Explicit Cost Research Articles

FARMERS’ INCOME OF CASSAVA AND MAIZE INTERCROPPING SYSTEM IN DRY LAND AGRICULTURE

Dry land agriculture, a less fertile land, only a few commodities that planted such as cassava, maize, sweet potatoes and any kind of nuts. Cassava and maize are secondary crops that usually cultivate in dry land. Cassava and maize are strategic food commodities after rice. This study aimed to analyze farmers’ income of cassava and maize intercropping system on dry land agriculture in Karanganyar Regency, Central Java, Indonesia. 60 farmers were taken as research respondents consist of 30 farmers who planted Jalak Towo cassava variety intercropping with maize and 30 farmers who planted other cassava varieties intercropping with maize. The data were analyzed with the concept of farmers’ income by subtracting revenues and explicit costs. The results showed that the intercropping of Jalak Towo cassava variety and maizeE yielded better farmers’ income.

What drives trend-following profits in stocks? The role of the trading signals’ volatility

ABSTRACT We document the influence of stock volatility on trend-following profits for a global sample of 1618 blue-chip stocks, across 43911 evaluation subperiods (2004–2018). We use the price sensitivity of trend signals (i.e. signal volatility) to isolate the detrimental impact of high stock volatility manifested through excessive/inefficient trading. Despite its almost null correlation with the stocks’ mean-variance characteristics, the signal volatility greatly complements them in explaining the time series variation in trend-following excess returns. The results hold for both the buy and sell excess returns, are robust across stock markets, and conserve after considering explicit and implicit trading costs. Investors can use ex postsignal volatility estimates as a valid criterion to choose across potential trading rules, according to their specific levels of risk aversion and transaction costs.

ANALISIS BIAYA DAN PENDAPATAN USAHATANI JAGUNG MANIS (Zea mays saccharata sturt) DI KELURAHAN LOKTABAT UTARA KECAMATAN BANJARBARU UTARA

This study aimed to determine the costs, production,revenue, and income of sweet corn in Loktabat utara village, Banjarbaru utara district. The method used in the reasearch is survey and observation method. . The sampling technique used purposive sampling method, so that 9 respondents were obtained. The results of this study showed that the average production of sweet corns in the loktabat utara village was 7.089 cobs/farmer or 6.262 kg/Ha. The everage explicit cost is Rp.1.236.856/ farmer. While The average revenue obtained is Rp.10.633.000/farmer. The everage income earned during one production process is Rp.9.379.000/farmer

Analyzing Explicit and Implicit accidents workplace costs

Accidents are one of most important phenomena in the production industries and treat the health of the factory workers. Work accidents are a burden for many parties in many ways. Accidents and incidents lead to costs for companies, individual workers, and society. The economic effects of accidents and injuries are not only as financial expenditures, damages or loss of resources, but also there are adverse effects (such as grief ,Loss of major body organs ,…) that are difficult to express in terms of money. Work-related accidents are a major safety and health topic. Every year, workers are faced to accidents in their workplace. This is a huge cost for businesses and a huge cost in terms of human suffering for the victims and their families. Workplace accidents can mean pain and disability and can affect the worker’s life, both in and out of work. According to the contents, it is very important to review and evaluate accidents and their costs. Some researchers have divided costs into, direct and indirect categories. In this study, costs have classified and described as: Explicit and Implicit costs, next has introduced regression model , analyzed and calculated workshop accident.

