Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches

Woraphon Yamaka,Xuefeng Zhang,Paravee Maneejuk

doi:10.3390/math9050515

Abstract

This study investigates the nonlinear impact of various modes of transportation (air, road, railway, and maritime) on the number of foreign visitors to China originating from major source countries. Our nonlinear tourism demand equations are determined through the Markov-switching regression (MSR) model, thereby, capturing the possible structural changes in Chinese tourism demand. Due to many variables and the limitations from the small number of observations confronted in this empirical study, we may face multicollinearity and endogeneity bias. Therefore, we introduce the two penalized maximum likelihoods, namely Ridge and Lasso, to estimate the high dimensional parameters in the MSR model. This investigation found the structural changes in all tourist arrival series with significant coefficient shifts in transportation variables. We observe that the coefficients are relatively more significant in regime 1 (low tourist arrival regime). The coefficients in regime 1 are all positive (except railway length in operation), while the estimated coefficients in regime 2 are positive in fewer numbers and weak. This study shows that, in the process of transportation, development and changing inbound tourism demand from ten countries, some variables with the originally strong positive effect will have a weak positive effect when tourist arrivals are classified in the high tourist arrival regime.

Highlights

As travel and tourism is one of the world’s largest economic sectors, it has played an essential role in contributing to job creation and economic growth and creating prosperity worldwide [1,2,3]
Since the the Chinese reform and opening-up policies were first put into action, the issue of investment in transportation has received considerable attention as a prerequisite for tourism development, and transportation development has been placed at a high priority until today
The two-regime Markov-switching lasso regression (MS-LR) and Markovswitching ridge regression (MS-RR) models are assumed to investigate the nonlinear effects of transportation modes on ten top-tourist arrivals to China

Summary

Introduction

As travel and tourism is one of the world’s largest economic sectors, it has played an essential role in contributing to job creation and economic growth and creating prosperity worldwide [1,2,3]. In China, tourism has become an important contributor to the domestic economy since implementing reform and opening-up policies in the early 1980s. China Tourism Academy (2020) reported that the Chinese tourism industry generates. The Chinese government takes tourism development into account when making essential policies on economic growth. One of the critical factors driving tourism development is transportation, of which its importance to tourism development has been widely recognized [4,5,6,7]. Since the the Chinese reform and opening-up policies were first put into action, the issue of investment in transportation has received considerable attention as a prerequisite for tourism development, and transportation development has been placed at a high priority until today. China has provided advanced tourism services for international tourists inbound and developed/constructed and improved the domestic transportation infrastruc-

Objectives

Methods

Results