Simulation-Based Econometric Methods
By Christian Gourieroux, Alain Monfort


Contents
1 Introduction and Motivations
  1.1 Introduction
  1.2 A Review of Nonlinear Estimation Methods
  1.3 Potential Applications of Simulated Methods
  1.4 Simulation

2 The Method of Simulated Moments (MSM)
  2.1 Path Calibration or Moments Calibration
  2.2 The Generalized Method of Moments (GMM)
  2.3 The Method of Simulated Moments (MSM)

3 Simulated Maximum Likelihood, Pseudo-Maximum Likelihood, and Nonlinear Least Squares Methods
  3.1 Simulated Maximum Likelihood Estimators (SML)
  3.2 Simulated Pseudo-Maximum Likelihood and Nonlinear Least Squares Methods
  3.3 Bias Corrections for Simulated Nonlinear Least Squares

4 Indirect Inference
  4.1 The Principle
  4.2 Properties of the Indirect Inference Estimators
  4.3 Examples
  4.4 Some Additional Properties of Indirect Inference Estimators

5 Applications to Limited Dependent Variable Models
  5.1 MSM and SML Applied to Qualitative Models
  5.2 Qualitative Models and Indirect Inference based on Multivariate Logistic Models
  5.3 Simulators for Limited Dependent Variable Models based on Gaussian Latent Variables
  5.4 Empirical Studies

6 Applications to Financial Series
  6.1 Estimation of Stochastic Differential Equations from Discrete Observations  by Indirect Inference
  6.2 Estimation of Stochastic Differential Equations from Moment
  6.3 Factor Models

7 Applications to Switching Regime Models
  7.1 Endogenously Switching Regime Models  
  7.2 Exogenously Switching Regime Models