Popular Support for Balancing Equity and Efficiency in Resource Allocation: A Case Study in Online Advertising to Increase Welfare Program Awareness

Cloud computing is one among the emerging platforms in business, IT enterprise and mobile computing applications. Resources like Software, CPU, Memory and I/O devices etc. are utilized and charged as per the usage, instead of buying it. A Proper and efficient resource allocation in this dynamic cloud environment becomes the challenging task due to drastic increment in cloud usage. Various promising technologies have been developed to improve the efficiency of resource allocation process. But still there is some incompetency in terms of task scheduling and power consumption, when the system gets overloaded. So an energy efficient task scheduling algorithm is required to improve the efficiency of resource allocation process. In this paper an improved task scheduling and an optimal power minimization approach is proposed for efficient dynamic resource allocation process. Using prediction mechanism and dynamic resource table updating algorithm, efficiency of resource allocation in terms of task completion and response time is achieved. This framework brings an efficient result in terms of power reduction since it reduces the power consumption in data centers. The proposed approach gives accurate values for updating resource table. An efficient resource allocation is achieved by an improved task scheduling technique and reduced power consumption approach. The Simulation result gives 8% better results when comparing to other existing methods.

Increasing the efficiency of resource allocation is the basis and guarantee for boosting high-quality economic development. Based on the panel data of Chinese industrial enterprises and cities from 2008 to 2013, this paper studies the influence of infrastructure construction demand shocks represented by local government debt expansion on the efficiency of sectoral resource allocation from the perspective of sectoral linkage. According to the empirical findings, local government debt significantly reduces the resource allocation efficiency of manufacturing sector that is highly related to infrastructure construction. This conclusion is still tenable after the robustness test using the simulated local government debt as an instrumental variable. Further mechanism tests show that there are two reasons for the decline of the efficiency of resource allocation in manufacturing sector that is highly related to infrastructure construction. First, more product demands and investments brought by the expansion of local government debt flow to less productive enterprises in the sector. Second, resource misallocation reduces the probability of high-productivity enterprises entering the market and low-productivity enterprises exiting the market, and the effect is more prominent in cities with high dependence on state-owned enterprises and high pressure on officials to be promoted. According to this study, the performance management of local government debt should be further strengthened, and particular attention should be paid to the influence of local government debt on enterprise investment and financing crowding out and resource misallocation.

International evidence on the effects of directed credit programmes on efficiency of resource allocation in developing countries: The case of development bank lendings

AI-based resource allocation techniques in D2D communication: Open issues and future directions

ABSTRACTIn this article, we analyzed the impact mechanism of Internet finance on the efficiency of regional financial resource allocation. A data envelopment analysis–Malmquist model is used to measure the efficiency of financial resource allocation in 30 provinces in China, and the impact of Internet finance on the efficiency of regional financial resource allocation is tested using a spatial Durbin model. The results show clear spatial agglomeration and spillover effects in the efficiency of regional financial resource allocation. In addition, developing Internet finance can promote the efficiency and technological progress of regional financial resource allocation and can enhance efficiency and technological progress in the allocation of financial resources in adjacent regions. However, it can hurt the technical efficiency of regional financial resource allocation.

BackgroundAlthough it has long been known that a broad range of factors beyond medical diagnoses affect health and health services use, it has been unclear whether additional income can decrease health service use. We examined whether Supplemental Nutrition Assistance Program (SNAP) receipt is associated with subsequent nursing home entry among low income older adults.MethodsWe examined the 77,678 older adults dually eligible for Medicaid and Medicare in Maryland, 2010–2012. Zero inflated negative binomial regression, adjusting for demographic and health factors, tested the association of either lagged SNAP enrollment or lagged benefit amount with nursing home admission. We used Heckman two-step model results to calculate potential savings of SNAP enrollment through reduced nursing home admissions and reduced duration.ResultsOnly 53.4% received SNAP in 2012, despite being income-eligible. SNAP participants had a 23% reduced odds of nursing home admission than nonparticipants (95% CI: 0.75–0.78). For SNAP participants, an additional $10 of monthly SNAP assistance was associated with lower odds of admission (OR = 0.93, 95% CI: 0.93–0.93), and fewer days stay among those admitted (IRR = 0.99, 95% CI: 0.98–0.99). Providing SNAP to all 2012 sample nonparticipants could be associated with $34 million in cost savings in Maryland.ConclusionsSNAP is underutilized and may reduce costly nursing home use among high-risk older adults. This study has policy implications at the State and Federal levels which include expanding access to SNAP and enhancing SNAP amounts.

