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Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.

This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends that of Han (1987) to incorporate time trend and nonstationary regressors. When the transformation is specified as an identity function, the model reduces to the conventional cointegrating regression, possibly with a time trend and other stationary regressors, which has been studied in Phillips and Durlauf (1986) and Park and Phillips (1988, 1989). The limiting distributions of the extremum estimator of the transformation parameter and the plug-in estimators of other model parameters are found to critically depend upon the transformation function and the order of the time trend. Simulations demonstrate that the estimators perform well in finite samples.

This paper examines the relationship between transportation quality, customer satisfaction and profitability. Specifically, this study examines the simultaneous and asynchronous effect of quality of transportation services on customer satisfaction and financial performance and then performs the same examination in relation to the effect of customer satisfaction on financial performance. The partial least squares approach to structural equation modelling is used to examine longitudinal data from 1995 to 2018 from the US airline industry. The findings suggest that low service quality in transportation has adverse effects on customer satisfaction and financial performance, while the impact of customer satisfaction on financial performance in the US Airline transportation industry is mixed. The authors found that the impact of customer satisfaction on financial performance is significant in full-service airlines but not in low-cost airlines. Surprisingly, the authors found no significant direct relationship between transportation quality and financial performance in the US airline industry.