Numerous studies have been conducted to comprehend the economic importance of market participation for producers. However, a significant gap remains, particularly in Central Asia. This study assesses market participation drivers for Kyrgyzstan’s milk producers using the Life in Kyrgyzstan dataset, encompassing a comprehensive nationwide farm-level survey. Findings reveal that household assets boost market entry and sales volume, whereas distance from markets discourages participation but can increase sales for active sellers, reflecting transportation cost strategies. The insights inform policy interventions benefiting rural small-scale milk producers in Central Asian countries that share similar cultural backgrounds.

This work shows that direct combustion of cotton gin waste (CGW) at cotton gins can profitably generate electricity. Many bioenergy processing centres emphasise very large-scale operations, which require a large and stable bio-stock supply that is not always available. Similarly, a small biorefinery processing gin trash at a cotton gin must wrestle with the high volatility of cotton yields and price variation in cotton and electricity. Fortunately, the smaller scale allows these risks to be somewhat countervailing. Low cotton yields allow the limited gin trash available to be applied to the highest peak electricity prices in winter. Similarly, high yields with low cotton prices generate revenue from power generation throughout high winter electric prices.

To assess the profitability of an onsite power plant requires high-resolution data. We utilise hourly electricity price data from 2010 to 2021 in West Texas and obtain a small data array of 15 years of gin trash at a medium-sized gin. Prior analyses have had neither. We leverage limited CGW data to better leverage generous electricity price data by generating a Bayesian distribution for CGW. We simulate 10,000 annual CGW outcomes and electricity prices. Using engineering parameters for combustion efficiency, we show the expected internal rates of return of 19–22% for a 1 MWe and a 2 MWe plant at a small gin. Simulations then compare economic returns to the variance of those returns, which allows the analyst to present to investors a frontier of stochastic dominant return outcomes (risk-returns trade-off) for plants of different sizes at different sized gins.

Little is known about the preferences of US at-home gardeners for potting mix characteristics. This study uses a Best-Worst Scaling approach to evaluate consumer preferences for eleven characteristics of potting mix. The most important characteristics identified are formulated for specific plant or garden types, pre-mixed ingredients, and price. The least important are the brand, packaging, and home delivery. There is some variation in the relative importance of these potting mix characteristics depending on consumer demographics. This study guides Industry stakeholders and policymakers on product development while enhancing environmental sustainability.

We analyze 2017–2021 data to examine whether weekly options offer unique insights compared to regular options on grain futures. These weeklies, increasingly popular for short-term use around major United States Department of Agriculture (USDA) reports, are found to be more effective in predicting near-term volatility, challenging the conventional view of longer-dated options’ superiority. However, they overprice realized volatility by 420 basis points (bps) for corn and 280 bps for soybeans. Major USDA reports add a premium of 650 bps for corn and 240 bps for soybeans, highlighting a trend toward more time-sensitive trading strategies, though the long-term impact on market efficiency of weeklies remains subdued.

The USDA has implemented policies to address inequities for socially disadvantaged farmers and ranchers. This research examines agricultural risk inequities and the impact of 2018 Farm Bill programs on crop insurance use among minority and veteran farmers. Results indicate that minority and veteran farmers are disproportionately located in regions of the U.S. with higher risks of drought and excess precipitation. Yet, these producer groups had lower use of crop insurance prior to the implementation of the 2018 Farm Bill. However, the incentive programs created under the 2018 Farm Bill have increased use of federal crop insurance among these vulnerable populations.

This study explores several alternative specifications of futures-based forecasting models to improve existing approaches constrained by restrictive assumptions and limited information sets. In lieu of historical averages, our approaches use rolling regressions and include current market information reflected in the deviation of the current basis from its historical average. To mitigate potential challenges arising from nonstationarity and structural changes in the relationship between farm and futures prices, we employ a 5-year rolling estimation window. We find that a rolling regression approach offers significant improvements (as evidenced by our Modified Diebold–Mariano test) in the accuracy and information content of forecasts of cotton season-average prices (SAPs) mostly at short forecast horizons.

In this paper, we examine the effect of the “Fresh From Florida” marketing program on the preferences of consumers located in geographically distant regions. We administered a choice experiment to consumers from the Northeastern region of the US, the Eastern region of Canada, and from Florida. Our findings show that the logo recall rate is significant for out-of-state consumers. While the WTP for the “Fresh from Florida” attribute is not statistically significant for Northeastern US respondents, logo recall positively influences the WTP. Logo recall positively affects WTP in Canada, but only for respondents with positive or neutral opinions of Florida.

The study analyzes productive efficiency of crop farming in the EU. We use publicly available data on crop farming from FADN database. Standard efficiency measurement techniques based on frontier analysis indicate that the representative farms provided in the database are fully efficient, even though there is ample evidence in the literature that this is highly unlikely. We find that this is a consequence of overly restrictive assumptions about the compound error in standard SF models. The efficiency benchmark, based on the best model given data with generalized error specification, reveals substantial differences in crop farming efficiency in the EU.

Past research shows that farm animal welfare (FAW) policies can reduce consumer and retailer welfare, but producer welfare implications are less certain. This study uses equilibrium displacement modeling of the U.S. wholesale shell egg market to determine how the transition to cage-free egg sales could affect short- and long-run producer welfare. Under varying assumptions and retailer demand shifts, the results consistently demonstrate that producer profits are expected to decline as retailers pivot toward cage-free purchasing, holding all else constant. These findings help explain the tension surrounding FAW policies across the supply chain and can be used to inform industry and policymaker discussions on the topic.