HIGH-DIMENSIONAL NEWEY–POWELL TEST VIA APPROXIMATE MESSAGE PASSING

We propose a high-dimensional extension of the heteroscedasticity test proposed in Newey and Powell (1987). Our test is based on expectile regression in the proportional asymptotic regime where $n/p \to \delta \in (0,1]$ . The asymptotic analysis of the test statistic uses the approximate message passing algorithm, from which we obtain the limiting distribution of the test and establish its asymptotic power. The numerical performance of the test is validated through an extensive simulation study. As real-data applications, we present the analysis based on “international economic growth” data (Belloni et al., 2013), which is found to be homoscedastic, and “supermarket” data (Lan et al., 2016), which is found to be heteroscedastic.