Rise In Costs Research Articles

A Time Series Analysis of the Total Program Expenditures to Support the Supplemental Nutrition Assistance Program in the United States

The Supplemental Nutrition Assistance Program (SNAP, also known as food stamps) offers tens of millions of American beneficiaries a crucial lifeline. This welfare benefit has been associated with better nutritional outcomes and has been linked to an efficient tool to fight hunger, improve labour market outcomes for the beneficiaries, achieve higher birth weight for children born to the beneficiary mothers, improve height and health outcomes for the beneficiaries. SNAP has been found to be an essential tool to ensure the availability of vital resources during times of need, etc. Despite the program’s numerous advantages, serious doubts exist about its viability and stability of the program especially, given the steep rise in program costs over the years. Over the past 50 years, SNAP has experienced tremendous growth both in terms of the number of beneficiaries and amount of spending. From over $1.82 billion in 1969 to over $113 billion in 2022, the total cost of the SNAP initiative has increased over 62 times in 53 years. This research uses data from the US Department of Agriculture to investigate the time series properties in the rise in the total expenditure devoted to the SNAP between 1969 and 2022. With and without trends, Augmented Dickey-Fuller tests are run with carefully chosen lag lengths. The existence of a unit root cannot be rejected in all specifications pointing to the possibility that the program might have grown in an unstable manner over time. An overwhelming amount of evidence points to an unstable and unstable growth in the overall amount spent on SNAP recipients. This unchecked growth may present substantial difficulties for policymakers especially since the program competes with other welfare programs in an environment of rapidly rising national debt and persistent budget deficits. The report does not attempt to estimate program fraud or abuse which may partially contribute to higher expenditures.

Internal determinants of bank deposit flows under different market conditions in Ghana

This study analyzes the effect of internal factors of bank performance on deposit flows, considering the changes in the stock market conditions in Ghana. A panel dataset covering 2007 to 2021 of 18 banks in Ghana is applied in a dynamic panel model for the analysis. The results show that the lagged deposit growth exerts an impressive influence of 0.68 percent on the future deposit flows of banks, thus positing a favorable implication for their trading momentum. Also, liquidity was found to have a negative relationship of –0.64 percent with deposit growth. This implies that the holding of excess liquidity diminishes investors’ confidence in a bank’s ability to generate more revenue to enhance the value of their funds, as high liquidity ratios reduce the bank’s capacity to grant more loans for profit. Furthermore, the analysis revealed a positive effect of 1.93 percent by expenditure on deposit growth, which suggests that depositors recognize a rise in operational costs as an indication of a bank’s potential for growth and rapid expansion. Moreover, the analysis found the existence of a negative effect of –0.88 percent by the stock market conditions on deposit growth, which implies that bullish market conditions reduce bank deposits. This verifies that the determinants of deposit flows adapt to the changes in market conditions. Policy strategies should include non-performance metrics such as an increase in the interest paid on customers’ deposits, product promotions, and targeted advertisements to sustain the inflow of depositors’ funds under changing market conditions.

Decomposed particle swarm optimization for optimal scheduling in energy hub considering battery lifetime

