County-level Policy Research Articles

What drives labor force participation rate variability? The case of West Virginia

This study examines the dynamics of labor force participation rates across counties in West Virginia to better understand local labor market integration and the factors influencing fluctuations in participation. Drawing on county-level data from January 1990 to July 2020, the research employs a dynamic factor model to decompose labor force participation rates into latent factors at the state, metropolitan/non-metropolitan, and county levels. The findings reveal a general lack of labor market integration across West Virginia, highlighting potential opportunities for growth through enhanced integration. Further analysis using panel data models identifies key determinants of labor force participation, including personal income, education, infrastructure, and the prominence of industries such as agriculture and natural gas. The results underscore the necessity for targeted county-level policies to bolster employment and promote economic expansion within the state.

The impact of cigar pack size and pricing policies on youth and adult cigar use in the US

BackgroundOver 250 US localities have adopted cigar pack quantity and price policies. No empirical studies exist on their impact on tobacco use. MethodsA quasi-experimental design was used to assess the impact of cigar policies on cigar and cigarette use among (1) Minnesota youth (n=569,528, triennially 2007–2019); (2) New York youth (n=111,236, annually 2000–2020), (3) New York adults (n=62,295, annually 2003–2019), and (4) District of Columbia (DC) adults (n=5027, annually 2015–2019). We estimated the county-level policy coverage for 15 local policies in Minnesota. Differences-in-differences approach was used to compare the policy in NYC with the rest of the state (no policy). We examined changes in DC use before and after policy implementation. Analyses adjust for sociodemographic characteristics. ResultsIn Minnesota, youth in counties with a greater proportion of the population covered by a policy had lower odds of cigar use (AOR: 0.51; 95% CI: 0.38–0.69). Similarly, adult cigar use in DC declined following policy enactment (AOR: 0.65; 95% CI: 0.46–0.93). Cigarette use also decreased in both Minnesota and DC following policy enactment. However, in New York, the NYC policy did not have a significant impact on cigar use among youth (AOR: 0.95; 95% CI: 0.47–1.93) or adults (AOR: 1.98; 95% CI: 0.85–1.37) in NYC compared to the rest of the state. The only significant effect in NYC was reduced odds for adult cigarette use (AOR: 0.79; 95% CI: 0.68–0.92). ConclusionsFindings suggest regulating cigar packaging could decrease cigar consumption without increasing cigarette consumption, but effects may differ across jurisdictions.

Contribution of on-road transportation to PM2.5

Fine particulate matter (PM2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM2.5 emission. The relationship between on-road transportation and PM2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km2 on-road transportation increase is associated with a 1-μg/m3 county-level PM2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM2.5 from on-road transportation.

Reduction of COVID-19 Incidence and Nonpharmacologic Interventions: Analysis Using a US County-Level Policy Data Set.

BackgroundWorldwide, nonpharmacologic interventions (NPIs) have been the main tool used to mitigate the COVID-19 pandemic. This includes social distancing measures (closing businesses, closing schools, and quarantining symptomatic persons) and contact tracing (tracking and following exposed individuals). While preliminary research across the globe has shown these policies to be effective, there is currently a lack of information on the effectiveness of NPIs in the United States.ObjectiveThe purpose of this study was to create a granular NPI data set at the county level and then analyze the relationship between NPI policies and changes in reported COVID-19 cases.MethodsUsing a standardized crowdsourcing methodology, we collected time-series data on 7 key NPIs for 1320 US counties.ResultsThis open-source data set is the largest and most comprehensive collection of county NPI policy data and meets the need for higher-resolution COVID-19 policy data. Our analysis revealed a wide variation in county-level policies both within and among states (P<.001). We identified a correlation between workplace closures and lower growth rates of COVID-19 cases (P=.004). We found weak correlations between shelter-in-place enforcement and measures of Democratic local voter proportion (R=0.21) and elected leadership (R=0.22).ConclusionsThis study is the first large-scale NPI analysis at the county level demonstrating a correlation between NPIs and decreased rates of COVID-19. Future work using this data set will explore the relationship between county-level policies and COVID-19 transmission to optimize real-time policy formulation.

Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020

The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from “nonessential” to “essential” businesses and from restaurants and bars toward groceries and other food sellers.

Analysis of influencing factors of cultivated land fragmentation based on hierarchical linear model: A case study of Jiangsu Province, China

Cultivated land fragmentation (CLF) is a common phenomenon of land use in the world, which has an essential effect on agricultural production. Given the limitations of single level in the previous study on the influencing factors of CLF, this study utilizes hierarchical linear model (HLM) to explore the influencing factors of CLF from township and county levels in Jiangsu Province, and puts forward policy suggestions for relieving the CLF. The results indicate that the spatial distribution of CLF shows obvious characteristics in Jiangsu, which gradually increases from north to south. Besides, hierarchical structure exists in the CLF, and 43 % of the differences in CLF come from townships, 57 % from counties. Furthermore, the CLF is affected by multilevel factors, average patch area, GDP, the proportion of secondary and tertiary industries, population density, and road accessibility are the dominant factors at the township level, which explain 76 % of CLF affected by townships, and the main factors at the county level include average patch area, GDP, land use intensity, and urbanization rate, which explain 64 % of CLF affected by counties. Ultimately, a positive interaction with county-level overall guidance and township-level specific implementation should be established to alleviate the CLF. Specifically, at the county level, we should scientifically formulate overall planning of land use, and arrange land consolidation projects according to local conditions, readjust and optimize the economic structure, coordinate kinds of land demands and revitalize inefficient urban land. At the township level, while strictly implementing county-level policies, we should also promote land consolidation projects focusing on basic farmland construction and rural residential land readjustment, and pay attention to the overall layout of agricultural production factors, optimize industrial structure, and orderly transfer rural surplus laborers. This study provides a new perspective for the research on the influencing factors of CLF, and also has important guiding effect on formulating land policies to alleviate the CLF and accelerate sustainable utilization of cultivated land.

