Price Variability Research Articles

Biodiesel and fishmeal from Nile tilapia waste: process, techno‐economic, and Monte Carlo analyses

AbstractWaste from the fish processing industry can provide a profitable and sustainable business. Industrial fish by‐products can be used as raw material to produce biofuels. This work evaluates the production process, characterization, and economic analysis for the production of biodiesel and fishmeal from tilapia processing waste. It demonstrates the potential of neutralized tilapia oil as a valuable raw material for biodiesel production. It presents specific mass, viscosity, and flash point results in line with ASTM and EN standards. Different plant sizes are modeled to evaluate biodiesel economic viability. Only the largest plant size was economically viable. In this case, the net present value (NPV) of US$ 13.89 million, the internal rate of return (IRR) of 50%, and the earnings before interest and taxes (EBIT) of US$ 7.87 million/year showed that the production of biodiesel and fishmeal using tilapia waste is economically attractive. Monte Carlo simulation was used to analyse the price distribution of biodiesel and fishmeal and their effects on the plant size. A large plant size gave 100% good scenarios, whereas a medium plant size showed 25% beneficial scenarios, and small plants did not have good scenarios. In this context, the plant size can overcome risks from price variability. The economic evaluation revealed that the production scale and the factory's location influenced the project's viability directly as raw material costs are associated with transportation expenses. The study therefore indicates that not all countries with well established tilapia production can produce biodiesel in a viable and sustainable way.

Exploring the impact of hotel attributes and services on price and revenue: A hedonic pricing model approach with a focus on internal and external segmentation and repeat customers

Hedonic pricing (HP) models are widely used to capture the price heterogeneity of hotel attributes and complementary services. This study uses a broad-ranging database with information about 11 hotels, located in the same Majorcan (Spain) coastal town, to identify the main attributes, complementary services and guest characteristics that affect hotel pricing, hotel revenue (RevPAR) and repeat stays. The results found that, aside from the main sources of price variability, such as accommodation type, location and season, other hotel attributes/services were found to influence these dependent variables: refurbishments, room type, occupancy level, number of stars, clients’ online ratings and the specific hotel. Attributes/services did not have a homogeneous effect on the three types of models estimated, as some attributes increased prices without increasing RevPAR or number of repeat stays.

A network-based strategy of price correlations for optimal cryptocurrency portfolios

A cryptocurrency is a digital asset maintained by a decentralised system using cryptography. The complex correlations between the cryptocurrencies’ prices may be exploited to understand the market dynamics and build efficient investment portfolios. We use network methods to select cryptocurrencies and the Markowitz Portfolio Theory to create portfolios that are agnostic to future market behaviour. The performance of our network-based portfolios is optimal with 46 cryptocurrencies and superior to benchmarks for short-term investments, reaching up to 1,066% average expected returns within 1 day. Cryptocurrency portfolio investment may be competitive but calls for caution given the high variability of prices.

Oil Price-Exchange Rate Interdependence: Relevance of Theory of Exchange Rate Overshooting in Nigeria

This article investigated the interdependence between crude oil variability and foreign exchange rate changes in Nigeria. Oil price variability is decomposed into fluctuation on Brent Oil, West Texas Intermediate, OPEC Basket Reference Crude Oils and Bonny Light Crude Oil Price Variability. All the data that used in this research come from secondary sources. Annual time series data for Nigeria are used from 1993 to 2022. The research design for the study is ex post facto research analysis of annual multivariate time series data. The study examined the historical data in order to understand the current state of foreign exchange rate in Nigeria and causal connections crude oil price variability using ARDL Bound test, Johansen approach and Error-Correction Mechanism (ECM) models. In the long run, the coefficient of oil price volatility shows a positive and significant relation with the f o r e i g n e x c h a n g e r a t e at 10 percent level of significance. This implies that a 10 percent, increase in oil price volatility induces foreign exchange rate by 0.61 percent. The positive coefficient of oil price volatility tends to reveal that Dornbusch (1976) Overshooting hypothesis of foreign exchange rate holds for Nigeria. This finding is in conformity with previous studies like (Driskill & McCafferty, 1982); Turnovsky & Bhandari, 1982; Driskill & McCafferty, 1982). Furthermore, the coefficient of BOP and OPEC show a negative and insignificant relationship with the foreign exchange rate in the long run. This implies that BOP and OPEC hav e no impact on foreign exchange rate. This is in contrast with economic theory particularly Dutch diseases proposition and in conformity with foreign exchange rate overshooting theory. The negative nexus can be blamed on the inability of government to manage the foreign exchange supply and demand effectively in the country. Diversifying away from oil to other non-oil activities that would generate foreign exchange sh

30. Evaluation of hospital compliance with federal price transparency regulations and variability of negotiated rates for spinal fusion

30. Evaluation of hospital compliance with federal price transparency regulations and variability of negotiated rates for spinal fusion

An Analysis of Community-Level Socioeconomic Status Effects on Pricing Transparency and Variability of Hand Surgery Procedures.

