Topic
Indirect Inference
About: Indirect Inference is a research topic. Over the lifetime, 503 publications have been published within this topic receiving 16119 citations.
Papers published on a yearly basis
Papers
Book•
16 Oct 2003
TL;DR: Econometric Theory and Methods International Edition as mentioned in this paper provides a unified treatment of modern econometric theory and practical Econometric methods, as well as the geometrical approach to least squares is emphasized, as is the method of moments.
Abstract: Econometric Theory and Methods International Edition provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively. The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation.
2,074 citations
TL;DR: In this paper, the authors proposed a simple modification of a conventional method of moments estimator for a discrete response model, replacing response probabilities that require numerical integration with estimators obtained by Monte Carlo simulation.
Abstract: This paper proposes a simple modification of a conventional method of moments estimator for a discrete response model, replacing response probabilities that require numerical integration with estimators obtained by Monte Carlo simulation. This method of simulated moments (MSM) does not require precise estimates of these probabilities for consistency and asymptotic normality, relying instead on the law of large numbers operating across observations to control simulation error, and hence can use simulations of practical size. The method is useful for models such as high-dimensional multinomial probit (MNP), where computation has restricted applications.
1,866 citations
Book•
1 Jan 1996
TL;DR: This book introduces a new generation of statistical econometrics, where the previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach.
Abstract: 1. Introduction and Motivations 2. The Method of Simulated Moments 3. Simulated Maximum Likelihood, Pseudo-maximum Likelihood, and Nonliner Least Squares Methods 4. Indirect Inference 5. Applications of Limited Dependent Variable Models 6. Applications to Financial Series 7. Applications to Switching Regime Models
1,376 citations
TL;DR: In this article, the authors use an indirect inference procedure to estimate the structural parameters of a rich speciflcation of capital adjustment costs, which are optimally chosen to reproduce a set of moments that capture the nonlinear relationship between investment and profitability found in plant-level data.
Abstract: This paper studies the nature of capital adjustment at the plant level. We use an indirect inference procedure to estimate the structural parameters of a rich speciflcation of capital adjustment costs. In efiect, the parameters are optimally chosen to reproduce a set of moments that capture the nonlinear relationship between investment and profltability found in plant-level data. Our flndings indicate that a model which
1,069 citations
TL;DR: In this article, the authors describe an approach to generate moment conditions for generalized method of moments (GMM) estimation of the parameters of a structural model, using the score of a density that has an analytic expression to define the GMM criterion.
Abstract: We describe an intuitive, simple, and systematic approach to generating moment conditions for generalized method of moments (GMM) estimation of the parameters of a structural model. The idea is to use the score of a density that has an analytic expression to define the GMM criterion. The auxiliary model that generates the score should closely approximate the distribution' of the observed data but is not required to nest it. If the auxiliary model nests the structural model then the estimator is as efficient as maximum likelihood. The estimator is advantageous when expectations under a structural model can be computed by simulation, by quadrature, or by analytic expressions but the likelihood cannot be computed easily.
1,006 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2024 | 1 |
| 2023 | 15 |
| 2022 | 10 |
| 2021 | 21 |
| 2020 | 24 |
| 2019 | 20 |