Profit Estimation Research Articles

Banks approved fraudulent loans to capture origination fees: evidence from the Paycheck Protection Program

Purpose The Small Business Administration (SBA) has estimated that a significant proportion of loans issued during the Paycheck Protection Program (PPP) were fraudulent. This paper aims to make strides to understand incentives that may have led to the approval of fraudulent loans. Design/methodology/approach The authors study the publicly available PPP loans data set, focusing on nonemployer businesses which make up about 51% of all loans. Because of the way businesses of this type were instructed to apply for loans, it is possible to deduce the monthly/annual profit each loan was claiming. Findings The authors find irregularities in the pattern of claimed profit by nonemployer businesses on PPP loans. There is a significant buildup of claimed profit just slightly under the threshold for the maximum loan claim, which does not align with estimates of average nonemployer business profitability. Research limitations/implications As it is not possible to verify individual business profits with publicly available data, the authors cannot identify or count loans, which are likely to be fraudulent. The focus on nonemployer businesses allows for the identification of reported profit, at the cost of eliminating most of the highest value loans from consideration. Practical implications Especially in areas with a high density of small banks, large numbers of potentially fraudulent loans were issued. In planning future disaster relief programs, the SBA must consider incentives, which led to fraudulent behavior during the PPP. Social implications Proponents of the PPP argue that it is impossible to completely eliminate fraudulent behavior due to the rapid nature by which the funds had to be distributed to avoid job loss. Nonetheless, the SBA estimates that up to 1/6 of the funding issued may have gone to fraudulent loans. Responsibility was placed on the banking system as regulators of the loans. However, the origination fee structure of the program, combined with limited liability to banks, may have produced adverse incentives. Originality/value Previous research on PPP fraud primarily identifies businesses and business owners as bad actors during the program. The authors argue that misuse of funds was not the only source of fraud during the program. Misrepresentation of business profits may have been widespread. Therefore, banks must have approved loans with misrepresented profit figures.

Estimation of Cost and Profit in Farming Some Major Crops During Last Two Decades in West Bengal: A Case Study in Birbhum District

The growth of agriculture in West Bengal significantly contributes the food supply through nationwide since last few decades. The cost of farming specially seed cost, irrigation cost increases rapidly. Though modern mechanization has been introduced for few crops to reduce the animal and human labor cost yet an unregulated market structure overall cost of farming increased during last two decades. The present paper emphasises the growth of cost and profit in cultivation for last twenty years in West Bengal. With the help of secondary data it has been tried to measure the cost and profit structure for seven major crops in West Bengal since 2001. The impact of various cost components on profit has also been derived with the help of a primary survey in the district of Birbhum.

Global Evidence on Profit Shifting Within Firms and Across Time

We provide estimates of profit shifting for over 2 million firm-year observations in 100 countries over the period 2009–2020. Employing nonparametric estimation techniques within a mainstay model of profit shifting, we examine how the profits of both parent and subsidiary firms within a multinational group respond to marginal changes in the composite tax indicator. The key advantage of this approach is that it yields firm-year estimates of profit shifting. Multinational firms engage in extensive profit shifting by maintaining affiliates in low-tax countries and zero-tax havens. Multinational groups with an ultimate tax-haven owner exhibit the largest profit response to tax incentives. Our new database opens important avenues for analyzing the sources and effects of profit shifting.

Raw Material Cost Prediction Planning and Ready-Mix Product Sales Using Adaptive Linear Neural Network Method

An important thing that needs to be considered to ensure the successful implementation of the project is planning. The current problem with RMC is the non-achievement of the target, which causes the company's condition to be not optimal. Stable production cost projections on construction projects have been a problem and a serious concern, especially for project contractors. Often, there is a deviation between the projected initial costs and the actual ones at the construction site. Production predictions need to be made to determine the accuracy of these needs. This study aims to predict the needs of production and raw materials in an industry and can accommodate the calculation of estimated profits. Prediction of an industry's production and raw material needs can be used as a reference in calculating profit estimates. The ADALINE method is a neural system consisting of several nodes. A node requires several input processes to produce one output, which can be used as a predictive model. The results show that the actual and simulation data results using the ADALINE model have 100% conformity. This shows that the ADALINE model on the neural network can also function as one of the prediction model choices in addition to performing a prediction function. Prediction results using neural networks are one of the alternative solutions for utilizing prediction models other than other prediction models.

Profit Estimation Model and Financial Risk Prediction Combining Multi-scale Convolutional Feature Extractor and BGRU Model

Profit Estimation Model and Financial Risk Prediction Combining Multi-scale Convolutional Feature Extractor and BGRU Model

Obtaining Conservative Estimates of Integrated Profitability for a Single-Period Product in an Own-Branding-and-Manufacturing Enterprise with Multiple Owned Channels

The achievable capacity index (ACI) is a simple and efficient approach for estimating the profitability of newsboy-type products, wherein profitability is defined as the probability of achieving the target profit by optimizing the order quantity. At present, the ACI is applicable to single retail stores (i.e., single demand) but not to multiple sales channels (i.e., multiple demand). This paper presents an integrated achievable capacity index (IACI) by which to measure the aggregate profitability of multiple mutually independent channels under normally distributed demand. An unbiased IACI estimator is also developed, to which is applied the Taylor expansion to approximate its sampling distribution, wherein the sizes, means, and variances of demand differ in each channel. Furthermore, overestimates due to sampling error are avoided by deriving the lower confidence bound for the IACI. This paper also provides generic tables to aid managers seeking conservative estimates of profitability. The applicability of the proposed scheme is demonstrated numerically using a real-world example involving an own-branding-and-manufacturing (OBM) enterprise with multiple owned channels.

Agronomic and economic productivity of summer annual forage systems under different poultry litter application methods

AbstractPoultry litter (litter) is a nutrient dense fertilizer that increases nutritive value and yield in pastures in the mid‐southern US. Nutrient losses due to runoff and nitrogen volatilization are common when broadcasting litter. As such, incorporating litter below the soil surface (subsurface) was evaluated in comparison to broadcasting in 2021 and 2022 by quantifying yield and nutritive value of annual forages. The study was a randomized complete block design with three forage treatments—sorghum‐sudangrass only (Sorghum bicolor L.), cowpea only (Vigna unguiculata L.), and their mixture, and three litter application methods (broadcast, subsurface, and a no litter control). Litter was applied in 2021 only as biennial application is common to save on application cost. Nutritive analyses included neutral detergent fiber and crude protein (CP). Partial budgeting led to relative profitability estimates by accounting for yield and cost differences across treatments. In comparison to the second‐highest yielding forage mixture, sorghum‐sudangrass yielded 4.5%–18.4% more regardless of litter application method. The forage mixture did not improve forage nutritive value, as cowpea were vastly outcompeted and did not average more than 5% of the total forage harvested in mixtures. Cowpea yields did not benefit from litter application. Subsurface application resulted in 8%–10% greater CP content compared to no litter and broadcast litter, respectively, across all forage species. Sorghum‐sudangrass with subsurface applied litter earned nearly $70/acre more than sorghum‐sudangrass with broadcast litter, the next highest treatment combination, and, with lesser nutrient loss.

A systematic review of the extent of the Taliban and FARC’s involvement and profit from drug trade and methods of estimating income from the drug trade

ABSTRACT The drug trade has garnered significant attention as a critical funding source for various terrorist organisations. This systematic review summarises the existing empirical knowledge about the Taliban and the Revolutionary Armed Forces of Colombia’s (FARC) involvement, and profit from the drug trade, and methods of estimating drug trade revenue. Thirty-one studies were identified. Twenty-three about the Taliban, seven about the FARC, and one about both groups. Estimates of annual profit varied from US$19 to US$500 million for the Taliban and US$140 to US$3.5 billion for the FARC. Fourteen of the twenty-four studies about the Taliban provided an estimate and merely six studies discussed the methods used to generate those estimates. Among the eight studies about the FARC, four provided an estimate but one described the method employed. Studies used a variety of information sources. The review shows the need for caution regarding existing estimates and a more methodologically rigorous analysis of linkages.

Integrated Profitability Evaluation for a Newsboy-Type Product in Own Brand Manufacturers

Effective inventory management depends on accurate estimates of product profitability to formulate ordering and manufacturing strategies. The achievable capacity index (ACI) is a simple yet efficient approach to measuring the profitability of newsboy-type products with normally distributed demand, wherein profitability is presented as the probability of achieving the target profit under the optimal ordering quantity. Unfortunately, the ACI is applicable only to retail stores with a single demand. In the current study, we addressed the issue of measuring the integrated profitability of newsboy-type products sold in multiple locations with independent demand levels, such as own-branding-and-manufacture (OBM) companies with multiple owned channels. We began by formulating profitability in accordance with multiple independent normal demands, and then developed an integrated ACI (IACI) to simplify expression. We also derived the statistical properties of the unbiased estimator to determine the true IACI in situations where demand patterns are unknown. Finally, we conducted hypothesis testing to determine whether the integrated profitability meets a stipulated minimum level. For convenience, we tabulated the critical values as a function of sample size, confidence level, the number of channels, and the stipulated minimum level. One can make decisions simply by estimating the IACI based on historical demand data from all channels and then looking up the critical value in the corresponding tables. Consequently, the proposed methods make it possible for OBM managers to address integrated profitability evaluation, which is effective in deciding the optimal timing to pull unprofitable items from the shelves by looking up generic tables. Furthermore, we also performed numerical and sensitivity analyses for a real-world case to illustrate the applicability and some managerial implications of the proposed scheme.

Profit- and risk-driven credit scoring under parameter uncertainty: A multiobjective approach

Profit-driven artificial intelligence (AI) systems and profit-based performance measures are widely used in credit scoring. When assessing the performance of an AI system for credit scoring, previous research typically assumes that the cost and benefit parameters and their distributional information are available. In reality, however, these parameters and their distributions are often not precisely known. This study considers parameter uncertainty in the development of credit-scoring models and the estimation of profits and risks generated by those models. We propose a novel profit-based metric—the worst-case expected minimum cost (WEMC)—to estimate the profit of credit-scoring models with uncertain parameters. Furthermore, we introduce the worst-case conditional value-at-risk (WCVaR) metric to measure the loss incurred from employing a classification model in credit scoring under the deterioration of cost parameters. A multiobjective feature-selection framework based on WEMC (or minimum cost) and WCVaR is then presented for model development. Using a comprehensive bankruptcy database, we compare the proposed methods with wrapper methods that use traditional metrics as selection criteria, as well as filter and embedding methods. We conduct extensive experiments to evaluate the economic benefits of the proposed methods under different scenarios that simulate dynamic changes in macroeconomic conditions. The results suggest that the proposed methods outperform other feature-selection methods in the aspects of profit and risk performance metrics in most cases.

Performance, processing yields, and fillet composition of specific United States diploid and triploid rainbow trout (Oncorhynchus mykiss) lines reared in a semi-commercial scale freshwater recirculating aquaculture system

Large rainbow trout marketed as steelhead are gaining considerable attention for production in recirculating aquaculture systems (RAS). Diploid and triploid trout with varying genetics are available from several commercial suppliers; however, the performance and processing metrics of these lines have not been compared when raised in freshwater RAS. Current data on these outcomes could support more accurate cost and profitability estimates for potential RAS projects and optimize operation for existing farms. Accordingly, the objective of this study was to quantify performance metrics, processing yield, and fillet composition of six all-female rainbow trout lines (three diploid and three triploid) exposed to an artificial winter (12:12 light: dark at 40 g (Artificial Winter Photoperiod; AWP)) or continuous, 24-h light (No Winter Photoperiod; NWP) grown in a semi-commercial scale freshwater RAS to 3.5 kg. Overall, growth was impacted by line, ploidy, and artificial winter photoperiod. Diploid and AWP trout were smaller than triploids and NWP trout at stocking and 500 g. Mean diploid and triploid weight was similar at larger sizes (>1 kg); however, triploid performance compared to diploids varied by commercial supplier. Mortality was lower in lines from commercial supplier 1 than lines from commercial supplier 2 and the United States Department of Agriculture (14.4 ± 0.8 vs 27.5 ± 2.0 and 29.8 ± 4.3%, respectively). Head-on gutted and skin-on fillet yields were related with larger fish weight. Mature prevalence in diploids may have led to differences observed between diploids and triploids in fillet lipid (10.9 ± 0.8 vs 13.3 ± 0.6%) and moisture (67.0 ± 0.6 vs 65.1 ± 0.4%). The results provide guidance for rainbow trout RAS producers to make informed decisions on optimal harvest size targets and tailor their rainbow trout line or ploidy selection to those harvest sizes.

Concentration and Competition: Evidence From Europe and Implications For Policy

Abstract The paper provides new evidence on proxy indicators of market power for major European countries. The data show moderately increasing average industry concentration over the last two decades, a considerably increasing proportion of high-concentration industries, and an overall tendency toward oligopolistic structure. Estimates of aggregate profitability also show a sustained increase over the recent decades for European economies. Although the academic and policy debate is not settled as to whether the causes of these trends are policy driven or reflect technological improvement, our findings suggest that competition policy is likely to face more challenges as large companies are becoming more common in more and more industries.

