Methods of Calculating the Marginal Cost of Incarceration: A Scoping Review

Criminal justice reforms and corrections cost forecasts require appropriate estimates of the marginal costs of incarceration to adequately assess cost savings and projections. Average costs are simple to calculate while marginal cost calculations require much more detailed data and advanced methods. We undertook a scoping review to identify, report, and summarize the existing academic and gray literature covering the different estimation methods of calculating the marginal costs of incarceration, following the Arksey and O’Malley framework. Eighteen publications met criteria for inclusion in this review, with only one from the peer-reviewed literature. The three main approaches in the literature and their use are reviewed and illustrated. We conclude that there is a lack of, and need for, peer-reviewed literature on methods for calculating the marginal cost of incarceration, and marginal cost estimates of incarceration, to assist program evaluation, policy, and cost forecasting in the field of corrections.

COMMODITY EXPERTISE OF JEWELRY

Background. Jewelry is one of the components of material, ritual, cultural and historical heritage of mankind.Modern jewelry has acquired significant differences from those created in the past. Changes in the field of production and trade in jewelry explain the relevance of the analysis of cost indicators in the modern jewelry market and the feasibility of improving commodity expertise. The aim of the workis to analyze the cost indicators on the jewelry market in Ukraine, to conduct their commodity expertiseand to develop an algorithm for cost forecastingof jewelry in accordance with their quality characteristics. Materials and methods. A database of initial data on jewelry present on the market was created in the following range: weddingrings, rings, pendants and earrings. All named products weigh up to 10 grams and are made of 925 silver and 585 gold. Most of them are decorated with precious and semi-precious stones or inserts that imitate them. To develop an algorithm for cost forecastingof jewelry, a mathematical model was built and the quality of the approximation was calculated according to K. Pearson. Results. The results of the analysis of cost indicators in the modern jewelry market are described, and also recommendations for performance of tasks of their com­modity expertise are given. Three commodity groups of jewelry have been identified and an algorithm for predicting their value has been developed.A protocol for assessing the quality of jewelry and standards for visual comparison operations are presented. An approach to determining the estimated value of exclusive jewelry is proposed. Conclusion. The general regulations of work of commodity expertise of jewelry are established. Creating a mathematical model for cost forecastingof jewelry requires the compi­lation of a database of initial data of representative samples presented on the market. For each cost interval it is necessary to build a regression mathematical model that will ensure maximum consideration of pricing factors and the authenticity and reproducibility of the results of commodity research. Commodity expertiseof the cheapest jewelry can be carried out only on the basis of the value of the used precious metals. Medium-value jewelry requires market analysis and mathematical forecasting. Jewelry with precious stones of natural origin also requires analysis of databases on precious stones. More expensive jewelry (more than UAH 300,000 per sample) can be valued only at the value of the gemstone. Keywords: commodity expertise, jewelry, cost forecasting, protocol, evaluation criterion.

An analytical model of the replacement costs of aircraft engine life-limited parts

Purpose The purpose of this paper is to present novel recursive expressions for modelling the replacement costs of aircraft engine life-limited parts during shop visits to assist engine operators in both evaluating their decisions regarding the applied life-limited parts management strategies and tracking the replacement costs consistently throughout the life of the engine. Design/methodology/approach The replacement costs of aircraft engine life-limited parts are modelled analytically in this research, which strives to quantify the costs of used and unused lives of the replaced parts, incurred during engine shop visit events. Inputs for this model include the list price of life-limited parts, the replacement decisions made on all previous shop visits and the number of cycles the engine has operated at different thrust ratings on all previous operating intervals. Findings The average annual escalation rate of life-limited parts list prices was shown to range from 5% to 7%. The presented model is not only suitable for calculating the costs of used and unused lives of life-limited parts during past engine shop visit events but also for application in the life-limited parts replacement cost forecasting and optimisation models. Originality/value Uniquely derived recursive expressions represent the final result of the developed model which, to the authors’ knowledge, had not been studied elsewhere in the academic literature. The analysis of aircraft engine life-limited part list prices carried out to account for the average annual escalation rate enables the prediction of replacement costs during subsequent shop visits.

Digitization of the agricultural crop industry as a factor for business growth

The production costs of agricultural enterprises of 43 rural areas in the South of Russia, which systematically cultivate the same types of crops: winter and spring grains, pulse crops, maize, sunflower, potatoes and open field vegetables, has been investigated. Mathematical tools for cost forecasting and long-term planning of production of the most competitive species for profitable sales on the world (grain) and domestic product markets are shown.

Battery cost forecasting: a review of methods and results with an outlook to 2050

This review analyzes 53 publications that forecast battery cost and provides transparency on methodological and technological details.

Conventional and Current way of Interpretation and Cost Forecasting

This study discuses Short-term cost interpretation, regression analysis with time-series data, long term cost interpretation, Regression analysis using cross-section data, cost forecasting and Changes in the productivity of production factors. Short-term cost interpretation lead to short-term decisions, the concept of incramental costs has a very important role which includes variable costs and changes in fixed costs. Long term cost interpretation to analyze the production function of several different firms, long-run cost estimates can be used. Based on these conditions, the estimation of long-term costs uses cross-section data. Forecasting costs for various levels of output in the coming period requires an assessment of changes in the efficiency of the production process physically, plus changes in the prices of production factors used in the production process.

The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects

Accurate and stable cost forecasting of substation projects is of great significance to ensure the economic construction and sustainable operation of power engineering projects. In this paper, a forecasting model based on the improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm (WPA) is proposed to improve the accuracy and stability of the cost forecasting of substation projects. Firstly, the optimal features are selected through the data inconsistency rate (DIR), which helps reduce redundant input vectors. Secondly, the wolf pack algorithm is used to optimize the parameters of the improved least square support vector machine. Lastly, the cost forecasting method of WPA-DIR-ILSSVM is established. In this paper, 88 substation projects in different regions from 2015 to 2017 are chosen to conduct the training tests to verify the validity of the model. The results indicate that the new hybrid WPA-DIR-ILSSVM model presents better accuracy, robustness, and generality in cost forecasting of substation projects.