Estimation in single-index varying-coefficient panel data model

Tonghui Wang, Liming Wang*, Xian Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we study the single-index varying-coefficient panel data model. Combining the refined minimum average variance estimation (RMAVE) method with the local linear regression, we estimate the parameters in single index and link function, and explain the steps of the iterative algorithm. Under certain regularity conditions, the asymptotic properties of the estimators of the parameters and link functions are derived. Finally, numerical simulations are presented and our model is shown to perform better than the single-index panel data model in a real-data example.

Original languageEnglish
Number of pages22
JournalCommunications in Statistics - Theory and Methods
DOIs
Publication statusE-pub ahead of print - 28 Jul 2020

Keywords

  • local linear regression
  • minimum average variance estimation
  • panel data
  • Single-index varying-coefficient model

Fingerprint Dive into the research topics of 'Estimation in single-index varying-coefficient panel data model'. Together they form a unique fingerprint.

Cite this