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We propose an econometric environment for structural break detection innonstationary quantile predictive regressions. We establish the limitdistributions for a class of Wald and fluctuation type statistics based on boththe ordinary least squares estimator and the endogenous instrumental regressionestimator proposed by Phillips and Magdalinos (2009a, Econometric Inference inthe Vicinity of Unity. Working paper, Singapore Management University).Although the asymptotic distribution of these test statistics appears to dependon the chosen estimator, the IVX based tests are shown to be asymptoticallynuisance parameter-free regardless of the degree of persistence and consistentunder local alternatives. The finite-sample performance of both tests isevaluated via simulation experiments. An empirical application to house pricingindex returns demonstrates the practicality of the proposed break tests forregression quantiles of nonstationary time series data.

Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates