패널모형을 적용한 대기오염과 국내 여행수요 간의 인과관계 분석

The Effects of Air Pollution on Domestic Travel Demand: Panel Data Analysis for Fine and Ultrafine Particulate Matter

This study conducted panel data analyses using time series data from 20 months (May 2016 to December 2017) of 17 metropolitan cities to investigate the negative effects of air pollution on domestic travel demand. In this study, a travel demand model with air pollution factors such as fine particulate matter (PM10), ultrafine particulate matter (PM2.5), and ozone (O3), including climate factors (precipitation, temperature) and demographic variables (income, age), was established. The diagnosis was finally interpreted as an estimate of the fixed effect model with first-order autoregressive disturbances. According to the main results, when the index of ultrafine dust is changed from the 'good' level to the 'normal' level, domestic travel demand is reduced by 27.9%, and when worsened to the 'bad' level, demand decrease of 9.5% is added. In addition, the change from the 'good' level to the 'normal' level caused by fine dust and ozone pollution showed 14.8% and 8.2% reduction in travel demand, respectively. The point is that the regional characteristics should be taken into account when establishing tourism policies to cope with ultrafine dust.