Price Information Research Articles

A study on using robust hedonic regression implementation

This article aims to determine the features affecting the price of a product with the hedonic regression model and to estimate the contribution of each feature to the price by using robust regression estimation methods. For the analysis, the price and feature information of the laptop product group were obtained from the big data source by using the web scraping method. Four alternatives of the hedonic regression model are used to determine the features affecting the price of the laptops. The contribution of each feature to the laptop price is estimated by using the robust (Huber M-estimator) estimation method and the Ordinary Least Squares (OLS) estimation method, and the resulting estimates are compared for both methods. In the framework of the data set used in the study, it is observed that the effective model is the Logarithmic Robust Hedonic Regression Model.

Evaluation of potential cost savings through chemotherapy and biotherapy dose-rounding at a pediatric institution.

Rapidly increasing costs of medication acquisition can pose a challenge for health-system pharmacy budgets. The impact of dose-rounding in a pediatric oncology population has not previously been well documented and a retrospective review was undertaken to quantify the potential cost benefits. A retrospective chart review of patients with an oncologic diagnosis was performed for cytotoxic agents, asparaginase products, and biotherapy administered between January 1, 2014, and December 31, 2017. In the analysis, orders that could be rounded down to the nearest vial size by 5 or 10% were included. Medication pricing information was based on wholesale acquisition cost (WAC) and was provided by the Department of Pharmacy. Cost savings per medication were determined by multiplying the WAC of the medication by the number of vials saved. Over a 4-year span, 347 patients were evaluated and 552 out of a possible 3110 orders (17.7%) met criteria for a theoretical cost savings of approximately $1,126,000 (∼$3200 per patient). Rounding down doses by up to 5% resulted in a potential savings of about $529,000. When rounding was extended to 5-10% of the originally ordered dose, an additional $597,000 of approximate cost savings could have been realized. The medications with the largest impact on cost savings were rituximab, pegaspargase, and erwinia asparaginase. For pediatric oncology patients, there exists a unique potential cost savings opportunity if doses are rounded down within 5 or 10% of the originally ordered weight-based or body surface area-calculated dose.

Banks, non-banks, and the incorporation of local information in CMBS loan pricing

Comparing banks to non-bank lenders, we investigate whether the geographical distance between lenders, borrowers, and their properties is reflected in the pricing of US mortgages that were included in US commercial mortgage-backed security (CMBS) pools during the 2000 to 2017 period. The difference in loan spreads when the bank-borrower distance increases from zero to the median of about 700 miles is 10 basis points, and this effect is more pronounced if the loan is collateralized by a riskier property. On the contrary, geographical distance does not seem to have any effect on the loan spread of mortgages granted by non-bank lenders. The difference in loan pricing across originator types (even after controlling for key mortgage and property characteristics) suggests that banks and non-bank lenders have different incentives, lending technologies, and/or different types of borrowers. Our results contribute to the emerging literature on non-bank lender behavior.

Security Analysts’ Site Visits and Stock Price Synchronicity

AbstractThis paper investigates how security analysts’ corporate site visits impact listed firms’ stock‐price informativeness. Examining a sample of security analysts’ visits to Chinese listed firms from 2010 to 2019, we find that security analysts incorporate firm‐specific information into share prices through site visits, significantly reducing the visited firms’ stock price synchronicity. This finding is robust to an alternative measure of stock price informativeness and a two‐stage least‐squares approach using the introduction of high‐speed rail as the instrumental variable. We also find that the impact of analysts’ site visits on firms’ stock price synchronicity is more pronounced for firms with lower information disclosure quality and poor corporate governance than for other firms. Further analysis on firm characteristics documents that this effect is stronger for large‐size firms, firms in the manufacturing industry, and state‐owned enterprises.

