and Models: Introduction Til Schuermann; 7. Simulated moment methods for empirical equivalent martingale measures Bent Jesper Christensen and Nicholas M. Kiefer; 8. Exact maximum likelihood estimation of observation-driven econometric models Francis X. Diebold and Til Schuermann; 9. Simulation-based inference in non-linear state space models: application to testing the permanent income hypothesis Roberto S. Mariano and Hisashi Tanizaki; 10. Simulation-based estimation of some factor models in econometrics Vance L. Martin and Adrian R. Pagan; 11. Simulation-based Bayesian inference for economic time series John Geweke; Part IV. Other Areas of Application and Technical Issues: Introduction Roberto S. Mariano; 12. A comparison of computational methods for hierarchical methods in customer survey questionnaire data Eric T. Bradlow; 13. Calibration by simulation for small sample bias correction Christian Gourieroux, Eric Renault and Nizar Touzi; 14. Simulation-based estimation of a nonlinear, latent factor aggregate production function Lee Ohanian, Giovanni L. Violante, Per Krusell, Jose-Victor Rios-Rull; 15. Testing calibrated general equilibrium models Fabio Canova and Eva Ortega; 16. Simulation variance reduction for bootstrapping Bryan W. Brown; Index.