Econometrics Journal最新文献_第8页

Sparse estimation of huge networks with a block-wise structure 具有块结构的大型网络的稀疏估计

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-11-24 DOI: 10.1111/ectj.12078

Francesco Moscone, Elisa Tosetti, Veronica Vinciotti

{"title":"Sparse estimation of huge networks with a block-wise structure","authors":"Francesco Moscone, Elisa Tosetti, Veronica Vinciotti","doi":"10.1111/ectj.12078","DOIUrl":"10.1111/ectj.12078","url":null,"abstract":"<p>Networks with a very large number of nodes appear in many application areas and pose challenges for traditional Gaussian graphical modelling approaches. In this paper, we focus on the estimation of a Gaussian graphical model when the dependence between variables has a block-wise structure. We propose a penalized likelihood estimation of the inverse covariance matrix, also called Graphical LASSO, applied to block averages of observations, and we derive its asymptotic properties. Monte Carlo experiments, comparing the properties of our estimator with those of the conventional Graphical LASSO, show that the proposed approach works well in the presence of block-wise dependence structure and that it is also robust to possible model misspecification. We conclude the paper with an empirical study on economic growth and convergence of 1,088 European small regions in the years 1980 to 2012. While requiring <i>a priori</i> information on the block structure – e.g. given by the hierarchical structure of data – our approach can be adopted for estimation and prediction using very large panel data sets. Also, it is particularly useful when there is a problem of missing values and outliers or when the focus of the analysis is on out-of-sample prediction.</p>","PeriodicalId":50555,"journal":{"name":"Econometrics Journal","volume":"20 3","pages":"S61-S85"},"PeriodicalIF":1.9,"publicationDate":"2016-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/ectj.12078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129917493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Second-order refinement of empirical likelihood ratio tests of nonlinear restrictions 非线性约束的经验似然比检验的二阶改进

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-11-24 DOI: 10.1111/ectj.12079

Jun Ma

引用次数: 3

Index to The Econometrics Journal Volume 19 计量经济学期刊第19卷索引

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-11-09 DOI: 10.1111/ectj.12076

引用次数: 0

Royal Economic Society Annual Conference 2013Special Issue on Econometrics of Heterogeneity 2013年英国皇家经济学会年会:异质性计量经济学专刊

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-11-09 DOI: 10.1111/ectj.12074

Richard J. Smith

引用次数: 0

Consistent tests for conditional treatment effects 条件治疗效果的一致性测试

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-11-01 DOI: 10.1111/ectj.12077

Yu-Chin Hsu

引用次数: 33

Change point tests in functional factor models with application to yield curves 功能因子模型的变点检验及其在产量曲线上的应用

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-10-10 DOI: 10.1111/ectj.12075

Patrick Bardsley, Lajos Horváth, Piotr Kokoszka, Gabriel Young

引用次数: 14

Peer effects in bedtime decisions among adolescents: a social network model with sampled data 青少年就寝决定中的同伴效应:一个抽样数据的社会网络模型

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-09-19 DOI: 10.1111/ectj.12072

Xiaodong Liu, Eleonora Patacchini, Edoardo Rainone

引用次数: 25

A Review of Economic Forecasting 经济预测综述

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-09-19 DOI: 10.1111/ectj.12073

Barbara Rossi

引用次数: 1

On ill-posedness of nonparametric instrumental variable regression with convexity constraints 凸性约束下非参数工具变量回归的病态性

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-09-05 DOI: 10.1111/ectj.12071

Olivier Scaillet

引用次数: 2

Lagrange multiplier type tests for slope homogeneity in panel data models 面板数据模型中斜率均匀性的拉格朗日乘数型检验

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2016-07-22 DOI: 10.1111/ectj.12070

Jörg Breitung, Christoph Roling, Nazarii Salish

{"title":"Lagrange multiplier type tests for slope homogeneity in panel data models","authors":"Jörg Breitung, Christoph Roling, Nazarii Salish","doi":"10.1111/ectj.12070","DOIUrl":"10.1111/ectj.12070","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we employ the Lagrange multiplier (LM) principle to test parameter homogeneity across cross-section units in panel data models. The test can be seen as a generalization of the Breusch–Pagan test against random individual effects to all regression coefficients. While the original test procedure assumes a likelihood framework under normality, several useful variants of the LM test are presented to allow for non-normality, heteroscedasticity and serially correlated errors. Moreover, the tests can be conveniently computed via simple artificial regressions. We derive the limiting distribution of the LM test and show that if the errors are not normally distributed, the original LM test is asymptotically valid if the number of time periods tends to infinity. A simple modification of the score statistic yields an LM test that is robust to non-normality if the number of time periods is fixed. Further adjustments provide versions of the LM test that are robust to heteroscedasticity and serial correlation. We compare the local power of our tests and the statistic proposed by Pesaran and Yamagata. The results of the Monte Carlo experiments suggest that the LM-type test can be substantially more powerful, in particular, when the number of time periods is small.</p></div>","PeriodicalId":50555,"journal":{"name":"Econometrics Journal","volume":"19 2","pages":"166-202"},"PeriodicalIF":1.9,"publicationDate":"2016-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/ectj.12070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130828435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15