Futures Market for Demand Responsive Travel Pricing

While transportation funding can be collected in a variety of direct (e.g., fares, tolls, and gas taxes) or indirect (e.g., property and sales tax) ways, dynamic demand responsive pricing not only collects revenue but also incentivizes travelers to avoid peak-demand periods, thus utilizing infrastructure capacity more efficiently. Unfortunately, the demand response to price changes, called the price elasticity of demand, is generally greater for longer-term travel planning (e.g., air and rail travel) than it is for more atomized short-term planning (e.g., highway tolls and transit fares). While this is caused by a plethora of factors (e.g., time flexibility, housing choice, automobile investment, etc.), a critical factor is that travelers simply lack sufficient information for future travel planning. For example, airline prices at different times can easily be compared, but a highway driver cannot accurately predict congestion nor congestion pricing. For this reason, such price changes have little effect on demand. This leaves any congestion abatement up to inefficient trial and error, and anecdotal speculation by travelers. Moreover, dynamic pricing is politically unsavory because of price uncertainty and collateral equity concerns. This article seeks to help remedy these concerns by proposing a simple “futures” market mechanism that can augment existing fare/toll collection technologies, providing travelers with sufficient pricing information and purchasing options to preplan their travel and avoid excessive prices. Users can optionally pre-pay their future fares/tolls to lock in a lower price for expected trips, thus encouraging good travel planning and efficient infrastructure utilization, while reducing price uncertainty.

SimVGNets: Similarity-Based Visibility Graph Networks for Carbon Price Forecasting

In response to global warming, carbon trading market emerges to reduce carbon emissions. However, uncertain fluctuations and complicated price mechanisms in the market have changed the characteristics of carbon data. Existing methods cannot track underlying structures among carbon data streams, failing to explain high variations and predict carbon prices accurately. In this case, how to predict carbon price is a problem demanding new and prompt solutions. Unlike existing predictive mechanisms with fixed structure, in this work, we investigate carbon price from a novel perspective of visibility graph networks, developing a variant forecasting framework based on visible relationships. Firstly, carbon prices are mapped into networks where data are transformed into corresponding nodes utilizing visibility algorithm. Then a novel similarity index is proposed to measure similarity distribution of nodes converted from carbon data, which extracts past and recent price information rather than only considering recent input, resulting in the loss of past knowledge. The forecasting model is finally established based on mutual visibility machamism and similarity of constructed carbon network. To verify the proposed method, experiments are conducted on real carbon datasets, and the results demonstrate the method is superior to existing models, suggesting the predictive potentials of graph network science. It is hoped that this work can act as a bridge between carbon data and networks, motivating further research on carbon price forecasting from graph network views.

Economic and environmental analysis of processing plant interventions to reduce fluid milk waste

With the increased awareness about the economic and environmental impact of food waste, many interventions along food supply chains have been proposed to mitigate food waste. Even though interventions used to target food waste usually revolve around logistics and operations management, we highlight a unique solution to address this issue, specifically for fluid milk. We target the intrinsic quality of fluid milk by evaluating interventions that will extend the product shelf life. We used data from a previous fluid milk spoilage simulation model, collected price and product information from retail stores, conducted an expert elicitation, and used hedonic price regressions to determine the private and social gains to the dairy processing plant when implementing 5 different interventions to extend shelf life. Our data suggest that the value of each additional day of shelf life is approximately $0.03 and indicate that increasing periodic equipment cleaning is the most cost-effective strategy for processing plants to achieve fluid milk shelf-life improvements, both from a firm's economic standpoint and from an environmental standpoint. Importantly, the approaches reported here will be valuable to help individual firms to generate customized facility and firm specific assessments that identify the most appropriate strategies for extending the shelf life of different dairy products.

Evidence-based cost estimation of essential medicines for pediatric cancer care in Peru.