Control Analysis of the Griya Jenggala Development Project using the Earned Value Method at PT Sarana Loka Almika in Kebayoran

Project control is a structured effort to establish standards in accordance with the plan, design information systems, compare implementation with established standards, analyze potential deviations, and take corrective actions necessary to ensure the effective and efficient use of resources in line with the set targets. Each project has its own specific plan and schedule, determining the start and end time of the project, implementation methods, and resource allocation. Operational challenges often arise in project planning, such as resource shortages, improper allocation, delays, and other issues that may hinder the achievement of project goals as planned. This research utilizes a descriptive quantitative approach, which is a research method that describes the specific conditions of the project through the analysis of available data. This article will discuss the cost variance (CV) and schedule variance (SV) in the development of Griya Jenggala at PT. Sarana Loka Almika, evaluate the cost performance index (CPI) and schedule performance index (SPI) in the development of Griya Jenggala to assess its effectiveness, estimate the cost at completion (EAC) and estimated duration at completion (EAS) required to complete the Griya Jenggala project, as well as provide an estimation of potential profits or losses that may arise in the Griya Jenggala development project.

Technical Note—Data-Driven Profit Estimation Error in the Newsvendor Model

An unbiased forecast of profit is important in most business environments. Typically, forecasts are generated from data. However, in “Technical Note—Data-Driven Profit Estimation Error in the newsvendor model,” Siegel and Wagner identify a strictly positive bias in a natural estimation of expected profit in a data-driven newsvendor model, where managers will expect more profit than will actually be realized, on average. This bias can reach significant proportions (in some cases 50%+) of the true expected profit and could therefore have undesired and damaging effects in the real world. Siegel and Wagner then design a data-driven adjustment that results in an unbiased estimator of expected profit, so that managers may have an accurate forecast of future profit that is free of systematic bias.

Studies on Water–Aluminum Scrap Reaction Kinetics in Two Steps and the Efficiency of Green Hydrogen Production

This work aims to explain aluminum hydrolysis reaction kinetics based on a properly chosen theoretical model with machined aluminum waste chips as well as alkali solutions up to 1M as a promoter and to estimate the overall reaction profit. The purpose of this work is to assess the optimal alkali concentration in the production of small- and medium-scale green hydrogen. To obtain results with better accuracy, we worked with flat Al waste chips, because a flat surface is preferable to maximally increase the time for the created hydrogen bubbles to reach the critical gas pressure. Describing the reaction kinetics, a flat shape allows for the use of a planar one-dimensional shrinking core model instead of a much more complicated polydisperse spheric shrinking core model. We analyzed the surface chemical reaction and mass transfer rate steps to obtain the first-order rate constant for the surface reaction and the diffusion coefficient of the aqueous reactant in the byproduct layer, respectively. We noted that measurements of the diffusion coefficient in the byproduct layer performed and discussed in this paper are rare to find in publications at alkali concentrations below 1M. With our reactor, we achieved a H2 yield of 1145 mL per 1 g of Al with 1M NaOH, which is 92% of the theoretical maximum. In the estimation of profit, the authors’ novelty is in paying great attention to the loss in alkali and finding a crucial dependence on its price. Nevertheless, in terms of consumed and originated materials for sale, the conversion of aluminum waste material into green hydrogen with properly chosen reaction parameters has positive profit even when consuming an alkali of a chemical grade.

Assessing the Sustainability of NTFP-Based Community Enterprises: A Viable Business Model for Indonesian Rural Forested Areas

Indonesia’s vast forested areas have the potential to serve as a crucial source of livelihood for local communities. However, the current contributions of these forests to community livelihoods are significantly underutilized in comparison to their potential. This study evaluates the financial performance and sustainability of community forest-based businesses operating around the forest management area of the Lakitan-Bukit Cogong forest management unit (LBC FMU). Data were collected through semi-structured and in-depth interviews with the key informants through purposive sampling. Financial viability analysis and a qualitative approach were used to assess the feasibility of the businesses. The findings revealed that all businesses show positive values for all financial indicators. From profit estimation and value-added distribution, all products are shown to be feasible. Concerning the value and supply chain, the rubber-processing industry has a remarkable flow. Moreover, small forest enterprises (SFEs) highlight natural capital optimization through multitudinous derivatives of products that could support a substantial regenerative economy, including citronella essential oil, native honeybees, rubber-based product, biochar, skewers, and liquid smoke. In addition, the multidimensional scaling and rapid appraisal for forest (MDS-RAPForest) approach generates a result based on multiple dimensions (ecology, economics, social and human resources, and institutional and administrative dimensions) showing that overall, SFEs are categorized as sufficient/quite sustainable. Furthermore, mainstreaming adaptable forest-based enterprises, jurisdiction approaches, and cross-production system strategies are also discussed. Our findings suggest that sustainable NTFP-based activities within a community context can be facilitated through interconnected market systems, appropriate price regulations, and support from stakeholders and legal frameworks.

