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Title: Consistent specification testing under network dependence Authors:  Abhimanyu Gupta - University of Essex (United Kingdom) [presenting]
Xi Qu - Shanghai Jiaotong University (China)
Abstract: A series-based nonparametric specification test is proposed for a regression function when data are dependent across a network. Our framework permits network dependence to be parametric, parametric with increasing dimension, semiparametric or any combination thereof, thus covering a vast variety of settings. These include spatial error models of varying types and levels of complexity. Despite being applicable so generally, our test statistic is easy to compute and asymptotically standard normal. To prove the latter property, we present a central limit theorem for quadratic forms in linear processes in an increasing dimension setting that may be of independent interest. We also show how our test can be applied to parametric regression models that become more complex as more data becomes available. Finite sample performance is studied in a simulation study and empirical examples with real data are also included.