Marginal Cost Research Articles

Emission patterns and marginal abatement cost of CO2 of world's largest pulp and paper production sector: An enterprise based estimation of China

ABSTRACT Using the hybrid New Keynesian Phillips Curve, this paper provides the first multi-country estimation for Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan using quarterly data from 1996 to 2023, and continuously-updating GMM. We estimate closed- and open-economy specifications with perfect and imperfect pass-through. Inflation combines substantial backward-looking inertia with a meaningful forward-looking component: persistence is strongest in Tajikistan and Turkmenistan, while Georgia and Armenia are the most forward-oriented, and Kazakhstan is balanced. In panel estimates the backward- and forward-looking weights are about 0.55 and 0.45. Cost slopes indicate that domestic real marginal costs dominate, but imported pressures are material, accounting for about 46% of cost slopes under perfect pass-through and 41% under imperfect pass-through, with external channels especially salient in Kyrgyzstan and Tajikistan. Structural parameters imply price resets roughly every two to two and a half quarters and a high yet incomplete exchange-rate pass-through near 0.87.

Abstract Bundle pricing is commonly adopted by service firms managing multiple congestion-prone service facilities. Under bundle pricing, the firm sells all services as a single package. This scheme is in contrast to à la carte pricing, whereby the firm sells each service separately. The existing theory generally sees bundling as being more lucrative when the marginal cost of production is low. However, little is known about how bundling compares to à la carte pricing in service systems with delay-sensitive customers, despite the prevalence of both practices. Our paper compares these two pricing schemes in congested service systems. We find that the classical prescription can be reversed in such congested service settings even in the absence of any marginal cost of service provision. Specifically, bundling generates less revenue than à la carte pricing when the potential arrival rate of customers is high relative to service capacity or when customers are highly delay-sensitive relative to their valuation of services. Moreover, the relative revenue difference between the two pricing schemes is non-monotone in either the potential arrival rate or delay sensitivity, with the percentage revenue loss from suboptimally practicing bundle pricing being the most substantial when the potential arrival rate or delay sensitivity is intermediate. From an operational perspective, bundle pricing results in higher (resp. lower) capacity utilization and thus more (resp. less) system congestion than à la carte pricing when the potential arrival rate is low (resp. high). For customers, bundling generates higher consumer surplus when the potential arrival rate is low or high, but may generate lower consumer surplus when the potential arrival rate is intermediate. Our results offer normative guidance to service firms considering these two pricing strategies and shed light on their operational and welfare implications.

ABSTRACT This study constructs an industry chain model that considers government subsidies and the proportion of state-owned shares, analyzes the equilibrium results under no government intervention, government subsidies, and nationalization, discusses the role of government subsidies and nationalization in promoting technology research and development (R&D), and explores the optimal policy under different cases. The results show that government subsidies and nationalization can encourage technology R&D, with the former having a more significant incentive effect. Under government subsidies, there exists an optimal subsidy level that maximizes social welfare and is influenced by various factors. From the nationalization perspective, complete nationalization is optimal. The marginal cost and cost-reducing effects of technology influence the equilibrium results. The government should fully consider the marginal cost, cost-reducing effect of technology, and industrial chain structure when formulating policies.

ABSTRACT The evolution of institutions in selecting government officials in ancient China reflected efficiency considerations and increased power concentration in the hands of the ruler. Selecting government officials in ancient China became more rule‐based over time, and standardisation and centralisation were some key features of this process. In this dynamic model, a higher volume of transactions, shown as the number of candidates needed to be evaluated, leads to institutionalisation, which has a higher fixed cost but a lower marginal cost in processing each transaction. In the steady state, a ruler with a more encompassing interest chooses a higher level of institutionalisation. The impact of a change in the level of elite power on the level of institutionalisation is sensitive to the relative power of the state versus society.

The condition of the environment remains at the forefront of contemporary debates among political leaders and societal stakeholders, particularly in the context of addressing climate change. Offshore wind farms are emerging as a promising pathway for renewable energy development in the Mediterranean. While existing literature extensively explores the potential of offshore wind technology in advancing climate neutrality targets by 2030, comparatively less attention has been paid to the challenges and risks of its implementation. This essay examines the economic, environmental, and social dimensions of offshore wind farm deployment in the Mediterranean, highlighting both its benefits and associated risks. Despite regulatory and environmental obstacles, expansion is expected, driven by low marginal costs, favourable conditions, and growing international investment. The study identifies critical gaps in the current legal and governance frameworks and evaluates their capacity to manage environmental and socio-economic impacts. It also provides insights into strategies and policy measures that could enhance the sustainable integration of offshore wind energy, supporting informed decision-making for policymakers, investors, and environmental stakeholders in the Mediterranean region.

