Shadow Prices Research Articles

Transport development performance with hazard-inducing variables: A frontier-based shadow pricing approach

While economic growth in a country can be spurred by the expansion of the transportation sector, traffic accidents resulting from an increase in vehicle numbers negatively impact social wellbeing. To integrate both the beneftis and costs in evaluating the transportation sector, this study incorporates traffic accidents as a risk factor (undesirable output) in analyzing the performance of road transportation across Chinese provinces. We propose a shadow price model to estimate the revenue generated and the losses incurred from the addition of each vehicle. The potential improvements in desirable outputs (freight and passenger traffic) and the possible reduction in risks (traffic accident losses) are assessed using a nonparametric approach. Our findings indicate that the overall performance of the Chinese transportation sector improved between 2001 and 2018. During this period, the shadow revenue of vehicles increased, while the shadow loss from traffic accidents showed a declining trend, attributed to enhanced transportation infrastructure and effective government regulations. However, we observe regional disparities in performance and offer targeted policy recommendations.

Cost of escaping air pollution: A way to prevent excessive expansion of industrial areas

To pursue economic growth, many emerging markets prioritize providing land and resources to industries rather than people, resulting in people being forced to relocate. This paper uses Taiwan’s largest industrial city (Kaohsiung) as an example to discuss the negative spillover effect brought about by its most polluted industrial area (the Kaohsiung Linhai Industrial Park, KLIP). This study finds that the proximity between residences and the pollution sources and air pollution severity both cause housing prices to decrease. The results also show that among different air pollution indicators, SO2 concentration exerts the largest influence on housing prices. This may be because the SO2 emitted by large coal-fired power plants and oil refineries in the KLIP is linked to pollution-based haze and creates a visible atmospheric brown haze. By discussing the industrial park’s air pollution problem, this paper illustrates the harm of the overdevelopment of an industrial park. To prevent people’s relocation events resulting from the overdevelopment of an industrial park occurring in the future, we must regularly estimate the shadow price that residents living near the industrial park are required to pay to escape air pollution. This paper also puts forward suggestions that contribute to the sustainable development of industrial parks.

Genome-Scale Metabolic Modeling of Halomonas elongata 153B Explains Polyhydroxyalkanoate and Ectoine Biosynthesis in Hypersaline Environments.

Halomonas elongata thrives in hypersaline environments producing polyhydroxyalkanoates (PHAs) and osmoprotectants such as ectoine. Despite its biotechnological importance, several aspects of the dynamics of its metabolism remain elusive. Here, we construct and validate a genome-scale metabolic network model for H. elongata 153B. Then, we investigate the flux distribution dynamics during optimal growth, ectoine, and PHA biosynthesis using statistical methods, and a pipeline based on shadow prices. Lastly, we use optimization algorithms to uncover novel engineering targets to increase PHA production. The resulting model (iEB1239) includes 1534 metabolites, 2314 reactions, and 1239 genes. iEB1239 can reproduce growth on several carbon sources and predict growth on previously unreported ones. It also reproduces biochemical phenotypes related to Oad and Ppc gene functions in ectoine biosynthesis. A flux distribution analysis during optimal ectoine and PHA biosynthesis shows decreased energy production through oxidative phosphorylation. Furthermore, our analysis unveils a diverse spectrum of metabolic alterations that extend beyond mere flux changes to encompass heightened precursor production for ectoine and PHA synthesis. Crucially, these findings capture other metabolic changes linked to adaptation in hypersaline environments. Bottlenecks in the glycolysis and fatty acid metabolism pathways are identified, in addition to PhaC, which has been shown to increase PHA production when overexpressed. Overall, our pipeline demonstrates the potential of genome-scale metabolic models in combination with statistical approaches to obtain insights into the metabolism of H. elongata. Our platform can be exploited for researching environmental adaptation, and for designing and optimizing metabolic engineering strategies for bioproduct synthesis.