The hospital price transparency final rule requires hospitals to publish pricing information about provided items and services by means of 2 methods: (1) a comprehensive machine-readable file and (2) a display tool of selected shoppable services. Using machine-readable files on hospital websites, the authors examined trends in pricing transparency and variation in association with community-level socioeconomic factors for 3 common hand surgery procedures among Association of American Medical Colleges-affiliated hospitals. Available discount cash prices and payer-specific negotiated prices for CPT codes 64721, 26615, and 25111 were recorded. Multivariate analysis was used to stratify hospitals into 2 groups based on their area's median household income, percentage uninsured, and geographic practice cost index practice expense scores. Generalized linear mixed effects modeling was used to evaluate price variability against community-level financial characteristics of the patient population. Of hospitals that met selection criteria, a majority did not display discount cash prices and payer-specific negotiated prices for the 3 procedures. Hospitals in lower-income areas and areas with a higher percentage of the uninsured tended to charge a higher average payer-specific negotiated price for CPT code 25111. They also tended to have greater variation in payer-specific negotiated prices than hospitals found in higher-income and lower-percentage-uninsured areas. This study demonstrates that considerable pricing variation and incomplete transparency exists for CPT codes 64721, 26615, and 25111 among Association of American Medical Colleges-affiliated hospitals. Patients in lower-income and higher-percentage-uninsured areas are more exposed to a higher variability and average of negotiated prices than those in higher-income areas, which may translate to higher out-of-pocket costs for those with higher coinsurance and less socioeconomic prowess.

Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty

Design and assessment of energy systems is affected by many sources of uncertainty and variability determining their technical and economic performances. This is even more relevant in systems exploiting renewable energy sources, given the intrinsic uncertainty in their availability. In this case, traditional design and evaluation methods based on deterministic analysis assuming average nominal values of involved parameters may lead to inaccurate decisions and underestimating inherent risk. Software tools for evaluating investment in renewable power systems are widespread, but uncertainty is often only included in the form of simple sensitivity analysis, changing one-element at time, thus failing to give a complete picture of uncertainty propagation effects. Some contributions on the economic evaluation of renewable energy systems under uncertainty are available in the literature, but only a few sources of uncertainty are considered. As a contribution to filling this gap, in this work, a framework for economic performance assessment of offshore wind power systems considering the effects of both epistemic and aleatory uncertainty is proposed by simultaneously considering the uncertainty of the correlations used to model the system, the variability of resource availability and energy sale price as well as the impact of failures and major disruptive events. The approach allows a thorough and realistic assessment of uncertainty propagation on the profitability of the investment, and is demonstrated in an accompanying application example.

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.

The Cost of Operating: Analysis of Single-Use Instrument Costs for Craniotomies.

Introduction All-cause craniotomies comprise a significant portion of neurosurgical practice as well as hospital costs. While some instruments are reusable with a fixed cost, price variability for similar single-use instruments exists. A better understanding of these cost variations within cranial procedures can better inform operating physicians to be cost-sensitive stewards. Objective In this study, we examine how single-use items contribute to the overall cost of cranial procedures. Methods A de-identified institutional database containing records of all single-use items from craniotomies between July 1, 2019, and June 30, 2020, was subject to a longitudinal analysis by three independent parties (one senior surgeon, one resident, and one medical student). Four hundred and sixty-nine unique single-use items were identified and classified by function. Similar items were combined, and a range of costs was provided. Three sample cases with sum costs were reviewed for cost division and primary contributors. Results The category with the highest median cost across all cases was non-specialty implants comprising dural onlays, mesh, aneurysm clips, and plates. The category with the lowest median cost was personal protective equipment. The items with the most cost variability were sterile surgical patties due to the variety of sizes and preset multipacks. The proportion of cost generators varies from craniotomy indication. Conclusion While institution dependent, awareness of cost generators in cranial cases is important for economic stewardship. For single-use items, costs are highly variable and not insignificant.Surgeons and neurosurgical departments are responsible for allocating single-use items in a responsibleand efficient manner.

