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Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood

Kristensen, Dennis - 2006

We propose a simulated maximum likelihood estimator (SMLE) for general stochastic dynamic models based on nonparametric kernel methods. The method requires that, while the actual likelihood function cannot be written down, we can still simulate observations from the model. From the simulated...

Persistent link: https://www.econbiz.de/10012734210

On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results …

Persistent link: https://www.econbiz.de/10011348357

Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood

Kristensen, Dennis - 2008

We propose a simulated maximum likelihood estimator for dynamic models based on non-parametric kernel methods. Our method is designed for models without latent dynamics from which one can simulate observations but cannot obtain a closed-form representation of the likelihood function. Using the...

Persistent link: https://www.econbiz.de/10012722610

Maximum likelihood estimation for the fractional Vasicek model

Tanaka, Katsuto; Xiao, Weilin; Yu, Jun - In: Econometrics : open access journal 8 (2020) 3/32, pp. 1-28

This paper estimates the drift parameters in the fractional Vasicek model from a continuous record of observations via maximum likelihood (ML). The asymptotic theory for the ML estimates (MLE) is established in the stationary case, the explosive case, and the boundary case for the entire range...

Persistent link: https://www.econbiz.de/10012265682

Estimating the structural credit risk model when equity prices are contaminated by trading noises

Duan, Jin-Chuan; Fulop, Andras - 2005

simulation study is then conducted to ascertain the performance of the estimation method. …

Persistent link: https://www.econbiz.de/10011560691

Estimation of linear dynamic panel data models with time-invariant regressors : conference paper

Kripfganz, Sebastian; Schwarz, Claudia - 2013 - This version: May 6, 2013

further simulation evidence that GMM estimators with a large number of instruments can be severely biased in finite samples …

Persistent link: https://www.econbiz.de/10010342822

Simulated Likelihood Estimators for Discretely Observed Jump-Diffusions

Giesecke, Kay - 2019

This paper develops an unbiased Monte Carlo approximation to the transition density of a jump-diffusion process with state-dependent drift, volatility, jump intensity, and jump magnitude. The approximation is used to construct a likelihood estimator of the parameters of a jump-diffusion observed...

Persistent link: https://www.econbiz.de/10012904646

Improvements in maximum likelihood estimators of truncated normal samples with prior knowledge of σ : a simulation based study with application to historical height samples

A'Hearn, Brian; Komlos, John - 2003

. Simulation methods are used to establish the mean squared error performance characteristics of the restricted and unconstrained …

Persistent link: https://www.econbiz.de/10010440937

Unbiased Simulators for Anaytic Functions and Maximum Unbiased Simulated Likelihood Estimation

Duncan, Gregory M. - 2005

The paper solves a longstanding problem in simulation: How to unbiasedly estimate analytic functions of expectations … results include unbiased estimation of finite degree polynomials and other analytic functions, unbiased simulation of the … estimation literatures, these seem unknown to both simulation researchers and practitioners, so they are collected here and …

Persistent link: https://www.econbiz.de/10014066064

Fractional cointegration rank estimation

Lasak, Katarzyna; Velasco, Carlos - 2014

We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The first step consists in estimating the...

Persistent link: https://www.econbiz.de/10010244531

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