Changes in the Supplemental Nutrition Assistance Program (SNAP) after the start of the COVID-19 pandemic included emergency benefit allotments and operation waivers. Using five expenditure-based measures of the nutritional quality of food purchases, we tested whether changes in SNAP during the first year of the pandemic were associated with better nutritional quality of food purchases by participating households with children relative to income-eligible nonparticipating households. Most nutritional quality measures declined from 2019 (pre-pandemic) to 2020 (pandemic) with larger decreases for SNAP households. SNAP participation was associated with small negative differences for nutritional quality of food purchases from stores.
We analyze district-level data for paddy, wheat, and millets (2010-2019) across India to identify yield hotspots with consistently high or rising productivity and coldspots with persistent declines. Spatial clustering and regression analyses show that weather, irrigation, fertilizer use, and farmers' mobile-based information access shape yield performance. Coldspots produce roughly half the yield of hotspots due to lower input and information use. Hotspots cluster in north and southern India, while coldspots dominate the west, east, and northeast. Average yield gaps for paddy, wheat, and millets are 2.0, 2.4, and 1.0 t ha-1, respectively. Closing these gaps could substantially raise farm revenues.
Irrigation is a key agricultural input that can influence nutrition through production and income pathways, yet its role in shaping diets remains underexamined. This study examines the effects of irrigation on food consumption and diet quality among farming households. We find that irrigation adoption increases consumption of milk, wheat, and sugar, but it has a limited or no effect on higher intake of nutrient-rich foods such as vegetables, fruits, legumes, eggs, and meat. Groundwater irrigation has stronger effects on nutrient-dense food consumption than surface water irrigation. These findings highlight the need for nutrition-sensitive irrigation policies to improve access to healthier and more diverse diets.
This paper presents research on the economic value of wildlife watching trips. Our analysis accounts for wildlife mobility and connectivity between viewing sites, which could bias basic welfare calculations, by linking demand to spatially connected, site-specific populations. We examine the potential for bias with an application to birdwatching in Indiana. Viewers value species diversity and population abundance, particularly sandhill cranes. Scenarios that ignore spatial connectivity overstate welfare losses by up to 34%.
Used farm machinery values play a critical role in farm management and in assessing the financial health of the agricultural sector. However, the heterogeneity of machines, particularly regarding embedded technology and usage, complicates efforts to isolate the factors that influence prices. This study leverages a detailed dataset from Tractor Zoom to estimate the effects of machine characteristics and market conditions on auction prices of used 300 to 450 horsepower tractors. We find a nonlinear relationship between machine usage and price: tractors with fewer than 500 hours of use lose approximately $118 per additional hour, while tractors with more than 10,000 hours show only a weakly significant decline of about $2 per hour. We also document pronounced seasonal patterns, with lower prices during the Midwest crop-growing season. These findings provide new evidence on machinery valuation and offer updated insights to inform farmers’ machinery replacement decisions.
This paper extends existing national and regional estimates of Cooprative Extension staffing and funding levels through 2024 and describes changes in Extension program priorities. From a peak of 17,694 professional staff working in Extension nation-wide in 1979, we estimate this declined to 13,188 by 2024. Funding sources for Extension became more diversified over time, relying less on Federal (especially formula) funds and more on State and non-government sources. Program content shifted along with funding sources, with a declining share of Extension resources devoted to agriculture, although with significant differences across States and regions.
This study develops a replicable framework for estimating the size and economic contribution of the bioeconomy and circular economy, using Southern Arizona as an illustrative case. It employs input-output modeling to include multiplier effects, reporting results in terms of jobs supported and value added. Because the framework relies exclusively on publicly available state- and county-level data, it can be readily applied to other U.S. regions, enabling consistent comparison across places and over time.
This article investigates the direct impact of energy prices (Crude Oil and Natural Gas) on agricultural markets (wheat, maize, soybeans) and the indirect effect through fertilizers using monthly data covering the period from January 1990 to February 2021. Additionally, the analysis is further extended up to 2024. The conditional covariances of energy and fertilizer prices capture the spikes in the 2008 crisis and the volatile time after, and the deterministic nonlinear Fourier trends eliminate the unit root problem. The results show that agricultural prices are affected directly by changes in energy prices and indirectly through fertilizer prices.
Researchers have struggled to identify heirs’ property (HP) via the use of real estate records for years. This paper evaluates seven distinct methodological approaches to identify HP using CoreLogic’s national property database. We find minimal convergence among these algorithms, with different methods flagging largely non-overlapping sets of properties. Certain approaches show promise – particularly in identifying properties with characteristics consistent with documented HP patterns. The lack of agreement across methods, however, makes estimating the prevalence of HP difficult. Several paths exist forward to identify HP such as adding extra property characteristics into existing algorithms, developing more sophisticated algorithms, and establishing protocols for cross-jurisdictional validation.