The Benefit of Cost-Transparency Calculators Does Not Extend to Vascular Surgery Patients

In 2021, the Centers for Medicare & Medicaid Services (CMS) mandated that every hospital create a publicly available webtool for pricing various medical services in an effort to give patients transparency in regard to their health care expenses and allow patients to "shop around" to receive the care most fitting their budget. Our objective is to investigate the utility this mandate provides for vascular surgery patients. Standardized searches were performed to find patient cost calculators for Newsweek's Top 50 Hospitals in the United States. If the webtool was found, a list of standardized searches were performed to investigate whether the tool listed prices for the following vascular procedures: Arteriovenous fistula (AVF), varicose vein procedures, and Endovascular Aneurysm Repair (EVAR). Of the 50 hospitals included, all had an easily accessible web-based cost estimator tool. The average time to find the cost estimator was 33.27sec. Of these 50 hospitals, 10% provided cost information on AVF surgery, 12% provided cost information on varicose vein procedures, and 0% provided information on EVAR. There was no difference in the hospital's likelihood to report a price based on region of the United States. Average preinsurance price for AVF surgery was $11,933.61 and $22,191 for vein procedures. In conclusion, despite good adherence to the CMS mandate requiring a publicly available pricing tool, these tools provide little to no information for vascular surgery patients. Overall, this discrepancy places vascular surgery patients at a significant disadvantage. As such, vascular patients do not have access to the knowledge necessary to financially prepare for surgery, and furthermore, they are not afforded the luxury to choose where to have procedures performed based on price variability. Hopefully this research will encourage hospitals to broaden the scope of their cost calculators to allow it to benefit all patients.

On the dynamic effects of the cross‐section distribution of sectoral price changes in China

AbstractThis paper investigates the dynamic interactions of the cross‐section distribution of sectoral price changes and the output growth in the Chinese economy. We compare in depth the results of Granger causality tests, Impulse Response, and Forecast Error Variance Decompositions from Mixed Sampling Frequency Vector Autoregression (MFVAR) with those from common frequency vector autoregression (VAR). It shows that potential causalities for inflation, relative price variability, relative price skewness, and output growth can be successfully detected by the MFVAR. The cross‐section distribution of sectoral price changes stands to be a fundamental determinant of fluctuations in the aggregate economy, not only in the short run but also in the long run. Moreover, the empirical results are robust to the identification restrictions imposed as well as to alternative measures for model variables. Our findings are in line with the predictions of a standard sticky‐price model, and thus pricing frictions are important factors behind the short‐run nonneutrality of nominal shocks. We highlight the primacy of the information contained in the higher‐order moments of cross‐section distribution of sectoral price changes. We propose that policy authorities should make proper use of all of the valuable information available, particularly those embodied in the distribution of sectoral prices.

Assessment of price variation in colorectal cancer screening procedures at US hospitals.

6652 Background: Following the 2021 Hospital Price Transparency Final Rule, US hospitals were mandated to publish their insurer-negotiated prices. We identified factors contributing to price variability of colorectal cancer (CRC) screening procedures across the US. Methods: We compared prices of colonoscopy, flexible sigmoidoscopy, CT colonography, fecal occult blood test, fecal immunochemical test, and Cologuard across U.S. hospitals using the Turquoise dataset (N = 6,378). Psychiatric, rehabilitation, and pediatric hospitals were excluded. Prices in the top and bottom 1% were also excluded to minimize the effect of outliers. Prices were adjusted by the Medicare Geographic Price Index to account for regional variability. We then compared prices across several subgroups, including National Cancer Institute (NCI) designated hospitals, teaching hospitals, and investor owned hospitals. Significance was assessed using the Kruskal-Wallis test. To quantify price variability across insurance plans within a hospital, we defined the within-center-ratio as the 90th percentile rate at a hospital divided by the 10th percentile rate. To quantify variability across hospitals, the across-center-ratio was defined as the 90th percentile median rate across all hospitals divided by the 10th percentile median rate. Results: 1,460 hospitals reported commercial prices for colonoscopy with a median commercial price of $1,867 (IQR: $1,208 - $2,689). For colonoscopy, the within center ratio was 2.5 (IQR: 1.5 – 3.8) and the across-center ratio was 6.2. Prices for other procedures are provided in the table. Compared to non-investor owned hospitals, prices of colonoscopy ($2,082 vs $1,787, P <0.001) and flexible sigmoidoscopy ($2,022 vs $1,289, P <0.001) were significantly higher at investor owned hospitals. Furthermore, across investor classes, hospitals with >5% ownership from private equity firms had the highest median price for both colonoscopy ($2,898), and flexible sigmoidoscopy ($2,697). We did not find significant differences in price by NCI designation, academic teaching center affiliation, overall hospital mortality, overall hospital readmission rate, or urban/rural location. Conclusions: CRC screening procedure prices vary significantly both within and across hospitals. Private equity and other investor owned hospitals had significantly higher prices compared to non-investor owned hospitals. [Table: see text]

