Exact Price Research Articles

Cross-validation of insurer and hospital price transparency data.

Given recent congressional interest in codifying price transparency regulations, it is important to understand the extent to which newly available price transparency data capture true underlying procedure-level prices. To that end, we compared the prices for maternity services negotiated between a large payer and 26 hospitals in Mississippi across 2 separate price transparency data sources: payer and hospital. The degree of file overlap is low, with only 16.3% of hospital-billing code observations appearing in both data sources. However, for the observations that overlap, pricing concordance is high: Corresponding prices have a correlation coefficient of 0.975, 77.4% match to the penny, and 84.4% are within 10%. Exact price matching rates are greater than 90% for 3 of the 4 service lines included in this study. Taken together, these results suggest that although administrative misalignment exists between payers and hospitals, there is a measure of signal amid the price transparency noise.

Sustainable Hydrogen Production from Oil Palm Trunk Biomass in Indonesia: A Techno-Economic Study

Hydrogen has been recognized as a global sustainable alternative sustainable energy source. The government of Indonesia has been working on a novel idea to launch the hydrogen industry. Accordingly, research and development of ecologically acceptable hydrogen manufacturing methods are essential. Supercritical water gasification (SCWG) is one of the recent techniques to create hydrogen. This research investigated the techno-economics of hydrogen production in Indonesia using SCWG. Oil palm trunks (OPT), a plentiful byproduct of palm oil plants, are the primary raw materials employed in this industry. This study extracted data from several research publications on SCWG-related hydrogen generation and performed computational analysis using several economic parameter equations. According to the analysis, with a potential OPT source of around 34 million tons, the plant could manufacture 304,166.67 tons of OPT per year, generating 365,000 tons of hydrogen annually. The production cost was projected to be USD 1,179,409,295, with a fixed capital investment of USD 1,178,853,030.47. The expected annual income was USD 1,825,000,000. This assessment yielded an ROI of 60% and an NPV of USD 1,888,889,382.70. The IRR value was 26.96%, with a PoT of 2.49 years. The sensitivity analysis revealed that the price of hydrogen significantly affected the values of IRR and PoT. Therefore, the government must determine the exact price of hydrogen to ensure its sustainability.

A Stochastically Correlated Bivariate Square-Root Model

We introduce a novel stochastically correlated two-factor (i.e., bivariate) diffusion process under the square-root format, for which we analytically obtain the corresponding solutions for the conditional moment-generating functions and conditional characteristic functions. Such solutions recover verbatim those of the uncorrelated case which encompasses a range of processes similar to those produced by a bivariate square-root process in which entries are correlated in the standard way, that is, via a constant correlation coefficient. Note that closed-form solutions for the conditional characteristic and moment-generating functions are not available for the latter. We focus on the financial scenario of obtaining closed-form expressions for the exact price of a zero-coupon bond and Asian option prices using a Fourier cosine series method.

Laws of Economics under Socialism

This article argues that praxeology, as a general theoretical approach, can explain the emergence of the socialist doctrine. However, socialist laws of economics cannot be derived from praxeology. It is specifically shown that the immutability of market economic laws does not allow society to achieve a full-fledged communist reality. Using the Soviet Union as an example, this article demonstrates that the market economy cannot be eradicated, despite government efforts, but is omnipresent even if it is ostensibly outlawed. Also, this article demonstrates that Ludwig von Mises’s conclusion about the principal impossibility of economic calculation under socialism is fully applicable to the highest stage of communism, as theorized in Marxism. In relation to socialism in a broader sense, as the collectivization of the means of production grows, the magnitude of the impairment of economic calculation grows with it. Socialist thinkers failed to rebuff Mises’s reasoning because all their proposals violated the economic uncertainty principle: the exact price structures before the exchange are unknown and are in superposition.

Does land market matter for urban energy efficiency? Empirical evidence from cities in China

Improving urban energy efficiency on the basis of cost-effectiveness is an important topic of universal concern across the world. The input cost has great influence on energy efficiency. Thus, as one of the important factors in the production progress, land price may exert an energy effect via affecting the urban industries. With a focus on land price levels and the variability, our study investigates the impact of land market on urban energy efficiency, based on the panel data of China's prefecture-level cities. Further, by exploring effects of the segment land markets, our study reveals the exact price features in land market that have driven the changes in energy efficiency of cities. The main results are: (a) Either of the price level and the price variability in urban land market has a positive net effect on energy efficiency. When price level and variability increase by 1%, urban energy efficiency respectively increases by 0.06% and 0.04%, and the effects vary with city's population size and geographic location; (b) An increase of land price level improves energy efficiency by optimizing industrial structure and reduces energy efficiency by weakening industrial production efficiency, while an increase in land price variability exerts a positive impact on energy efficiency by adjusting industrial structure; (c) The price level factor affecting urban energy efficiency is mainly the commercial-residential land prices, while the difference between commercial-residential and industrial land prices is the variability factor that affects energy efficiency.