The energy hub has become pivotal in optimizing multi-carrier energy systems, aiming to enhance the flexibility and efficiency of the overall infrastructure. By incorporating energy storage within these hubs, it becomes feasible to dynamically coordinate the balance between energy generation and consumption. This coordination considers diverse energy pricing structures and local renewable energy generation, leading to substantial reductions in energy expenditures. To further amplify the long-term utilization of batteries, it is essential to account for the associated costs related to their lifespan during the optimization process. Nonetheless, optimizing the operation of an interconnected energy hub system while factoring in battery lifespan introduces a complex challenge, encompassing various limitations, spanning multiple time frames, and involving non-convex aspects. This article introduces an inventive strategy termed the “decomposition technique,” which entails amalgamating particle swarm optimization with a numerical approach. By disassembling the complex optimization predicament into more manageable sub-problems, particularly the organization of storage and other elements within the energy hub system, this approach capitalizes on the individual strengths of particle swarm optimization and the interior point method. To assess the efficacy of this proposed method, it is applied across various scenarios, encompassing a two-hub system and a three-hub system spanning a 24-h timeframe. Through comparison with analytical methods, the results obtained affirm the technique's capability to converge remarkably close to the global minimum. Moreover, the computational efficiency of this approach enables its online implementation, with a reduced time horizon, and ensures real-time optimization. The success of this approach opens up potential applications in diverse energy hub systems and emphasizes its adaptability and scalability. Using the strengths of particle swarm optimization and the interior point method, this technique provides an effective solution for optimizing energy hub systems while considering battery lifetime costs. It enables near-optimal performance while overcoming limitations related to convergence and computation time. The findings of this research contribute to the broader field of energy optimization and pave the way for more efficient and sustainable energy management strategies. The decomposition technique yielded a significant 12% reduction in total energy cost compared to conventional particle swarm optimization. In the three-hub system, the decomposition technique showcased a 15% increase in computational efficiency, affirming its adaptability for larger systems. Considering battery lifetime costs, excluding them led to a 6% boost in energy savings but resulted in a 2% rise in overall system cost, emphasizing the need for a balanced optimization approach.

An Evaluation of Performance of Indigenous Chicken and Irish Potato Value Chains by Smallholder Farmers under Kopia Project in Meru County, Kenya

Adequate, nutritious and safe food is a basic human need. A bilateral project on food security was implemented in Meru County with support from the Republic of South Korea and the County government of Meru between January 2020 and December 2022. The ordinary two-year handover period is ending in December 2024. Its objective was to improve the performance of indigenous chicken and Irish potato value chains among smallholder producers. Despite the existence of high demand for both Indigenous chicken and Irish potatoes, market supply remains low. A stratified sampling method was used to identify 4 Indigenous chickens, Ng’onyi, Mbaria, Ntalami, and Kangeta, and 2 Irish potatoes, Katheri and Murungurune villages, to serve as models. Two hundred practising farmers were selected from each village. All the farmers identified inadequate knowledge, poor genetic materials (Indigenous chicken and Irish potato), high disease incidences, and poorly developed market structures as the main challenges they faced. A training hall was constructed in each of the six model villages and equipped with a computer, a printer, and a monitor. Each chicken-keeping village had a hatchery unit, and those growing potatoes had a potato storage unit constructed and equipped. Egg incubators and Hatchers were provided to the Indigenous chicken-keeping villages. A motorcycle to assist lead-farmer movement was provided to each model village. A curriculum with 22 areas and another one with 20 units were developed to train the Indigenous chicken keepers and Irish potato farmers, respectively. Each curriculum included both technical and non-technical aspects. A total of 73, 837 day old Improved Indigenous chicks were equitably supplied to all the four model villages, with 41600 day old chicks procured from Kenya agriculture, livestock research organization (KALRO) and 32237 locally hatched. A total of 51 tonnes of assorted clean-seed potatoes were procured and supplied to the farmers. The total annual revenue from eggs (tray) rose from Ksh15583.3 before intervention to Ksh133588.7 after intervention. The quantity of eggs sold in trays increased from 54.4 to 193.7, while those sold in pieces increased from 482 to 969. The number of hens sold increased from 17 to 29, and that of cocks sold doubled from 15 to 30. However, all the variable cost components increased during the intervention period. Broilers Mash witnessed the biggest increase in cost by 217.6% from Ksh 1358.9 before intervention to Ksh 2956.5. Despite a rise in the total variable cost by 213%, the average annual gross margin rose from Ksh.7092 to Ksh 91523. The Irish potato farmers had an increase of 192 % in weight (Kg/acre) of total tubers, with production rising from 8711 to 16711 Kg. The potato farmers had a 75.4% increase in household incomes, and their gross margins increased by 76.9 %. The potato farm gate prices increased by 28.57%. After interventions, the potato farmer's gross margin recorded an increase from Ksh. 9 566.5 to 16927.4, translating to a 77% increase. The average total seasonal production increased from 1,394.5 Kg to 2,120.5 Kg. The revenue received from potatoes per season increased from Ksh.46855.2. to Ksh.91605.6 per season. The increase in revenue was a result of the increase in the quantity produced and the price per kg. From the results above, it can be concluded that the implementation of the Indigenous chicken and Irish potato value chains project helped to improve production and household incomes. It is recommended that policy-makers adopt this model village approach in all the agricultural-based value chains.

