Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5053173 | Economic Modelling | 2017 | 7 Pages |
Abstract
This paper proposes a semiparametric partially linear varying coefficient spatial autoregressive model, which is a generalization of standard spatial autoregressive model and partially linear spatial autoregressive model. To estimate the unknown spatial lag parameter, constant coefficients and coefficient functions, a profile quasi-maximum likelihood approach based on the local-linear method is introduced. To test the existence of the spatial effects, a generalized likelihood ratio test statistic is proposed, and a residual-based bootstrap procedure is used to derive the p-value of the test. Some simulations are conducted to examine the performance of our proposed procedures and the results are satisfactory. Furthermore, a real-world example is given to demonstrate the application of the proposed procedures.
Keywords
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Social Sciences and Humanities
Economics, Econometrics and Finance
Economics and Econometrics
Authors
Chuanhua Wei, Shuang Guo, Shufen Zhai,