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Roderick Rejesus

Department of Agricultural and Resource Economics

Professor and Extension Specialist

NC State Extension

Nelson Hall 4340

Bio

Roderick “Rod” M. Rejesus is a Professor and Extension Specialist in the Department of Agricultural and Resource Economics at North Carolina State University. He received his Ph.D. in Agricultural Economics from the University of Illinois at Urbana-Champaign. Dr. Rejesus has an active research and extension program that focuses on applied production economics, with special emphasis on agricultural policies related to risk management (e.g., crop insurance and other safety-net policies for farmers) and economic impact assessment of agricultural technologies. His applied research program in crop insurance covers both compliance issues (i.e., fraud prevention) and topics related to premium rate-setting. He also has extensive experience evaluating economic impacts of various agricultural technologies, policies, and programs (in the US and other countries).

RePEc Profile

Extension Links:

Teaching:

  • ARE 303: Farm Management (Fall Semesters)

Publications

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Selected Publications

The impact of no-till on agricultural land values in the United States Midwest. American Journal of Agricultural Economics (2022)

Payments from Agricultural Conservation Programs and Cover Crop AdoptionApplied Economic Perspectives and Policy (2022)

Crop insurance participation and cover crop use: Evidence from Indiana county-level dataApplied Economic Perspectives and Policy (2022)

Quantifying the Yield Sensitivity of Modern Rice Varieties to Warming Temperatures: Evidence from the PhilippinesAmerican Journal of Agricultural Economics (2022)

Warming Temperatures, Yield Risk, and Crop Insurance ParticipationEuropean Review of Agricultural Economics (2021)

Economic Dimensions of Soil Health Practices that Sequester Carbon: Promising Research DirectionsJournal of Soil and Water Conservation (2021)

Nonparametric Estimation and Inference of Production RiskAmerican Journal of Agricultural Economics (2021)

Advantageous Selection in Crop Insurance: Theory and EvidenceJournal of Agricultural Economics (2018)

Greater sensitivity to drought accompanies maize yield increase in the US MidwestScience (2014)

Adoption and economics of alternate wetting and drying water management for irrigated lowland riceField Crops Research (2015)

Factors affecting farmers’ utilization of agricultural risk management tools: the case of crop insurance, forward contracting, and spreading salesJournal of Agricultural and Applied Economics (2009)

Productivity and exporting status of manufacturing firms: Evidence from quantile regressions. Review of World Economics (2006)

Developing Experience-Based Premium Rate Discounts in Crop InsuranceAmerican Journal of Agricultural Economics (2006)

Education

Ph.D. University of Illinois at Urbana-Champaign 2001

Publications

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Grants

Date: 04/01/23 - 3/31/28
Amount: $424,079.00
Funding Agencies: National Aeronautics & Space Administration (NASA)

The proposed project will look to develop and analyze systems that would allow for earth observation data (i.e., remote sensing and satellite data sets) to strengthen US agriculture resilience against cliamte change.

Date: 09/01/21 - 8/31/25
Amount: $325,000.00
Funding Agencies: USDA - National Institute of Food and Agriculture (NIFA)

The objectives of this project are to 1. train county agents on corn agronomy and corn pests 2. quantify the cost difference in growing non-Bt and Bt corn and 3. increase plantings of refuge (non-Bt) corn.

Date: 05/15/20 - 5/14/25
Amount: $499,912.00
Funding Agencies: USDA - National Institute of Food and Agriculture (NIFA)

The long-term goal and main objective of this proposed project is to develop semi-nonparametric econometric methods that will improve empirical understanding of the relationship between planting density and corn production risk in the US. The specific objectives of the project are: (1) To develop semi-nonparametric estimation and inference procedures that would allow for empirical analysis of production risk based on agricultural data sets (i.e., cross-sectional and panel data sets with high-dimensionality); (2) To estimate the effect of planting density on mean yields and production risk (i.e., the higher moments of the yield distribution) using novel semi-nonparametric methods; (3) To determine how planting density choices influence the impact of climate change on mean corn yields and production risk, using novel semi-nonparametric methods; and, (4) To determine how the impact of genetically-modified (GM) traits on mean corn yields and production risk are affected by planting density, using novel semi-nonparametric methods.

Date: 05/15/20 - 5/14/25
Amount: $499,998.00
Funding Agencies: USDA - National Institute of Food and Agriculture (NIFA)

The number of foreign mergers and acquisitions (M&A) of U.S. firms has increased dramatically. Policy-makers and regulators are increasingly more concerned, especially when acquisitions take place in sensitive sectors, such as the agrifood industry. There is little research evaluating the effects of foreign M&As on employment, output, price (volatility), imports, and exports. Our proposal seeks to fill this gap by collecting a comprehensive dataset on foreign acquisitions and domestic economic indicators and providing estimates of the impact of such M&As on domestic employment, output, price volatility, and exports in all sectors, and in the agrifood sector in particular. The ultimate long term goal of the project we propose is to help guide policy-makers in their discussions and potential regulation foreign acquisitions in the U.S. agrifood industry.

Date: 02/08/22 - 1/20/25
Amount: $1,061,790.00
Funding Agencies: USDA - Natural Resources Conservation Service (NRCS)

On-farm trials will be used to measure mitigation of nitrous oxide and ammonia emissions from nitrogen fertilization of corn with and without the use of a urease and nitrification inhibitor. Control plots receiving zero N will be used to examine inherent soil health in the system and supply power relative to corn yields.


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