The stock-to-use ratio (STU) is a widely utilized indicator to assess market conditions and forecast price movements for agricultural commodities. However, before drawing any conclusions, it is essential to empirically investigate the relationship between STU and commodity prices. Using rice as a case study, this research examines the empirical linkage between rice prices and STU, both collectively and individually across 16 leading rice-producing and consuming countries. To do so, the study first employs the panel vector autoregression approach to capture the dynamic interrelationships in a panel data setting, followed by vector autoregression estimation at the individual country level. The results suggest an inverse relationship between rice prices and STU: higher rice prices are associated with lower STU levels (i.e., higher scarcity), and vice versa. Furthermore, the Toda-Yamamoto Granger causality tests indicate that monitoring the STU levels of a select group of influential countries can yield significant insights into global rice export price dynamics. In addition, the analysis highlights the pivotal role of urea fertilizer in maintaining the stability of global rice prices. These findings are particularly relevant in the context of strong government intervention in managing rice stocks in several key rice markets.

The cattle feeding industry is sandwiched between relatively volatile commodity markets, and efficiency is critical. Changing prices for feedstuffs may cause substitution and output effects, in turn impacting technical efficiency. Using Kansas feedlot data, we estimate the effects of feed prices on cattle performance, focusing on the feed conversion ratio, average daily gain, and days on feed. Results show that several feed prices do indeed impact technical efficiency. These results have implications for management adapting to changing feed prices. Further, there are policy implications for programs that may impact commodity prices.

Fisheries industry plays a crucial role in addressing food and nutrition security challenges in developing countries. This study examines the dynamics of price pass-through along the spatial markets in Sri Lanka. Findings reveal that Colombo and Kandy markets are the main driver of price pass-through due to their strategic locations and advanced infrastructure. We further identify that one standard deviation positive price shock in Colombo and Kandy markets has an immediate significant impact on other regional markets. Policies related to improving transportation and cold storage facilities can help to reduce reliance on central markets for nationwide distribution.

Since the Conservation Reserve Program (CRP) was created in 1985, producers in the United States (US) have voluntarily enrolled their environmentally sensitive agricultural lands for conservation in exchange for an annual rental payment. However, enrollment in General CRP has been decreasing over time. This study used a discrete-time duration analysis model to examine factors influencing the length of time producers in the southeastern US (n = 5000) take to enroll in the General CRP. Younger producers enrolled relatively faster than their older counterparts. Furthermore, increased total land area, awareness about CRP, and positive perspectives on the sign-up ranking process reduced overall time to enrollment.

We investigate the optimal asset allocation and repayment strategy of an agricultural loan under a guaranteed repayment condition in a continuous-time setting. We propose two forms of the problem: an analytically solvable “separable” problem and a more realistic “nominal” problem that is investigated numerically. In the numerical study, we calibrate our model to publicly available farm data and explore various forms of repayment structures. While the widely used constant repayment structure has a surprisingly outstanding performance, we also design two repayment structures for the nominal problem that perform quite well.

This study estimates correlates of willingness-to-pay (WTP) for routine, elective, and urgent equine veterinary services in the United States. Through a nationwide online survey of US horse owners aged 18 and older, a payment card approach was utilized to elicit WTP for annual vaccinations, a lameness exam, and emergency colic surgery. Based on the results from an interval regression model, we found that financial capacity, income level, and the number of horses owned were significant predictors of WTP across all three service types. These findings have implications for equine veterinary practice management and client communication regarding treatment costs.

This study tests for sample selection using data from a feedlot in Oklahoma by analyzing the distribution of cattle quality between alternative marketing arrangements and cash markets. Unlike previous studies employing Heckman and Roy models to detect sample selection, we directly examine the empirical distributions of cattle quality variables derived from heteroskedastic probit, residual, truncated, and generalized least squares regressions. Nonparametric procedures are used to identify differences in the empirical distribution functions of quality variables between the two markets. The results find strong evidence of sample selection in cattle procurement for the analyzed dataset. Initiatives promoting greater disclosure of quality-related information for cattle sold in the cash market are recommended to mitigate this issue.

Understanding how households adapt to hurricanes is increasingly important as these events become more frequent and severe. This paper examines how past hurricane exposure influences current household preparedness, focusing specifically on the stockpiling of bottled water. Leveraging scanner data on bottled water purchases for households in the Southeastern United States, we employ a difference-in-differences event study framework to analyze how repeated hurricane experiences affect consumer behavior. Our results indicate that households exposed to hurricane warnings do not increase their preparedness in the subsequent hurricane season, and those experiencing a landfall event underprepare. These results suggest limited learning from past events.

The German grain legume market is characterized by fragmentation and limited competition, restricting farmers’ market access and legume cultivation. The aim of this study is to analyze the current trader structure and optimize its configurations using k-means clustering. Results reveal a concentration of traders in southern and western Germany, while many farmers lack access to traders, even within a 100 km radius. A more competitive market can be achieved without increasing the number of traders, but by expanding their trading distance between farmers and dealers. Optimized site selection is of central importance in this context. Policy should create incentives – for example, by supporting digital platforms – that encourage farmers to engage with more traders through improved information and transparency, and conversely, motivate traders to expand their service radius via drop shipping.