The last seminar in the MT 2017 Statistics Seminar Series will be with Yundong Tu who is Assistant Professor at Guanghua School of Management, Peking University. You can find details of Yundong's talk below:
Title: Spurious Regressions in Functional-coefficient Models with Nonstationarity
Abstract: Functional coefficient cointegrating models have become popular to model nonlinear nonstationarity in econometrics (Cai, Li, Park, 2009; Xiao 2009). However, there is rare study on testing the existence of functional coefficient cointegration. Consequently, functional coefficient regressions involving nonstationary regressors may be spurious. This paper investigates the effect that spurious functional coefficient regression has on the usual diagnostics. We find that common characteristics of spurious regression are manifest, including divergent local significance tests, random local goodness-of-fit, and local Durbin-Watson ratio converging to zero, complementing those discovered in spurious linear and nonparametric regressions (Phillips1986, Phillips2009). In addition, spuriousness causes the divergence of the global significance tests proposed by Xiao (2009) and Sun, Cai and Li (2016), which is likely to produce misleading conclusions for practitioners. To resolve the problems, we propose a simple-to-implement inference procedure based on a semiparametric balanced regression, by augmenting regressors of the original spurious regression with lagged dependent variable and independent variables. This procedure achieves spurious regression detection via standard inferential asymptotics. Monte Carlo simulations show that the proposed tests enjoy nice finite sample performance.