About

Dr. Chad Fiechter is an Assistant Professor of Agricultural Economics at Purdue University. His research focuses on issues related to farm policy, farmland markets, and agricultural economics. He is involved in the Farm Policy Study Group, where he contributes to discussions and presentations on topics such as the evolving urban-rural divide, renewable energy and farmland market dynamics, and the future of farming. Dr. Fiechter's work is aimed at understanding and analyzing the economic factors influencing agriculture and rural communities, with an emphasis on policy implications and sustainable development.

Research topics

• Economics
• Business
• Agricultural economics
• Finance
• Monetary economics
• Financial system
• Macroeconomics

Selected publications

• Is Precision Agriculture Technology Adoption Persistently Overestimated?

  Agribusiness · 2026-03-25

  articleOpen accessCorresponding

  ABSTRACT Precision agriculture is sometimes assumed to diffuse steadily over time, and industry planning frequently extrapolates early adoption trends forward. This study evaluates the accuracy of such expectations by comparing agricultural input dealers' forecasts of future service offerings with the actual levels of offerings that dealerships eventually provided. Using 21 waves of the CropLife‐Purdue Precision Agriculture Dealership Survey from 2000 to 2025, we examine expected and realized precision agriculture offerings across 26 technologies. We document systematic and persistent overestimation of adoption: for most technologies, expected diffusion exceeds realized outcomes, with forecast errors becoming especially pronounced as adoption flattened or declined in the early 2020s. These findings suggest that managers have a difficult time forecasting precision agriculture adoption, with implications for investment, staffing, and service provision decisions in agribusiness supply chains.

  PublisherDOI

• Farm Efficiency and Precision Agriculture Technology

  Journal of Agricultural and Applied Economics · 2025-12-01 · 1 citations

  articleOpen access1st authorCorresponding

  Abstract Precision agriculture technology (PAT) is often viewed as a potential driver of future efficiency gains in farming. Using within-farm variation from an unbalanced panel of Kansas farms, this study examines the impact of PAT bundles on efficiency in generating gross revenue. On average, we find little evidence that these technologies improve efficiency. However, among less efficient farms, several bundles are linked to notable efficiency gains, underscoring the importance of accounting for farm heterogeneity.

  PublisherDOI

• Farmer Corn Marketing and Over-the-Counter Derivatives

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• The Loss Function of USDA Forecasters: Evidence from WASDE Animal Product Price Forecasts

  Journal of Agricultural and Applied Economics · 2025-12-23 · 1 citations

  articleOpen access1st authorCorresponding

  Abstract The loss function is a mathematical representation of the costs experienced by a forecaster when observed outcomes differ from what was predicted. Prior studies suggest that USDA forecasts are not optimal based on an assumed mean-zero quadratic loss function. This study proposes an alternative view of forecast evaluation, which assumes all USDA forecasts are produced to minimize the forecasters’ costs, and searches for the dimensions of the loss function under which optimality holds. We illustrate the degree to which USDA loss functions vary across a series of WASDE price forecasts. A better understanding of USDA forecasters’ costs will benefit forecasters and forecast users.

  PublisherOA PDFDOI

• The Economics of Us Row Crop Production with Large-Scale Autonomous Machines

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  preprintOpen access
  PublisherDOI

• The economics of US row crop production with large-scale autonomous machines

  Smart Agricultural Technology · 2025-11-08

  articleOpen accessCorresponding

  Labor challenges are underpinning large multinational farm machine manufacturers' development of autonomy solutions for their large-scale machine offerings. This study simulates a linear optimization model to examine the economics of large-scale autonomous machines for a rotational maize and soybean farm in the Midwest US. Results support the hypothesis that autonomous machines can be economically viable for farms facing severe labor shortages. However, under current technology and pricing structures, conventional mechanization remains the most profitable option for farms with reliable labor. Critical factors shaping the competitiveness of autonomy include subscription fees, field efficiency, and human supervision requirements. As these factors evolve, farm expansion is likely to emerge as an early pathway where large-scale autonomous machines deliver economic advantages.

