Journal of Business & Economic Statistics最新文献_第6页

Homogeneity and Sparsity Analysis for High Dimensional Panel Data Models 高维面板数据模型的同质性和稀疏性分析

Journal of Business & Economic Statistics Pub Date : 2022-10-26 DOI: 10.1080/07350015.2022.2140667

Wu Wang, Zhongyi Zhu

引用次数: 1

Large Spillover Networks of Nonstationary Systems 非平稳系统的大溢出网络

Journal of Business & Economic Statistics Pub Date : 2022-07-11 DOI: 10.1080/07350015.2022.2099870

ShiuNan Chen, M. Schienle

{"title":"Large Spillover Networks of Nonstationary Systems","authors":"ShiuNan Chen, M. Schienle","doi":"10.1080/07350015.2022.2099870","DOIUrl":"https://doi.org/10.1080/07350015.2022.2099870","url":null,"abstract":"This paper proposes a vector error correction framework for constructing large consistent spillover networks of nonstationary systems grounded in the network theory of Diebold and Yılmaz (2014). We aim to provide a tailored methodology for the large non-stationary (macro)economic and financial system application settings avoiding technical and often hard to verify assumptions for general statistical highdimensional approaches where the dimension can also increase with sample size. To achieve this, we propose an elementwise Lasso-type technique for consistent and numerically efficient model selection of VECM, and relate the resulting forecast error variance decomposition to the network topology representation. We also derive the corresponding asymptotic results for model selection and network estimation under standard assumptions. Moreover, we develop a refinement strategy for efficient estimation and show implications and modifications for general dependent innovations. In a comprehensive simulation study, we show convincing finite sample performance of our technique in all cases of moderate and low dimensions. In an application to a system of FX rates, the proposed method leads to novel insights on the connectedness and spillover effects in the FX market among the OECD countries. JEL classification: C3, C5, F3","PeriodicalId":118766,"journal":{"name":"Journal of Business & Economic Statistics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124512442","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: 3

Consistent Estimation of Multiple Breakpoints in Dependence Measures* 依赖测度中多断点的一致性估计*

Journal of Business & Economic Statistics Pub Date : 2022-06-09 DOI: 10.1080/07350015.2023.2224850

Marvin Borsch, Alexander Mayer, Dominik Wied

引用次数: 0

Covariance Model with General Linear Structure and Divergent Parameters 具有一般线性结构和发散参数的协方差模型

Journal of Business & Economic Statistics Pub Date : 2022-05-15 DOI: 10.1080/07350015.2022.2142593

Xinyan Fan, Wei Lan, Tao Zou, Chih-Ling Tsai

{"title":"Covariance Model with General Linear Structure and Divergent Parameters","authors":"Xinyan Fan, Wei Lan, Tao Zou, Chih-Ling Tsai","doi":"10.1080/07350015.2022.2142593","DOIUrl":"https://doi.org/10.1080/07350015.2022.2142593","url":null,"abstract":"For estimating the large covariance matrix with a limited sample size, we propose the covariance model with general linear structure (CMGL) by employing the general link function to connect the covariance of the continuous response vector to a linear combination of weight matrices. Without assuming the distribution of responses, and allowing the number of parameters associated with weight matrices to diverge, we obtain the quasi-maximum likelihood estimators (QMLE) of parameters and show their asymptotic properties. In addition, an extended Bayesian information criteria (EBIC) is proposed to select relevant weight matrices, and the consistency of EBIC is demonstrated. Under the identity link function, we introduce the ordinary least squares estimator (OLS) that has the closed form. Hence, its computational burden is reduced compared to QMLE, and the theoretical properties of OLS are also investigated. To assess the adequacy of the link function, we further propose the quasi-likelihood ratio test and obtain its limiting distribution. Simulation studies are presented to assess the performance of the proposed methods, and the usefulness of generalized covariance models is illustrated by an analysis of the US stock market.","PeriodicalId":118766,"journal":{"name":"Journal of Business & Economic Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133613490","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

A General Framework for Constructing Locally Self-Normalized Multiple-Change-Point Tests 构造局部自归一化多变点测试的一般框架

Journal of Business & Economic Statistics Pub Date : 2022-04-30 DOI: 10.1080/07350015.2023.2231041

Cheuk Hin Cheng, Kin Wai Chan

引用次数: 1

High-dimensional Censored Regression via the Penalized Tobit Likelihood 基于惩罚Tobit似然的高维截尾回归

Journal of Business & Economic Statistics Pub Date : 2022-03-04 DOI: 10.1080/07350015.2023.2182309