An integrated techno-economic analysis on wastewater reclamation in Hong Kong: A comprehensive cost – Benefit analysis with life cycle assessment

Wastewater reclamation and reuse projects have been gaining significant attention as ways to secure sustainable water resources while preventing environmental degradation. However, traditional cost-benefit analyses do not reflect the true net benefits of these processes as they do not consider all externalities, particularly due to the difficulties in monetizing environmental impacts, thereby leading to underutilization. In this study, we conducted a hybrid cost-benefit analysis with an integrated environmental externality approach to evaluate the true net benefit of wastewater treatment and reclamation with explicit and implicit costs and estimated benefits. Firstly, we developed a cost-benefit analysis model based on the Drainage Service Department's statistical data from the Shek Wu Hui plant in Hong Kong from 2014 to 2018. Next, we estimated the external environmental benefits from pollutant abatement based on the shadow price of each pollutant by adopting a distance frontier function. We then conducted a life-cycle assessment to investigate the potential environmental impacts of the process using SimaPro 8.5.2.0 software and the EcoInvent 3 database, utilizing Stepwise2006 methodology for full monetization. A sensitivity analysis was applied to control for uncertainties as a robustness check. Our results show that aggregate cost, shadow price, and monetized environmental impact are estimated to be 4.47, 4.75, and 1.23 HKD per m3 of treated water respectively. Based on these results, our study illustrates that the true benefit is noticeably higher than the unit cost of wastewater reclamation, dependent upon a scale, and represents a breakeven point of 63,769 m3 of water reclamation per day. Our study further demonstrates that wastewater reclamation is viable from both social and economic perspectives and will increase the government budget by 81 million HKD. Therefore, this study can provide a basic guideline for developing a more complete economic valuation of wastewater treatment and reclamation projects.

Genetic Mean Reversion Strategy for Online Portfolio Selection with Transaction Costs

Online portfolio selection (OLPS) is a procedure for allocating portfolio assets using only past information to maximize an expected return. There have been successful mean reversion strategies that have achieved large excess returns on the traditional OLPS benchmark datasets. We propose a genetic mean reversion strategy that evolves a population of portfolio vectors using a hybrid genetic algorithm. Each vector represents the proportion of the portfolio assets, and our strategy chooses the best vector in terms of the expected returns on every trading day. To test our strategy, we used the price information of the S&P 500 constituents from 2000 to 2017 and compared various strategies for online portfolio selection. Our hybrid genetic framework successfully evolved the portfolio vectors; therefore, our strategy outperformed the other strategies when explicit or implicit transaction costs were incurred.

The Reflection Principle in the Control Problem of the Heat Equation

We consider the control problem for the generalized heat equation for a Schrödinger operator on a domain with a reflection symmetry with respect to a hyperplane. We show that if this system is null-controllable, then so is the system on its respective parts and the corresponding control cost does not exceed the one on the whole domain. As an application, we obtain null-controllability results for the heat equation on half-spaces, orthants, and sectors of angle π/2n. As a byproduct, we also obtain explicit control cost bounds for the heat equation on certain triangles and corresponding prisms in terms of geometric parameters of the control set.

Staff Planning for Hospitals with Implicit Cost Estimation and Stochastic Optimization

We consider the anesthesiologist staff planning problem for operating services departments in large multi‐specialty hospitals without limit on anesthesiologist supply, where the planner makes monthly and daily decisions to minimize total costs. Each month the staff planner decides the number of anesthesiologists on regular duty and an on‐call consideration list for each day of the following month. In addition, each day, the staff planner decides how many on‐call anesthesiologists to call for the following day. Total costs consist of explicit and implicit costs. Explicit costs include the costs of calling an anesthesiologist and overtime costs. These costs are specified by the organization. Implicit costs encompass costs of not calling an on‐call anesthesiologist and under‐utilizing an anesthesiologist, and these have to be deduced from past decisions. We model the staff planning problem as a two‐stage integer stochastic dynamic program. We develop structural properties of this model and use them in a sample average approximation algorithm constructed to solve this problem. We also develop a procedure to estimate the implicit costs, which are included in this model. Using data from the operating services department at the UCLA Ronald Reagan Medical Center, our model shows the potential to reduce overall costs by 16%. We provide managerial insights related to the relative scale of these costs, hiring decisions by service, sensitivity to cost parameters, and improvements in the prediction of the booked time durations.

