Showing 1 - 10 of 1,918
Applied researchers often need to estimate confidence intervals for functions of parameters, such as the effects of counterfactual policy changes. If the function is continuously differentiable and has non-zero and bounded derivatives, then they can use the delta method. However, if the function...
Persistent link: https://www.econbiz.de/10009747952
the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …
Persistent link: https://www.econbiz.de/10011301159
Survey research studies make extensive use of rating scales to measure constructs of interest. The bounded nature of such scales presents econometric estimation challenges. Linear estimation methods (e.g. OLS) often produce predicted values that lie outside the rating scales, and fail to account...
Persistent link: https://www.econbiz.de/10011536090
in latent-variable and other models estimated through simulation-based methods. In both re-parameterizations the …, and discusses the potential comparative advantages of using them in the context of regression modeling and simulation …
Persistent link: https://www.econbiz.de/10012756542
The purpose of this paper is to present a comprehensive Monte Carlo simulation study on the performance of minimum …
Persistent link: https://www.econbiz.de/10012757942
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
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
We develop a simulation algorithm that generates multivariate samples with exact means, covariances, and multivariate … simulation of risk factors for the risk management of financial institutions. We use the Kollo measure of multivariate skewness …
Persistent link: https://www.econbiz.de/10012855299
The paper introduces four unbiased probability-simulators which produce continuous (simulated) log-likelihood functions with almost everywhere continuous derivatives. Identification conditions are derived which show that in the presence of intercepts in the latent utilities, then the shocks'...
Persistent link: https://www.econbiz.de/10012858456
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