Effectiveness and efficiency of support schemes in promoting renewable energy sources in the Spanish electricity market

This research paper delves into the central mechanisms implemented in Spain to foster the adoption of clean energy projects. The study scrutinizes various mechanisms established from 2005 onwards, evaluating their efficacy in achieving the desired outcome of supporting clean energy project implementation. The aim is to comprehensively assess the associated costs, effectiveness, and attainment of renewable energy objectives stemming from implementing diverse support schemes. This paper explores the effectiveness of feed-in tariffs and feed-in premium mechanisms in promoting the integration of new renewable energy generation into the power system. However, the Spanish experience suggests that exhaustive planning control is imperative to prevent excessive support costs that could jeopardize the entire market and cause a significant rise in final energy costs. The research studies the support schemes and associated market distortion and presents the roadmap from regulated tariffs to a “total market” for wind and solar energy. The findings demonstrate that, under proper supervision and planning, a transitional retribution scheme effectively promotes renewable energy plant integration. Finally, the analysis examines the need to regulate the excess benefits that non-emitting power sources receive in a marginal price market, as this can lead to market imbalances and a substantial increase in final costs. These plans serve as a crucial tool in achieving the decarbonization objectives of the European Power System.

Multi-criteria decision-making methods for optimal design of intermittent water distribution network

ABSTRACT Multi-objective optimization of water distribution networks (WDNs) is crucial for achieving a balance between cost, equity, and reliability. The present study conducts a comparative analysis, evaluating the effectiveness of four multi-objective optimization algorithms implemented within the EPANET framework for the optimal design of three distinct WDNs taken from the literature. The networks were optimized considering three objectives: maximizing network resilience, and uniformity coefficient (CU, a measure of uniformity), alongside minimizing the cost of the network. Further, multi-criteria decision-making (MCDM) analysis is carried out, encompassing various MCDM techniques and weighting methods, to explore the sensitivity of solution rankings. In Network 1, non-dominated sorting genetic algorithm 2 (NSGA-II) produced suboptimal solutions with CU and In values below 0.4, while caRamel, multi-objective particle swarm optimization based on crowding distance (MOPSO-CD), and multi-objective evolutionary algorithm with decomposition (MOEA/D) showcased increasing CU and In values towards 1, paralleled by a rise in network cost. The performance of NSGA-II in Network 3 was unsatisfactory (CU < 0.32), while the other algorithms demonstrated satisfactory values (>0.98) for reliability and (>0.5) for CU. The findings offer valuable insights into cost-effective strategies for achieving equity in water supply without substantial impact on overall network cost. The findings of the study also underscore the sensitivity of ranking outcomes in MCDM analysis to the choice of technique and weighting method.

Econometric Study: E-commerce Adoption on Inventory Management for Manufacturing Companies in Nigeria

The study examined the effect of Business-to-Business E-commerce adoption on inventory management using manufacturing companies in Nigeria under the category of consumer goods as a case study. Inefficient inventory management leading to a rise in costs and a decrease in customer satisfaction level is one of the major challenges encountered by Nigerian manufacturing companies but this can be resolved through the implementation of e-commerce hence the study focussed on inventory management variables which are; inventory accuracy, stockout frequency, inventory turnover rate, demand forecasting accuracy, storage optimization, inventory holding costs, supplier reliability, inventory audit frequency, obsolete inventory and inventory replenishment. The explosion of e-commerce in the logistics sector has posed a challenge that must be effectively managed to susstain the volume of goods across long distances, the interface between e-commerce and in particular inventory management, for instance via stocks and warehousing has become so important to be overlooked. The study was carried out in Nigeria and the population of the study include staff of 20 manufacturing companies listed on the Nigerian Stock Exchange as at 2023. Simple random sampling technique was used to select 718 respondents. Data was collected through a structured questionnaire and was analysed using both one sample t-test analysis and multivariant regression analysis. E-commerce has positive and significant effect on stockout frequency (P = .000), inventory turnover rate (P=0.000), demand forecasting accuracy (P=0.000), storage optimization (P=0.000) and inventory replenishment (P=0.000). The findings revealed significant improvements in inventory accuracy, reduced stockout frequency, increased inventory turnover rate, and improved demand forecasting accuracy. Evidently, these findings imply that the adoption of e-commerce is essential in optimizing inventory management processes and thus recommends that manufacturing companies should further utilize digital tools to enable better forecasting in inventory management and efficient stock handling.