Asymmetric information and insurance cycles

AbstractThis paper extends the theoretical literature on underwriting cycles by assuming insurers have heterogeneous exposure to a catastrophe. Distinct from the existing literature on insurance cycles, we model optimal contracting by competitive insurers. Since losses take time to pay out, and insurers are better informed about their catastrophe exposure than external investors, catastrophes compromise the capital‐raising ability of insurers by increasing asymmetric information. Capital is restricted following a catastrophe because investors do not know the catastrophe exposure of each insurer, not because of explicit costs of raising capital. Thus, insurers decide to hold less capital following a catastrophe, giving rise to the insurance cycle.

Child support systems and government budgets: thorny policy choices to recover costs

Abstract Australia, New Zealand, the UK, and the USA instituted child support agencies in the late 1900s and had some policies that resulted in having lowered governmental expenditures when child support was paid. Building on previous research comparing these four countries, this article examines the extent to which these countries currently use explicit cost recovery policies, implicit policies revealed in programme interactions, and fees. Using data from country informants on hypothetical families, we show the percentage of child support payments that are retained through these different tools. In addition to characterizing country approaches, we discuss advantages and disadvantages of different cost-recovery strategies.

Improving the photobioreactor operation efficiency in the technological scheme of wastewater treatment

Conventional process schemes of municipal sewage water treatment, advantages, and disadvantages of the methods applied when removing biogenic elements were considered. It was shown that the existing shortcomings cause additional explicit costs and difficulties when disposing of the resulting waste. Low efficiency of the removal processes themselves causing residual concentrations of biogenic elements in the treated sewage water was also shown. A process scheme for treating municipal sewage water was proposed. It includes the use of a photobioreactor of a proposed design for the removal of biogenic elements due to the metabolism of microalgae. It was experimentally shown that the use of Euglena gracilis strain for removal of phosphates in initial concentrations of 4, 7, and 14 mg/dm3 from sewage water is the most efficient way. It makes it possible to reduce these concentrations to residual 0…0.55 mg/dm3 in four days. A 3.75…5.58 times increment of microalgae biomass during this period was also shown. A mathematical model was constructed for calculating the time of staying the sewage water and microalgae mixture in a photobioreactor to achieve the required degree of removal of biogenic elements. Based on the proposed model and experimental studies, the required time of staying in the rector working area was calculated. It was shown that with the use of Euglena gracilis strain but without removal of biogenic elements at previous purification stages (process schemes including only mechanical purification), the time of mixture staying in the working zone was 37.81 hrs. With partial removal of biogenic elements at the stage of biological treatment (0.55 mg/dm3 total nitrogen, 0.91 mg/dm3 ammonium nitrogen, 0.44 mg/dm3 phosphates), this time was reduced to 26.66 hrs. It was found that the use of Euglena gracilis strain instead of Chlorella vulgaris (FC-16) in the removal of phosphates results in a 2-time increase in the process efficiency and a 50 % decrease in time of mixture staying in the working zone. Recommendations for calculating geometric parameters of photobioreactors of the proposed design were given for use in the process schemes

Corporate tax - a new paradigm is needed! -II. A new global value-added tax is needed instead of a corporate tax

Abstract: The corporate tax system is easy to manipulate in modern economies, with high explicit and implicit costs of maintaining it. Attempts to reform it have been unsuccessful, with aggressive tax planning and tax evasion gaining ground at the international level. The source of constant conflicts between national tax administrations and companies is also the corporate tax base and tax accounting. Therefore, based on a new paradigm, I have developed a new, globally introduce, corporate value-added tax on corporate adjusted sales. Revenues from this tax would replace general government revenues lost due to the abolition of corporate tax. Based on the GDP of the member states of the European Union, I calculated the rate of the new tax for all member states. In the study, I present in detail, the mechanism of operation of the new tax, then describe the advantages of the introduction of the new tax compared to the corporate tax. Finally, I will thoroughly present how the taxation of dividends from company owners/shareholders would change if the new tax I planned was introduced and operated. This new type of taxation of dividends would, in my view, contribute more fairly to the burden-sharing. Journal of Economic Literature (JEL) codes: C 53, E 62, H 24, K 34

Spatially explicit models for decision‐making in animal conservation and restoration

Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision‐making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene‐to‐individual level and the community‐to‐ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision‐making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier‐to‐use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best‐practise guidelines for applying these models. Further, more robust decision‐making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long‐term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.

