Estimasi Persamaan Sistem Non Linear Seemingly Unrelated Regression pada Model Perdagangan Internasional
نویسندگان
چکیده
منابع مشابه
Bayesian Geoadditive Seemingly Unrelated Regression
Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may result in inefficient estimates of covariate effects. A weakness of parametric models is that they require strong assumptions on the functional form of possibly nonlinear effects of metrical covaria...
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Seemingly unrelated regression (SUR) models are useful in studying the interactions among different variables. In a high dimensional setting or when applied to large panel of time series, these models require a large number of parameters to be estimated and suffer of inferential problems. To avoid overparametrization and overfitting issues, we propose a hierarchical Dirichlet process prior for ...
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We propose an efficient semiparametric estimator for the coefficients of a multivariate linear regression model — with a conditional quantile restriction for each equation — in which the conditional distributions of errors given regressors are unknown. The procedure can be used to estimate multiple conditional quantiles of the same regression relationship. The proposed estimator is asymptotical...
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Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may result in inefficient estimates of covariate effects. A weakness of parametric models is that they require strong assumptions on the functional form of possibly nonlinear effects of metrical covaria...
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ژورنال
عنوان ژورنال: Jurnal Ekonomi dan Pembangunan Indonesia
سال: 2004
ISSN: 2406-9280,1411-5212
DOI: 10.21002/jepi.v4i2.91