Threats to human capital: The effect of health risk on corporate financial policy

AbstractI examine the relation between threats to human capital and corporate financial policy using morbidity and mortality data related to infectious diseases. I observe a strong association between deteriorating health and declines in leverage, which seems to be influenced by increasing human capital costs offsetting debt benefits. Firms consider reducing debt as a strategic response to perceived employee valuation of human capital insurance, which tends to be affected by a disease‐induced rise in human capital costs. This association appears more pronounced in technology firms, distressed firms, and labor‐intensive firms, and during higher disease‐induced labor uncertainty, with some moderation by labor unions.

Optimal power flow of thermal-wind-solar power system using enhanced Kepler optimization algorithm: Case study of a large-scale practical power system

In the current century, electrical networks have witnessed great developments and continuous increases in the demand for fossil fuels based energy, leading to an excessive rise in the total production cost (TPC), as well as the pollutant (toxic) gases emitted by thermal plants. Under this circumstances, energy supply from different resources became necessary, such as renewable energy sources (RES) as an alternative solution. This latter, however, characterized with uncertainty nature in its operation principle, especially when operator system wants to define the optimal contribution of each resource in an effort to ensure economic and enhanced reliability of grid. This paper presents an Enhanced version of Kepler optimization algorithm (EKOA) to solve the problem of stochastic optimal power flow (SOPF) in a most efficient way incorporating wind power generators and solar photovoltaic with different objective functions, the stochastic nature of wind speed and solar is modeled using Weibull and lognormal probability density functions respectively. To prove the effectiveness of the proposed EKOA, various case studies were carried out on two test systems IEEE 30-bus system and Algerian power system 114-bus, obtained results were evaluated in comparison with those obtained using the original KOA and other methods published in the literatures. Thus, shows the effectiveness and superiority of the efficient EKOA over other optimizers to solve complex problem. The incorporation of RES resulted in a significant 2.39% decrease in production cost, showcasing EKOA’s efficiency with a $780/h, compared to KOA’s $781/h, for IEEE 30-bus system. For the DZA 114-bus system revealed even more substantial reductions, with EKOA achieving an impressive 12.6% reduction, and KOA following closely with a 12.4% decrease in production cost.

Improving the Indoor Air Quality of Office Buildings in the Post-Pandemic Era—Impact on Energy Consumption and Costs

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope.

Modelling a sorghum logistics as a substitution of wheat to encourage food diversification program and enhance the productivity of local crops

the current diet trend in Indonesia suggests noodles made from wheat as the alternative to rice. This condition leads Indonesia to import the wheat as much as 11.5 million tonnes per year. In fact, Indonesia has become the world’s second largest wheat importer and ranks among East Asia’s largest staple food importers, mainly for wheat. The distribution of wheat commodity is being hampered due to the conflict between Russia and Ukraine, both of whom are major wheat suppliers in global market. As a solution, President of Indonesia, declaring a means to utilise other crops or implementing food diversification by using sorghum. Sorghum is a grain that able to thrive in tropical and dry areas, such as Indonesia and is possible to substitute that of some wheat. This final project aims to plan door to door sorghum logistic model whenever used as a substitution of wheat in a dry noodle factory located in Sidoarjo Regency by acquiring the lowest cost and a scheduling of sorghum deliveries to fulfil daily demand of the factory itself. The method applied to model the logistic planning is Vehicle Routing Problem (VRP) to determine which scenario giving the most minimum cost. The result of the analysis performed showing that the operational pattern chosen is port to port with voyage charter option obtained a freight cost of Rp17.549.076.988 or a unit cost of Rp558.571 /ton. The scheduling model shows that scenario of warehouse renting in every field is chosen and by doing the sensitivity analysis giving the total cost of Rp11.566.026.812 which includes trucking cost, warehouse cost, and stacking cost. The result shows the overall cost of the sorghum logistic model is Rp29.115.103.800 or equal to Rp926.708 /ton. Furthermore, the partial substitution of sorghum flour for wheat flour results in an 9,81% rise in production costs