The Shadow Prices of Voluntary Caregiving: Using Well-Being Panel Data to Estimate the Cost of Informal Care

Abstract This article uses the well-being valuation (WV) approach to estimate and monetize the well-being impacts of informal care provision on caregivers. Using nationally representative longitudinal data from the UK, the British Household Panel Survey, we address two challenging methodological issues related to the economic valuation of informal care: (i) the anticipatory nature of informal care; and (ii) the sensitivity of income estimates used in valuation. We address the anticipatory issue by focusing on well-being impacts associated with caring for a relative who had recently suffered a serious accident. We use the fixed effects filtered (FEF) estimator to estimate a “time-invariant income” coefficient free from individual fixed effects bias, which helps to partially improve the quality of the income estimate as an alternative to using instrumental variables. This estimate is used in the calculation of shadow prices of informal care. Our estimates suggest that, focusing on the first year of unanticipated care provision, those experiencing the well-being losses from providing unanticipated informal care would be willing to pay approximately £13,167 on average to avoid it.

Seeking sustainable efficient global agricultural production with nexus approach

This study aims to estimate the shadow prices of water and carbon dioxide (CO2) in global agriculture under three scenarios: pursuing economic efficiency, sustainable development goals (SDGs), and environmental protection. It assesses the social cost of environmental impacts compared to actual prices. This study also evaluates substitutability among water, labor, and capital in the three scenarios for developing relevant agricultural policies depending on distinct agricultural conditions. Social costs tend to be underestimated because they are not directly observed. Our society has faced an overproduction of agriculture in terms of CO2 emissions and the exploitation of water. This study employs a method of a directional technology distance function for global agricultural production based on Food and Agriculture Organization data on agricultural inputs and outputs. The following three critical findings were obtained: First, the average shadow price of water under the economic scenario was close to the current actual water prices, and water prices would increase if agricultural production accomplished the three SDGs (Goal 2, 6, and 13). Second, labor is substituted for water under the environmental scenario because water prices increase rapidly. In contrast, water is complementary to labor under the SDGs scenario, implying that labor becomes more important for increasing food production. Third, the current CO2 prices are lower than those in the economic scenario. These values are significantly lower than those under the SDGs and environmental scenarios. Based on these results, we conclude that agricultural products are often undervalued because the appropriate value of water is overlooked in real markets. The contribution to reducing CO2 in agriculture is insufficient, owing to current low carbon taxes.

Enterprise information and communications technology software pricing and developer productivity measurement

AbstractThe 1999 addition of business sector software and services spending to the National Income and Product Accounts was an important innovation, achieving a novel focus on the measurement of intangible asset investment. Over the intervening years, enterprise information and communication technology (ICT) has fundamentally changed. The transformation has raised questions about the extent of the decline of ICT function software prices. As a software producing sector, the business sector ICT function now has a much wider array of production factor choices. In addition, labor and multifactor software development productivity, an important sources of value creation, varies widely from year to year. With the use of a two‐sector model and a standard growth accounting framework, a business sector ICT function shadow price is estimated, finding that software price declines have been underestimated by 4.4 percentage points (ppt) over 2015 to 2021. The impact on GDP growth is a 0.1 ppt underestimate. Correcting the underestimate increases software spending from 19.6% to 24.7% of nonresidential fixed investment, and from 47.4% to 59.9% of real intellectual property product spending.

Market-incentivized environmental regulation, industrial agglomeration and the effects on carbon shadow price: Evidence from China's local pilot policies for carbon market construction

Market-incentivized environmental regulation, industrial agglomeration and the effects on carbon shadow price: Evidence from China's local pilot policies for carbon market construction

Contextualized Metabolic Modelling Revealed Factors Affecting Isoflavone Accumulation in Soybean Seeds.