Machine Learning Implementation for Profit Estimation

The company must have a unique strategy to help grow its business. One of the ways to strengthen the company's business is by estimating the company's profit. This is because with an estimated profit, the company can manage the transactions made. Some companies still use a manual profit determination process that requires several steps. Processes that are carried out manually result in a long time, which can cause delays in completing tasks and results that are less accurate than desired. Multiple linear regression is an algorithm used to determine the relationship between the dependent variable and at least two independent variables. This algorithm is a type of supervised learning algorithm that develops estimation models based on input data. The use of this algorithm is included in part of machine learning. Implementation of machine learning to calculate company profit estimates using the Python programming language. From the estimation results using multiple linear regression and Python programming, the result is that multiple linear regression can be utilized or used to predict company profits. 98% of Profit is influenced by independent factors, namely R&D Spend and Marketing Spend, while the remaining 2% is influenced by variables that are not included in this calculation.

A flight sensing detector for apple maturity indexes in orchard

Apples quality monitoring and maturity measurement are important for yield evaluation, profit estimation, determination of harvest time and postharvest storage conditions. This study explored the monitoring ability of the micro-Unmanned Aerial Vehicle (UAV) to the orchard, the force sensor and gyroscope are used to observe the force and posture changes of apples during the spectral collection process. The UAV carries 18 channels of visible/near-infrared multispectral sensor to collect the internal information of growing apples at close range. A total of 200 apples were collected in the orchard, and then soluble solid content (SSC), titratable acid (TA), firmness, and starch pattern index (SPI) were destructively tested. Multiple scatter correction (MSC) and Standard normal variate (SNV) pretreatment combined with partial least squares regression (PLSR) were used to establish the internal quality prediction model. Streif index is used to evaluate the maturity of apples. The results showed that the detection of apples on trees by UAV would not affect the growth of apples and could collect the internal quality information. The correlation coefficient of the prediction model for apple maturity is 0.8593 and root mean square error is 0.0102. It shows that this study has potential in detecting the changes of quality and maturity of growing apples and is helpful to the overall perception of orchards.

Reduced real lifetime of PV panels – Economic consequences

The maintenance and analyzing failures of PV systems and plants are becoming more and more important issues. Our data from the long-term operation of 85 photovoltaic power plants in central Europe show that their actual lifetime is about half that of the originally planned lifetime. After about 10 years, serious failures of 1st tier (bankable) PV panels occur at an increasing rate. This article presents selected typical data and describes the most serious failures. Furthermore, economic calculations of returns on investment are carried out in relation to the price of electricity, which is currently changing at a rapid pace. It shows that the PV panel lifetime reduction from 20 to 30 years, declared at commercial leaflets, to real lifetime about 10–12 years can reduce PV power plant profit substantially, but the investment is still worth it. The reason is that after 10–12 years ser vice/maintenance expenses to replace damaged PV panels and inverters are growing very quickly. The new information could be helpful for owners of PV power plants to get a more realistic estimation of profits.

Innovation in Company Profit Management: Socialization of Numerical Calculation for Efficiency Improvement at PT Ajisaka

This community service project aimed to enhance the efficiency and effectiveness of PT. AJISAKA's business management through the introduction of a sophisticated software tool for forecasting and profitability estimation. Blending management science with computational science, the project sought to facilitate informed decision-making by leveraging artificial intelligence in profitability ratio prediction. The methods employed involved the execution of Tri Dharma Perguruan Tinggi and extensive socialization of numerical calculation techniques related to the company's profit estimation. The project was well received by the company's management, with the software's potential to enhance business insight and streamline operations being widely appreciated. The result of this endeavor underscores the potential of AI in revolutionizing profitability forecasts and business management. Furthermore, it bolsters the case for technological self-sufficiency in the economic and business sectors, paving the way for future innovation and the broad adoption of artificial intelligence in business management.
 Highlights:
 
 Utilization of artificial intelligence for accurate profitability forecasting and enhanced business decision-making.
 Successful execution of Tri Dharma Perguruan Tinggi, promoting technological independence in the economic sector.
 Broad appreciation and potential for AI application in streamlining operations and fostering business insight.
 
 Keywords: Artificial Intelligence, Profitability Forecasting, Business Management, Technological Self-sufficiency, Numerical Calculation.