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Literature shows that religiosity can provide individual resilience to life shocks as well as regional resilience to disasters caused by natural hazards. Related work has examined the complicated links between religion and economic growth. Yet few, if any, studies examine the role of regional levels of religiosity on a region's resilience to recession—or how quickly the employment rate returns to pre-recession levels (a common measure of resilience in the economics literature). As the recovery period of the Great Recession cools and economists warn of future economic downturns, all known variables that may be linked with regional resilience are worthy of exploration. Using survey results from the Gosling-Potter Internet Project and General Social Surveys, we applied logarithmic functions to pre- and post-Great Recession employment data for 2,836 U.S. counties. We found a modest and statistically significant association between religious belief and regional resilience to recession. Religiosity was the strongest of sixteen psychosocial variables that we examined in association with the speed of job recovery; despite having negative links with other economic variables. This has particular salience for more rural economies; policy implications are discussed.

Dairy-related Extension programming is important in many states, but the economic impact of such programming has received little attention. We examined the impact of Know Your Numbers, an educational program offered by the Penn State Extension Dairy Team. Using follow-up evaluation data and the economic impact tool IMPLAN, we estimated that the program had a total financial impact of $9.5 million and an employment impact of 69 jobs in 2014. The overall financial impacts of the Dairy Team, given its abundance of other programming, likely are significantly higher. Our approach for estimating the economic impact of an Extension program can be used by others to understand and demonstrate the value of their work.

This study tests for potential bias in self-reported innovation due to the inclusion of a research and development (R&D) module that only microbusinesses (less than 10 employees) receive in the Annual Business Survey (ABS). Previous research found that respondents to combined innovation/R&D surveys reported innovation at lower rates than respondents to innovation-only surveys. A regression discontinuity design is used to test whether microbusinesses, which constitute a significant portion of U.S. firms with employees, are less likely to report innovation compared to other small businesses. In the vicinity of the 10-employee threshold, the study does not detect statistically significant biases for new-to-market and new-to-business product innovation. Statistical power analysis confirms the nonexistence of biases with a high power. Comparing the survey design of ABS to earlier combined innovation/R&D surveys provides valuable insights for the proposed integration of multiple Federal surveys into a single enterprise platform survey. The findings also have important implications for the accuracy and reliability of innovation data used as an input to policymaking and business development strategies in the United States. [ABSTRACT FROM AUTHOR]

Schools that fail to make "adequate yearly progress" under NCLB face sanctions and may lose students to other schools. In smaller schools, random yearly variation in innate student ability and behavior can cause changes in scores that are beyond the influence of teachers. This study examines changes in reading and math scores across Pennsylvania's schools over time. There is no evidence that rural or smaller schools are systematically disadvantaged by NCLB. In smaller schools, 80% of the increase in scores is estimated to be caused by factors that generally cannot be influenced by school staff. Some schools likely should have received an award in a given year, but failed to earn one because nonpersistent factors reduced their scores to a level that disqualified them. Poverty depresses the gains achieved by schools, but small schools are able to offset the negative effect of poverty on changes in scores over time. Also, increases in poverty in a district reduce the gains in scores that can be achieved.

We use state-level Census Household Pulse Survey data to examine the role of community food services such as food banks and pantries in reducing food insufficiency during the COVID-19 pandemic in the United States. Food insufficiency increased for all income classes during the pandemic, and especially for the lower and middle classes. We adopt a fixed effects filtered estimator to estimate the coefficients on time-invariant regressors in a fixed effects panel model. Estimation results suggest community food services contribute to mitigating food insufficiency, especially for the middle class and in the early months of the pandemic. [ABSTRACT FROM AUTHOR]

The statistical analysis of the spatial effects of political factors on infrastructural development and the regional trends of poverty in the United States is presented.

A study on measuring the production of social capital at the level of United States counties is presented. A production function for social capital is also discussed.

The development of interlinked markets in the African context under certain preconditions, as well as the failure of markets and the emergence of indigenous institutions, is discussed. The discussion is made within the framework of production relations in land-abundant tropical agriculture. An annual cash crops production in a subsistence-oriented agrarian system is suggested. Furthermore, based on the analysis of the program's effects on household organizations, policies for structural and food self-sufficiency are proposed.

A network analysis can quantify the depth and breadth of a farmer's relationships with other local farmers, buyers and sellers, or other groups and organizations. Such an analysis can potentially also reveal farmers' incentives, situations, and behaviors, and it may explain their economic success more generally. This study examines small and minority farmers' networks using a primary survey in three farming communities. We emphasize networks related to production, marketing, and resource-sharing activities of 127 farmers (nodes) in Tennessee, 46 in Maryland, and 23 in Delaware, and compute three different measures of network importance or "centrality" for each farmer. We then use generalized least squares analysis relating farmer's age, gender, race, educational attainment, labor use on the farm, and farm location to the farmer's centrality position or importance in the network, defined by number and strength of links or connections. In additional regression analyses, we find significantly positive effects of the centrality position on farm sales of specialty crops: our model predicts that a farmer who adds one additional link or connection can expect a 19% to 25% increase in sales, all else equal. Our results can potentially be used not only to disseminate information more efficiently, but also to identify farmers who would benefit the most from more targeted extension services. [ABSTRACT FROM AUTHOR]

The article offers information on the sociodemographic factors and distance from metro areas in the U.S. which causes problem of low 2020 census participation. It further discusses raising the response rate significantly through outreach and by using on-line survey forms; lack of sufficient broadband internet in rural areas affects the 2020 census; and also mentions that effects of the sociodemographic variables also differ by county type.