Isoflavones, secondary metabolites with numerous health benefits, are predominantly found in legume seeds, especially soybean; however, their contents in domesticated soybean seeds are highly variable. Wild soybeans are known for higher seed isoflavone contents than cultivars. Here we used experimental and modelling approaches on wild soybean (W05) and cultivated soybean (C08) to delineate factors influencing isoflavone accumulation. We found imported nutrients were converted into storage compounds, with isoflavone accumulation in W05 seeds being faster than in C08 ones. The isoflavone accumulation during seed development was simulated using context-specific cotyledon metabolic models of four developmental stages on cultivar C08, and the metabolic burden imposed by increasing biomass was evaluated. Trade-off analyses between biomass and isoflavone suggest that high biomass requirement in cultivars could limit the reallocation of resources for secondary metabolite production. Isoflavone production in mature seeds was also influenced by biomass compositions. Seeds with higher carbohydrate contents favour isoflavone production, while those with highest protein and oil contents had lowest isoflavone contents. Although seeds could synthesize isoflavones on their own, the predicted fluxes from biosynthesis alone were lower than the empirical levels. Shadow price analyses indicated that isoflavone accumulation depended on both intrinsic biosynthesis and direct contribution from the plant.

Why gender norms matter

AbstractThis study examines the influence of gender norms on household behaviour and welfare. Using Japanese household data, we find that households with a conventional norm on gender roles spend more time on housework and less money on family‐common goods. To understand the underlying mechanism, we construct a collective labour supply model that explicitly introduces gender norms. We show that an inefficient ratio of wives' household time to that of husbands leads to an increase in the shadow price of domestic goods, through which the norm distorts the time and money allocated to home production and decreases household welfare.

Cost-benefit Analysis of PPP Construction Projects

This paper discusses the cost and benefit of the cross-river Bridge PPP construction project in Y City, and analyzes the application of PPP model in China and its economic benefits. Research shows that PPP model not only effectively alleviates traffic pressure and promotes regional economic development, but also significantly reduces project construction and transportation costs and improves the quality of public services through social capital investment and operation. As a typical case, the cross-River Bridge project accounts for 95% of social capital, and its successful implementation validates the significant advantages of the PPP model in improving economic and social benefits. In the national economic evaluation, the project made fine adjustments to the investment cost, including the application of shadow price and the adjustment of the conversion factor of labor wages, to ensure the accuracy of the evaluation results. In addition, the technical and economic data of various types of motor vehicles are listed in detail, especially the adjustment of the cost of motor transportation related to time, which provides an important cost reference for the transportation industry. Through the comprehensive analysis of the theoretical basis, practical application and economic cost and benefit of PPP model, this paper not only enriches the cost and benefit analysis theory of PPP projects, but also provides valuable practical experience and theoretical support for similar projects. Looking ahead, suggestions such as improving the governance system and strengthening risk management and control will promote the widespread application of the PPP model in China and inject new vitality into economic and social development.

Factor market distortion, total factor energy efficiency and energy shadow price: A case of Chinese manufacturing industry

The manufacturing industry is responsible for the highest share of energy consumption in China and improving its energy efficiency is important for reducing the dependence of economic growth on the growth of fossil energy consumption and carbon emissions. However, factor market distortion (FMD) has substantially inhibited effective resource allocation. This study proposes a metafrontier parametric linear programming method based on the Shephard energy distance function to measure the total factor energy efficiency (TFEE) of Chinese manufacturing industry. Then, we derive the energy shadow price by cost minimization. Finally, we compare and analyze the impact of different levels of FMD on TFEE and energy shadow price. The results showed that regions with lower FMD had higher TFEE from 2000 to 2021. FMD hindered TFEE mainly by affecting technical efficiency and scale efficiency. The energy shadow price within China's manufacturing industry exhibited a downward trend and regions with low FMD had a higher energy shadow price. This implies that the manufacturing industry in China is progressively diminishing its reliance on fossil fuels for production activities. The efficient distribution of production factors may enhance the actual marginal value of energy inputs.

