Econometrics Journal最新文献_第2页

Forecasting using cross-section average–augmented time series regressions 利用截面平均增广时间序列回归进行预测

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-06-29 DOI: 10.1093/ectj/utaa031

Hande Karabıyık, J. Westerlund

{"title":"Forecasting using cross-section average–augmented time series regressions","authors":"Hande Karabıyık, J. Westerlund","doi":"10.1093/ectj/utaa031","DOIUrl":"https://doi.org/10.1093/ectj/utaa031","url":null,"abstract":"There is a large and growing literature concerned with forecasting time series variables using factor-augmented regression models. The workhorse of this literature is a two-step approach in which the factors are first estimated by applying the principal components method to a large panel of variables, and the forecast regression is estimated conditional on the first-step factor estimates. Another stream of research that has attracted much attention is concerned with the use of cross-section averages as common factor estimates in interactive effects panel regression models. The main justification for this second development is the simplicity and good performance of the cross-section averages when compared to estimated principal component factors. In view of this, it is quite surprising that no one has yet considered the use of cross-section averages for forecasting. Indeed, given the purpose to forecast the conditional mean, the use of the cross-sectional average to estimate the factors is only natural. The present paper can be seen as a reaction to this. The purpose is to investigate the asymptotic and small-sample properties of forecasts based on cross-section average-augmented regressions. In contrast to existing studies, the investigation is carried out while allowing the number of factors to be unknown. JEL Classification: C12; C13; C33.","PeriodicalId":50555,"journal":{"name":"Econometrics Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/ectj/utaa031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49181040","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: 6

Estimation of nonstationary nonparametric regression model with multiplicative structure 具有乘型结构的非平稳非参数回归模型的估计

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-06-12 DOI: 10.1093/ECTJ/UTAB018

Likai Chen, E. Smetanina, W. Wu

引用次数: 3

Nonparametric panel data regression with parametric cross-sectional dependence 具有参数横截面依赖性的非参数面板数据回归

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-05-08 DOI: 10.1093/ECTJ/UTAB016

A. Soberón, Juan M. Rodríguez-Póo, P. Robinson

引用次数: 0

Using a Satisficing Model of Experimenter Decision-Making to Guide Finite-Sample Inference for Compromised Experiments. 利用实验者决策的满意模型指导折衷实验的有限样本推理。

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-05-01 Epub Date: 2021-06-29 DOI: 10.1093/ectj/utab009

James J Heckman, Ganesh Karapakula

引用次数: 3

Factor-augmented forecasting regressions with threshold effects 具有阈值效应的因子增强预测回归

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-04-06 DOI: 10.1093/ECTJ/UTAB011

Yayi Yan, Tingting Cheng

引用次数: 2

Unifying inference for semiparametric regression 半参数回归的统一推理

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-03-11 DOI: 10.1093/ECTJ/UTAB005

Shaoxin Hong, Jiancheng Jiang, Xuejun Jiang, Zhijie Xiao

{"title":"Unifying inference for semiparametric regression","authors":"Shaoxin Hong, Jiancheng Jiang, Xuejun Jiang, Zhijie Xiao","doi":"10.1093/ECTJ/UTAB005","DOIUrl":"https://doi.org/10.1093/ECTJ/UTAB005","url":null,"abstract":"\u0000 In the literature, a discrepancy in the limiting distributions of least square estimators between the stationary and nonstationary cases exists in various regression models with different persistence level regressors. This hinders further statistical inference since one has to decide which distribution should be used next. In this paper, we develop a semiparametric partially linear regression model with stationary and nonstationary regressors to attenuate this difficulty, and propose a unifying inference procedure for the coefficients. To be specific, we propose a profile weighted estimation equation method that facilitates the unifying inference. The proposed method is applied to the predictive regressions of stock returns, and an empirical likelihood procedure is developed to test the predictability. It is shown that the Wilks theorem holds for the empirical likelihood ratio regardless of predictors being stationary or not, which provides a unifying method for constructing confidence regions of the coefficients of state variables. Simulations show that the proposed method works well and has favourable finite sample performance over some existing approaches. An empirical application examining the predictability of equity returns highlights the value of our methodology.","PeriodicalId":50555,"journal":{"name":"Econometrics Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2021-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47822127","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: 1

On unit free assessment of the extent of multilateral distributional variation 关于多边分布变化程度的单位自由评估

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2021-02-01 DOI: 10.1093/ECTJ/UTAB003

G. Anderson, O. Linton, M. G. Pittau, Yoon-Jae Whang, Roberto Zelli

{"title":"On unit free assessment of the extent of multilateral distributional variation","authors":"G. Anderson, O. Linton, M. G. Pittau, Yoon-Jae Whang, Roberto Zelli","doi":"10.1093/ECTJ/UTAB003","DOIUrl":"https://doi.org/10.1093/ECTJ/UTAB003","url":null,"abstract":"Multilateral comparison of outcomes drawn from multiple groups pervade the social sciences and measurement of their variability, usually involving functions of respective group location and scale parameters, is of intrinsic interest. However, such approaches frequently mask more fundamental differences that more comprehensive examination of relative group distributional structures reveal. Indeed, in categorical data contexts, location and scale based techniques are no longer feasible without artificial and questionable cardinalization of categories. Here, Ginis’ Transvariation measure is extended and employed in providing quantitative and visual multilateral comparison tools in discrete, continuous, categorical, univariate or multivariate settings which are particularly useful in paradigms where cardinal measure is absent. Two applications, one analyzing Eurozone cohesion in terms of the convergence or divergence of constituent nations income distributions, the other, drawn from a study of aging, health and income inequality in China, exemplify their use in a continuous and categorical data environment. Department of Economics, University of Toronto. Faculty of Economics, University of Cambridge. Department of Statistical Sciences, Sapienza University of Rome. Department of Economics, Seoul National University. 1","PeriodicalId":50555,"journal":{"name":"Econometrics Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42548360","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: 3

Identification without assuming mean stationarity: quasi–maximum likelihood estimation of dynamic panel models with endogenous regressors 不假设平均平稳性的识别:具有内生回归因子的动态面板模型的准极大似然估计

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2020-12-10 DOI: 10.1093/ectj/utaa036

H. Kruiniger

引用次数: 2

Panel kink threshold regression model with a covariate-dependent threshold 具有协变量相关阈值的面板扭结阈值回归模型

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2020-12-08 DOI: 10.1093/ectj/utaa035

Lixiong Yang, Chunli Zhang, Chingnun Lee, I‐Po Chen

引用次数: 6

Model averaging estimation for high-dimensional covariance matrices with a network structure. 具有网络结构的高维协方差矩阵的模型平均估计。

IF 1.9 4区经济学

Econometrics Journal Pub Date : 2020-09-29 eCollection Date: 2021-01-01 DOI: 10.1093/ectj/utaa030

Rong Zhu, Xinyu Zhang, Yanyuan Ma, Guohua Zou

引用次数: 3