 Estimation and inference of semi-varying coefficient models with heteroscedastic errorsSi-Lian Shen, Jian-Ling Cui, Chang-Lin Mei and Chun-Wei Wang Journal of Multivariate Analysis, 2014, vol. 124, issue C, 70-93 Abstract: This article focuses on the estimation of the parametric component, which is of primary interest, in semi-varying coefficient models with heteroscedastic errors. Specifically, we first present a procedure for estimating the variance function of the error term and the resulting estimator is proved to be consistent. Then, by applying the local linear smoothing technique, and taking the estimated error heteroscedasticity into account, we suggest a re-weighting estimation of the constant coefficients and the resulting estimators are shown to have smaller asymptotic variances than the profile least-squares estimators that neglect the error heteroscedasticity while remaining the same biases. Some simulation experiments are conducted to evaluate the finite sample performance of the proposed methodologies. Finally, a real-world data set is analyzed to demonstrate the application of the methods. Keywords: Semi-varying coefficient model; Heteroscedasticity; Local linear smoothing; Re-weighting estimation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:124:y:2014:i:c:p:70-93 Ordering information: This journal article can be ordered from DOI: 10.1016/j.jmva.2013.10.010 Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
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