An Algorithm to Predict Real Estate Price using Machine Learning

Real Estate Pricing has always been a varying from time to time keeping a buyer confuse on how to get exact price of the property at certain point of time. A machine learning algorithm is used to predict the exact price of the property. Predicting the accurate amount of the real estate is very much a matter of concern as people are investing too much now a days in property where a property dealer could easily charge more amount if the buyer is not knowing the market price of the property. The major focus of this research paper is to predict the accurate price of the property without a hassle. Apart from that it also focuses on increasing the accuracy of the already existing system. There is various machine learning algorithm available for prediction such as Naive Bayes, Logistic Regression, Classification, Random Forest KNN, Support Vector Machine, Lasso, Linear Regression etc. The aim of this research is to predict the market value of real estate properties based on geological location. By analyzing previous market patterns, value ranges, and upcoming developments, we can determine a starting price for a property based on geological variables. Our study is applicable to any location, and we have utilized three machine learning algorithms to make predictions. Our findings indicate that linear regression provides the most accurate predictions, with an accuracy rate of 85%. This system eliminates the need for clients to rely on brokers and provides them with the confidence to invest in real estate. The accuracy of our system surpasses that of previous methods used in the industry.

On the Semantic Expansion of the Word “Change” among Yorùbá Speakers of English Bilinguals

The paper investigates the semantic evolution that has characterised the word ‘change’ in the Yorùbá-English speech community. It undertakes this descriptive effort through pragmatic and sociolinguistic perspectives that give credence to the impact of widespread usage and acceptability on the semantic elasticity of particular words. Moving from the pedestrian and original financial-related meaning of the money given back when a customer hands over more that the exact price of an item, it has now assumed broader and more socially significant interpretations that may only be comprehensible to a certain class of the Yorùbá-English bilinguals who occupy South Western Nigeria. These contextual meanings are socially inclined and are largely influenced by a certain leaning that borders on the ‘membership’ of an undefined social group that consists of semi-literates in that particular subset of the Nigerian sociolinguistic environment. The paper concludes that the uses of ‘change’ in the aforementioned contexts present a valid case of gradual semantic expansion in the widespread use of some words.

VALUATION OF INTELLECTUAL PROPERTY ON NFT TRANSACTION FOR NFT PLATFORM IN INDONESIAN PERSPECTIVES

Recently, NFT enable its owner to sell and buy intellectual properties. The research result shows that an NFT transaction process – such as in the sale and purchase of intellectual property-requires a determined price valuation. The authors consider that it is necessary to determine a clear valuation to predict the exact price of the intellectual property digitally transacted on NFT. The price database on NFT can be used to determine the price by first collecting the NFT and the price database can also calculate the value of the NFT in the future.

BERT’s sentiment score for portfolio optimization: a fine-tuned view in Black and Litterman model

In financial markets, sentiment analysis on natural language sentences can improve forecasting. Many investors rely on information extracted from newspapers or their feelings. Therefore, this information is expressed in their language. Sentiment analysis models classify sentences (or entire texts) with their polarity (positive, negative, or neutral) and derive a sentiment score. In this paper, we use this sentiment (polarity) score to improve the forecasting of stocks and use it as a new “view” in the Black and Litterman model. This score is related to various events (both positive and negative) that have affected some stocks. The sentences used to determine the scores are taken from articles published in Financial Times (an international financial newspaper). To improve the forecast using this average sentiment score, we use a Monte Carlo method to generate a series of possible paths for several trading hours after the article was published to discretize (or approximate) the Wiener measure, which is applied to the paths and returning an exact price as results. Finally, we use the price determined in this way to calculate a yield to be used as views in a new type of “dynamic” portfolio optimization, based on hourly prices. We compare the results by applying the views obtained, disregarding the sentiment and leaving the initial portfolio unchanged.

Exploring the inter-factor and inter-fuel substitution possibilities in Tunisia: the potential of renewable energy.