Analisis Sensitivitas dan Dualitas Program Linear Metode Simpleks untuk Optimalisasi Keuntungan Penjualan Nasi Kuning dan Nasi Goreng

This study presents a secondary analysis of the optimization of yellow rice and fried rice production at Ibu Hamina's shop using the linear programming method. Previously, optimization was carried out using a graphical method but did not conduct a sensitivity analysis to evaluate the impact of changes in production parameters on the optimal solution. The method used is a more sophisticated simplex method, while simultaneously conducting duality analysis to understand shadow prices and resource efficiency by evaluating the relationship between primal and dual problems, and evaluating the impact of changes in production parameters on optimal solutions by conducting sensitivity analysis. The results of this study show that the optimal solution is achieved by producing 7 packages of yellow rice and 3 packages of fried rice per week, resulting in a maximum profit of IDR 7,350,000.00 per week; which is IDR 1,050,000 higher than the results of previous research. The duality analysis shows the consistency of the optimal value between the primal and dual problems. The sensitivity analysis shows that small changes in parameters can affect the value of the objective function. This study shows that the simplex method is effective in optimizing the production of yellow rice and fried rice, providing a more significant maximum profit

Study on controllability assessment of a new type of power system based on lagrangian function integrated assessment method

The complex structure and multiple controllability metrics of the new power system require a comprehensive assessment approach. We propose a controllability assessment method based on the Lagrangian function, analyzing key factors that influence controllability. Our index system includes distributed power supply utilization rate, energy storage station charge state, power factor, and voltage offset. Using Lagrange shadow price theory, we construct a guideline layer index system treating bottom indexes as constraints. We formulate an optimization function utilizing the Lagrangian shadow price theory and considering weights calculated from the bottom index’s shadow price. These weights inform primary evaluation. By combining primary evaluation results, weights, and variable coefficients using the percentage system method, we determine comprehensive evaluation results for the new power system’s controllability. Experimental results demonstrate the high reliability of this method’s evaluation indexes, indicating their effectiveness. This research provides valuable insight for the advancement of the new power system. Region 1 had the lowest overall evaluation score of 51.57 and was rated general. The overall score of Region 2 was 77.24, which was considered good. Region 3 received the highest overall score of 86.29 and was rated as excellent.Graphical

Shadow prices of agrochemicals in the Chinese farming sector: A convex expectile regression approach

The use of agrochemical inputs has significantly enhanced agricultural yields in China; however, their excessive utilization has also caused a range of environmental issues. This paper examines the costs associated with reducing agrochemicals by employing shadow prices, which represent the value of the marginal product of agrochemicals, to further develop cost-effective environmental policy measures for reducing their usage. To this end, the shadow prices of agrochemicals have been assessed by adopting a newly developed convex expectile regression approach and using statistical data from 31 provinces in China spanning from 2005 to 2020. Furthermore, the present study investigates the disparities between shadow prices and market prices for different agrochemicals across various regions in China. The findings suggest that the costs of reducing chemical fertilizers are higher than those of reducing pesticides and plastic films. Moreover, the results indicate that central China exhibits relatively high potential for decreasing agrochemical usage. Finally, these findings can inform the Chinese government's restructuring of producer support and environmental policy in a cost-effective way to mitigate agrochemicals use in the future. Additionally, the research method employed in this study holds potential for extension to other agrochemicals-dependent countries.

Numeraire choice, shadow profit, and inefficiency measurement

We study a programming approach to inducing inefficiency measures for convex technologies. It takes the technology and the numeraire as given and uses variational arguments to isolate shadow prices that make a decision maker’s observed behavior as efficient as possible. The focus is on how the numeraire determines the element of the efficient frontier to which a decision maker’s performance is compared, the resulting technical inefficiency measure, and whether that measure offers a cardinal representation of the technology. We use the results to study an inefficiency measure, the polyhedral measure, that generalizes an array of existing measures.

