Economic incentives for adoption of alternative crops in the rainfed US

Zhang, Na

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https://hdl.handle.net/2142/130054 Copy

Description

Title

Economic incentives for adoption of alternative crops in the rainfed US

Author(s)

Zhang, Na

Issue Date

2025-07-18

Director of Research (if dissertation) or Advisor (if thesis)

• Khanna, Madhu
• Atallah, Shadi

Doctoral Committee Chair(s)

• Khanna, Madhu
• Atallah, Shadi

Committee Member(s)

• Hutchins, Jared
• Guan, Kaiyu

Department of Study

Agr & Consumer Economics

Discipline

Agricultural & Applied Econ

Degree Granting Institution

University of Illinois Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Bioenergy crops
• Cover crops
• Neighborhood effect
• Dynamics of farmer decision-making
• Nature-based solutions

Abstract

Bioenergy crops and cover crops are promising nature-based climate solutions. Despite their potential to provide public benefits (e.g., reducing carbon emissions, sequestering carbon) for society and private benefits for farmers, the commercial-scale production of bioenergy crops such as miscanthus and switchgrass has not yet been realized, and the adoption of cover crops remains low across the United States. In this dissertation, I determine the best management practices of producing perennial energy crops using a simulation approach and examine the dynamics of farmer decision-making regarding cover crop adoption using observational data and econometric models. This research contributes to the broader literature of agricultural and environmental economics. The dissertation consists of three chapters below. Chapter 1 studies the spatially varying best management practices for producing bioenergy crops in the rainfed region of the United States. Determining optimal management practices for the profitable production of perennial energy crops is critical for scaling up production beyond experimental levels. Although many experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as on optimal rotation age of the energy crop to maximize profits. I develop a modeling framework to determine economically optimal crop management decisions and simulate the variability under various scenarios for miscanthus and switchgrass production across 2287 counties in the rainfed United States. I find that profit-maximizing N recommendations for these crops vary across maturity stages and regions and can increase the landowner's profits compared with a uniform N rate across ages and regions. I also find that the optimal rotation for these crops is shorter than the productive physical lifespan (15–20 and 10 years for miscanthus and switchgrass, respectively). Specifically, the N rate that maximizes the economic returns is negligible for miscanthus and 111 kg ha−1 for switchgrass production at age 2. The mean profit-maximizing N rate increases with age for miscanthus, peaking at 151 kg ha−1 at age 11 before declining to 114 kg ha−1 at the optimal rotation age of 13 years while that for switchgrass is 150 kg ha−1 for middle-aged stands and declines to 114 kg ha−1 at the optimal rotation of 8–9 years. I find that miscanthus is the most profitable energy crop in the northern region of the rainfed United States, while switchgrass is most profitable in the south of the rainfed United States. These findings are useful for improving assessments of the profitability of energy crops and guiding future management. Chapter 2 studies the determinants of cover crop adoption in the Midwest of the United States. The potential for cover crops to improve soil health, enhance soil carbon sequestration, and provide other environmental benefits has motivated interest in accelerating adoption. Existing studies using farmer surveys provide cross-sectional evidence of the farm and farmer characteristics influencing adoption but do not explain location-specific adoption dynamics over time for the same farmer. I combine detailed field, farm, and farmer attributes with novel satellite-detected, grid-level cover crop data to track the annual adoption decisions at the farmer and field level and the adoption intensity decision for a restricted random sample across three Midwestern states from 2011 to 2021. I develop empirical models to examine the role of neighborhood adoption behavior in inducing adoption by a farmer and a parcel. Using panel data models with instrumental variables to address endogeneity, I find that a 1 percentage point increase in neighborhood adoption intensity of cover crops increases a farmer’s adoption probability by 11 percentage points, a land parcel’s adoption probability by 4.3 percentage points, and the share of the farmer’s land area under cover cropping by 2.4 percentage points. The effects of farm, farmer, and field attributes selected as controls are consistent with previous studies. I find robust evidence of neighborhood effects controlling for farmers’ own adoption experience and time-varying confounders in dynamic panel data models and using an alternative satellite-based cover crop dataset. These findings suggest the potential for demonstrations, extension efforts, and farmer networks to accelerate the learning and adoption of cover crops. Chapter 3 examines the temporal dynamics of farmer decision-making regarding cover crops, with a focus on continuous adoption behavior and the factors associated with adoption duration. Using newly developed satellite-based data, I track field-level cover crop adoption for a stratified random sample of corn producers in Iowa, Illinois, and Indiana from 2011 to 2021. Based on annual adoption patterns, farmers or field parcels are categorized as always adopters, intermittent adopters, or never adopters. Focusing on adopters or parcels planted with cover crops, I define an “adoption spell” as a sequence of consecutive years during which cover crops are continuously adopted by a farmer or on a field parcel. The duration analysis reveals that time-varying factors, including planted acreage, the share of owner-operated land, pre-planting mean temperature, and conservation payments, are significantly associated with the length of adoption spells. In addition, farmer characteristics such as education and age, and field characteristics such as soil clay content, are also significant factors associated with adoption duration. These findings shed light on the adoption dynamics and the determinants of adoption duration, which are relevant for designing agri-environmental policies that promote sustained adoption and for modeling the long-term environmental and economic benefits of cover cropping.

Graduation Semester

2025-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/130054

Copyright and License Information

Copyright 2025 Na Zhang

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