Add to ORKGOver the last few years, major advances have occurred in the field of simulation. In partic-ular, McFadden(1989) and Pakes and Pollard(1989) have developed simulation methods to simulate expected values of random functions and have shown how to use those simulators in econometric estimation routines. Also, for example, Geweke(1989), Chib(1993), andMc
We note that likelihood inference can be based on an unbiased simulation-based estimator of the like...
This paper looks at the problem of performing likelihood inference for limited dependent processes. ...
International audienceSimulation approaches to inference have gained prominence in statistics educat...
Simulation models have become increasingly popular in economics in the last two decades, because the...
Many studies in econometric theory are supplemented by Monte Carlo simulation investigations. These ...
textabstractIn this paper we discuss several aspects of simulation based Bayesian econometric infere...
In this paper, I present a number of leading examples in the empirical literature that use simulatio...
In the process of trying to estimate a behavioral equation (either structural or reduced from) deriv...
The focus of this thesis is twofold. First, it delivers a new look at existing simulation-based meth...
In this paper we discuss several aspects of simulation based Bayesian econometric inference. We star...
Summary. This chapter overviews some recent advances on simulation-based methods of estimating finan...
This paper surveys recently developed methods for Bayesian inference and their use in economic time ...
Summary. This chapter overviews some recent advances on simulation-based methods of estimating finan...
This paper looks at the problem of performing likelihood inference for limited dependent processes. ...
The last century has seen a growing interest in complexity in economics and social sciences. The nee...
We note that likelihood inference can be based on an unbiased simulation-based estimator of the like...
This paper looks at the problem of performing likelihood inference for limited dependent processes. ...
International audienceSimulation approaches to inference have gained prominence in statistics educat...
Simulation models have become increasingly popular in economics in the last two decades, because the...
Many studies in econometric theory are supplemented by Monte Carlo simulation investigations. These ...
textabstractIn this paper we discuss several aspects of simulation based Bayesian econometric infere...
In this paper, I present a number of leading examples in the empirical literature that use simulatio...
In the process of trying to estimate a behavioral equation (either structural or reduced from) deriv...
The focus of this thesis is twofold. First, it delivers a new look at existing simulation-based meth...
In this paper we discuss several aspects of simulation based Bayesian econometric inference. We star...
Summary. This chapter overviews some recent advances on simulation-based methods of estimating finan...
This paper surveys recently developed methods for Bayesian inference and their use in economic time ...
Summary. This chapter overviews some recent advances on simulation-based methods of estimating finan...
This paper looks at the problem of performing likelihood inference for limited dependent processes. ...
The last century has seen a growing interest in complexity in economics and social sciences. The nee...
We note that likelihood inference can be based on an unbiased simulation-based estimator of the like...
This paper looks at the problem of performing likelihood inference for limited dependent processes. ...
International audienceSimulation approaches to inference have gained prominence in statistics educat...