Name
Title | ||
|---|---|---|
Empirical likelihood of varying coefficient errors-in-variables models with longitudinal data. |
Abstract | ||
|---|---|---|
In this paper, we investigate the empirical likelihood inferences of varying coefficient errors-in-variables models with longitudinal data. The naive empirical log-likelihood ratios for the time-varying coefficient function based on the global and local variance structures are introduced. The corresponding maximum empirical likelihood estimators of the time-varying coefficients are derived, and their asymptotic properties are established. Wilks’ phenomenon of the naive empirical log-likelihood ratio, which ignores the within subject correlation, is proven through the employment of undersmoothing. To avoid the undersmoothing, we recommend a residual-adjust empirical log-likelihood ratio and prove that its asymptotic distribution is standard chi-squared. Thus, this result can be used to construct the confidence regions of the time-varying coefficients. We also establish the asymptotic distribution theory for the corresponding residual-adjust maximum empirical likelihood estimator and find it to be unbiased even when an optimal bandwidth is used. Furthermore, we consider the construction of the pointwise confidence interval for a component of the time-varying coefficients and provide the simulation studies to assess the finite sample performance, while we conduct a real example to illustrate the proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.jmva.2014.02.004 | Journal of Multivariate Analysis |
Keywords | Field | DocType |
primary,secondary | Econometrics,Errors-in-variables models,Empirical likelihood,Estimation theory,Confidence interval,Statistics,Restricted maximum likelihood,Mathematics,Estimator,Asymptotic distribution,Pointwise | Journal |
Volume | Issue | ISSN |
127 | null | 0047-259X |
Citations | PageRank | References |
2 | 0.55 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yiping Yang | 1 | 44 | 9.84 |
| Gaorong Li | 2 | 64 | 14.58 |
| Heng Peng | 3 | 32 | 6.09 |