P7 You SNAP, We Match: Improving Food Access and Stimulating a Rural, Local Food System During a Public Health Crisis

BackgroundThe Supplemental Nutrition Assistance Program (SNAP) has well-established positive impacts on child health outcomes, including increased birth weight and decreased likelihood of underweight status. Studies in adult populations suggest that SNAP is associated with lower health care costs, although less is known in children.MethodsRetrospective analysis of U.S. children (age <18 years) living in low-income households (< 200% of the federal poverty level) in the 2013-2017 Medical Expenditure Panel Survey. We used multivariable regression, adjusting for sociodemographic and clinical covariates, to model the effect of continuous SNAP enrollment on health expenditures as compared to non-enrollees at 12 and 24 months.ResultsThe sample included 5,626 children, of whom 49.2% consistently received SNAP for the entire two-year survey period. Compared with SNAP non-recipients, SNAP-recipient households more often had incomes below 100% FPL (78.3% vs 37.9%), and children in SNAP-recipient households were more often publicly insured (94.9% vs 64.5%). Unadjusted expenditures were lower for children in SNAP-recipient households at 12 ($1222 vs $1603) and 24 months ($2447 vs $3009). However, when adjusting for sociodemographic and clinical differences, no statistically significant differences in health care expenditures, including emergency department, inpatient, outpatient, and prescription costs, were identified.ConclusionSNAP participant children experience heightened social hardships across multiple domains. There were no differences in short term health care costs based on SNAP enrollment when accounting for differences in sociodemographic and clinical factors. Despite demonstrated child health benefits, we found that sustained enrollment in SNAP over a two-year period did not generate significant short- term health care cost reductions. Our findings suggest that although SNAP is intended to act as a benefit towards the health and well-being of its recipients, unlike among adults, it may not reduce health care costs among children.

The Development, Implementation, and Evaluation of Innovative Strategies to Reduce Food Insecurity among Children in the United States

This paper uses the circular-flow diagram to illustrate the efficiency of resource allocation at market equilibria. This diagram not only depicts the circulation of goods and money within a market economy but also suggests the efficiency of resource allocation at market equilibrium. However, economics instructors usually invoke the Edgeworth box diagram to demonstrate efficient resource allocation. Therefore, for an intermediate economics class, this paper proposes a simple method to describe the efficiency of resource allocation: the circular-flow diagram.

Food insecurity (FI) prevalence rates among U.S. refugees can range up to 85%. FI-related health outcomes, such as hypertension and obesity, are also prevalent among refugees. The Supplemental Nutrition Assistance Program (SNAP) is an evidence-based federal nutrition assistance program that can reduce FI and improve health outcomes. Previous research shows that not every eligible refugee can access SNAP. What remains unknown is the SNAP nonparticipation rate among a representative sample of U.S. refugees. We estimated this rate using the 2021 Annual Survey of Refugees, which provides nationally representative data of U.S. refugees who were resettled between fiscal years 2016 and 2020. We determined the eligibility for SNAP by using the average monthly net household income of a household, the household size (i.e., the number of people residing in a household), and the SNAP net income eligibility thresholds for 2021. Percentages and their 95% confidence intervals were calculated with weighted data to be nationally representative of the U.S. refugee population. Results suggest that 28.6% (95% confidence interval: 23.4-33.8) of income-eligible refugee households (those with a net income below the federal poverty level) did not participate in SNAP. Future research should comprehensively identify barriers and facilitators in accessing SNAP and develop strategies to improve refugees' access to SNAP.

