Efficient phosphorus (P) management is essential for balancing agricultural productivity and environmental outcomes. Using high-resolution experimental data and Bayesian Hierarchical Model, this study examines how soil heterogeneity shapes yield responses to a fixed P application. Results show strong context dependence: the yield response to the fixed P treatment varies with baseline M3P, soil buffering capacity, and neighboring M3P. Economic simulations indicate that site-specific P management increases net returns by $13.21 per acre relative to the current recommendation, while reducing P inputs by up to 60.9%. The enhanced-information rule generates on-farm benefits $18.1 million annually in Kentucky.

As fertility rates drop to another historical low, understanding the economic burden of child-rearing on household income, a main economic reason for falling birth rate, has become more crucial than ever. This study calculates a subjective equivalence scale explaining how much the income of a two-adult, one-child household should increase to maintain the same level of life satisfaction as a two-adult household, using a nationally representative U.S. sample. The results suggest that the equivalence scale for a two-adult, one-child household is 1.18, indicating that raising a child costs 18 % of a two-adult household’s income. Our analysis indicates that programs like the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and the National School Lunch Program (NSLP) may be overly generous for households with one child, while the tax deduction policy does not cover child-rearing costs sufficiently.

This paper uses China’s 2016 Pollutant Discharge Permits System (PDPS) to evaluate its impact on innovation in the food processing industry. We begin by exploring the entry and exit decisions of food processing firms. The findings suggest that stricter environmental enforcement following the PDPS leads to decreased local firm entry but increased neighboring firm entry, indicating that new firms tend to locate in neighboring regions with less stringent regulations. Building upon this pattern, we argue that the PDPS’s positive impact on firm innovation is primarily driven by increased industry agglomeration – a dynamic directly stimulated by heterogeneous regulatory pressures.

The U.S. agricultural trade deficit has increased in the past two years, echoing trade patterns between the U.S. and China. This report focuses on U.S. agricultural trade with China, a main trade partner in the 1st quarter of 2024, despite total import and export volume between China and the U.S. falling by 32.8% compared to the same period in 2023. On the import side, tobacco and vegetables increased, while seafood products and fruits decreased. On the export side, soybean, corn, and meat products significantly declined, while wheat and cotton increased. Additionally, this report highlights the U.S.’s immense potential advantage in alfalfa trade with China. Changes in China’s dietary structure, especially the growing demand for dairy products, may turn alfalfa trade into a new highlight.

Socioeconomic-related health inequality remains a crucial topic in health eco- nomics, where the Concentration Index (CI) is commonly used to quantify dispari- ties. However, applying CI is challenging due to the common categorization of income data in survey datasets. Building on the KWD framework proposed by Kakwani et al. (1997) and extended by Chen & Roy (2009), this study develops a novel ma- chine learning-based Concentration Index (ML-CI) to improve inequality estimation under categorical income data. Both the simulation and empirical results show that ML-CI recovers the true level of inequality more accurately and more consistently, and its performance remains stable across a range of sensitivity analyses and alter- native simulation settings. We apply this method to the USDA’s Purchase to Plate Crosswalk (PPC), which links Circana (formerly IRI) household scanner data with the USDA Food and Nutrient Database for Dietary Studies (FNDDS). This allows us to compute both purchased kilocalories per adult-equivalent household member and Healthy Eating Index (HEI) scores for each household, making this one of the first studies to directly quantify dietary inequality in the U.S. Our findings reveal a pro- rich gradient in HEI scores in the U.S., indicating healthier diets among wealthier groups, while kcal/capita exhibits a pro-poor distribution, reflecting higher calorie consumption but less nutritious diets among lower-income groups.

