Abstract

The adoption of genetically engineered (GE) crops has reshaped U.S. agriculture, yet its implications for market power in agricultural input industries are still not well understood. This study examines how GE seed innovation affects markups, profitability, and input relationships across fertilizer, chemical, seed, machinery, multiproduct, and “Big Six” biotechnology firms. Using firm-level Compustat data and production-based markups estimated under a Leontief structure, we find that fertilizer firms experienced rising markups that translated into higher profits. However, multi-product firms and the Big Six experienced large increases in markups following GE adoption, but higher prices charged were primarily used to offset rising overhead costs, including R&D. Regression results and counterfactual analyses further indicate that GE technology has increased market power for multiproduct firms and the Big Six, with markup increases that were substantially larger than those for pure seed producers, indicating strengthened complementarities between seeds and crop protection chemicals, reducing farmers’ ability to substitute across input suppliers. 

Abstract:

This study examines the official announcement effect of the Market Facilitation Program (MFP) and the Coronavirus Food Assistance Program (CFAP) on the corn and soybean futures market. Using a permutation test and a 2-stage GLS model, we find no significant official announcement effect. However, pre-official announcements significantly increase futures contracts' full-trading day volatility—by 0.945% (4 cents) for corn and 1.301% (16 cents) for soybeans. These findings suggest that information may have been absorbed by the market prior to the official announcements, indicating market efficiency. Moreover, the results highlight that pre-official announcements successfully serve as signals to boost market participants' confidence in the short term following a negative market shock. 

Abstract

The U.S. Federal Reserve has undertaken several interest rate interventions in the past decade. This study explores the relationship between U.S. corn and soybean prices and Federal Reserve monetary policy interventions, in the short and long run. We use a nonlinear autoregressive distributed lag model to capture three key features of agricultural commodity price responses to changes in interest rates. Firstly, we observe that corn and soybean prices initially overreact to changes in interest rates, overshooting their long-run equilibrium before gradually reverting. Secondly, in the short run, the relationship between soybean prices and interest rates is asymmetric; the initial price change is more pronounced for an interest rate increase than for a decrease of the same magnitude. Lastly, both corn and soybean prices display symmetry in the long run. These results help to understand how changes in interest rates affect commodity prices. Assessing the relationship between agricultural commodity prices and interest rates can assist farmers and processors in planning investments and loans based on interest rate forecasts.

Abstract

The U.S. Department of Agriculture’s (USDA) World Agricultural Supply and Demand Estimates (WASDE) play a central role in how agricultural commodity markets process information about supply, demand, and prices. This study examines how global and domestic shocks, as well as policy interventions, are reflected in the similarity of WASDE forecasts and forecast errors across eight major U.S. crops, including corn, soybeans, wheat, sorghum, barley, oats, rice, and cotton. Using Dynamic Time Warping (DTW), we measure the distance between forecast series or forecast error series to quantify the degree of similarity across crops. Using WASDE data from marketing years 1999-2000 to 2022-2023, results show that crop forecast series have more distinct forecast patterns, while their forecast errors are more similar across crops, suggesting that the forecast errors may be due to the common market shocks affecting all crops. Additionally, using regression models controlling for government payments and economic recessions, we find that greater forecast similarity is associated with larger forecast errors, especially for cotton and rice ending stocks. Government payments are associated with lower forecast errors for trade-related variables (export and import), but higher errors for crop price and yield, whereas recessions are associated with lower area harvested forecast errors. These findings can help inform adjustments and improve the overall accuracy of the WASDE forecasts.

Abstract

The number of U.S. farms has declined to 1.9 million and the total operated acres have declined to 880 million acres, while the average farm size has increased to 463 acres (Census of Agriculture). More beginning producers are entering farming, who are younger, work more off-farm, and manage smaller operations.