Food insecurity among lower income adults is associated with adverse health outcomes including sleep disorders. Using data from the National Health and Nutrition Examination Survey (NHANES), 2005-2008, we explored the association between participation in the Supplemental Nutrition Assistance Program (SNAP), a safety net program addressing food insecurity, and sleep outcomes among older adults. Total sleep duration (<7 hours inadequate sleep, ≥7 hours adequate sleep) and sleep latency (10-20 mins normal sleep latency, ≤ 9 mins and ≥ 21mins abnormal sleep latency) were available for 805 participants 50 years and older and eligible for SNAP participation (≤130% federal poverty level). SNAP participation (yes/no) was assessed for the previous year. Sleep inadequacy was higher among SNAP participants (46.5%) compared to SNAP-eligible non-participants (36.3%), whereas the corresponding numbers for abnormal sleep latency were 71.8% and 64.1%. Binary logistic regression analysis showed no significant association between SNAP participation and inadequate sleep duration (OR=1.19, 95% CI 0.84-1.70) after adjusting for age, gender, race/ethnicity, education, and food security status. SNAP participation was also not associated with abnormal sleep latency (adjusted OR=1.49, 95% CI 1.00-2.23). SNAP participation was not protective against poor sleep outcomes among a sample of low-income, at risk of food insecurity older adults.

Racial and ethnic minority groups disproportionately experience food insecurity. During the COVID-19 pandemic, the US enacted temporary food assistance policies, including emergency allotments for Supplemental Nutrition Assistance Program (SNAP) benefits. The effects of the pandemic and these policies on food insecurity by race and ethnicity are unclear. To examine prevalence trends in food insecurity by racial and ethnic groups and SNAP use before and during the pandemic. This cross-sectional survey study analyzed National Health Interview Survey data before (January 2019 to March 2020) and during the COVID-19 pandemic (April 2020 to December 2022). Participants were noninstitutionalized US adults (≥18 years) with low income (<200% federal poverty level). Statistical analysis was performed from September 25, 2023, to February 27, 2024. COVID-19 pandemic time period. Food insecurity was measured using the 10-item US Department of Agriculture Adult Food Security Survey module, categorizing participants as food secure (high or marginal food security) or insecure (low or very low food security). Survey-weighted Poisson regressions were modeled to examine changes in food insecurity prevalence over time by race and ethnicity (Asian, Black, Hispanic, and White) and by race and ethnicity and SNAP use (yes or no) including a 3-way interaction term (time × race and ethnicity × SNAP). Among 30 396 adults with low income, approximately one-half were female (56.0% [95% CI, 54.7%-57.2%] during the pre-COVID-19 time period; 57.4% [95% CI, 56.4%-58.4%] during the COVID-19 time period). Food insecurity prevalence decreased from 20.9% (95% CI, 19.9%-22.0%) before the COVID-19 pandemic to 18.8% (95% CI, 17.9%-19.7%) during the pandemic (P < .001). SNAP use prevalence increased overall (from 31.5% [95% CI, 30.1%-32.9%] to 36.0% [95% CI, 34.8%-37.3%]; P < .001) and for each racial and ethnic group. There were no significant differences in food insecurity changes over time by racial and ethnic group (Wald test F = 1.29; P = .28 for 2-way interaction). Among SNAP participants, food insecurity decreased for Asian, Hispanic, and White adults but did not change for Black adults; among non-SNAP participants, food insecurity did not change for Black, Hispanic, and White adults but increased for Asian adults (Wald test F = 4.43; P = .02 for 3-way interaction). During the COVID-19 pandemic, food insecurity decreased among SNAP participants in most racial and ethnic groups but did not decrease among non-SNAP participants in any group. These results suggest that during the pandemic, increased SNAP benefit amounts were associated with ameliorating food insecurity for many US adults who were able to access SNAP but did not reduce racial and ethnic disparities in food insecurity.