  PublisherDOI

• Information Rigidities and Farmland Value Expectations

  Land Economics · 2024-11-30

  articleOpen access1st authorCorresponding

  <h3>Abstract</h3> This study examines the degree to which information inefficiency influences farmland price expectations. Using expectations and observed values of Iowa farmland from 1964 to 2021 and the empirical test of Coibion and Gorodnichenko (2015), this study estimates the degree to which information rigidities hold explanatory power for information inefficiency. Our results suggest Iowa farmland professionals infrequently update their information set or underweight new information. This study provides a necessary step toward a better understanding of the role of information in farmland market efficiency, furthering the discussion of development of additional public information in farmland markets.

  PublisherOA PDFDOI

• Monetary Incentives, Landowner Preferences: Estimating Cross-Elasticities in Farmland Conversion to Renewable Energy

  arXiv (Cornell University) · 2024-11-15

  preprintOpen access1st authorCorresponding

  This study examines the impact of monetary factors on the conversion of farmland to renewable energy generation, specifically solar and wind, in the context of expanding U.S. energy production. We propose a new econometric method that accounts for the diverse circumstances of landowners, including their unordered alternative land use options, non-monetary benefits from farming, and the influence of local regulations. We demonstrate that identifying the cross elasticity of landowners' farming income in relation to the conversion of farmland to renewable energy requires an understanding of their preferences. By utilizing county legislation that we assume to be shaped by land-use preferences, we estimate the cross-elasticities of farming income. Our findings indicate that monetary incentives may only influence landowners' decisions in areas with potential for future residential development, underscoring the importance of considering both preferences and regulatory contexts.

  PublisherOA PDFDOI

• Farmer sentiment and farm service agency direct loan applications

  Agricultural Finance Review · 2024-05-14

  article1st authorCorresponding

  Purpose Farmer sentiment may be an important indicator for the agricultural sector, similar to the way that consumer sentiment is linked to the general economy. This study uses the Purdue University–CME Group Ag Economy Barometer to test the degree to which farmer sentiment is correlated with demand for United States Department of Agriculture Farm Service Agency (FSA) direct loan applications. Design/methodology/approach We estimate the dynamics between farmer sentiment and applications to FSA direct operating or farm ownership loans using monthly measures of farmer sentiment and loan applications from October 2015 to April 2023 and pairwise vector autoregression. Findings A negative relationship exists between farmer sentiment and FSA direct operating loan applications. In contrast, a positive relationship exists between farmer sentiment and FSA direct farm ownership loan applications. Together, the estimated nonzero relationships suggests that the Ag Economy Barometer may be a leading indicator for the Agricultural Economy and that FSA loan programs play a nuanced role in the agricultural credit market. Originality/value This study uses unique data sources to further the discussion on the link between farmer sentiment and real economic outcomes and the role of an important US Federal Government farmer lending program: FSA direct loans.

  PublisherDOI

• Change in farmer expectations from information surprises in the corn market

  American Journal of Agricultural Economics · 2024-07-03 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract Farmers make production decisions despite future output price uncertainty. As a result, farmers' expectation of future output price is an important determinant of investment and the supply of commodities. However, our understanding of the process by which farmers form their expectations is still limited. This study uses direct measures of farmers' financial condition expectations collected through the Purdue University–CME Group Ag Economy Barometer to measure the effect of surprise information on farmers' short‐ and long‐term expectations. The effect is identified using an event study framework previously used to examine the impact of market information on commodity futures markets. Using ordered logistic regressions and variation between professional and United States Department of Agriculture forecasts of corn ending stocks, we demonstrate that farmers' short‐term expectations of the financial condition of the broader agricultural economy is altered by surprise information. This study provides a novel step toward understanding the process by which farmers incorporate new information in their price expectations. For example, our findings suggest that farmers perceive short‐term corn market information surprises will affect the U.S. agricultural sector to a greater degree than their farm. Additionally, farmers do not perceive that short‐term corn market information surprises will carry long‐term implications.

  PublisherOA PDFDOI

Frequent coauthors

• Todd Kuethe

  7 shared

• David B. Oppedahl

  Federal Reserve Bank of Chicago

  2 shared

• Michael R. Langemeier

  2 shared

• James Mintert

  2 shared

• Wendong Zhang

  2 shared

• Brady Brewer

  1 shared

• Sarah A. Atkinson

  1 shared

• Guy Tchuente

  1 shared

Awards & honors

• James C. Snyder Memorial Lecture