No abstract

Renewable subsidies and mandates currently play a central role in the environmental and energy policy in the United States, one of the world’s top greenhouse gas emitters. Therefore, accurately estimating the environmental benefits from wind energy is key to evaluating the existing policies and setting future directions and has been studied within a growing body of the literature. However, most of the existing studies do not take the intermittency into account, and the small number of studies that do only study a relatively short time period limiting the extent to which they can be informative within different ranges of wind generation capacity. In this paper, we present the first estimates of the environmental benefits of wind energy generation using a dataset that spans well over a decade. Specifically, we use 13 years of hourly and sub-hourly data to estimate the causal effect of wind generation and its intermittency on CO2, NOx, and SO2 emissions from the electricity sector in Texas. Additionally, we compared the full sample results to those from sub-samples where the dataset is divided into subgroups based on wind output level. We found that while wind generation clearly has a statistically significant negative marginal effect on all pollutants we studied, the marginal effect of intermittency varies across different wind output levels in a highly irregular way. Our findings suggest that conducting pooled analyses has the potential to mask the irregularity in the variation of the effect of intermittency in wind generation across different wind output levels.

No abstract

We study supply response to irrigation water salinity-an important and ubiquitous environmental problem facing agriculture around the world. The geographical setting is the Sacramento-San Joaquin River Delta, a main water hub in California, where salinity is a significant part of recent policy debates over water management and infrastructure. We use highly granular farm-level panel data on Delta farming activity to estimate two sets of response parameters using (i) standard (fixed coefficients) logit model, and (ii) a mixed (random coefficient) logit model. The mixed logit results provide evidence for heterogeneity in supply response across farmers. To put these findings in a meaningful economic context, we use the results from both models to simulate estimates for aggregate acreage responses under two alternative salinity scenarios. We implement a method to simulate individual specific responses together with their confidence intervals, which provides additional insight into the composition of farmer heterogeneity. Based on these post-regression simulation results, we find the mixed logit model predicts an elasticity of aggregate acreage for salt-sensitive (hence higher value) crops that is an order of magnitude larger compared to that of the standard fixed coefficients logit method. This result sheds light on category of costs likely to increase in response to rising salinity in the Delta region.

No abstract