Introduction: The Supplemental Nutrition Assistance Program (SNAP) plays an important role in shaping the diet of low-income individuals and families. Trends in ultra-processed food intake (UPF) among SNAP participants and non-participants has not been studied. Hypothesis: Compared to non-participants, SNAP participants would have a higher UPF intake; purchases would be larger for foods from SNAP-eligible versus ineligible venues. Methods: Data from NHANES survey cycles 2003-2004 through 2017-2018 were used. Dietary recalls from individuals ≥1 year of age were categorized according to Nova classification. Venues from which individuals reported buying food were grouped as SNAP-eligible (ex. grocery/supermarkets, convenience stores) or SNAP-ineligible venues (ex. restaurant/cafeteria). SNAP participation status was self-reported and categorized as SNAP participants; income-eligible nonparticipants (no SNAP + family income ≤130% of federal poverty line, FPL); lower-income, ineligible non-participants (no SNAP + family income &gt;130% - ≤300% of FPL); higher-income ineligible non-participants (no SNAP + family income &gt;300% FPL). UPF (% of total daily kcal) across eight survey cycles was examined using multivariable linear regression, stratified by SNAP participation status. Heterogeneous trends across SNAP participation status were tested by Wald F models. Trends were examined for UPF purchased from different venues. Analyses were conducted in youths (ages 1-19) and adults (≥ 20), separately. Results: The sample included 54979 participants from 2003-2004 through 2017-2018. The % of energy from UPF increased over time in both youth (Δ 2018-2003 , 4.3%; 95% CI, 2.9% - 5.8%; P linear trend &lt; .001) and adults (Δ 2018-2003 , 2.5%; 95% CI, 0.2% - 4.9%; P linear trend = .002). There were no differences between SNAP participants, income-eligible non-participants, lower-income ineligible and higher-income non-participants. The mean contribution of UPF from SNAP-eligible venues decreased in both youth (Δ 2018-2003 , -2.6%; 95% CI, -6.1% - 0.9%; P linear trend = .001) and adults (Δ 2018-2003 , -2.3%; 95% CI, -5.0% - 0.8%; P cubic trend &lt; .001) with no differences by SNAP participation. UPF purchases from fast-food restaurants increased in youth (Δ 2018-2003 , 2.2%; 95% CI, -0.4% - 4.8%; P quadratic trend = .036) and adults (Δ 2018-2003 , 2.9%; 95% CI, 0.6% - 5.1%; P cubic trend = .007), while those from schools remained unchanged. There were no differences by SNAP participation status. Conclusions: Total UPF consumption increased between 2003-2004 and 2017-2018 and were seen among both participants of SNAP and among income-eligible and ineligible non-participants. UPF were increasingly sourced from SNAP ineligible venues. SNAP benefit allotments should account for secular changes in dietary patterns by enabling the purchase of healthier processed and prepared foods.

Digital consumption, driven by the widespread application of information technology, has led to more efficient resource allocation and industrial structure optimization. This promotes green transformation and has a positive impact on carbon productivity. This research examined 275 cities across China, employing a difference-in-differences approach alongside the national information consumption pilot policy to carry out a quasi-natural experiment. The study found that the information consumption pilot policy enhances carbon productivity at the 1% significance level. After controlling for other variables, the regions affected by the information consumption policy saw an increase in carbon productivity that was 0.233 higher than in the regions that were not affected. This growth reflects the positive impact of the information consumption pilot policy or measures on carbon productivity. Meanwhile, the increase in technological resources and the transformation of the industrial framework encouraged by the policy indirectly promote the development of carbon productivity. The information consumption pilot policy promotes technological innovation and increases resource density, leading to more efficient technology application and resource allocation. It also drives industrial structure optimization, particularly accelerating the development of low-carbon industries, thereby effectively enhancing carbon productivity. This study provides theoretical and empirical references for the promotion of carbon productivity through digital consumption.