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On the ambiguous consequences of omitting variables

De Luca, Giuseppe; Magnus, Jan R.; Peracchi, Franco - 2015

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have...

Persistent link: https://www.econbiz.de/10010532602

Decomposing portfolio value-at-risk : a general analysis

Hallerbach, Winfried G. - 1999 - This rev.: May 10, 1999

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

On the Finite Sample Accuracy of Nonparametric Resampling Algorithms for Economic Time Series

Berkowitz, Jeremy; Birgean, Ionel; Kilian, Lutz - 1999

In recent years, there has been increasing interest in nonparametric bootstrap inference for economic time series. Nonparametric resampling techniques help protect against overly optimistic inference in time series models of unknown structure. They are particularly useful for evaluating the fit...

Persistent link: https://www.econbiz.de/10014198030

Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems

Malhotra, Yogesh - 2015

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

Persistent link: https://www.econbiz.de/10013029835

Estimating Average Treatment Effects With Propensity Scores Estimated With Four Machine Learning Procedures : Simulation Results in High Dimensional Settings and With Time to Event...

Brown, Kip - 2018

Background: The increased availability of claims data allows one to build high dimensional datasets, rich in covariates, for accurately estimating treatment effects in medical and epidemiological cohort studies. This paper shows the full potential of machine learning for the estimation of...

Persistent link: https://www.econbiz.de/10012908991

Simulation Study on Estimation Bias in Spatial Lag Model from Omitted Variable Correlated with Regressors

Yokoi, Takahisa - 2012

In this research, the omitted variable problem in a spatial autoregressive model is analyzed by simulation. We examine … variable correlated with regressors, there have been theoretical discussions of consistency and simulation analyses on the … square error. Our simulation results show that the S-2SLS estimator is strongly affected by the omitted variable under …

Persistent link: https://www.econbiz.de/10013098186

Combinations of High Order Gaussian Kernel Estimator with Simulation Historical of Value at Risk (VaR) Return Portfolio Measurement

2014

VaR calculation that will be developed in the form of High-order kernel estimator of VaR with historical simulation method … with Historical Simulation estimation methods and the combination of high order kernels increase with increasing order … kernel estimates and tend to be larger than the Historical Simulation estimation methods. Statistical properties indicates …

Persistent link: https://www.econbiz.de/10013056260

Simulation-Based Two-Step Estimation with Endogenous Regressors

Kan, Kamhon - 2011

This paper considers models with latent/discrete endogenous regressors and presents a simulation-based two-step (STS …) estimator. The endogeneity is corrected by adopting a simulation-based control function approach. The first step consists of …

Persistent link: https://www.econbiz.de/10013126679

Bias-correction in vector autoregressive models : a simulation study

Engsted, Tom; Pedersen, Thomas Q. - In: Econometrics : open access journal 2 (2014) 1, pp. 45-71

identical. Next, based on a detailed simulation study, we show that when the model is stationary this simple bias formula …

Persistent link: https://www.econbiz.de/10010336196

Minimum distance estimation of possibly non-invertible moving average models

Gospodinov, Nikolaj; Ng, Serena - 2013

the cumulants on the model parameters is analytically intractable, we consider simulation-based estimators with two … accommodate a large class of distributions with non-Gaussian features. The proposed simulation estimators are also asymptotically …

Persistent link: https://www.econbiz.de/10010201380