How Housing Stress Affect Health Care Costs: A Panel Data Study.

As housing prices in China continue to escalate and the limitations of the "personal unlimited liability system" for housing loans become more evident, the financial stress on families has significantly increased. This stress not only impacts the physical and mental health of family members but also results in rising health care costs. This paper presents empirical research examining how housing stress influences changes in household health care costs through a panel data analysis. The study is based on the China Family Panel Study (CFPS) database and employs a panel two-way fixed effect model alongside a mediating effect model to examine the impact of housing stress, family income, and health status on health care costs. The findings reveal a significant positive correlation between housing stress and health care costs; specifically, for every 1% point increase in housing stress, health care costs rise by 0.141. Robustness tests and propensity score matching (PSM) further validate these findings, even after addressing endogeneity issues. Mediation effect analysis indicates that for every 1% point increase in housing stress, household disposable income decreases by 1.749, and health status declines by 0.468, thereby increasing household health care costs. Heterogeneity analysis demonstrates that housing stress has a more pronounced impact on health care costs among western, eastern, urban, and rental households. The government should implement various measures, such as promoting a "personal limited liability system" mortgage policy, reducing housing prices, and ensuring equal rights to rent and purchase, to alleviate housing stress, enhance family income, and improve residents' health status. These actions would contribute to the promotion of both the housing market and medical care, supporting the sustainable development of the health care sector and ultimately improving long-term social welfare.

Manipulating larval rearing media to optimise mass production of the blow fly Calliphora vicina (Diptera: Calliphoridae)

AbstractThe oviparous blow fly Calliphora vicina has shown potential as a managed pollinator to support honeybee (Apis mellifera) usage in Australian horticulture. A series of three laboratory‐based studies reared newly hatched larvae of C. vicina on meatmeal with varying amounts of either whole egg powder, whole eggs (including shells), bran flakes, brewer's yeast, fish paste or milk powder. The objective was to determine the best larval media for quick and efficient production of adult flies in a mass‐rearing environment. Pure meatmeal or meatmeal with only brewer's yeast added were the least productive media. Larvae fed meatmeal with either 10% or 20% whole dried egg powder had the fastest development to pupae, the highest pupation rate, the heaviest pupae and the highest subsequent adult eclosion. Larval media containing fish paste had the highest survival through to adult emergence (>85%) of all the media treatments, which suggests that this ingredient is of value when mass rearing C. vicina. In addition, newly hatched larvae (n = 50) were reared on varying amounts of media (i.e., 4, 2, 1, 0.5, 0.25 and 0.125 g per larvae) to determine the minimum amount of media required to produce adults. Reductions in media per larvae resulted in smaller pupae and adults that emerged with no subsequent reduction in adult eclosion, indicating the adaptability of this fly to food deprivation. Replacing whole egg powder with whole eggs reduces the costs of rearing C. vicina larvae significantly. In order to rear 1 million adult C. vicina, these studies showed that 0.5 g of media per larvae is sufficient to produce high numbers of pupae with >95% adult eclosion. Although larval development and pupation are optimal on media containing whole egg powder, its recent rapid rise in costs makes it far less economical compared with the use of discarded whole eggs from egg producers. Sourcing of seafood waste could also reduce media costs and improve production of C. vicina. The costs of each media required to realise 1 million adult C. vicina are between $540 and $1900 depending on the media ingredients.