Tracking health sector priority setting processes and outcomes for human resources for health, five-years after political devolution: a county-level case study in Kenya

BackgroundHealth sector priority setting in Low and Middle-Income Countries (LMICs) entails balancing between a high demand and low supply of scarce resources. Human Resources for Health (HRH) consume the largest allocation of health sector resources in LMICs. Health sector decentralization continues to be promoted for its perceived ability to improve efficiency, relevance and participation in health sector priority setting. Following the 2013 devolution in Kenya, both health service delivery and human resource management were decentralized to county level. Little is known about priority setting practices and outcomes of HRH within decentralized health systems in LMICs. Our study sought to examine if and how the Kenyan devolution has improved health sector priority setting practices and outcomes for HRH.MethodsWe used a mixed methods case study design to examine health sector priority setting practices and outcomes at county level in Kenya. We used three sources of data. First, we reviewed all relevant national and county level policy and guidelines documents relating to HRH management. We then accessed and reviewed county records of HRH recruitment and distribution between 2013 and 2018. We finally conducted eight key informant interviews with various stakeholder involved in HRH priority setting within our study county.ResultsWe found that HRH numbers in the county increased by almost two-fold since devolution. The county had two forms of HRH recruitment: one led by the County Public Services Board as outlined by policy and guidelines and a parallel, politically-driven recruitment done directly by the County Department of Health. Though there were clear guidelines on HRH recruitment, there were no similar guidelines on allocation and distribution of HRH. Since devolution, the county has preferentially staffed higher level hospitals over primary care facilities. Additionally, there has been local county level innovations to address some HRH management challenges, including recruiting doctors and other highly specialized staff on fixed term contract as opposed to permanent basis; and implementation of local incentives to attract and retain HRH to remote areas within the county.ConclusionDevolution has significantly increased county level decision-space for HRH priority setting in Kenya. However, HRH management and accountability challenges still exist at the county level. There is need for interventions to strengthen county level HRH management capacity and accountability mechanisms beyond additional resources allocation. This will boost the realization of the country’s efforts for promoting service delivery equity as a key goal – both for the devolution and the country’s quest towards Universal Health Coverage (UHC).

Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline 2020

The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions on activity versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in activity, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer activity away from “nonessential” to “essential” businesses and from restaurants and bars toward groceries and other food sellers.

When Voters Matter: The Limits of Local Government Responsiveness

I use over-time variation resulting from geographic sorting to estimate the impact of local preferences on local policy. Building a new panel data set of county-level voting behavior and county-level policy choices, I find a causal impact of changes in preferences on changes in policy. However, this responsiveness is not unlimited. While public safety and infrastructure spending respond, policies more constrained by state laws do not; and while general purpose government spending is responsive, school and special district spending are not. These results corroborate recent evidence of local responsiveness using a more extensive sample, and a research design that rules out many alternative explanations. They also reveal many local policies to be unresponsive due to state-imposed constraints.

Policies and Practices to Address the Educational Needs of Foster Children in Ten Florida Counties

Children in foster care have persistently low academic outcomes. Federal and Florida state law has tried to address some of the structural barriers that contribute to these poor outcomes. Florida was one of the first states, in 2004, to enact legislation requiring school and child welfare systems to collaboratively address the needs of this high-risk group for whom they share responsibility. Since then, similar mandates have been incorporated into federal child welfare and education laws. Yet there is little information about whether these high-level policies have translated into meaning changes in practice to better support the academic needs of children in foster care. This report contributes to filling that gap by examining county-level policy and practice in 10 Florida counties. The researchers interviewed the child welfare and education staff who served as the point of contact for the other agency in each county. The report presents findings in key areas such as the role of the liaison, collaboration and coordination between the systems, policies and practices to decrease school mobility, monitoring and promoting academic progress, information-sharing and the process for appointing surrogate parents. The study revealed wide variation in whether the county had full-time liaisons, the extent of their inter-agency collaboration, and electronic exchange of school records. Counties with established inter-agency relationships appeared well positioned to identify and address system-level barriers that interfere with education. The next step for these counties is to translate those system-level efforts into data-driven strategies that lead to improved outcomes for individual children. Other counties are further behind and have not even begun to devote sufficient resources to collaboration and addressing foster care education issues. The report also shares recommendations for federal, state and local policymakers and stakeholders.

School-Linked Collaborative Services and Systems Change

This study examines whether the alternative policy instrument, systems change, fits the problem of efficient and effective local services. An initiative known as school-linked collaborative services, implemented by a team of county-level policy makers and community-based teams, is the focus. The findings reveal that the policy instrument of systems change devolved authority to the street-level bureaucrats but not responsibility for meeting objectives. As well, the effort to minimize duplication of services through collaboration inadvertently created new layers of bureaucratic control. Implications suggest that systems change alone is not an adequate policy instrument. Suggestions for combining policy instruments of systems change and capacity building are discussed.

INFLUENCES ON COUNTY FARMLAND PROTECTION EFFORTS IN CALIFORNIA: A DISCRIMINANT ANALYSIS∗

County-level policies and programs to conserve farmland in California are examined through discriminant analysis. Based on 1981 state planning data, four degrees of farmland protection effort are established. A two-function discriminant analysis using 17 agricultural, socioeconomic, and political-ideological variables correctly predicts the fourfold classification of 88 percent of the counties. The propensity to enact protective actions is associated with the intensity of agricultural development, local government spending and taxing practices, demographic characteristics, ideological and political party voting traditions.