Rong (Charlotte) Wang
Research
Research
Constructed structural models and estimated model parameters using MLE methods for quantitative decision making in Python and Matlab.
Solved and simulated Dynamic Discrete Choice models using Nested Fixed Point Algorithm in Python and Matlab.
Applied time series analysis techniques to conduct econometric analysis on VAR and ARIMA models.
Executed counter-factual analysis to predict different policy implications, focusing on industrial and environmental policies.
How Should We Price Carbon? A Policy Design on the Electricity Market
Discussed the Pros and Cons of the two major carbon pricing programs: Carbon Tax Program and Cap-and-trade Program.
Used a structural dynamic model to analyze the effects of different carbon policies on electricity generation, in terms of efficiency, equity, and realibility of the electricity grid.
The impacts of Crime on Residental Property Choices
Entry and Exit Decisions of Fossil Fuel Generators Facing Renewable Energy Intergration