The role of electricity market design for energy storage in cost-efficient decarbonization

The role of electricity market design for energy storage in cost-efficient decarbonization

Association of participation in Medicare’s Oncology Care Model with spending, utilization, and quality outcomes among commercially insured and Medicare Advantage members: A national difference-in-differences analysis.

1596 Background: Medicare’s Oncology Care Model (OCM) was a voluntary, episode-based model between 2016 and 2021 that provided participating practices with additional payments to fund care enhancements such as extended clinical hours and urgent care. While it resulted in net losses for traditional Medicare beneficiaries, the OCM may have had “spillover” improvements on spending, utilization, and quality for commercially insured (CM) and Medicare Advantage (MA) members who were not targeted by the program. Methods: This retrospective analysis used claims from Elevance Health, a large national payer, to identify commercially insured and Medicare Advantage members diagnosed with breast, colorectal, lung, prostate, and pancreatic cancer initiating systemic therapy between 2014 to 2021. We identified 85 OCM practices and 581 matched non-OCM practices based on episode, practice, demographic, and market factors. The exposure variable was participation in the OCM model. All outcomes were defined in 6-month episodes; the primary outcome was overall inflation-adjusted spending; secondary outcomes included hospitalization and emergency room visits, and end-of-life acute care utilization. We utilized adjusted difference-in-differences linear probability models, with state-level fixed effects to control for market price variability, to estimate the association between OCM participation and all outcomes. Results: We studied 45,296 episodes of care in OCM practices and 122,231 episodes in non-OCM practices among CM and MA members during the post-implementation period. OCM participation was associated with a $5,275 (SE $749.40) reduction in total allowed spending (p<0.001), driven by reductions in outpatient and systemic therapy spending. OCM was associated with improvements in end-of-life utilization and ED visits but none in hospitalizations and timely chemotherapy initiation. Conclusions: Participation in the OCM was associated with modest spillover spending benefit onto CM and MA members, but minimal utilization and quality benefits. Resultant practice innovations may have benefited non-targeted patients. Evaluations limited to targeted patients may have underestimated the full impact of the OCM.[Table: see text]

Income elasticity of demand and stock market beta

AbstractSystematic risk, or beta, measures stock price variability in the overall stock market. A considerable body of literature focuses on estimating beta. To the best of our knowledge, there is, however, a lack of definitive research on the impact of income elasticity of demand on stock market beta. This study is the first to examine this relationship using 659 publicly traded firms from 47 industries in South Korea from 2001 to 2020. To estimate the value of the stock market beta, we employ an econometric model with a fixed effects‐two stage least squares approach and use industry concentration as an instrumental variable to deal with the endogeneity problem in the estimation. The overall objective of this study is to investigate the influence of income elasticity of demand on stock market beta.

Price bands and their effects on equity markets: Evidence from a natural experiment

We exploit a unique experiment, where the intraday price moves of Indian IPO listings are restricted within a narrow band, to examine the consequences of price bands for stock prices, investor trading behavior, and stock market liquidity. Based on difference-in-differences estimations, we find that price bands lead to a significant reduction in the price variability of IPO stocks. The decrease in variability is accompanied by increases in post-IPO selling by individual investors, the price impact of trades, and IPO expected returns. Bid-ask spreads remain similar. The findings provide new evidence on the effects of intraday price bands on equity markets.

Does access to improved grain storage technology increase farmers' welfare? Experimental evidence from maize farming in Ethiopia

AbstractSeasonal price variability for cereals is two to three times higher in Africa than on the international reference market. Seasonality is even more pronounced when access to appropriate storage and opportunities for price arbitrage are limited. As smallholder farmers typically sell their production after harvest, when prices are low, this leads to lower incomes as well as higher food insecurity during the lean season, when prices are high. One solution to reduce seasonal stress is the use of improved storage technologies. Using data from a randomised controlled trial, in a major maize‐growing region of Western Ethiopia, we study the impact of hermetic bags, a technology that protects stored grain against insect pests, so that the grain can be stored longer. Despite considerable price seasonality—maize prices in the lean season are 36% higher than after harvesting—we find no evidence that hermetic bags improve welfare, except that access to these bags allowed for a marginally longer storage period of maize intended for sale by 2 weeks. But this did not translate into measurable welfare gains as we found no changes in any of our welfare outcome indicators. This ‘near‐null’ effect is due to the fact that maize storage losses in our study region are relatively lower than previous studies suggested—around 10% of the quantity stored—likely because of the widespread use of an alternative to protect maize during storage, for example a cheap but highly toxic fumigant. These findings are important for policies that seek to promote improved storage technologies in these settings.