The current analysis aimed to evaluate the cost-effectiveness of benmelstobart plus anlotinib and chemotherapy for patients with ES-SCLC from the Chinese health-care system perspective. A mathematical decision model that simulated patients’ 3-week transition in 20-year time horizon was conducted to evaluate the economic value. Survival and safety data were gathered from ETER701 trial, cost and utility values were obtained from the local charges and previously published studies. Sensitivity and subgroup analyses were performed to examine the robustness of the model results and to support the health-decision making. For intention-to-treat (ITT) patients, benmelstobart plus anlotinib and carboplatin/etoposide could bring additional 0.60 and 0.71 QALYs with marginal cost of $91,424.86 and $98,504.86 compared with anlotinib plus carboplatin/etoposide and carboplatin plus etoposide, respectively, resulting in an incremental cost-effectiveness ratios (ICERs) were $153,444.29/QALY and $138,272.39/QALY, respectively, which were higher than the Chinese willingness-to-pay (WTP) threshold. Sensitivity analyses and subgroup analyses confirmed the robustness of the model results when parameters changed. Benmelstobart plus anlotinib and carboplatin/etoposide was unlikely to be the cost-effective first-line strategy compared with anlotinib plus carboplatin/etoposide and carboplatin plus etoposide for ES-SCLC patients in China. Reducing the price of benmelstobart could increase its cost-effectiveness.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20649-8.

As the scale of distributed resources continues to expand, decentralization and multi-agent characteristics bring significant challenges to low-carbon dispatching and market participation of power grids. To this end, this paper proposes a collaborative optimization scheduling framework with distributed resource aggregators (DRAs) as the main body, innovatively coupling carbon Emission trading (CET) with electric vehicle carbon quota participation, and the renewable energy quota (RPS) with tradable green certificate (TGC) transaction as the carrier, as well as constructing the connection path between the two to realize the integrated utilization of environmental rights and interests. Based on the ε-constraint method, a bi-objective optimization model of economic cost minimization and carbon emission minimization is established, and a multi-dimensional evaluation system, covering the internal and overall operation performance of the aggregator, is designed. The example shows that, under the proposed CET-RPS coupling mechanism, the total cost of DRA is about 23.4% lower than that of the existing mechanism. When the carbon emission constraint is relaxed from 2700 t to 3000 t, the total cost decreases from CNY 2537.32 to CNY 2487.74, indicating that the carbon constraint has a significant impact on the marginal cost. This study provides a feasible path for the large-scale participation of distributed resources in low-carbon power systems.

This article takes the perspective of Hydrogen Load Aggregator (HLA) to optimize the declaration strategy of peak shaving market, improve the flexible regulation capability of power system and HLA economy as the research objectives, and proposes an optimization strategy method for HLA to participate in peak shaving market. Firstly, an improved Convolutional Neural Networks–Long Short-Term Memory (CNN-LSTM) time series prediction model is developed to address peak shaving demand uncertainty. Secondly, a bidding strategy model incorporating dynamic pricing is constructed by comprehensively considering electrolyzer regulation costs, market supply–demand relationships, and system constraints. Thirdly, a market clearing model for peak shaving markets with HLA participation is designed through analysis of capacity contribution and marginal costs among different regulation resources. Finally, the capacity allocation model is designed with the goal of minimizing the total cost of peak shaving among various stakeholders within HLA, and the capacity won by HLA in the peak shaving market is reasonably allocated. Simulations conducted on a Python3.12-based experimental platform demonstrate the following: the improved CNN-LSTM model exhibits strong adaptability and robustness, the bidding model effectively enhances HLA market competitiveness, and the clearing model reduces system operator costs by 5.64%.