e18533 Background: Inequitable access to essential medicines is a large contributor to the inferior outcomes experienced by children with cancer living in low-and-middle-income countries. In collaboration with the Peruvian Ministry of Health and the Pan American Health Organization, we aimed to predict annual aggregate drug costs as well as primary cost drivers for treating Peruvian children with cancer to inform more accurate and efficient drug procurement. Methods: FORxECAST is a pediatric cancer-specific model that projects required drug quantity and cost for 18 common pediatric cancers, drawing on internationally adopted standard treatment protocols. It is customizable to geographic region, local cancer incidence, stage distribution, and domestic drug prices. To estimate aggregate costs utilizing FORxECAST, Peruvian incidence, stage at diagnosis, and per-unit drug prices were provided by local stakeholders. FORxECAST-embedded standardized data for country-specific age, sex, and BSA sourced by the World Health Organization and the Global Childhood Cancer Microsimulation Model were used. To provide comparative analyses, aggregate costs adapted for Peruvian incidence were calculated utilizing reference drug prices available through the Management Sciences for Health (MSH) International Medical Products Price Guide. Results: FORxECAST projected Peruvian aggregate drug costs to be USD$1,672,795.47 annually, which was 47% less than expected by median MSH prices and represents 4% of the total Peruvian cancer care budget. 19 of 22 medicines were cheaper on a per-unit basis relative to MSH. Dactinomycin was the costliest per-unit agent but contributes to less than 2% of the overall budget due to low aggregate demand. Primary cost drivers were 6-mercaptopurine, intravenous methotrexate, and asparaginase, due to the large quantities needed for treatment of Peru’s most common pediatric cancer: acute lymphoblastic leukemia. However, because of their low per-unit prices, sensitivity analyses showed that the annual drug budget would remain lower than predicted by MSH, even if the per-unit price for these 3 agents increased by 50% (USD$2,431,550.71 vs. USD$3,099,401.31). Conclusions: The cost of procuring accurate quantities of essential pediatric cancer medicines to meet population-level need is a small percentage of the total cancer budget for the Peruvian healthcare system. Given the potential impact that improved drug access could have on pediatric cancer survival, these data can justify health systemic efforts to effectively earmark funds for pediatric cancer care and minimize risks of stockout. Our analyses also demonstrate the importance of incorporating context-specific drug prices when estimating domestic budget impact. Next steps include comparative analyses with neighboring health systems in Latin America to assess regional price variation and inform opportunities for pooled procurement.

Cryptocurrency Price Prediction Using Enhanced PSO with Extreme Gradient Boosting Algorithm

Abstract Due to the highly volatile tendency of Bitcoin, there is a necessity for a better price prediction model. Only a few researchers have focused on the feasibility to apply various modelling approaches. These approaches may prone to have low convergence issues in outcomes and acquire high computation time. Hence a model is put forward based on machine learning techniques using regression algorithm and Particle Swarm Optimization with XGBoost algorithm, for more precise prediction outcomes of three cryptocurrencies; Bitcoin, Dogecoin, and Ethereum. The approach uses time series that consists of daily price information of cryptocurrencies. In this paper, the XGBoost algorithm is incorporated with an enhanced PSO method to tune the optimal hyper-parameters to yield out better prediction output rate. The comparative assessment delineated that the proposed method shows less root mean squared error, mean absolute error and mean squared error values. In this aspect, the proposed model stands predominant in showing high efficiency of prediction rate.

Institutional Investor Trading and Stock Price Informativeness: Empirical Evidence from the Vietnamese Stock Market

Bài viết nghiên cứu ảnh hưởng của giao dịch mua bán cổ phiếu của nhà đầu tư tổ chức đến tính thông tin của giá cổ phiếu của các doanh nghiệp niêm yết Việt Nam. Kết quả chỉ ra rằng giao dịch của nhà đầu tư tổ chức truyền tải các thông tin nội bộ của doanh nghiệp đến thị trường, từ đó làm tăng tính thông tin của giá cổ phiếu. Bên cạnh đó, giao dịch mua của nhà đầu tư tổ chức chứa đựng các tín hiệu tích cực về giá cổ phiếu. Tín hiệu này làm gia tăng giao dịch mua của các nhà đầu tư khác, dẫn đến lợi suất bất thường sau ngày thông báo mua cổ phiếu của nhà đầu tư tổ chức.

Variations in global prices of chemotherapy for childhood cancer: a descriptive analysis.

