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Short-term forecasts of French GDP: A dynamic factor model with targeted predictors

Bessec, Marie - Université Paris-Dauphine (Paris IX) - 2013

In recent years, factor models have received increasing attention from both econometricians and practitioners in the forecasting of macroeconomic variables. In this context, Bai and Ng (2008) find an improvement in selecting indicators according to the forecast variable prior to factor...

Persistent link: https://www.econbiz.de/10010706538

Sparse Estimators and the Oracle Property, or the Return of Hodges' Estimator

Leeb, Hannes; Poetscher, Benedikt M. - Cowles Foundation for Research in Economics, Yale University - 2005

We point out some pitfalls related to the concept of an oracle property as used in Fan and Li (2001, 2002, 2004) which are reminiscent of the well-known pitfalls related to Hodges’ estimator. The oracle property is often a consequence of sparsity of an estimator. We show that any estimator...

Persistent link: https://www.econbiz.de/10005593633

Nowcasting Turkish GDP growth with targeted predictors : fill in the blanks

Günay, Mahmut - 2020

Persistent link: https://www.econbiz.de/10012939791

Model selection in linear mixed effect models

Peng, Heng; Lu, Ying - In: Journal of Multivariate Analysis 109 (2012) C, pp. 109-129

Mixed effect models are fundamental tools for the analysis of longitudinal data, panel data and cross-sectional data. They are widely used by various fields of social sciences, medical and biological sciences. However, the complex nature of these models has made variable selection and parameter...

Persistent link: https://www.econbiz.de/10010572296

SCAD penalized rank regression with a diverging number of parameters

Yang, Hu; Guo, Chaohui; Lv, Jing - In: Journal of Multivariate Analysis 133 (2015) C, pp. 321-333

In this paper, we study the robust variable selection and estimation based on rank regression and SCAD penalty function in linear regression models when the number of parameters diverges with the sample size increasing. The proposed method is resistant to heavy-tailed errors or outliers in the...

Persistent link: https://www.econbiz.de/10011116251

Financial Services to the Unbanked: the case of the Mzansi intervention in South Africa

Kostov, Philip; Arun, Thankom; Annim, Samuel - In: Contemporary Economics 8 (2014) 2, pp. 191-206

The Mzansi intervention is a major initiative designed to provide banking services to the unbanked South African population. This study investigates the underlying variables that define the choice of a Mzansi account from a consumer perspective. Unlike previous studies, we do not assume that...

Persistent link: https://www.econbiz.de/10010436058

Financial services to the unbanked : the case of the Mzansi intervention in South Africa

Kostov, Philip; Arun, Thankom; Annim, Samuel Kobina - In: Contemporary economics 8 (2014) 2, pp. 191-206

Persistent link: https://www.econbiz.de/10010407295

Binary quantile regression and variable selection : a new approach

Aristodemou, Katerina; He, Jian; Yu, Keming - In: Econometric reviews 38 (2019) 6, pp. 679-694

Persistent link: https://www.econbiz.de/10012181345

Variable selection in high-dimensional partially linear additive models for composite quantile regression

Guo, Jie; Tang, Manlai; Tian, Maozai; Zhu, Kai - In: Computational Statistics & Data Analysis 65 (2013) C, pp. 56-67

to the sample size, a variable selection procedure based on adaptive Lasso is proposed to conduct estimation and variable … selection simultaneously. The procedure is shown to possess the oracle property, and is much superior to the adaptive Lasso … penalty are considered, namely the composite quantile regression estimates and Lasso penalized composite quantile regression …

Persistent link: https://www.econbiz.de/10010871336

Variable selection in the additive rate model for recurrent event data

Chen, Xiaolin; Wang, Qihua - In: Computational Statistics & Data Analysis 57 (2013) 1, pp. 491-503

In this paper, we investigate the variable selection problem for recurrent event data under the additive rate model. According to the explicit estimator of the regression coefficients of the additive rate model, a loss function is constructed. It has a form similar to the ordinary least squares...

Persistent link: https://www.econbiz.de/10010871439