Detoxification and enhancement of in vitro rumen digestibility of exhausted olive pomace wastes through alkaline hydrogen peroxide treatment

Abstract Background Due to the sharp rise in animal feed costs, funding alternatives to substitute high-cost raw materials used in animal feed is a persistent need. This study investigated the effect of alkaline hydrogen peroxide pretreatment as straightforward non-toxic technology to enhance the in vitro rumen digestibility of exhausted olive pomace (EOP), an abundant agricultural waste, to be suitable as animal feedstock. It examined the efficiency to eliminate the toxic phenolic content and minimize lipid oxidation of EOP. Results The pretreatment was first optimized using a central composite experimental design. Under the optimized conditions (1.6% H2O2, 5% NaOH), the measured phenolic content was 1.51 ± 0.03 mg/100 g dry weight (DW) for treated olive pomace (TOP) versus 4.91 ± 0.06 mg/100 g for the untreated one. The pretreatment showed that approximately 25% of the lignin was removed. Crude proteins, neutral detergent fibers, and acid detergent fibers yields of TOP were, respectively, 3.320 ± 0.05, 75.24 ± 0.23, and 54.05 ± 0.35 g/100 g of DW, significantly more important than those of untreated EOP. The enzymatic hydrolysis with a cellulase-based cocktail (Celluclast15 FPU/gDW), recorded a 48% of reducing sugar yield for TOP against 33% for EOP. When the in vitro organic matter digestibility (IVOMD) was assayed, the potential gas production of TOP (41.371 ml/g DM) was significantly higher than EOP (25.771 ml/g DM). The metabolizable energy of TOP (9.28 kcal/kg DM) was higher than that of EOP (7.78 kcal/kg DM). Conclusions The present study revealed that alkaline hydrogen peroxide (AHP) could be an efficient treatment for the detoxification and enhancement of in vitro rumen digestibility of olive pomace. This straightforward approach demonstrated that treated olive pomace waste may be well valorized as suitable animal feedstock. Graphical Abstract

Energy shock, industrial transformation and macroeconomic fluctuations

This paper analyzes the impact of coal shock and oil shock on China's macro economy by constructing SVAR model, and clarifies the impact mechanism of the two shocks and corresponding countermeasures by constructing a small open DSGE model. We find that: 1) The impact of exogenous coal impact mainly affects the total output by influencing thermal power generation. Due to the incomplete release of power price in China, under the impact of exogenous coal, the rise of thermal power generation cost will lead to the decline of thermal power generation, which will lead to the shortage of power supply for industrial production and the decline of output. 2) Exogenous oil shock mainly affects total output by influencing monetary policy. Different from coal, oil is widely used and its price rise has a significant impact on industrial product prices, which will lead to a certain degree of monetary policy contraction and total output decline. 3) According to the counterfactual analysis and welfare analysis, we find that the exogenous coal shock can be mitigated by reducing the external dependence of coal and industrial green transformation. At the same time, the exogenous oil shock can be mitigated by establishing strategic cooperation and industrial green transformation with oil-rich countries. This paper has certain policy implications for Chinese government departments to promote industrial green transformation and improve energy security.

Fabrication and Simulation of an E-Vehicle

An electric vehicle is one that is powered by on-board electric sources and is driven by electric motors. Electric vehicles have emerged only because of the rise in cost of fuels and pollution. As they are ecologically sound, they are referred to as green transportation. The electric motor based was selected based on its rating of energy efficient. The rated values of the vehicle dynamics include on various parameters e.g motor output, power, traction-torque and speed. The motor rating is adjusted according to the carrying load, so as to achieve the characteristics of traction. The IC engine of the traditional vehicles is replaced by the electric motor which would act as the leading prime mover component used to drive the E-vehicle. Thus, the selected electric motor provides an adequate power for traction purpose. The structural optimization of the vehicle in-terms of deflection, proof-resilience and Von-misses stress analysis has been carried out using FEA software. EVs are gaining popularity due to their low emissions, reduced operating costs and advances in battery technology, which have increased their range and performance.