The stark disparity in survival for children with cancer across the world has inspired a global call to expand chemotherapy access in low and middle income countries. Among the numerous barriers to success, a paucity of reliable information regarding chemotherapy pricing hinders the ability of governments and other key stakeholders to make informed budget decisions or negotiate lower medication prices. The aim of this study was to generate comparative price information on both individual chemotherapy agents and comprehensive treatment regimens for common childhood cancers using real-world data. Chemotherapy agents were selected based on their inclusion in the World Health Organization (WHO) Essential Medicines List for Children (EMLc) and their use in frontline regimens for the tracer cancer types prioritized by the WHO's Global Initiative for Childhood Cancer (GICC). Sources included IQVIA MIDAS data, obtained under license from IQVIA, and publicly available data from Management Sciences for Health (MSH). Data on chemotherapy prices and purchase volumes spanning 2012-2019 were aggregated according to WHO region and World Bank (WB) income classification. Cumulative chemotherapy prices for treatment regimens were compared across WB income classification. Data representing an estimated 1.1 billion doses of chemotherapy were obtained for 97 countries: 43 high income countries (HICs), 28 upper middle income countries (UMICs), and 26 low and lower middle income countries (LLMICs). Median drug prices in HICs were 0.9-20.4 times those of UMICs and 0.9-15.5 times those of LMICs. Regimen prices were generally higher for HICs, hematologic malignancies, non-adapted protocols, and higher risk stratification or stage, albeit with notable exceptions. This study represents the largest price analysis to date of chemotherapy agents used globally in childhood cancer therapy. The findings of this study form a basis for future cost-effectiveness analysis in pediatric cancer and should inform efforts of governments and stakeholders to negotiate drug prices and develop pooled purchasing strategies. NB received funding support from the American Lebanese Syrian Associated Charities and Cancer Center Support grant (CA21765) from the National Cancer Institute through the National Institutes of Health. TA received funding through the University of North Carolina Oncology K12 (K12CA120780) and the University Cancer Research Fund from the UNC Lineberger Comprehensive Cancer Center.

Price information, inter-village networks, and “bargaining spillovers”: Experimental evidence from Ghana

Through a randomized experiment and detailed data on inter-village communication, we identify the impact of providing commodity price information to smallholder farmers. For yam, a crop with high prevalence of bargaining, the intervention leads to a 9% increase in the prices received by farmers in the treatment group in the first year and possibly to mixed indirect effects in the second year in areas with high density of treatment. While control farmers do not gain price information, we speculate that bargaining spillovers might lead to indirect benefits and capture this intuition in a formal model. The intervention has no impact on other crops grown in the area, which are characterized by different market structures and lower incidence of bargaining. The results expand our understanding of the market structure characteristics that affect the effectiveness of ICT interventions and highlight the importance of considering longer-run inter-village spillover effects.

Stock ranking prediction using a graph aggregation network based on stock price and stock relationship information

The volatility of stock prices makes it difficult to predict stock price trends correctly. This volatility is affected by many factors, including other stocks related to it. Stock prediction based on graph learning uses various graph neural networks to learn how stocks interact to provide more information. However, they tend to adopt statically defined stock relations based on prior knowledge (such as industry relations and Wiki relations), making it difficult to capture the interplay between stocks over time. In addition, their predictions mostly rely on a single stock relationship, while many types of stock relationships affect the volatility of stock prices in a complex and intertwined manner. A new price similarity relation graph is first constructed using the multi-view stock price similarity to capture dynamic stock relationships. Based on three stock graphs (price similarity, Wiki and industry), we further propose a multi-relational graph attention ranking (MGAR) network. In MGAR, the multi-graph aggregation is achieved by applying adaptive learning mechanisms, thereby forming effective relation embeddings. When combined with the captured price trend embedding, MGAR model gives a ranking list of future returns and chooses K stocks with the best returns to trade so that the return on investment is maximized. Extensive experiments demonstrate that MGAR method outperforms state-of-the-art stock predicting solutions, achieving average returns of 164% and 236% on two real datasets, respectively.

PERILAKU KONSUMEN DAGING AYAM BROILER DI PASAR TRADISIONAL DAN MODERN

The purpose of this study was are to describe consumer behavior in buying broiler meat at the traditional and Modern Market. This research was conducted September-Oktober in Sorong City, West Papua. The sampling method used accidental sampling, and used descriptive data analysis. Variables namely Quality, Location, Price, and product information. The results of the study were obtained. First, broiler meat distribution channels at Saga supermarkets, namely from breeders to retailers and to consumers. Supermarker Saga as a Retail Merchant. The behavior of broiler meat consumers based on the quality of the meat in the Warmon market was 64%, because consumers prefer the freshness of traditional market meat. Based on location, consumers prefer Saga supermarkets as much as 74% because of complete facilities and convenience. Based on the price of broiler meat, the percentage of supermarket saga is 66% because this place sells meat according to the wishes of consumers in the form of cuts of meat at the right price. Based on information from Saga supermarkets, there were 78% due to more information on products to consumers through sosial media.

