Browsing by Author "Ma, Junxiao"

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    Essays on Urban Economics
    (2021-07-27) Ma, Junxiao; Whalley, Alexander; Muehlenbachs, Lucija; Staubli, Stephan; David Walls, William; Oguzoglu, Umut
    This dissertation includes three essays exploring topics related to Urban Economics. Using advanced empirical methodologies, I examine the effects of traffic pricing policies and rider-hailing services on traffic and air quality. Chapter 1 investigates the traffic and environmental impact of traffic pricing policy. This paper estimates the heterogeneous effect of the London congestion charging scheme (CCZ) on the traffic by vehicles with different pollution intensities and ambient air quality within the Greater London Area. The implementation of such a policy effectively reduces the traffic flows from less-polluted vehicles, like private cars by roughly 16% inside central London. However, about 25% more trips by polluting vehicles (light and heavy goods vehicles) are induced from this traffic charge. About 28% and 18% drops in NO and NO2 emissions are detected following CCZ order. PM2:5 reduces slightly by 6% after the charge. Chapter 2 examines the effects of the air pollution charge on traffic by vehicle types. Compared to the congestion charge, air pollution pricing specifically targets highly polluting vehicles, such as heavy trucks. This paper estimates the heterogeneous effect of the Low Emission Zone (LEZ) on highway traffic volume in the Greater London Area (GLA). The introduction of LEZ leads to about an 11% drop in overall traffic. However, the response to air pollution charges varies across different vehicle groups. Following the enactment of LEZ, traffic by light goods vehicle (LGV) decreases by roughly 14% while traffic of heavy good vehicle (HGV) increases by 18%. Chapter 3 studies the impact of ride-hailing services on the traffic of different automobiles. This paper studies the effect of such a service on traffic using a natural experiment created by the abrupt exit of Uber from London. Adopting the difference-in-difference approach with granular traffic data, my study finds an overall drop of 13.2% in average traffic volume and an increase of 21.2% in average traffic speed following the suspension order of Uber in London. For other transit modes, the evidence in support of a rise of 13.7% in public traffic and 19.6% in private-hire traffic is found after the temporary exit of Uber.