The New Stage of State Real Estate Cadastre Valuation (in the Russian Federation)

Accurate real estate market data is crucial for decision-making by governments, businesses, and individuals. Without it, costs rise and development of investment and tax policies suffers. In Russia, the state real estate cadastre valuation is the main data source, but its credibility wanes due to errors and delayed updates. This article reviews the 20-year evolution of this system through four stages. The aim of this study is to analyse the problems and shortcomings in conducting cadastre valuation and property assessment in the Russian Federation, and to propose recommendations for improving this system. In the process of research, normative documents that served as an information base for achieving the set goal were analysed, and a comparative analysis of property tax assessment systems and tax policies of various countries was conducted. Based on the conducted analysis, the author proposes recommendations to enhance tax policy and real estate cadastre valuation in Russia. The recommendations involve adjustments, updated tax value criteria, considering diverse property value factors, separating cadastre valuation from mass appraisal, and accommodating variations in tax base calculation. Implementing these recommendations can contribute to addressing issues in cadastre valuation and create a fairer, more effective taxation system for land and property.

The optimal placement model for electric vehicle charging stations using bayesian networks

As costs rise and fossil fuels have harmful environ- mental effects more and more people choose electric cars or electric cars this change shows how electric cars are becoming more and more popular in the transportation industry as their fleet grows it becomes clear that more infrastructure is required for charging the first step in the optimization method of this study which aims to identify ideal locations for stations considering user accessibility and investment costs is to identify potential charging locations and places are carefully studied using mixed integer linear programming MLP techniques to identify optimal locations based on historical EV paths the study examines this complex urban environment.

Inadequate Demonstration: EPA’s Latest Effort to Force a Clean Energy Transition on the Power Sector Rests on Technologies That Have Not Been Adequately Demonstrated

The Environmental Protection Agency's (EPA) proposed regulations of power plant carbon emissions under Section 111 of the Clean Air Act, which were proposed in May of 2023, raise a number of concerns. The proposed regulations target a transition in the U.S. power sector towards clean energy, relying heavily on Carbon Capture & Storage (CCS) and green hydrogen technologies to achieve nearly net zero carbon emissions from existing fossil fuel power plants. These technologies, however, do not seem to satisfy the Section 111 requirement that the Best System of Emissions Reduction (BSER) be adequately demonstrated at the scale and for the purposes envisioned by the EPA. The critique highlights a discrepancy between the EPA's proposed New Source Performance Standards and the statutory requirement that the BSER must be technically feasible and cost-effective. Concerns are raised about the potential for these regulations to unconstitutionally coerce state governments and to neglect the economic implications, including the potential rise in electricity costs and the environmental impact of shifting away from coal and natural gas. Additionally, the critique questions the EPA's interpretation of Section 111 as it may extend the agency's authority to significantly alter the American economy in the pursuit of addressing climate change. The warning is of a "disorderly transition" that might compromise the reliability and affordability of electricity supply, undermining efforts towards a sustainable low-carbon power sector transition.

“Downs's Law” under the lens of theory: Roads lower congestion and increase distance traveled

Downs (1962) claimed a “Law”: that expressways lower congestion even though they reach maximum traffic flow. In urban economics since Strotz (1965), road capacity is measured by road width, and congestion as the delay in travel: wider roads lower congestion. Duranton and Turner (2011), in an econometric study, atypically defined congestion, not as delay in travel, but as aggregate vehicle kilometers traveled (VKT) relative to the aggregate length of roads, concluding that roads are unlikely to relieve congestion. We first provide the theory behind “Downs's Law”. Then, in a series of theoretical models, we endogenize rent, income, the value of time, leisure, Marshallian productivity, consumption-linked trips, road costs, spatial detail, and a suburb-to-city expressway competing with existing roads. In each case we prove that adding more road capacity lowers congestion and increases utility in the short run when city population is fixed; and lowers congestion in the long run too despite induced travel or population growth. Aggregate travel cost and VKT rise or fall, depending on how much congestion is lowered, on the cost elasticity of travel demand, on location-based income and substitution effects, and on which roads are widened.