RCML: A Novel Algorithm for Regressing Price Movement during Commodity Futures Stress Testing Based on Machine Learning

Stress testing, an essential part of the risk management toolkit of financial institutions, refers to the evaluation of a portfolio’s potential risk under an extreme, but plausible, scenario. The most representative method for performing stress testing is historical scenario simulation, which aims to evaluate historical adverse market events on the current portfolios of financial institutions. However, some current commodities were not listed in the commodity futures market at the time of the historical event, causing a lack of the necessary price information to revalue the current positions of these commodities. To avoid over reliance on human hypothesis for these non-existent commodity futures, we propose a novel approach, RCML, to infer reasonable price movements for commodities unlisted in historical events. Unlike the previous methods, based on subjective hypothesis, RCML takes advantage of not only machine learning algorithms, but also multi-view information. Back testing and hypothesis testing are adopted to prove the rationality of RCML results.

More Risk, More Information: How Passive Ownership Can Improve Informational Efficiency

Abstract We identify a novel economic mechanism through which passive ownership positively affects informational efficiency in the cross-section of firms. Passive investors’ inelastic demand lowers a firm’s cost-of-capital, inducing it to take more risk. The higher cash flow variance, in turn, incentivizes active investors to acquire more precise private information, pushing up price informativeness for firms with high passive ownership. High passive ownership also implies higher stock prices and higher stock-return variances. An increase in the aggregate size of passive investors amplifies these cross-sectional differences. We also document complementarities in firms’ real investment and investors’ information choices that can cause information crashes. Received May 31, 2020; editorial decision January 4, 2023 by Editor Holger Mueller. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online

(169) Characteristics of Telehealth Platforms Offering Erectile Dysfunction Treatment

Abstract Introduction Telehealth platforms are becoming more prevalent in the field of medicine, including men’s sexual health. Due to the sensitivity and potential embarrassment of discussing erectile dysfunction (ED) issues in-person, men may seek alternative methods to obtain ED treatment without leaving their homes. Objective We sought to compare the offerings of telehealth platforms for ED treatment with respect to consultation, price, services provided, and privacy policy. Methods Google was queried in June 2022 to identify online telehealth platforms offering ED treatment. Two reviewers identified and analyzed the top 50 results using the keywords “telehealth erectile dysfunction,” “telemedicine erectile dysfunction,” and “online erectile dysfunction.” Inclusion criteria are as follows: platforms must serve a majority of US states, exist online-only, provide both the consultation and prescription for phosphodiesterase 5 inhibitors (PDE5i), and deliver the prescription to the patient. Descriptive analysis of pricing information, physician access, and HIPAA compliance was performed. Results Fifteen online platforms met inclusion criteria. Ten provided “free” consultations; however, patients were expected to pay monthly or quarterly fees for prescriptions. Four bundled the consultation fee with the first month of the prescription; one of these functioned as a subscription service with a $10 monthly charge plus monthly refill fee. Fourteen (93%) platforms began the consult with an online form and ten (67%) platforms advertised review by the prescriber within two business days. Four (33%) platforms explicitly advertised physician-only consults, five (27%) used the vague term “provider,” and the remaining six (40%) advertised either physicians or other prescribers on staff. Direct contact with the prescriber (digital/audio/video) would only occur if needed or if required by state law at eight (53%) platforms. The ability to directly purchase sildenafil and tadalafil was advertised on all platforms. Pricing information varied depending on pill strength and quantity ordered on eight platforms. Six platforms only offered pricing per dose without specifying medication strength. Minimum prices of sildenafil ranged from $0.99-35/pill (mean $5.37/pill, median $2.50/pill) while tadalafil ranged from $0.90-44/pill (mean $8.48/pill, median $6/pill). In addition to ED therapy, thirteen (86%) platforms offered treatment for other men’s health issues such as premature ejaculation or hair loss. All platforms included a privacy policy, but only ten (66%) mentioned HIPAA compliance with two of these claiming to not be “covered entities.” Conclusions Telehealth platforms are changing the face of healthcare to offer evaluation and treatment of health conditions, including ED, privately from the patient’s own home. Although platforms are transparent with PDE5i medication and subscription pricing information, very few offer direct contact with a physician to further discuss issues related to ED after completion of the online intake form. For patients seeking a more comprehensive evaluation for their ED in a HIPAA compliant setting, a formal in-person or telemedicine visit should be arranged with their physician. Disclosure No

