Department or Program
Environmental Studies
Abstract
The merit-order effect suggests that integrating green energy into the grid should push generation with higher operational costs out of the electricity market, lowering wholesale prices. Considering this price effect, I construct well-specified models for electricity prices over multiple timespans to see if an increase in solar and wind generation decreases wholesale electricity rates, specifically in the United States. Using ordinary-least-squares regression models, I initially find that electricity demand, input prices, and lagged electricity prices are all significant determinants in the model for electricity prices. My findings for demand and input prices align with results from international literature, while the inclusion of lagged electricity prices as a determinant in the model is unique to this thesis. Then, using vector autoregressive estimators, I find that a one-standard-deviation positive shock in U.S. solar and wind generation initiates a statistically significant negative response in national electricity prices. This negative relationship is reflected by various articles which focus on international energy markets. Furthermore, this finding shows that the merit-order effect holds empirical truth in the United States at the national level. I also find that the response in electricity prices varies across timespans and regions, likely due to different energy generation compositions and green-energy incentive programs.
Level of Access
Restricted: Campus/Bates Community Only Access
First Advisor
Lynn Lewis
Date of Graduation
5-2018
Degree Name
Bachelor of Arts
Recommended Citation
Marcus, Matthew R., "The Empirical Impact of Renewable Generation on Electricity Prices via OLS and Vector Autoregressive Estimators" (2018). Standard Theses. 178.
https://scarab.bates.edu/envr_studies_theses/178
Number of Pages
67
Restricted
Available to Bates community via local IP address or Bates login.