Synergism of floated paperboard sludge cake /sewage sludge for maximizing biomethane yield and biochar recovery from digestate: A step towards circular economy

Anaerobic digestion of floated paperboard sludge (PS) cake suffers from volatile fatty acids (VFAs) accumulation, nutrient unbalanced condition, and generation of digestate with a risk of secondary pollution. To overcome these drawbacks, sewage sludge (SS) was added to PS cake for biogas recovery improvement under a co-digestion process followed by the thermal treatment of solid fraction of digestate for biochar production. Batch experimental assays were conducted at different SS:PS mixing ratios of 70:30, 50:50, 30:70, and 20:80 (w/w), and their anaerobic co-digestion performances were compared to the mono-digestion systems at 35 ± 0.2 °C for 45 days. The highest methane yield (MY) of 241.68 ± 14.81 mL/g CODremoved was obtained at the optimum SS:PS ratio of 50:50 (w/w). This experimental condition was accompanied by protein, carbohydrate, and VFA conversion efficiencies of 47.3 ± 3.2%, 46.8 ± 3.2%, and 56.3 ± 3.8%, respectively. The synergistic effect of SS and PS cake encouraged the dominance of Bacteroidota (23.19%), Proteobacteria (49.65%), Patescibacteria (8.12%), and Acidovorax (12.60%) responsible for hydrolyzing the complex organic compounds and converting the VFAs into biomethane. Further, the solid fraction of digestate was subjected to thermal treatment at a temperature of 500 °C for 2.0 h, under an oxygen-limited condition. The obtained biochar had a yield of 0.48 g/g dry digestate, and its oxygen-to-carbon (O/C), carbon-to-nitrogen (C/N), and carbon-to-phosphorous (C/P) ratios were 0.55, 10.23, and 16.42, respectively. A combined anaerobic co-digestion/pyrolysis system (capacity 50 m3/d) was designed based on the COD mass balance experimental data and biogenic CO2 market price of 22 USD/ton. This project could earn profits from biogas (12,565 USD/yr), biochar (6641 USD/yr), carbon credit (8014 USD/yr), and COD shadow price (6932 USD/yr). The proposed project could maintain a payback period of 6.60 yr. However, further studies are required to determine the associated life cycle cost model that is useful to validate the batch experiment assumptions.

Does Residents’ Perception of Information Influence the Implementation Effect of Increasing-Block Water Pricing Policy?

Since the 1990s, China has gradually implemented price reform. The increasing-block pricing policy (referred to as “IBP”) began to be applied in different kinds of household resource-based products so as to produce resource-saving effect. However, when evaluating policy effects, the information factors are often ignored. This paper concentrates on evaluating the residential increasing-block water pricing policy (referred to as “IBWP”) and divides the information into two categories: policy information and bill information. Among them, policy information is divided into implementation information and rule information, and bill information is subdivided into three aspects: price, volume and fee. Based on the household data of the Chinese Household Water Use Behavior Survey 2019, this paper uses the propensity score matching (PSM) method to investigate the impact of households’ information cognition on water consumption. The results show that residents with policy information will increase their water consumption, while the availability of rule information will reduce the increase in water consumption; bill information encourages households to take behavioral water-saving measures more frequently, and among different types of bill information, residents are the most sensitive to water fee information. Through further analysis, the shadow price of household water is much higher than the current water price. Hence it can be considered that the current water price is distorted to a large extent, which leads to the deviation of the policy information received by consumers. Therefore, the water-saving effect of IBWP at the present stage is very limited. The policy implication shows that IBWP needs to further optimize its structure, the government should gradually increase the current residential water price; relevant departments ought to strengthen the policy publicity, and improve the acquisition rate of previous bills for residents.

