Is Organic Rice bean (Vigna umbellata) Farmers Economically better Off? AnEmpirical Analysis

The study was conducted in North Eastern Hill (NEH) region of India during 2018-2020.Multistage sampling technique was adopted. Sikkim was selected purposively as the controlstate and Nagaland was selected based on the highest area and production under pulses. 60respondents each from organic adopter and non-adopter were selected making a total samplesize of 120. The growth rate in area, production and productivity at the world, India andNEH states were found to be positive. However, higher growth rate were observed forthe NEH region. Significance difference was observed only on cost of fertilizers. The totalcost of rice bean cultivation was lower in organic adopter by 1.71 per cent. The averageyield was significantly higher for the organic adopter. The gross income and net incomewere also higher for the organic adopter. Organic farming was found to be more profitableand it can enhance the farmer’s income. Allocative efficiency indicates that all the resourcesused in the region need to be increase so as to achieve the maximum potential yield andhenceforth increase the returns.

Determinants of resource use efficiencies among lowland rice farmers of Enugu State, Nigeria

The gap in supply and demand of rice could be due to observable differentials in the allocative efficiency of the rice farmers in Nigeria. Therefore, the study focused on the determinants of resource-use efficiencies and profitability of lowland rice farmers of Enugu State, Nigeria. A multistage sampling technique was used to collect cross-sectional data from 300 smallholder rice farmers across the six agricultural zones of the State. The gross margin (GM) analysis was used to estimate the profitability while the marginal value productmarginal factor cost (MVP-MFC) was used to evaluate the efficiency of rice farming. The Stochastic Frontier Cost Function was also used to estimate the determinants of resource use efficiency among lowland rice farmers in Enugu state. The results from the GM showed that rice production is profitable with an average rate of returns on investment (ROI) of 2.80. The MVP-MFC analysis showed that all the input factors hypothesized were over-utilised indicating the existence of large-scale resource-use inefficiency among lowland rice farmers of the state. Education and age were the only socio-economic variables that affected the allocative efficiency of the rice farmers. The study recommends a farm-level policy directed towards the encouragement of younger adults since they are more likely to adopt innovation and boost efficiency and investment in extension education for advisory services to facilitate resource-use efficiencies.

Cost of TB services in healthcare facilities in Kenya (No 3)

BACKGROUND: The reduction of Kenya´s TB burden requires improving resource allocation both to and within the National TB, Leprosy and Lung Disease Program (NTLD-P). We aimed to estimate the unit costs of TB services for budgeting by NTLD-P, and allocative efficiency analyses for future National Strategic Plan (NSP) costing.METHODS: We estimated costs of all TB interventions in a sample of 20 public and private health facilities from eight counties. We calculated national-level unit costs from a health provider´s perspective using bottom-up (BU) and top-down (TD) approaches for the financial year 2017–2018 using Microsoft Excel and STATA v16.RESULTS: The mean unit cost for passive case-finding (PCF) was respectively US$38 and US$60 using the BU and TD approaches. The unit BU and TD costs of a 6-month first-line treatment (FLT) course, including monitoring tests, was respectively US$135 and US$160, while those for adult drug-resistant TB (DR-TB) treatment was respectively US$3,230.28 and US$3,926.52 for the 9-month short regimen. Intervention costs highlighted variations between BU and TD approaches. Overall, TD costs were higher than BU, as these are able to capture more costs due to inefficiency (breaks/downtime/leave).CONCLUSION: The activity-based TB unit costs form a comprehensive cost database, and the costing process has built-in capacity within the NTLD-P and international TB research networks, which will inform future TB budgeting processes.

Using allocative efficiency analysis to inform health benefits package design for progressing towards Universal Health Coverage: Proof-of-concept studies in countries seeking decision support

Background Countries are increasingly defining health benefits packages (HBPs) as a way of progressing towards Universal Health Coverage (UHC). Resources for health are commonly constrained, so it is imperative to allocate funds as efficiently as possible. We conducted allocative efficiency analyses using the Health Interventions Prioritization tool (HIPtool) to estimate the cost and impact of potential HBPs in three countries. These analyses explore the usefulness of allocative efficiency analysis and HIPtool in particular, in contributing to priority setting discussions. Methods and findings HIPtool is an open-access and open-source allocative efficiency modelling tool. It is preloaded with publicly available data, including data on the 218 cost-effective interventions comprising the Essential UHC package identified in the 3rd Edition of Disease Control Priorities, and global burden of disease data from the Institute for Health Metrics and Evaluation. For these analyses, the data were adapted to the health systems of Armenia, Côte d’Ivoire and Zimbabwe. Local data replaced global data where possible. Optimized resource allocations were then estimated using the optimization algorithm. In Armenia, optimized spending on UHC interventions could avert 26% more disability-adjusted life years (DALYs), but even highly cost-effective interventions are not funded without an increase in the current health budget. In Côte d’Ivoire, surgical interventions, maternal and child health and health promotion interventions are scaled up under optimized spending with an estimated 22% increase in DALYs averted–mostly at the primary care level. In Zimbabwe, the estimated gain was even higher at 49% of additional DALYs averted through optimized spending. Conclusions HIPtool applications can assist discussions around spending prioritization, HBP design and primary health care transformation. The analyses provided actionable policy recommendations regarding spending allocations across specific delivery platforms, disease programs and interventions. Resource constraints exacerbated by the COVID-19 pandemic increase the need for formal planning of resource allocation to maximize health benefits.

Faktor yang Berpengaruh Terhadap Produksi Tebu di Kecamatan Pucakwangi Kabupaten Pati

This study aims to analyze the factors that influence sugarcane production and analyze the allocative efficiency of the use of sugarcane production factors. This research uses descriptive quantitative method. The method of determining the research location was determined by purposive sampling. The number of sugarcane farmer respondents involved was 72 farmers. The data analysis method uses multiple linear regression analysis which is transformed into a production function of the Cobb-Douglas model. The results of the regression analysis show that the factors that affect sugarcane production in Pucakwangi District, Pati Regency are land, phonska fertilizer and labor factors. Meanwhile, the ZA fertilizer factor has no significant effect on sugarcane production. Allocative efficiency of the use of production factors which include land, phonska fertilizer, ZA fertilizer and labor is not efficient.

Economic Efficiency of the Main Oil Producing Countries in Upstream Sector in the Period 2010-2017

This work aims to calculate the economic efficiency of the main upstream oil producing countries in 2010-2017, using the Data Envelopment Analysis (DEA) methodology. In the begining the technical efficiency is determined, next allocative efficiency is calculated to finally obtain the economic efficiency. The countries analyzed were: United States, Russia, Canada, China, United Arab Emirates, Kuwait, Brazil, Kazakhstan, Mexico, Angola, Venezuela, Algeria, United Kingdom, Holland, France and Spain. It can be seen from the results that no country was efficient in economic terms. However, Russia had the highest levels of economic efficiency, on the opposite side, France has the lowest values in this indicator. It is recommended to establish strategies in the sector to avoid economic vulnerability in some countries. The main limitation is the availability of the data. The originality of the research consists in obtaining economic efficiency in this industry, since there are no studies with these specific characteristics. It is concluded that in terms of economic efficiency, there was no adequate use of resources in the upstream oil industry.