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.

Heirs’ property is a form a land tenure that can negatively impact landowners, particularly those who want to use their land for agricultural purposes. Over the past decade there has been an increase in legal reforms and assistance programs aimed at addressing issues associated with heirs’ property. Yet, this phenomenon has received little attention in the applied economics literature. With the aim of motivating future economic research, we make the following two contributions. First, we synthesize the existing multi-disciplinary literature on heirs’ property into an economically tractable framework. Second, we use parcel-level tax record data from 2015 and 2021 to track changes to the amount of heirs’ property over time and examine its rate of formation net of land leaving heirs’ property. We examine the changes to heirs’ property on non-agricultural and agricultural parcels (and the number of acres of land within parcels) separately. We find that the total number of parcels and acres, on non-agricultural lands, declined by about one percent and six percent, respectively. Whereas, acreage on heirs’ property agricultural lands decreased by about two percent. These small changes mask large transitions in and out of heirs’ property. Our estimates suggest that the formation of heirs’ property persists today and offsets most of the reductions obtained from land leaving heirs’ property. Additional analysis reveals significant heterogeneity across regions and localities.

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.

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 article serves as an introduction to the Special Issue section “Measuring and Enhancing Resilience of United States Rural Communities in the Context of Climate Variability.” To set the stage for this section, we review how climate hazards impact rural areas and synthesize insights that emerge across the issue’s four papers, noting their policy relevance and highlighting opportunities for continued research. We argue that emerging data tools can help program designers and policy makers better support the resilience of rural areas, but that doing so remains complicated by heterogeneity in resources and vulnerabilities across rural areas.

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).