Resource (United States)

ABSTRACT This study examines the competitiveness between Latin American and U.S. livestock and meat sectors. We employ a computable general equilibrium modeling framework to evaluate two scenarios: coordinated improvements in Latin American productivity, transport efficiency, and market access (Scenario I), and the minimum productivity gains required in the U.S. to regain its competitive position given improvements from Scenario I (Scenario II). Results highlight Latin America's transformative potential through advancements in technology, infrastructure, and trade, while emphasizing the importance of U.S. strategies to maintain market leadership. Policy implications focus on innovation, supply chain efficiency, and trade agreements to ensure sustained global competitiveness.

ABSTRACT We study how expanding alcohol availability at grocery and convenience stores affects consumer traffic in liquor stores by leveraging recent changes in state‐level alcohol distribution laws in a difference‐in‐difference quasi‐experimental design. Results indicate that more extensive liberalization results in higher losses of traffic at liquor stores and that the impact is dynamic over time. Additionally, the overall impact at rural stores is larger compared to urban stores. We discuss the economic, geographic, and behavioral factors behind the heterogeneous impacts of the policy and develop a general theory of the effects of liberalization on the liquor store sector.

Abstract Literature examining the effects of changes in trade agreements and import competition on US employment and wages has focused primarily on non‐agricultural industries and changes in US import tariffs. We propose a method for measuring worker exposure to changes in agricultural tariffs using a newly developed county‐level dataset of employment shares by crop and livestock type. We apply the method to examine the spatial concentration of US county‐level employment‐weighted exposure to changes in tariffs caused by the North American Free Trade Agreement (NAFTA). Results reveal noteworthy decreases in average US county‐level crop and livestock employment exposure to Mexican import tariffs on US products. Findings also show spatial variation in US employment exposure to changes in Mexican import tariffs on US agricultural and non‐agricultural goods. Changes in county‐level employment exposure to US and Canadian import tariffs after NAFTA implementation are relatively minor given low initial tariff rates prior to the agreement.

Discoloration of beef products leads retailers to offer discounts or discard beef products, as consumers tend to reject a brownish beef color. This practice contributes to retail food waste and inefficient resource allocation linked to beef production. The objective of this study was to investigate U.S. consumer preferences for beef color and price discounts. After an initial test for screen acuity regarding color perception using a condensed form the ishihara test, data on meat purchasing behavior as well as demographic information was collected for all participants. An additional part of the study undertook a hypothetical discrete choice experiment using digital photos of beef steaks with different meat color, price, and discount labels in retail packaging to examine consumer preferences, willingness to pay, and the effects of discount pricing. Results of a Mixed Logit Model based on choice data show that beef shoppers perceive, see, and prefer color nearly linearly across days of retail display. Consumers' willingness to pay was negative for 4, 7 and 9 days of retail display relative to day zero and decreased with an increase in discoloration. Results indicate that beef shoppers would have to be financially compensated for choosing a steak that was discolored after 9 days of retail display. However, male beef buyers exhibit weaker preferences for color and could be a target segment for promoting discolored beef products to reduce meat waste.

The Foundations for Evidence-Based Policymaking Act of 2018 and supporting open science efforts offer a new opportunity for federal agencies to enhance government data ecosystems that improve public access to federal data. Public engagement will be critical to ensure that the efforts are sustainable. This article focuses on learning from other models to provide insights into building successful user engagement, drawing from fields as diverse as marketing, psychology, health care, economics, and information systems.

In the final months of 2022, two substantial earthquakes with magnitudes exceeding ML 5.0 hit West Texas, USA, causing widespread public concerns about the effect of industrial activities on human and environmental safety. The monitoring of earthquakes in this region is largely based on the data of the public regional seismic array, which consists of stations spaced typically tens of kilometers apart. Accurate hypocenter determination of these induced events is crucial as it provides insight into the triggering mechanism, enabling operators and regulators to develop effective mitigation strategies. However, there are debates regarding the accuracy of the publicly reported induced event data due to discrepancies between public reports of event hypocenters and those determined using local dense arrays operated by private companies. The primary objective of this study is to identify the underlying causes of the discrepancies between results obtained from the public regional array in West Texas and local dense arrays. Through modeling and analysis of field data collected by a local dense array in the Permian Basin, we determine that three critical factors influence the reliability of induced event results. First, the accuracy of the velocity model used for the event location is the most crucial factor. Second, the distance between a station and an event plays a crucial role in determining the sensitivity of the data to the hypocenter depth. Finally, consistency between the observed and modeled wave propagation behavior is crucial for ensuring the validity of the objective function in the inversion. Our findings indicate that it is challenging to obtain reliable hypocenters using a regional sparse array with station spacing on the order of tens of kilometers. The best practice for obtaining an accurate event hypocenter and magnitude is to monitor induced seismicity using a local dense array and process the data with a velocity model that fully characterizes the local basin’s geology.

PurposeClimate change is expected to cause larger and more frequent precipitation events in key agricultural regions of the United States, damaging crops and soils. Subsurface tile drainage is an important technology for mitigating the risks of a wetter climate in crop production. In this study, the authors examine how quickly farmers adapt to increased precipitation by investing in drainage technology.Design/methodology/approachUsing farm-level data from the 2018 Agricultural Resource Management Survey (ARMS) of soybean producers, the authors construct a drainage adoption timeline based on when the operator began farming their land and when tile drainage was installed, if at all. The authors examine both the initial investment decision and the speed with which drainage is installed by adopters. A Heckman-style Poisson regression is used to model the count nature of adoption speed (measured in years taken to install tile drainage) and to correct for potential sample-selection bias.FindingsThe authors find that local precipitation is not a significant determinant of the drainage investment decision but may be highly influential in the timing of adoption among drainage users. Farms exposed to crop-damaging levels of precipitation install tile drainage faster than those with low to moderate levels of rainfall. Estimates of farm adaptation speeds are heterogeneous across farm and operator characteristics, most notably land tenure status.Originality/valueUnderstanding how US farmers adapt to extreme weather through technology adoption is key to predicting the long-term impacts of climate change on America's food system. This study extends the existing climate adaptation literature by focusing on the speed of adoption of an important and increasingly common climate-mitigating technology – subsurface tile drainage.

Abstract Cooperative management of shared groundwater resources in the High Plains region of the United States is critical to support sustainable agricultural‐based economies. This research uses a repeat‐sample survey of agricultural producers in the states of Colorado and Nebraska to analyze how seasonal changes and variation in stress and salience influence support for groundwater management. We find that support for groundwater management tends to be lower in the fall, when agricultural producers are engaged in harvest activities. The results also reveal that changes in the salience of commodity prices and water availability can drive changes in support for groundwater management.

The original article has been corrected. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract In the US, elderly households are more food secure than younger households. A possible explanation is that increased time availability enables elderly households to adopt strategies to improve their food security. Using time use data, we find elderly households spend more time in meal preparation and eating time than younger households. Creating a matched dataset of household time use and food security, we find that meal preparation and eating time have a small contribution to differences in food insecurity between older and younger households. However, these relationships are heterogeneous depending upon marital status and age cohort of the household head.