This study investigates the trade implications of agricultural Voluntary Sustainability Standards (VSSs), with a novel distinction between Quality-Enhancement (QE) and Labor Welfare (LW) certifications. While VSSs are increasingly adopted to address sustainability concerns in agriculture, their trade effects remain ambiguous. We develop a theoretical gravity model grounded in Melitz (2002) to explore how product quality improvements and labor welfare gains influence trade, and test these mechanisms empirically. Decomposing trade into intensive and extensive margins, we find that QE-VSSs significantly boost both trade volume and new trade relationships in the short term, with effects tapering after four years. LW-VSSs, in contrast, show delayed benefits: while their early impact on trade is statistically indistinguishable from zero, they enhance trade volume in the longer run. Heterogeneity analyses reveal that developing exporters trading with developed importers benefit most from both types of standards, especially under non-mandatory frameworks. We also find that VSS adoption is associated with a reduction in income disparity, suggesting that sustainability standards may support more inclusive global trade. Our findings highlight the differentiated trade mechanisms of QE- and LW-VSSs and underscore the need for tailored policy support to balance sustainability objectives with trade competitiveness.

The effects of public food safety disclosures on consumer online purchasing behavior remain insufficiently understood. In 2025, Consumer Reports identified heavy metal contamination in selected infant formula products, raising widespread safety concerns; among leading brands, certain Similac products were labeled as “Worse Choices,” whereas its primary competitor, Enfamil, received more favorable ratings. This study examines how such disclosures affect online sales and pricing dynamics. Hourly price and sales rank data were collected from Amazon via Keepa from January 2024 to February 2026, and a regression discontinuity in time (RDiT) design was applied to estimate causal effects. The results indicate no significant short-term price responses for either Similac or Enfamil following the disclosure. However, sales rank improved for unflagged Similac products (τ = −0.892; 95% CI: −1.109, −0.675; p < 0.001), suggesting increased demand, while flagged Similac products experienced a deterioration in sales rank; Enfamil exhibited no statistically significant change. Overall, the findings suggest that consumers respond to product-specific safety disclosures by reallocating purchases within a trusted brand toward safer options rather than switching across brands or reacting through price adjustments, highlighting the importance of targeted safety information in shaping consumer choice in online markets.

Equivalence scales measure the income difference needed to compare income across households of different sizes and types, important for policy actions such as setting welfare program eligibility thresholds in an equitable manner. Empirical estimates of equivalence scales have been subject to criticism over features such as significant sensitivity to identifying assumptions. This paper presents a Bayesian method of combining estimates of equivalence scales from two disparate sources of empirical estimates: surveys and scanner data. We treat estimates from a survey in which respondents were asked how much extra (or less) income it would take to equalize their financial situation if their household size went up (or down) as our prior. Then we use revealed expenditure patterns from households with two adults and either with zero or one child as our data and numerical Bayesian techniques to estimate a posterior distribution of the equivalence scale for this change in household type. This takes advantage of the fact that while Bayesian methods are typically thought of as a method for combining subjective prior beliefs with data-based information, they are actually a flexible, optimal method for combining any two sets of information on the same measures of interest. Our results provide insight on the equitable setting of poverty lines and welfare program eligibility standards as well as provide a future framework for producing more robust estimates by utilizing multiple different data sources. Further, the Bayesian methodology raises red flags when empirical estimates of equivalence scales from the two sources disagree to such an extent that the combined estimates (and at least one of the component estimates) should be considered unreliable.

Precise and reliable measurement of food insecurity rates not only informs and shapes public food policy but also serves as an indicator of the effectiveness of broader public policies aimed at enhancing household welfare. This paper examines the consistency of the measurement of household-level food insecurity using the USDA’s “Food Security Module”, an instrument in use for almost 30 years. Applying Tree-based item response models, known as IRTree models, this study verifies areas of the FSM and data coding process that are effective and reveals other parts that could benefit from improvements. The results confirm the validity of current practice, which treats invalid responses, such as “Don’t know” or “Refused” or “No response”, as random missing data. Furthermore, the results support the practice of treating all affirmative responses, such as “Often true” and “Sometimes true” as equivalent when determining the level of food insecurity among households. However, the Screen-out process before the second stage of the Module leads to information loss. Moreover, the analysis reveals racial discrepancies in the measurement outcomes, with food insecurity rates being underestimated for “Black or African American” and “American Indian or Alaska Native” groups relative to others. These results suggest further research to confirm them and perhaps some pilot testing of alternative wording to ensure the continued reliability of the FSM.