Showing 1 - 10 of 149
censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semipara …
Persistent link: https://www.econbiz.de/10011091424
The inverse probability weighted Generalised Empirical Likelihood (IPW-GEL) estimator is proposed for the estimation of the parameters of a vector of possibly non-linear unconditional moment functions in the presence of conditionally independent sample selection or attrition.The estimator is...
Persistent link: https://www.econbiz.de/10011090314
method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the … absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estimator. An …
Persistent link: https://www.econbiz.de/10011092158
A new class of robust regression estimators is proposed that forms an alternative to traditional robust one-step estimators and that achieves the √n rate of convergence irrespective of the initial estimator under a wide range of distributional assumptions. The proposed reweighted least trimmed...
Persistent link: https://www.econbiz.de/10011091783
The binary-choice regression models such as probit and logit are used to describe the effect of explanatory variables on a binary response vari- able. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedastic- ity and...
Persistent link: https://www.econbiz.de/10011092154
This paper introduces a new class of robust regression estimators. The proposed twostep least weighted squares (2S-LWS) estimator employs data-adaptive weights determined from the empirical distribution, quantile, or density functions of regression residuals obtained from an initial robust fit....
Persistent link: https://www.econbiz.de/10011092502
Abstract. This paper studies a new class of robust regression estimators based on the two-step least weighted squares (2S-LWS) estimator which employs data-adaptive weights determined from the empirical distribution or quantile functions of regression residuals obtained from an initial robust...
Persistent link: https://www.econbiz.de/10011092820
Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known BMA and the recently developed WALS. Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using...
Persistent link: https://www.econbiz.de/10011090802
Empirical growth research faces a high degree of model uncertainty. Apart from the neoclassical growth model, many new (endogenous) growth models have been proposed. This causes a lack of robustness of the parameter estimates and makes the determination of the key determinants of growth...
Persistent link: https://www.econbiz.de/10011091371
Abstract: In specifying a regression equation, we need to determine which regressors to include, but also how these regressors are measured. This gives rise to two levels of uncertainty: concepts (level 1) and measurements within each concept (level 2). In this paper we propose a hierarchical...
Persistent link: https://www.econbiz.de/10011092776