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- Title
Local Polynomial Estimation of Heteroscedasticity in a Multivariate Linear Regression Model and Its Applications in Economics.
- Authors
Liyun Su; Yanyong Zhao; Tianshun Yan; Fenglan Li; Ravasi, Timothy
- Abstract
Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.
- Subjects
POLYNOMIALS; HETEROSCEDASTICITY; REGRESSION analysis; LEAST squares; ESTIMATION theory; ANALYSIS of variance
- Publication
PLoS ONE, 2012, Vol 7, Issue 9, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0043719