Integrating Mechanistic-Empirical Pavement Analysis in the Life Cycle Assessment Use Phase and Monetization of Environmental Impacts to Promote Low Carbon Transportation Materials

This study attempted to integrate the Mechanistic-Empirical Pavement Design Guide (MEPDG) analysis into the life cycle assessment (LCA) framework to explore the potential of terminal blend rubberized bitumen (TBRB) technology as a sustainable alternative to traditional paving materials in the United Arab Emirates (UAE). In addition, the concept of environmental impact monetization is introduced for quantifying shadow prices to be used in cost–benefit analyses and encourage the adoption of sustainable technologies in pavement construction. The findings demonstrate that hot mixed asphalt (HMA) with TBRB outperforms asphalt mixtures with neat bitumen (NB) and polymer-modified bitumen (PMB) containing 7% linear styrene–butadiene–styrene, with respect to durability and environmental impacts. The cradle-to-grave analysis, which includes maintenance and rehabilitation cycles based on the MEPDG results, alters the hierarchy among scenarios compared to conventional cradle-to-gate analyses, highlighting the importance of the use phase in LCA. Overall, the asphalt mixture with TBRB exhibits 83% and 63% less global warming potential than mixtures with NB and PMB, respectively. The monetization process through the distance-to-target approach returned the shadow price of US$157 per metric ton of CO2eq in the UAE. Based on this value, the HMA with TBRB, if selected over those with NB and PMB, offers environmental savings of US$47,186/km-lane and US$15,852/km-lane for the case study investigated.

Dynamic Exception Points for Fair Liver Allocation

There are disparities in access to livers based on transplant patients’ height, which disproportionately affects Hispanics, Asians, and women (across all ethnicities), because short patients can receive transplants from a smaller pool of available deceased donors for medical reasons. Reduced likelihood of transplantation leads to higher mortality rates and longer waiting times. We analyze fairness within the current U.S. liver allocation system where patients receive priority dynamically, based on their model for end-stage liver disease (MELD) scores, which reflect the severity of liver disease. We propose a simple adjustment, providing additional (exception) points based on height and MELD score, that can be easily implemented in practice, which materially reduces the disparity without sacrificing overall efficiency. We model the liver allocation system as a multiclass fluid model of overloaded queues with heterogeneous servers. We impose explicit equity constraints for all static patient classes, that is, height. We characterize the optimal solution under the objective of minimizing pretransplant mortality. The discretized version of the optimal policy is numerically solved using estimates from clinical data and a detailed simulation study demonstrates its effectiveness. The optimal policy, called the equity adjusted mortality risk policy, advocates ranking patients based on their short-term mortality risk adjusted for equity among height classes. Interpretation of the shadow prices of equity constraints in the optimal control problem as MELD exception points is novel in the transplant context since they can be seamlessly mapped into the existing system. Our simulations show that for women, the disparity can be almost completely eliminated. Hispanics and Asians greatly benefit from receiving these MELD exception points also. Our work provides a remedy to reduce the disparities in access to liver transplantation within the MELD-based allocation. Our approach can help the on-going analysis of the continuous distribution model for livers because it also considers aspects of candidate biology, notably height and body surface area. Funding: M. Akan was supported by the National Science Foundation [Grant CMMI-1334194] and the Carnegie Mellon University (CMU) [Onetto Fellowship in Operations Management]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0092 .

Break down the decentralization-security-privacy trilemma in management of distributed energy systems.

Distributed energy systems encompass a diverse range of generation and storage solutions on the user side, where decentralized management schemes to maximize the overall social welfare are preferred considering their dispersed ownership. However, either security or privacy problems occur in recently proposed schemes. Here we report a decentralized framework leveraging the strengths of blockchain and parallelizable mathematical algorithms to overcome these potential drawbacks. The system owners bid cost functions and operating constraints through masked but coupled management subproblems, which are redistributed by the blockchain to be verifiably solved by competent peers. Such processes are iteratively executed as decisions and shadow prices are exchanged among participants, until an equilibrium is reached. The interactive framework ensures decentralized, privacy-preserving, and secure management of multiple energy sources, and reduces the total cost by 3.0 ~ 7.5% in the test system. Our results benefit the energy prosumers and promote a more active and competitive power grid.