Farmer Profitability and Willingness to Accept Payment to Adopt Cover Crops in Alabama

Progress report for GS22-257

Project Type: Graduate Student
Funds awarded in 2022: $16,500.00
Projected End Date: 08/31/2024
Grant Recipient: Auburn University
Region: Southern
State: Alabama
Graduate Student:
Major Professor:
Dr. Wendiam Sawadgo
Auburn University
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Project Information


The adverse impacts of agriculture on the environment – including waterways and climate – have received increasing attention in recent years. The use of cover crops has been lauded for its ecosystem services. Cover crops can reduce nonpoint-source nutrient pollution to waterways, and they play a key role in novel carbon markets due to their ability to sequester carbon in the soil. In addition to these off-farm benefits, cover crops have been shown to be effective at reducing soil erosion, improving soil-water dynamics, and improving soil health, which can translate to higher yields. Despite these benefits, adoption of cover crops remains limited with just 4% of cropland using the practice, nationwide. The additional cost and uncertain effects on net farm income is one of the reasons cited for the low adoption rate of cover crops.

Our proposed study will examine the profitability of using cover crops in Alabama. We will develop a survey to evaluate farmers’ costs of implementing cover crops. We will also study farmers’ willingness to accept payment to adopt cover crops, to better understand the potential for cost-share or carbon markets to increase use of the practice in the region. Lastly, we will evaluate current barriers to adopting cover crops. The proposed project will contribute to SARE program areas objectives of informing decision making, policy design, and interactions between agriculture and the environment.

Project Objectives:

1) Evaluate the profitability of using cover crops in Alabama.

Opportunities for farmers to be paid for planting cover crops have arisen due to the emergence of novel carbon markets. These programs have led to a lot of interest among producers, but knowledge on how cover crops affect net returns of the operation are not well known in Alabama. This objective will look to better understand the magnitude of the costs of planting and terminating cover crops, the two largest additional costs from the use of the practice. On the benefit side, we will analyze whether producers observe a yield bump to their following cash crop that could increase their revenue and offset some of these additional costs, or if they observe a yield drag from using cover crops. In all, we will estimate the effect of cover crops on farm profitability to better inform producers of the short-term costs of adopting the practice.

2) Measure farmers’ willingness to adopt cover crops through the use of payment-for-environmental-service programs.

Novel carbon markets and other cost-share programs for cover crops have the goal of increasing cover crop acreage. However, for these programs to be cost-effective, it is important to understand whether such programs lead to additionality, or acreage in cover crops that would not have been planted to cover crops without the payment. We will use a choice experiment to better understand whether payment-for-environmental-service programs have the desired effect of increasing farmers’ cover crop acreage and the payment rate per acre that farmers would require to participate.

3) Examine barriers to cover crop adoption.

While many of the existing barriers to cover crop use are cost related and could be potentially be addressed via incentive payments to farmers, there may be other non-cost related challenges that farmers face. These could include limited access to cover crop seed, weather conditions that make it difficult to plant or terminate the cover crop, the belief that cover crops take soil moisture at the expense of cash crops, lack of labor available to plant cover crops, or other limitations. These perceived limitations may differ between farmers who use cover crops and farmers who do not currently use cover crops. Understanding the main perceived barriers that non-adopters have for not using cover crops could be important in informing whether the reasons producers do not currently use cover crops are similar to the challenges observed by current adopters. This knowledge could inform educators from cooperative Extension or other organizations on potential challenges to increasing cover crop use.


Materials and methods:

Data will be collected through a survey of Alabama farm operators. A target sample of 600 farmers will be selected from a commodity organization database to obtain a general sample of Alabama producers. The survey will be conducted by mail following Dillman's guidelines (Dillman, 2009).

We will study farmers’ willingness to adopt cover crops as noted in Objective 2 by using discrete choice experiments disseminated through a survey instrument to farmers. In year 1, we developed a survey questionnaire after reviewing prior studies on cover crops, including SARE's 2020 cover crop survey. The project and survey questionnaire was approved by the Institutional Review Board at Auburn University. The questions include multiple choice with some open-ended short answer questions as well. The survey instrument asks questions about farmers’ demographic information such as age, gender, race, highest level of education, and on-farm income sources, among other things. Farm information includes farm operations decision-makers, farm enterprise type, farm acres, crop types grown, and so on. Farmers’ knowledge and perceptions of cover crops and carbon markets are also solicited. We asked about challenges to using cover crops. We also questioned farmers on their yields with and without cover crops. Finally, we designed a choice experiment with different scenarios versus keeping the status quo use of a field currently used as cropland for a fall-planted crop without a cover crop. 

In year 1, the empirical strategy for analyzing the choice experiment was developed. Based  on an extension of the random utility maximization model that underpins discrete choice contingent valuation responses and cover crop contract attribute choices between competing alternatives, we developed a model to analyze the responses to the choice experiment. The format of the choice experiment draws respondents’ attention to the inherent trade-offs between attributes. Utility differences between the alternatives in a choice set are the basis for our model estimations. The random utility model presupposes that respondents have a firm understanding of their utility.  The unobservable components of the respondent utility form a part of the random error since we are unable to observe it perfectly. This assumption is made explicit in a model where utility equals the sum of systematic (v) and random (e) components for respondent, k:

                                        Vik = vik(Zi, yk - pi) + eik

where Vik  is the actual but unobservable indirect utility linked to the alternative i, Zi is a vector of attributes linked with alternative i, pi is the cost of alternative i, yk is income, and eik is a random error term with zero mean.

In the coming months, Qualtrics will be used to distribute the survey questionnaire to the agricultural producers. To estimate willingness to participate in the programs, descriptive and statistical analysis, including logistic regression, will be employed. 

Participation Summary

Educational & Outreach Activities

1 Consultations

Participation Summary:

Education/outreach description:

After the survey is administered and data are analyzed, the results will be presented to Alabama farmers and other stakeholders, including at Extension meetings and commodity group conferences. Research will also be presented at academic conferences, such as the Southern Agricultural Economics Association Annual Meeting. We expect to complete one Extension fact sheet, one newsletter article, one journal article, and several presentations based on the results of this project.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.