UC Berkeley

Chapter One examines how firms respond to changes in environmental regulations that rely on self-reporting. Routine natural gas flaring at oil wells in the U.S. has soared in the last decade as advances in hydraulic fracturing enabled oil production in previously unprofitable regions, leading to concerns over climate and health damages. What is the effect of environmental policy aimed at reducing gas flaring? How do responses in self-reported versus remotely detected flaring data compare? I employ a difference-in-differences approach comparing North Dakota to Montana wells before and after the policy implementation to estimate the effect of the policy on reported and remotely-detected flaring. I construct a novel monthly well level remotely detected flared volume dataset, that is comparable to administrative well level flared volume data between 2012-2019 in the Bakken Shale. I document both an unprecedented uptick in natural gas flaring and an increasing gap between self-reported and remotely detected flaring. During the first two years of the policy, wells reduced flaring in compliance with the policy and reported truthfully; however, in the last three years, compliance fell, and half the gains in reported flaring reduction are from misreporting. This paper fits into a growing body of literature utilizing newly available satellite data to evaluate the effectiveness of environmental policy and measure the activity of the oil and gas industry. This paper fits into a growing body of literature utilizing newly available satellite data to evaluate the effectiveness of environmental policy and measure the activity of the oil and gas industry.

Chapter Two presents a novel hydrological approach to identifying and addressing nonpoint source pollution from agricultural runoff in national-scale river networks.

Freshwater and coastal ecosystems worldwide increasingly suffer from eutrophication caused by nonpoint source agricultural runoff, resulting in detrimental environmental, social, and economic outcomes.

The main challenge for policymakers in regulating and reducing nonpoint source water pollution is the difficulty in identifying the source of nutrient runoff and measuring whether policy changes effectively reduce pollution.

Our paper addresses this problem through modeling pollutant flux in national-scale river networks and identifying which catchments exhibit higher nutrient loss at a spatially and temporally granular level.

Our spatial approach combines publicly available water data and hydrographic methods to localize annual nitrogen and phosphorus based pollutant loads at the sub-watershed level in the United States Mississippi River Basin (USMRB) and the country of New Zealand between 1981 -- 2018.

We found that the distribution of nitrogen and phosphorus pollutant loads are spatially heterogeneous even within the same region in the two watersheds that we evaluated. We found that average total nitrogen and total phosphorus runoff was consistently highest in the Southland and Gisborne Regional Councils in New Zealand. In the USMRB, average total nitrogen and total phosphorus runoff was highest in the central region of the watershed.

Our results are useful for evaluating historical water pollution and establishing baseline pollutant loads, measuring changes in agricultural runoff over time, and monitoring the effects of changes in water quality regulations and land use activities at annual and sub-annual time steps.The use of our spatial model can be used to shed light on the effect of water pollution on human health, how water pollution differentially impacts disadvantaged populations and communities of color, and the distribution of water pollution under varying climate change scenarios.

Chapter Three investigates whether there is evidence of multinational oil producers engaging in base erosion and profit shifting practices. I do this through estimating the responsiveness of reported profits of oil companies with respect to corporate tax rate differences. The elasticity of reported profits with respect to changes in corporate tax rates helps to elucidate whether companies employ artificial profit shifting techniques. My identification strategy exploits exogenous changes in corporate tax rate differentials for multinational corporations whose foreign subsidiaries pay taxes in the country where they are located. Identifying a significant and substantive corporate tax differential elasticity to reported profits will provide evidence that firms extralegally choose where to report their profits based on the locations of their subsidiaries, thereby artificially shifting their profits from high to low tax jurisdictions.