This article develops a novel stochastic tree ensemble method for nonlinear regression, referred to as accelerated Bayesian additive regression trees, or XBART. By combining regularization and search strategies from modeling with computationally efficient techniques recursive partitioning algorithms, XBART attains state-of-the-art performance at prediction function estimation. Simulation studie...

This paper develops an asymptotic theory for nonlinear cointegrating power function regression. The framework extends earlier work on the deterministic trend case and allows both endogeneity heteroskedasticity, which makes models inferential methods relevant to many empirical economic financial applications, including predictive A new test linear cointegration against departures is developed ba...