ANALISIS PENDAPATAN USAHATANI JAHE (ZINGIBER officinale) Di Kecamatan Liang Anggang Kota Banjarbaru Provinsi Kalimantan Selatan

The research aimed to determine the explicit cost, revenue, income, and feasibility obtained from ginger farming. This research was conducted for 3 months from June 2020 to September 2020 in Liang Anggang District Banjarbaru City South Kalimantan Province. This research uses a case study method of farmers who do ginger farming, which only has one person in this research location. From this research, it was found that the total explicit cost is Rp. 66.475.000, total revenue is Rp. 158.525.000 and the total income is Rp. 225.000.000. Also ginger is a plant that deserves to be cultivated because R/C > 1, which is 3.38, which means that for every Rp. 100, - issued, you will receive an income of Rp. 338,-. And efforts that can be made to increase income are by increasing the area of ginger plants and intensive care to prevent rhizome rot to increase ginger production

“PRODUKSI DAN PENDAPATAN USAHATANI GETAH KARET (LATEKS) DI DESA BABAYAU KECAMATAN PARINGIN KABUPATEN BALANGAN PROVINSI KALIMANTAN SELATAN”

This research aims to determine the cultivation and cost, income of rubber farmers. The study used a survey method with participatory observation techniques. In its implementation, this activity is for analysis purposes including primary data collection and secondary data. Rubber sap farming income in Babayau Village is currently a fairly serious problem because the income earned by farmers is constantly changing due to various factors, one of which is weather and market conditions. The sampling technique in this study was the purposive sampling method. Rubber farming activities in Babayau Village, Paringin District, Balangan Regency have technically been running effectively and efficiently from the stages of land clearing, planting, fertilizing, maintaining, and tapping processes. The total production is 73,221 kg for Rp. 7,000, - / kg. The average production is 2,929 / kg perpetual with average revenue of Rp. 20,501,880, per farmer. With an average income of Rp. 20,501,880 per farmer and an average explicit cost of Rp. 267,675.0 per farmer, the average income is Rp. 20,234,205,04, -per farmer

The value of intermediation in the stock market

We estimate a structural model of broker choice to quantitatively decompose the value that institutional investors attach to broker services. Studying over 300 million institutional equity trades, we find that investors are sensitive to both explicit and implicit trading costs and are willing to pay a premium for access to formal and informal research. Formal and informal research account for roughly half of the value generated by brokers. In addition, we use our model to investigate soft dollar arrangements, where research and execution services are bundled, and find that such arrangements allow hedge funds and mutual funds to underreport management fees by 10%.

Cost-effectiveness of Multidisciplinary Care in Plastic Surgery: A Systematic Review.

Multidisciplinary care has been previously shown to improve outcomes for patients and providers alike, fostering interprofessional collaboration and communication. Many studies have demonstrated the beneficial health care outcomes of interdisciplinary care. However, there has been minimal focus on the cost-effectiveness of such care, particularly in the realm of plastic surgery. This is the first systematic review to examine cost savings attributable to plastic surgery involvement in multidisciplinary care. A comprehensive literature review of articles published on cost outcomes associated with multidisciplinary teams including a plastic surgeon was performed. Included articles reported on cost outcomes directly or indirectly attributable to a collaborative intervention. Explicitly reported cost savings were totaled on a per-patient basis. Each article was also reviewed to determine whether the authors ultimately recommended the team-based intervention described. A total of 604 articles were identified in the initial query, of which 8 met the inclusion criteria. Three studies reported explicit cost savings from multidisciplinary care, with cost savings ranging from $707 to $26,098 per patient, and 5 studies reported changes in secondary factors such as complication rates and length of stay. All studies ultimately recommended multidisciplinary care, regardless of whether cost savings were achieved. This systematic review of the cost-effectiveness of multidisciplinary plastic surgery care examined both primary cost savings and associated quality outcomes, such as length of stay, complication rate, and resource consumption. Our findings indicate that the inclusion of plastic surgery in team-based care provides both direct and indirect cost savings to all involved parties.