This study investigates consumer preferences for two emerging food waste reduction technologies - gene editing and all-natural spray coating - applied to apples. Using a discrete choice experiment with a nationally representative sample of U.S. consumers (n = 413), we estimate willingness to pay for gene-edited apples, spray-coated apples, and untreated apples. A generalized mixed logit model in willingness to pay space reveals that consumers exhibit the highest WTP for gene-edited apples ($2.45/lb), followed by spray-coated apples ($2.37/lb), with untreated apples valued least ($1.79/lb). Latent Class Analysis identifies three consumer segments: Price-Sensitive Skeptics, Sustainability-Oriented Consumers, and Selective Technology Adopters. Sustainability-Oriented Consumers showed the strongest support for both technologies, while Selective Technology Adopters displayed a clear preference for gene editing. Behavioral attitudes, rather than demographic variables, were the main drivers of segmentation. These findings suggest that tailored marketing strategies and policy interventions, including sustainability messaging, pricing incentives, and educational outreach, can support the adoption of food waste-reducing technologies. Overall, consumers are receptive to both gene-edited and spray-coated apples, though concerns about biotechnology and price sensitivity remain. Results offer insights for producers, retailers, and regulators aiming to enhance fresh produce sustainability and reduce food waste along the supply chain.
Inland valley wetlands in West African countries are considered to hold immense potential for rice-based production systems. Policies to increase rice production in inland valleys have until now not lived up to expectations. Previous studies have examined biophysical factors that affect the adoption of inland valley farming, but little empirical work has explored the socio-economic drivers of adoption. This study explores the determinants of farmers' decisions to adopt inland valley farming and rice production in C & ocirc;te d'Ivoire and Ghana using probit model with data collected from 742 farmers. We show that owners of perennial tree crops are less likely to adopt inland valley farming and rice production than non-owners. This could be because perennial tree crops yield higher economic returns and provide financial stability, also for the next generation, than inland valley farming and rice production. Furthermore, farm size positively correlates with inland valley farming, but households with larger farms tend not to opt for rice production. Our results underscore that the relation between farm size and agricultural production decisions may depend on the type of agricultural practice. These results suggest that policymakers could strengthen local institutions and service providers to target specific groups of farmers when promoting inland valley farming and rice production.
Heirs' property poses barriers to income and wealth generation, especially in rural and underserved communities. Using county-level data from the contiguous U.S., this study examines spatial clustering and socioeconomic correlates of heirs' property prevalence. Results show strong spatial concentration in the South and higher prevalence in counties with large Black populations, rural areas, and Appalachia. Income inequality and financial factors are more strongly associated with heirs' property than poverty. Spatial spillovers suggest that addressing heirs' property in one county may benefit neighbors. Findings highlight spatial dynamics and offer insights for targeting communities and promoting equitable land ownership.
Irrigation can enhance yields and serve as a climate adaptation strategy. In the Southeastern U.S., where water resources are relatively abundant, irrigation has experienced significant growth. However, despite the region’s capacity for further expansion, irrigation adoption rates remain low. This study estimates the influence of peer effects on farmers’ decisions to adopt irrigation in South Carolina, using a unique parcel-level dataset on irrigation withdrawals. We find that adoption increases as farmers observe more peer adopting irrigation – social interactions – and as peers’ pumping increases, such as during drought periods, when the benefits of irrigation become more visible, facilitating social learning.
Traditionally, many meat demand analyses have used publicly available data amassed by the U.S. Department of Agriculture (USDA) and the Bureau of Labor Statistics (BLS). Circana retail point-of-sale scanner data offer an alternative to these publicly available data sources. Scanner data allow for quantity-weighting retail prices to account for increased purchases at lower prices due to sales and promotions. We find that quantity-weighted scanner-based beef and pork prices are lower than those reported by USDA, whereas quantity-weighted chicken prices are higher. Rotterdam demand models are estimated using both publicly available and scanner data sources. Own- and cross-price elasticities estimated using scanner data are greater in magnitude than those estimated using publicly available data, suggesting meat consumers may be more price sensitive than indicated by elasticity estimates from publicly available data sources. Scanner data insights are further explored by estimating demand for meat products with organic or natural claims. Demand elasticities for these differentiated meat products are more elastic than those for meat products without such claims, highlighting a greater amount of consumer price sensitivity when purchasing such products.
