Author ORCID Identifier



Date of Graduation


Document Type


Degree Type



Davis College of Agriculture, Natural Resources and Design


Division of Resource Economics & Management

Committee Chair

Alan R. Collins

Committee Member

Mark Sperow

Committee Member

Levan Elbakidze

Committee Member

Samir Safi


In this dissertation, three related topics are investigated about environmental and energy economics. The research in these essays utilize panel data and regression models. The overall theme of these essays is to explore the relationships between energy and the environment in the United States (U.S.).

In the first essay, using data from fifty U.S. states between 2012 and 2020, the impacts of three types of state level policies on electric vehicles (EV) adoption are examined: 1) policies that mitigate the environmental impacts from energy production, 2) policies that provide financial incentives to consumers for EV purchase, and 3) policies that provide publicly available EV charging infrastructure. With a dependent variable of EV registration per 100,000 population, impacts are assessed with a panel data, fixed effects model. Evidence is found that policies which either increase low greenhouse gas (GHG) energy through increasing the renewable and nuclear energy sources in the energy mix or reduce carbon dioxide (CO2) emissions from electricity generation by reducing the reliance on fossil fuels in the electric sector result in statistically significant increases in EV adoption rate. Financial incentives are important as the presence of a state income tax credit positively impacts EV adoption rate. Comparable elasticities on EV adoption rate from statistically significant coefficients show that per capita income has the largest effect on adoption (+10.1), while impacts of low GHG energy and per capita CO2 emissions elasticities are much smaller at + 0.64 and -1.0, respectively. Since state policies that enhance low GHG and provide tax credits positively impact EV adoption rates, our research demonstrates the need to nationalize both types of policies in order to uniformly improve adoption across all states.

In the second essay, the impact of climate change on U.S. electricity consumption, production, and efficiency is examined using annual state-level data for 48 states over 30 years (1990 – 2019). Research results show that an increase in averaged maximum ambient air temperatures increases electricity demand and decreases generation efficiency. The electric sector in the U.S. is found to be vulnerable to climate change, such that a rise in the ambient temperature increases demand for electricity and decreases supply and efficiency of power plants. On the demand side, the per capita electricity consumption at the state level is responsive to the climate change, such that when the averaged maximum ambient temperature increases by 1 ͦ F (0.56 ͦ C), the per capita electricity consumption increases by a 0.52%. However, the most powerful impact on the per capita electricity consumption was found to be from the electricity retail prices such that a one cent increase in average per kilowatt-hours (kWh) price will result in a decrease of 7.1% in the per capita electricity consumption.

On the supply side, power generation is also responsive to climate change such that increasing the average maximum temperature by 1 ͦ F (0.56 ͦ C) results in a reduction of 3.9% in the total electricity generation at the state level. Estimates for fossil fuels weighted average price consistently agree with law of demand as increasing fossil fuels weighted average price by $1 per million British Thermal Unit (MMBtu)[1] results in reduction of demand for fossil fuels and accordingly will result in a reduction of electricity supply by 10.2%. Finally, the efficiency of fossil fired power plants decreases with increasing ambient temperature due to increased fuel consumption.

In the third essay, the existence of the Environmental Kuznets Curve (EKC) in the presence of low GHG energy consumption is empirically examined using state level data in the U.S. This research explores whether the per capita income still retains an inverted U shape impact on per capita CO2 emissions in the presence of state level environmental and energy policies which promote reduced fossil fuel use in the electricity sector. An Autoregressive Distributive Lag (ARDL) econometric model is employed using panel data for 50 U.S. states during the period of 1990 to 2018. The findings provide statistically significant evidence for the presence of the EKC for CO2 emissions at the state level. Regression estimates find a turning point of $50,766.5 in the relationship between per capita income and CO2 emissions. For the Low GHG energy variable, increased primary energy consumption for electricity from renewable and nuclear energy sources has a negative impact on per capita CO2 emissions. When the per capita average low GHG energy consumption increases by one MMBtu[2], per capita CO2 emissions reduces by 0.05%. With these findings, the existence of the EKC hypothesis for CO2 emissions at the state level is supported.

The conclusion from essay three is that implementation of new energy technologies serves to reduce CO2 emissions. However, these technologies do not diminish the entire impact of increasing per capita income on reducing these emissions. Other factors, in addition to new energy technologies, are at work in reducing CO2 emissions with increasing per capita income past the turning point. These factors may include changes associated with higher levels of per capita income including an economic structure more heavily dependent upon services involving renewable energy source and increasing the adoption of green technologies such as EV, movement of production locations to other locations with lower income in helps stimulating the economic growth which in turn has a positive impact on the reduction of CO2, and enhanced consumer awareness about climate change and behavioral changes related fossil fuel consumption.

[1] In average, this increase is equal to an increase of 2 cents per short ton of coal, $1.02 per 1000 CF of natural gas, or 12 cents per gallon of petroleum.

[2] One million Btu is equal to 293 kWh.