Tunisia is among the developing countries that have taken initiatives to develop renewable energy and strengthen energy efficiency. Moreover, it has considerable potential, especially in the field of wind and solar energy. However, the country is still dependent on fossil fuel energy. In this context, the transition to renewable energy is considered one of the possible solutions to reduce energy dependence and strengthen the economy in general. Therefore, the aim of this research study is to evaluate the role of renewable energy in shaping the energy transition in Tunisia in order to qualify the possibilities of energy transition. Accordingly, we investigate the potential for substitution between the following factors and fuels: Capital, labor, renewable, and non-renewable energy in Tunisia using a translog production function approach. Due to the multicollinearity of the model, the ridge regression method is used to estimate the parameters of the function. The obtained results showed that the possibility of substitution between inputs, especially between renewable and non-renewable energy, can replace fossil fuels with clean energy consumption. Moreover, to maximize the potential of renewable energy in Tunisia, this study recommends that policy makers should take more reliable measures to reflect the exact price of energy through price regulation measures, encourage investment in research and development, and introduce carbon taxes that could accelerate this transition.

Spread Option Pricing in Regime-Switching Jump Diffusion Models

In this paper, we consider the problem of pricing a spread option when the underlying assets follow a bivariate regime-switching jump diffusion model. We exploit an approximation technique which is based on the univariate Fourier transform representation of the option price. The method proves to be computationally very effective with respect to benchmark Monte Carlo estimators and permits the use of several kinds of jump models other than the standard Gaussian setting. As a by-product, the exact price of an Exchange Option may be efficiently computed within this framework.

Column generation for minimizing total completion time in a parallel-batching environment

This paper deals with the 1|{p-text {batch}, s_jle b}|sum C_j scheduling problem, where jobs are scheduled in batches on a single machine in order to minimize the total completion time. A size is given for each job, such that the total size of each batch cannot exceed a fixed capacity b. A graph-based model is proposed for computing a very effective lower bound based on linear programming; the model, with an exponential number of variables, is solved by column generation and embedded into both a heuristic price and branch algorithm and an exact branch and price algorithm. The same model is able to handle parallel-machine problems like Pm|{p-text {batch}, s_jle b}|sum C_j very efficiently. Computational results show that the new lower bound strongly dominates the bounds currently available in the literature, and the proposed heuristic algorithm is able to achieve high-quality solutions on large problems in a reasonable computation time. For the single-machine case, the exact branch and price algorithm is able to solve all the tested instances with 30 jobs and a good amount of 40-job examples.

The role of metacognition and schematic support in younger and older adults' episodic memory.

Older adults experience deficits in associative memory. However, age-related differences are reduced when information is consistent with prior knowledge (i.e., schematic support), suggesting that episodic and semantic memory are interrelated. It is unclear what role metacognitive processes play in schematic support. Prior knowledge may reduce encoding demands, but older adults may allocate cognitive resources to schema-consistent information because it is more meaningful. We examined metacognitive awareness of and control over associative information that was consistent or inconsistent with prior knowledge. In Experiment 1, participants self-paced their study of grocery items paired with either market prices or unusually high prices and were tested on the exact price of each item over four study-test lists with new items on each list. In Experiment 2, participants studied items for a fixed time but made judgments of learning (JOLs) at encoding. Older adults better remembered the prices of market-value items than overpriced items. In Experiment 1, younger and older adults studied overpriced items longer than market-priced items, consistent with a discrepancy reduction model of self-regulated learning, but study time did not relate to later recall accuracy, suggesting a labor-in-vain effect. In Experiment 2, participants gave higher JOLs to market-priced items than overpriced items and were generally metacognitively aware of the benefits of schematic support. Together, these results suggest that the benefits of schematic support may not be dependent on or influenced by metacognitive control processes, supporting the hypothesis that episodic memory may be less distinct from semantic memory in younger and older adults.

КОНТРОЛЬ КОСВЕННЫХ ЗАТРАТ В СТРОИТЕЛЬСТВЕ

The calculation of direct costs, which mainly consist of consumables and labor, is not difficult for special-ists. Indirect costs, also known as overhead costs, often create problems for the accountant when determining the exact cost price. The article considers the issue of calculating indirect costs as a new, more improved approach to calculating the final cost of an object and its costs. The article considers an example of the use of ABC in the construction of a library hall and its potential advantages compared to traditional costs. The project can cover cost control by implementing an activity-based cost calculation system.

Market heterogeneity and the distributional incidence of soft-drink taxes: evidence from France

Abstract Market heterogeneity may affect the distributional incidence of nutritional taxes if households sort by income across markets with different characteristics. We use scanner data to analyse the distributional incidence of the 2012 French soda tax on Exact Price Indices that measure consumer welfare from the price and availability of soft-drinks at a local level. While the average pass-through was small—about 45 per cent—, tax incidence was significantly higher in low-income and less-competitive markets. Market heterogeneity ultimately has substantial distributional effects: it accounts for at least 33 per cent of the difference in welfare variation between low- and high-income consumers.

