Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands

With the rapid development of electric vehicles (EVs), one of the urgent issues is how to deploy limited charging facilities to provide services for as many EVs as possible. This paper proposes a bilevel model to depict the interaction between traffic flow distribution and the location of charging stations (CSs) in the EVs and gasoline vehicles (GVs) hybrid network. The upper level model is a maximum flow-covering model where the CSs are deployed on links with higher demands. The lower level model is a stochastic user equilibrium model under elastic demands (SUE-ED) that considers both demands uncertainty and perceived path constraints, which have a significant influence on the distribution of link flow. Besides the path travel cost, the utility of charging facilities, charging speed, and waiting time at CSs due to space capacity restraint are also considered for the EVs when making a path assignment in the lower level model. A mixed-integer nonlinear program is constructed, and the equivalence of SUE-ED is proven, where a heuristic algorithm is used to solve the model. Finally, the network trial and sensitivity analysis are carried out to illustrate the feasibility and effectiveness of the proposed model.

The Private Income Tax Shock Premium

This paper investigates the asset pricing implications of tax policy changes. News about tax cuts decreases future tax revenues and increases future consumer demand and output. Using cross-sectional variation in industry exposure to structurally identified tax news, I develop a factor mimicking private income tax shocks. I construct an investment strategy, which generates annualized risk-adjusted returns of 5.16 % over the Fama-French 3-factor model. I rationalize the finding by arguing that firms with more elastic demands bear higher consumption risk, which works through a wealth effect.