Information and optimal trading strategies with dark pools

This paper examines the effects of the competition between asset trading venues with different levels of transparency: an opaque dark pool alongside a transparent exchange organized as a limit order book (two-venue market). In a model with asymmetric information, we compare traders’ strategies and market performance in the two-venue market with that of a single-venue market (trading only in the exchange). We show that price informativeness is lower in the two-venue market when informed traders migrate to the dark pool and uninformed investors remain in the exchange. We also find that when orders migrate to the dark pool in the first period, market liquidity is lower (higher) in the two-venue market for high (low) fundamental volatility stocks as traders migrating to the dark pool would have demanded (supplied) liquidity in the exchange. Finally, the expected profits of informed traders are never lower in the two-venue market, but this may not always be true for uninformed traders.

Information sharing in African perishable agri-food supply chains: a systematic literature review and research agenda

PurposeThe aim of this paper is to provide a review of state-of-the-art literature on information sharing in the context of African perishable agri-food supply chains (AFSCs). In doing so, the authors hope to stimulate further research and advance both theory and practice on African perishable AFSCs, which is a relevant, but under-investigated context.Design/methodology/approachThe authors’ systematic literature review covers a period of 21 years (2000–2021). After providing the bibliometric and methodological insights related to this sample of literature, the authors provide a detailed analysis and discussion of the key aspects of information sharing in African perishable AFSCs, based on a review framework grounded in the information sharing literature.FindingsThe authors’ review revealed that information sharing in African AFSCs is still in its nascent stage. Findings are based on four themes of (1) why share information (mainly to gain market access), (2) what information is shared (price and market information) (3) how it is shared (still traditional communication, with limited adoption of digital technologies?) and (4) antecedents, drivers and barriers (technology adoption and socio-economic background of Africans).Research limitations/implicationsThis paper outlines a research agenda for advancing the theory on information sharing in AFSCs. Furthermore, the review highlights the importance of context, supply chain structure, relationships, product characteristics and culture in studying AFSCs.Originality/valueA review on information sharing in African perishable AFSCs does not appear to exist in operations and supply chain management (O&SCM) and agribusiness journals.

Should Private Exchanges of List Price Information Be Presumed to Be Anticompetitive?

Harrington (2022) provides a novel theory that explains how a private information exchange involving gross list prices can lead to higher transaction prices. On this basis, he considers that private list price exchanges between competitors should be presumed to harm competition. The theory, which has received much attention in the context of the EU trucks cartel case, was recently referred to by the UK Competition Appeal Tribunal as a “unilateral effects” theory, given that it involves no coordination once list prices have been exchanged. Unlike conventional collusion, the theory does not rely on a monitoring and retaliation mechanism. Given its novelty and relevance for recent competition cases, we consider it useful to explore its potential limitations. We show that both the scope for and magnitude of harm are sensitive to key modelling parameters such as the number of firms, the degree of product substitutability, and the level of marginal cost—sometimes in opposite directions. We also show that there may be no scope for the anticompetitive effect when firms are capacity constrained. Finally, we discuss several additional qualitative aspects that may undermine the theory of harm: the adaptability of internal pricing processes over time, the lack of verifiability of exchanged list price information (especially when the exchange is private), and possible procompetitive or competitively neutral reasons for the conduct. We conclude that, although Harrington provides an insightful addition to the wider literature on the competitive effects of information exchanges, the effects of list price exchanges are not sufficiently unambiguous to justify a general presumption of competitive harm.