Projects Funded for James Sallee

2021-2022

Solar Farms Land Supply: A Dynamic Discrete Choice Model

  • Connor Jackson
  • Tyler Anthony
  • James Sallee

2020-2021

Evaluating Optimal and Second-Best Nitrogen Regulations in California

  • Connor Jackson
  • James Sallee

Abstract

Specific Objectives of the Project
The goal of this project is to analyze the efficacy, efficiency and equity of plausible regulatory policies that seek to reduce nitrogen emissions from agricultural soils.

Summary of Results
The research team used the funds to develop new understandings and create a research agenda around the use of biogeochemical models to perform policy analysis and an emissions inventory related to greenhouse gas emissions from synthetic fertilizer use in croplands.

We are actively collaborating with a social scientist at UC Berkeley to build a new tool based on the biogeochemical model, DayCent. We have (after some delay) gotten full approval to access the necessary survey data from the USDA. We have vetted our research questions with several experts. We are now building the computer code that will enable us to create the tool that will serve as the basis for our policy analysis and simulation. This ongoing work is being supported by a new Giannini grant, and we have identified several extramural grants to provide additional support.

In the meantime, we have some preliminary conclusions from our research pertaining to the magnitude of the greenhouse gas emissions costs from the use of fertilizers, which we are summarizing in a piece to be sent to ARE update this fall.

2019-2020

An Optimal Tax Approach to Policy Problems in California Agriculture

  • James Sallee

Abstract

Specific Objectives of the Project:
The aim of this project is to apply a particular set of economic tools to analyze policies aimed at mitigating externalities from agriculture, using data from California.

Project Report/Summary of Results:
The goal of this project is applying the tools of public finance to evaluate policies aimed at mitigating externalities from California agriculture. The research team studied several possible applications and settled on the use of digesters to mitigate methane emissions from dairies. The team assembled data on the cost and location of all digesters in the state and used those data to estimate mitigation costs per ton of emissions. These costs vary substantially due to economies of scale and agglomeration effects, because cost depends on the proximity of each dairy to existing natural gas infrastructure and other dairies.

Given this distribution of costs, we can characterize the efficiency and distributional consequences of different regulatory policies (e.g., digester mandates versus digester subsidies versus a renewable natural gas feed-in tariff versus a tax on emissions or dairy products). In addition, we have identified direct measures of methane emissions tied to individual dairies from remotely sensed data collected by NASA’s Jet Propulsion Laboratory that provide a check on our modeled mitigation potentials.