Integrated Soil Fertility Management (ISFM) refers to a holistic approach to managing soil fertility that combines a variety of techniques and practices to improve soil health and enhance agricultural productivity, particularly in smallholder farming systems. Despite the associated higher labor and other input demands associated with ISFM adoption, there is limited empirical evidence regarding the positive outcomes of these investments at the household level. Using data from 380 tomato farmers in three regions of Ghana, we explore the relationship between ISFM adoption and household welfare. The methodology employed relies on inverse probability weighting regression adjustment (IPWRA). The findings reveal that ISFM adoption positively impacts household welfare by increasing net income by GH₵436.88 ($60.43)/ha, improving household assets by GH₵518.17 ($71.67)/ha, enhancing food security by 1.23 points, and reducing household expenditure by GH₵57.39 ($7.94)/ha. The results highlight ISFM’s potential to enhance smallholder welfare through increased income, improved household assets, and better food security, contributing to poverty reduction and sustainable agricultural development. Policies should focus on improving access to fertilizers, seeds, and pesticides, coupled with extension services and farmer education programs to promote ISFM adoption. Tailored interventions targeting older and more experienced farmers, as well as household heads, are essential to overcome barriers to adoption and maximize the economic and welfare benefits of ISFM practices.
Smartphones, as more sophisticated versions of mobile phones, are expected to significantly influence how rural households manage their farms. This paper examines the extent to which smartphone ownership affects the adoption of modern agricultural inputs and technologies at the extensive margin. Using a rich, nationally representative household-level dataset from Nigeria and appropriate identification strategies, we find that smartphone ownership increases the likelihood of hiring labor, using phytosanitary inputs, and operating tractors. These findings suggest that promoting the diffusion of modern digital tools in rural areas can complement traditional agricultural input support programs, offering a promising avenue to enhance agricultural productivity and livelihoods in Nigeria.
Although forests play a vital role in US climate strategies, US forest area is expected to decline in the coming decades. Policymakers can help arrest or reverse that decline by strengthening incentives for forest carbon sequestration. Increased funding for afforestation, restoration, and bioenergy and wood products market development will likely benefit the forest sector unevenly across geographic, commercial, and demographic dimensions. This review explores the effects of policies – particularly incentives for afforestation and reforestation, carbon credit market participation, and wood products utilization – on US forest communities. We describe this policy landscape and use various data to investigate effects on diverse stakeholders, with special emphasis on the implications for disadvantaged and forest-dependent communities. Afforestation policies in the South-Central region could significantly enhance carbon dioxide removal while reshaping rural dynamics. Forest carbon credit markets, though crucial for climate goals, may disadvantage small forest owners and communities, instead favoring large corporate entities. Policies promoting wood products in the South-Central region could benefit forest-dependent, high-poverty communities. We also note how policy implementation might ensure an equitable distribution of climate-related benefits among stakeholders in the forest sector.
An increasing number of disaster relief programs rely on weather data to trigger automated payouts. However, several factors can meaningfully affect payouts, including the choice of data set, its spatial resolution, and the historical reference period used to determine abnormal conditions to be indemnified. We investigate these issues for a subsidized rainfall-based insurance program in the U.S. using data averaged over 0.25° × 0.25° grids to trigger payouts. We simulate the program using 5x finer spatial resolution precipitation estimates and evaluate differences in payouts from the current design. Our analysis across the highest enrolling state (Texas) from 2012 to 2023 reveals that payout determinations would differ in 13% of cases, with payout amounts ranging from 46 to 83% of those calculated using the original data. This potentially reduces payouts by tens of millions annually, assuming unchanged premiums. We then discuss likely factors contributing to payout differences, including intra-grid variation, reference periods used, and varying precipitation distributions. Finally, to address basis risk concerns, we propose ways to use these results to identify where mismatches may lurk, in turn informing strategic sampling campaigns or alternative designs that could enhance the value of insurance and protect producers from downside risks of poor weather conditions.
The term resilience has begun to proliferate in regional economic literature over the last decade as more and more authors have sought to connect the term to economic shocks. Resilience as a concept is not new, particularly for ecology and engineering, but its use in regional economic analysis is more recent. Many authors have sought to define and measure the resilience of regions to exogenous shocks, utilizing multifaceted interdisciplinary approaches. This paper uses a bibliometric approach to conduct an in-depth critical review of both the definitions and metrics associated with regional resilience. We found 98 unique studies that were reviewed to collate and analyze methods and indicators used to measure regional economic resilience. Our analysis identified 202 unique metrics (e.g., educational attainment) associated with regional economic resilience that can be aggregated into 15 overarching themes (e.g., demographics), and represented in 3 distinct clusters (e.g., community development).
Integrating nature and green space into urban areas is a growing social challenge. The dollar value that renters place on public amenities when choosing where to live is essential for policymakers and urban planners looking to provide equitable access to environmental amenities and other public goods. This study estimates renter willingness to pay (WTP) for urban green space in the greater Boston area, utilizing a sorting model framework with data on census, transit, and neighborhood quality measures. My results suggest that renter household WTP is between $1.17 and $1.64 for an additional percentage point of urban green space in their location decisions. I examine differences in WTP for green space between white and minority renters, uncovering both shared and divergent sorting behaviors, as well as disparities in the distribution of environmental benefits across groups.
