Econometrics and Statistics最新文献_第2页

Panel cointegrating polynomial regression analysis and an illustration with the environmental kuznets curve

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Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.03.005

Robert M. de Jong , Martin Wagner

引用次数: 0

Erratum regarding missing Declaration of Competing Interest statements in previously published articles

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.02.001

引用次数: 0

New estimation approaches for graphical models with elastic net penalty 具有弹性网惩罚的图形模型的新估计方法

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.06.003

Davide Bernardini, Sandra Paterlini, Emanuele Taufer

{"title":"New estimation approaches for graphical models with elastic net penalty","authors":"Davide Bernardini, Sandra Paterlini, Emanuele Taufer","doi":"10.1016/j.ecosta.2022.06.003","DOIUrl":"10.1016/j.ecosta.2022.06.003","url":null,"abstract":"<div><div>In the context of undirected Gaussian graphical models, three estimators based on elastic net penalty for the underlying dependence graph are introduced. The aim is to estimate a sparse precision matrix, from which to retrieve both the underlying conditional dependence graph and the partial correlations. The first estimator is derived from the direct penalization of the precision matrix in the likelihood function, while the second uses penalized regressions to estimate the precision matrix. Finally, the third estimator relies on a two stage procedure that estimates the edge set first and then the precision matrix elements. Through simulations the performances of the proposed methods are investigated on a set of well-known network structures. Results on simulated data show that in high-dimensional situations the second estimator performs relatively well, while in low-dimensional settings the two stage procedure outperforms most estimators as the sample size grows. Nonetheless, there are situations where the first estimator is also a good choice. Mixed results suggest that the elastic net penalty is not always the best choice when compared to the LASSO penalty, i.e. pure <span><math><msub><mi>ℓ</mi><mn>1</mn></msub></math></span><span> penalty, even if elastic net penalty tends to outperform LASSO in presence of highly correlated data from the cluster structure. Finally, using real-world data on U.S. economic sectors, dependencies are estimated and the impact of Covid-19 pandemic on the network strength is studied.</span></div></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"33 ","pages":"Pages 258-281"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88726912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing the Predictive Ability of Possibly Persistent Variables under Asymmetric Loss 非对称损失下可能持续变量的预测能力检验

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.09.004

Matei Demetrescu , Christoph Roling

{"title":"Testing the Predictive Ability of Possibly Persistent Variables under Asymmetric Loss","authors":"Matei Demetrescu , Christoph Roling","doi":"10.1016/j.ecosta.2021.09.004","DOIUrl":"10.1016/j.ecosta.2021.09.004","url":null,"abstract":"<div><div>Tests of no predictability under an asymmetric power loss function are considered. While this task does not pose difficulties for stationary predictors, non-standard limiting distributions may arise for standard inferential tools when the putative predictors are endogenous (i.e. there is contemporaneous dependence between the shocks of the regressor and of the dependent variable) and of high persistence (i.e. the predictor is reverting slowly to its long-run mean, if at all). It is argued that endogeneity should be interpreted in relation to the relevant loss-function; thus, no endogeneity under MSE loss does not imply, and is not implied by, lack of endogeneity under an asymmetric loss function. To deal with other loss functions than the MSE loss, an overidentified instrumental variable-based test is proposed. The test statistic uses an instrument of high persistence, yet exogenous, and a possibly endogenous one, yet less persistent. The statistic follows a limiting null chi-squared distribution irrespective of the actual degree of persistence of the predictor. The proposed methodology is applied with the forward premium puzzle by providing evidence that asymmetric losses are of empirical relevance and by subsequently conducting robust inference of the rational expectations hypothesis.</div></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"33 ","pages":"Pages 80-104"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88979690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quasi Maximum Likelihood Estimation of Value at Risk and Expected Shortfall

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Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.08.003

Leopoldo Catania , Alessandra Luati

引用次数: 0

Directional Tests and Confidence Bounds on Economic Inequality 经济不平等的方向检验和置信限

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Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.02.003

Jean-Marie Dufour , Emmanuel Flachaire , Lynda Khalaf , Abdallah Zalghout

引用次数: 0

Threshold Autoregressive Nearest-Neighbour Models for Claims Reserving 索赔保留的阈值自回归近邻模型

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.03.006

Tak Kuen Siu

引用次数: 0

ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control ICS用于多变量功能异常检测，并应用于预测性维护和质量控制

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.03.003

Aurore Archimbaud , Feriel Boulfani , Xavier Gendre , Klaus Nordhausen , Anne Ruiz-Gazen , Joni Virta

{"title":"ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control","authors":"Aurore Archimbaud , Feriel Boulfani , Xavier Gendre , Klaus Nordhausen , Anne Ruiz-Gazen , Joni Virta","doi":"10.1016/j.ecosta.2022.03.003","DOIUrl":"10.1016/j.ecosta.2022.03.003","url":null,"abstract":"<div><div><span>Multivariate functional anomaly detection has received a large amount of attention recently. Accounting both the time dimension and the correlations between variables is challenging due to the existence of different types of outliers and the dimension of the data. In the context of </span>predictive maintenance<span> and quality control<span>, data sets often contain a large number of functional variables. However, most of the existing methods focus on a small number of functional variables. Moreover, in fields that have high reliability standards, detecting a small number of potential multivariate functional outliers with as few false positives as possible is crucial. In such a context, the adaptation of the Invariant Coordinate Selection (ICS) method from the multivariate to the multivariate functional case is of particular interest. Two extensions of ICS are proposed: point-wise and global. For both methods, the choice of the relevant components together with outlier identification and interpretation are discussed. A comparison is made on a predictive maintenance example from the avionics field and a quality control example from the microelectronics field. It appears that in such a context, point-wise and global ICS with a small number of selected components can be recommended.</span></span></div></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"33 ","pages":"Pages 282-303"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82405360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The dynamics of U.S. industrial production: A time-varying Granger causality perspective 美国工业生产的动态:一个时变格兰杰因果关系的观点

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Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.10.012

Christopher F. Baum , Stan Hurn , Jesús Otero

引用次数: 0

Erratum regarding missing Declaration of Competing Interest statements in previously published articles

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.02.004

引用次数: 0