异质性的非参数时变面板数据模型

IF 1 4区经济学 Q3 ECONOMICS

Econometric Theory Pub Date : 2023-10-23 DOI:10.1017/s0266466623000324

Fei Liu

{"title":"异质性的非参数时变面板数据模型","authors":"Fei Liu","doi":"10.1017/s0266466623000324","DOIUrl":null,"url":null,"abstract":"Abstract Since Bai (2009, Econometrica 77, 1229–1279), considerable extensions have been made to panel data models with interactive fixed effects (IFEs). However, little work has been conducted to understand the associated iterative algorithm, which, to the best of our knowledge, is the most commonly adopted approach in this line of research. In this paper, we refine the algorithm of panel data models with IFEs using the nuclear-norm penalization method and duple least-squares (DLS) iterations. Meanwhile, we allow the regression coefficients to be individual-specific and evolve over time. Accordingly, asymptotic properties are established to demonstrate the theoretical validity of the proposed approach. Furthermore, we show that the proposed methodology exhibits good finite-sample performance using simulation and real data examples.","PeriodicalId":49275,"journal":{"name":"Econometric Theory","volume":"2003 45","pages":"0"},"PeriodicalIF":1.0000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NONPARAMETRIC TIME-VARYING PANEL DATA MODELS WITH HETEROGENEITY\",\"authors\":\"Fei Liu\",\"doi\":\"10.1017/s0266466623000324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Since Bai (2009, Econometrica 77, 1229–1279), considerable extensions have been made to panel data models with interactive fixed effects (IFEs). However, little work has been conducted to understand the associated iterative algorithm, which, to the best of our knowledge, is the most commonly adopted approach in this line of research. In this paper, we refine the algorithm of panel data models with IFEs using the nuclear-norm penalization method and duple least-squares (DLS) iterations. Meanwhile, we allow the regression coefficients to be individual-specific and evolve over time. Accordingly, asymptotic properties are established to demonstrate the theoretical validity of the proposed approach. Furthermore, we show that the proposed methodology exhibits good finite-sample performance using simulation and real data examples.\",\"PeriodicalId\":49275,\"journal\":{\"name\":\"Econometric Theory\",\"volume\":\"2003 45\",\"pages\":\"0\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/s0266466623000324\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/s0266466623000324","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}

引用次数: 0

摘要

自Bai (2009, Econometrica 77, 1229-1279)以来，对具有交互固定效应的面板数据模型(IFEs)进行了大量扩展。然而，很少有人进行工作来理解相关的迭代算法，据我们所知，迭代算法是这方面研究中最常用的方法。本文采用核范数惩罚法和双最小二乘迭代法，对面板数据模型的算法进行了改进。同时，我们允许回归系数是个体特定的，并随着时间的推移而演变。通过建立渐近性质证明了该方法的理论有效性。此外，我们通过仿真和实际数据实例表明，所提出的方法具有良好的有限样本性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

NONPARAMETRIC TIME-VARYING PANEL DATA MODELS WITH HETEROGENEITY

Abstract Since Bai (2009, Econometrica 77, 1229–1279), considerable extensions have been made to panel data models with interactive fixed effects (IFEs). However, little work has been conducted to understand the associated iterative algorithm, which, to the best of our knowledge, is the most commonly adopted approach in this line of research. In this paper, we refine the algorithm of panel data models with IFEs using the nuclear-norm penalization method and duple least-squares (DLS) iterations. Meanwhile, we allow the regression coefficients to be individual-specific and evolve over time. Accordingly, asymptotic properties are established to demonstrate the theoretical validity of the proposed approach. Furthermore, we show that the proposed methodology exhibits good finite-sample performance using simulation and real data examples.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Econometric Theory MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY

CiteScore

1.90

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Since its inception, Econometric Theory has aimed to endow econometrics with an innovative journal dedicated to advance theoretical research in econometrics. It provides a centralized professional outlet for original theoretical contributions in all of the major areas of econometrics, and all fields of research in econometric theory fall within the scope of ET. In addition, ET fosters the multidisciplinary features of econometrics that extend beyond economics. Particularly welcome are articles that promote original econometric research in relation to mathematical finance, stochastic processes, statistics, and probability theory, as well as computationally intensive areas of economics such as modern industrial organization and dynamic macroeconomics.