Tate Jacobson, H. Zou

{"title":"High-dimensional Censored Regression via the Penalized Tobit Likelihood","authors":"Tate Jacobson, H. Zou","doi":"10.1080/07350015.2023.2182309","DOIUrl":"https://doi.org/10.1080/07350015.2023.2182309","url":null,"abstract":"High-dimensional regression and regression with a left-censored response are each well-studied topics. In spite of this, few methods have been proposed which deal with both of these complications simultaneously. The Tobit model -- long the standard method for censored regression in economics -- has not been adapted for high-dimensional regression at all. To fill this gap and bring up-to-date techniques from high-dimensional statistics to the field of high-dimensional left-censored regression, we propose several penalized Tobit models. We develop a fast algorithm which combines quadratic minimization with coordinate descent to compute the penalized Tobit solution path. Theoretically, we analyze the Tobit lasso and Tobit with a folded concave penalty, bounding the $ell_2$ estimation loss for the former and proving that a local linear approximation estimator for the latter possesses the strong oracle property. Through an extensive simulation study, we find that our penalized Tobit models provide more accurate predictions and parameter estimates than other methods. We use a penalized Tobit model to analyze high-dimensional left-censored HIV viral load data from the AIDS Clinical Trials Group and identify potential drug resistance mutations in the HIV genome. Appendices contain intermediate theoretical results and technical proofs.","PeriodicalId":118766,"journal":{"name":"Journal of Business & Economic Statistics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114574390","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: 1

Instrumental variable estimation of dynamic treatment effects on a duration outcome 动态治疗对持续结果影响的工具变量估计

Journal of Business & Economic Statistics Pub Date : 2022-01-26 DOI: 10.1080/07350015.2023.2231053

Jad Beyhum, S. Centorrino, J. Florens, I. Van Keilegom

引用次数: 1

Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach 具有溢出效应的连续处理模型的估计:一种控制函数方法

Journal of Business & Economic Statistics Pub Date : 2021-12-30 DOI: 10.1080/07350015.2023.2207617

Tadao Hoshino

引用次数: 0

Matrix Factor Analysis: From Least Squares to Iterative Projection* 矩阵因子分析:从最小二乘到迭代投影*

Journal of Business & Economic Statistics Pub Date : 2021-12-08 DOI: 10.1080/07350015.2023.2191676

Yong He, Xin-Bing Kong, Long Yu, Xinsheng Zhang, Changwei Zhao

{"title":"Matrix Factor Analysis: From Least Squares to Iterative Projection*","authors":"Yong He, Xin-Bing Kong, Long Yu, Xinsheng Zhang, Changwei Zhao","doi":"10.1080/07350015.2023.2191676","DOIUrl":"https://doi.org/10.1080/07350015.2023.2191676","url":null,"abstract":"In this article, we study large-dimensional matrix factor models and estimate the factor loading matrices and factor score matrix by minimizing square loss function. Interestingly, the resultant estimators coincide with the Projected Estimators (PE) in Yu et al.(2022), which was proposed from the perspective of simultaneous reduction of the dimensionality and the magnitudes of the idiosyncratic error matrix. In other word, we provide a least-square interpretation of the PE for matrix factor model, which parallels to the least-square interpretation of the PCA for the vector factor model. We derive the convergence rates of the theoretical minimizers under sub-Gaussian tails. Considering the robustness to the heavy tails of the idiosyncratic errors, we extend the least squares to minimizing the Huber loss function, which leads to a weighted iterative projection approach to compute and learn the parameters. We also derive the convergence rates of the theoretical minimizers of the Huber loss function under bounded $(2+epsilon)$th moment of the idiosyncratic errors. We conduct extensive numerical studies to investigate the empirical performance of the proposed Huber estimators relative to the state-of-the-art ones. The Huber estimators perform robustly and much better than existing ones when the data are heavy-tailed, and as a result can be used as a safe replacement in practice. An application to a Fama-French financial portfolio dataset demonstrates the empirical advantage of the Huber estimator.","PeriodicalId":118766,"journal":{"name":"Journal of Business & Economic Statistics","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132015175","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: 10

Model-assisted complier average treatment effect estimates in randomized experiments with non-compliance 非依从性随机实验中模型辅助编译器平均治疗效果估计

Journal of Business & Economic Statistics Pub Date : 2021-11-19 DOI: 10.1080/07350015.2023.2224851

Jiyang Ren

{"title":"Model-assisted complier average treatment effect estimates in randomized experiments with non-compliance","authors":"Jiyang Ren","doi":"10.1080/07350015.2023.2224851","DOIUrl":"https://doi.org/10.1080/07350015.2023.2224851","url":null,"abstract":"In randomized experiments, the actual treatments received by some experimental units may differ from their treatment assignments. This non-compliance issue often occurs in clinical trials, social experiments, and the applications of randomized experiments in many other fields. Under certain assumptions, the average treatment effect for the compliers is identifiable and equal to the ratio of the intention-to-treat effects of the potential outcomes to that of the potential treatment received. To improve the estimation efficiency, we propose three model-assisted estimators for the complier average treatment effect in randomized experiments with a binary outcome. We study their asymptotic properties, compare their efficiencies with that of the Wald estimator, and propose the Neyman-type conservative variance estimators to facilitate valid inferences. Moreover, we extend our methods and theory to estimate the multiplicative complier average treatment effect. Our analysis is randomization-based, allowing the working models to be misspecified. Finally, we conduct simulation studies to illustrate the advantages of the model-assisted methods and apply these analysis methods in a randomized experiment to evaluate the effect of academic services or incentives on academic performance.","PeriodicalId":118766,"journal":{"name":"Journal of Business & Economic Statistics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124596938","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: 2

Journal of Business &amp; Economic Statistics最新文献

Journal of Business & Economic Statistics最新文献