Haiqi Li

Testing for a unit root in a nonlinear quantile autoregression framework

ABSTRACT The nonlinear unit root test of Kapetanios, Shin, and Snell (2003) (KSS) has attracted much recent attention. However, the KSS test relies on the ordinary least squares (OLS) estimator, which is not robust to a heavy-tailed distribution and, in practice, the test suffers from a large power loss. This study develops three kinds of quantile nonlinear unit root tests: the quantile t-ratio test; the quantile Kolmogorov–Smirnov test; and the quantile Cramer–von Mises test. A Monte Carlo simulation shows that these tests have significantly better power when an innovation follows a non-normal distribution. In addition, the quantile t-ratio test can reveal the heterogeneity of the asymmetric dynamics in a time series. In our empirical studies, we investigate the unit root properties of U.S. macroeconomic time series and the real effective exchange rates for 61 countries. The results show that our proposed tests reject the unit roots more often, indicating that the series are likely to be asymmetric nonlinear reverting processes.

Quantile elasticity of international tourism demand for South Korea using the quantile autoregressive distributed lag model

Using the quantile autoregressive model, this paper investigates international inbound tourism demand for South Korea and its determinants. In contrast to previous studies which have dealt with the conditional mean only, the authors examine the effects of covariates at various conditional quantile levels. US and Japanese tourism demand are considered for inbound tourism demand. For US tourism demand, the costs of living in Korea and competing destinations have moderately significant negative effects at very high and low quantiles only, while income does not have any significant effect on tourism demand. On the other hand, for Japanese tourism demand, income has significant positive effects at lower quantiles, and living costs in Korea and competing destinations have significant negative effects at higher quantiles. These results address the heterogeneity in tourism demand analysis.