AN ANALYSIS TOWARDS A SUSTAINABLE ENERGY SYSTEM IN ALBANIA HIGHLY SUPPORTED BY LARGE SCALE INTEGRATION OF WIND RESOURCES: A CASE STUDY OF MAMAJ WIND FARM

This article presents a highly important and detailed techno-economic analysis of a grid-connected wind farm, considered as one of the most potential location in the south of Albania, part of Tepelena region, Mamaj village. The procedure of selection of the wind turbine type is performed by evaluating the maximum Capacity Factor (CF) among 15 different types of wind turbines applied using WAsP energy tool enabling the optimization of energy system while economic analysis uses a Monte Carlo simulation well designed on RETScreen Expert tool. This modeling framework can address some beneficial values and solution which can be used from policy makers in the country to better assess the penetration of renewable energy sources into a large scale by finding the exact selling price of electricity and correcting the latest decrease of bonus factor from 1.3 in 2019 to 1.2 in 2020, which should be adjusted by a factor of 1.4. To check the economic feasibility of this project, the parameter of net present value (NPV), internal rate of return (IRR) and simple payback period (SPB) are adjusted accordingly and the financial feasible investment zone is determined.

WITHDRAWN: Sensor based integrated smart trolley system using Zigbee-experimental analysis

Abstract The Automated Shopping Trolley is a Smart Trolley which consolidates an Embedded Chip consisting of RFID reader with tag and a battery kit to allow users to self-depart at Super Markets. Knowing the significance of time, no one wants to waste their time in doing their regular works. In shopping mall, normally the waiting time is more for billing and we will not know the price of the product that is purchased. With the help of this project the waiting time is small, and customers can know the exact price of the products which will help them to shop within their budget. The important index of this project is RFID technology.

Utility Design for Distributed Resource Allocation—Part I: Characterizing and Optimizing the Exact Price of Anarchy

Game theory has emerged as a fruitful paradigm for the design of networked multiagent systems. A fundamental component of this approach is the design of agents' utility functions so that their self-interested maximization results in a desirable collective behavior. In this work we focus on a well-studied class of distributed resource allocation problems where each agent is requested to select a subset of resources with the goal of optimizing a given system-level objective. Our core contribution is the development of a novel framework to tightly characterize the worst case performance of any resulting Nash equilibrium (price of anarchy) as a function of the chosen agents' utility functions. Leveraging this result, we identify how to design such utilities so as to optimize the price of anarchy through a tractable linear program. This provides us with a priori performance certificates applicable to any existing learning algorithm capable of driving the system to an equilibrium. Part II of this work specializes these results to submodular and supermodular objectives, discusses the complexity of computing Nash equilibria, and provides multiple illustrations of the theoretical findings.

Optimal Resource Procurement and the Price of Causality

In this article, we study the problem of procuring diverse resources in a forward market to cover a set <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf E}$</tex-math></inline-formula> of uncertain demand signals <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> . We consider two scenarios: 1) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> is revealed all at once by an oracle and 2) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> reveals itself causally. Each scenario induces an optimal procurement cost. The ratio between these two costs is defined as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">price of causality</i> . It captures the additional cost of not knowing the future values of the uncertain demand signal. We consider two application contexts: Procuring energy reserves from a forward capacity market, and purchasing virtual machine instances from a cloud service. An upper bound on the price of causality is obtained, and the exact price of causality is computed for some special cases. The algorithmic basis for all these computations is set containment linear programming. A mechanism is proposed to allocate the procurement cost to consumers who in aggregate produce the demand signal. We show that the proposed cost allocation is fair, budget-balanced, and respects the cost causation principle. The results are validated through numerical simulations.

Modeling the Exact Convergence of Electricity Prices in Interconnected Markets

The liberalization of energy markets worldwide during recent decades has introduced severe implications on the price formation in these markets. Especially within the European day-ahead electricity markets, increased physical connections between different market areas and a joint effort on optimizing the aggregate social welfare have led to highly connected markets. Consequently, observing the exact same hourly day-ahead prices --- exact price convergence --- for two or more interconnected electricity markets in Europe happens frequently, which affects the modeling of such prices and in turn the valuation of derivatives written on prices from such interconnected market areas. In this paper, we propose a continuous-time model that takes this feature into account in a reduced-form manner. We discuss the properties of the model and propose an estimation procedure. Furthermore, the properties of the model reveals that analytical prices are attainable for e.g. forwards and spread options.