Zero-order moving horizon estimation for large-scale nonlinear processes

Moving Horizon Estimation (MHE) is an optimization-based approach to nonlinear state estimation where the state estimate is obtained as the solution of a nonlinear optimization problem. Especially for large-scale nonlinear systems, the computational burden associated with the numerical solution of nonlinear optimization problems poses a major challenge when applying MHE in practice. To alleviate the computational effort, we propose an inexact, but computationally less expensive variant of the Gauss–Newton algorithm tailored to the nonlinear least-squares problem arising from the MHE formulation. The proposed algorithm combines two ideas: On the one hand, it uses the fact that the arrival cost matrix appears naturally within the Gauss–Newton Hessian approximation in order to avoid any explicit arrival cost update. On the other hand, the method follows a zero-order optimization approach, where fixed sensitivity approximations are used in order to reduce the number of sensitivity evaluations, while accepting some loss of optimality. The combination of these two ideas allows one to reuse the factorizations of the Hessian blocks associated with each stage, when moving from one MHE problem to the next, therefore significantly reducing the computational complexity. Additionally, a tailored integration method for large-scale stiff systems is proposed that can efficiently propagate approximate forward sensitivities, which are used within the inexact MHE algorithm. Both estimation accuracy and computational efficiency of the proposed method are evaluated by applying it to two case studies: a small-scale batch reactor model and the large-scale dynamic process of acrylic acid production.

Active Measure Reinforcement Learning for Observation Cost Minimization

Markov Decision Processes (MDP) with explicit measurement cost are a class of environments in which the agent learns to maximize the costed return. Here, we define the costed return as the discounted sum of rewards minus the sum of the explicit cost of measuring the next state. The RL agent can freely explore the relationship between actions and rewards but is charged each time it measures the next state. Thus, an optimal agent must learn a policy without making a large number of measurements. We propose the active measure RL framework (Amrl) as a solution to this novel class of problem, and contrast it with standard reinforcement learning under full observability and planning under partially observability. We demonstrate that Amrl-Q agents learn to shift from a reliance on costly measurements to exploiting a learned transition model in order to reduce the number of real-world measurements and achieve a higher costed return. Our results demonstrate the superiority of Amrl-Q over standard RL methods, Q-learning and Dyna-Q, and POMCP for planning under a POMDP in environments with explicit measurement costs.

Understanding how opportunity cost affects multi-objective conservation investment in the Central and Southern Appalachian Region (USA)

SummaryConsensus does not exist for which cost forms (i.e., one accounting solely for explicit cost and the other for both explicit and opportunity costs as in relative opportunity cost) are used in calculating return on investment (ROI) for conservation-related decisions. This research examines how the cost of conservation investment with and without inclusion of the opportunity cost of the protected area results in different solutions in a multi-objective optimization framework at the county level in the Central and Southern Appalachian Region of the USA. We maximize rates of ROI of both forest-dependent biodiversity and economic impact generated by forest-based payments for ecosystem services. We find that the conservation budget is optimally distributed more narrowly among counties that are more likely to be rural when the investment cost measure is relative opportunity cost than when it is explicit cost. We also find that the sacrifice in forest-dependent biodiversity per unit increase in economic impact is higher when investment cost is measured by relative opportunity cost rather than when measured by explicit cost. By understanding the consequences of using one cost measure over the other, a conservation agency can decide on which cost measure is more appropriate for informing the agency’s decision-making process.