Commodity price shocks: Order within chaos?

The prices of 27 internationally traded commodities are decomposed into transitory and permanent components by applying an ideal band-pass filter to monthly data during 1970–2022. The two components account roughly equally to price variations, but with wide heterogeneity. The permanent component accounts for two-thirds of the variability in agricultural prices but less than 30 percent in energy prices. The transitory component revealed three medium-term cycles. The first (from the early 1970s to the mid-1980s) and third (from the early 2000s to 2020) exhibit similar duration and involve almost all commodities, while the second (spanning the 1990s) is mostly applicable to metals, with the notable absence of energy. The permanent component differs across commodities, with an upward trend for most industrial commodities and downward trend for agriculture. Moreover, the permanent component of commodities in which investment is irreversible (including energy, metals, and tree crops) exhibits a high degree of nonlinearity, most likely reflecting less flexibility in investment allocation and input use of these commodities. Prices of commodities subjected to widespread policy interventions, such as internationally-coordinated supply management schemes, exhibit persistent deviations from linear trends.

A quantitative case study assessment of the biophysical and economic effects of three different feed management systems in a Northland farmlet trial

A three-year farm-systems trial was conducted in Northland from 2018–2021 with three independent 28-ha farms: 1) PAST: 2.7 cows/ha, no imported feed; 2) PKE: 3.1 cows/ha, palm kernel to meet pasture deficits; 3) PKE-PLUS: 3.1 cows/ha, palm kernel plus other supplementary feeds to meet pasture deficits. On average, cows on the PKE-PLUS farm were fed more supplementary feed and produced more milksolidsthan cows in the PAST and PKE farms (1328, 916 and 1209 kg MS/ha, respectively). Due to large variability in climate, pasture grown, milk and feed prices, there was no significant difference in mean operating profit ($2,636, $3,053, and $2,939 for the PAST, PKE and PKE-PLUS farms, respectively). The PAST farm had least personnel and machinery hours, and lowest methane emissions per hectare (316, 386 and 412kg methane/ha, for PAST, PKE and PKE-PLUS, respectively). The low-input system was more affected by climate, whereas supplementary-feed systems were affected by externalities (milk and feed prices). With increasing environmental challenges and the need to ensure appropriate staff, farm systems should be evaluated by considering environmental, personnel and profit, rather than just milk production. Greaterproduction may lead to more hours worked and more methane emissions, without any increase in profit.

Optimizing heating operation via GA- and ANN-based model predictive control: Concept for a real nearly-zero energy building

Using a simulation- and optimization-based framework that leverages artificial neural networks for the model predictive control of space heating operation, machine learning techniques are explored to predict the energy performance of a real nearly zero energy building located in Benevento (Southern Italy, Mediterranean climate). The framework's goal is to minimize heating energy costs and thermal discomfort by providing optimal values of setpoint temperatures on a day-ahead planning horizon based on weather forecasts. To achieve this, a Pareto multi-objective approach is applied, which considers thermal comfort via the adaptive theory of ASHRAE 55, assessing a comfort penalty function. The optimization problem is solved using a genetic algorithm in the MATLAB® environment. Objective functions are evaluated using the coupling between MATLAB® and EnergyPlus, which is used as building performance simulation tool. Multi-criteria decision-making is performed to select an optimal solution from the Pareto front while setting a limit to the comfort penalty. To test the framework, EnergyPlus weather data is used to simulate weather forecasts for typical days of the winter season. Two different economic scenarios are simulated in order to be able to analyze both conditions and given the variability of the electricity price. For the different days tested, the best results in terms of savings achieved through the proposed solution are on Feb. 28, corresponding to the coldest day and the highest energy cost, with daily savings of 26% compared to a reference control with a fixed setpoint of 21 °C, while maintaining similar comfort performance. The results suggest that optimized control is a crucial aspect of sustainable building design, and the proposed framework can be virtually implemented or integrated into automation systems for real-time model predictive control.