The economics of IVF operations remain opaque despite growing prevalence and substantial investment in fertility services. Traditional accounting methods often fall short by failing to capture the complex relationship between biological inputs (number of eggs and embryos processed), skilled labor, and equipment utilization, creating a distorted view across different procedures and patient characteristics. This paper presents Activity-Based Costing (ABC) as a methodological framework for understanding true IVF laboratory costs. We demonstrate a use case with an analysis of data from five IVF laboratories (600-2200 annual egg retrieval cycles) across different US regions including time studies of 500 + procedures at each site, with theoretical projections to 4000 annual egg retrieval cycles based on queuing theory. We identify significant cost elasticity with biological inputs; costs increase by 55% for egg freezing when the number of eggs per patient triples, and by 30% for complex IVF procedures (such as those requiring embryo biopsy) when egg count per patient doubles. We also describe substantial scale effects, with marginal lab costs 40% higher in centers performing 500 yearly egg retrieval cycles versus 2000-cycle centers, and 4000-cycle centers estimated to achieve 13-40% lower costs per procedure than operations performing 500 retrieval cycles annually. Finally, we show labor efficiency increases by 30% between centers performing 500 and 2000 annual egg retrieval cycles, an observation supported by a queuing rule of thumb (QROT) analysis, with capital utilization also improving dramatically. ABC enables evidence-based pricing, capacity planning, technology assessment, and consolidation strategizing. ABC is intended to inform operational efficiency, not clinical treatment, ensuring that quality of care and patient outcomes remain the primary considerations in fertility services.

Abstract Ergonomics is frequently invoked to foster productivity, competitiveness, regulatory compliance, consumer welfare, and the fulfillment of organizational objectives. As a first step to integrate ergonomics in the theory of the firm, we use a simple but non-standard principal-agent model. The principal (the firm) sets monetary compensation, while also investing in decreasing the agent’s (a representative employee’s) marginal cost of effort – thanks to process ergonomics – and increasing consumers’ willingness-to-pay for a more user-friendly product – thanks to product ergonomics. Our main finding/prediction is that investing in ergonomics comes with relatively lower incentive pay but entails higher output. Some policy implications and potential research avenues are briefly discussed.

ABSTRACTThis paper shows that product positioning affects the incentives to invest in process innovation. The result is found using a model of price competition with three firms under horizontal product differentiation—and then extended to a more general Bertrand triopoly. The central firm may have a higher gain from a cost reduction than the peripheral firms, even if it reaps a lower profit or has a lower demand. By contrast, the peripheral firms have a larger gain if, and only if, they also have larger profits. Furthermore, we argue that the central firm exploits a reduction in the marginal cost mainly to expand its sales, whereas the peripheral ones to increase their markup. We finally show that the aggregate innovation incentives are larger the more clustered toward the center are the firms and the larger the preinnovation cost asymmetry. We also analyze the effects of mergers on innovation incentives, confirming that they tend to reduce the merged firms' incentives to innovate.

The congestion pricing based on marginal cost has been proven to be a potentially effective management model for alleviating congestion during peak hours at airports. However, airlines' overestimation of certain adjustment schemes often fails to reflect their actual social value. When the congestion management process relies solely on congestion pricing, it may lead to inefficient final outcomes following flight pushback slot adjustments (FPSA). Therefore, this paper proposes a bi-level slot optimisation framework based on reinforcement learning to regulate airlines' behaviour in the congestion pricing implementation process (CPIP) and ensure the flexibility of the pricing process by formulating FPSA plans. Reinforcement learning is used to solve the nonlinear constraints in the model and its compatibility with the algorithm. The upper level generates FPSA plans based on the slot congestion situation. The lower level evaluates the potential benefits generated by the FPSA plans from the upper level and passes these results to the upper-level model for continuously optimising the agent's congestion management and constraint strategy. Additionally, illegal action masking and prioritised experience replay techniques are introduced to reduce the search space and accelerate convergence. Experimental results show that the proposed optimisation framework reduces the volatility of congestion indices by 41.82% during periods with behaviour management, decreases total costs by 11.29%, and saves airlines an average of 3,442.77 RMB per flight adjustment. Additionally, the framework has been validated to have the potential to regulate airlines' behaviours in various scenarios and achieve efficient price-based congestion management under different constraints.

This paper develops a novel framework for nonprofit pricing by conceptualizing nonprofits as multi-sided platforms (MSPs) that mediate exchanges between clients and donors. It introduces the Nonprofit Platform Lerner Index (NPLI), a tool that helps nonprofit managers optimize pricing by accounting for both client-price elasticity and donor-side cross-platform effects. The framework demonstrates how nonprofits can strategically leverage donor market power to subsidize client prices, including scenarios where prices fall below marginal cost or become negative. The study reconceptualizes donor engagement activities as core production inputs rather than overhead costs, aligning them with mission-critical objectives. It also explores policy implications, offering insights into antitrust considerations in donor markets. The NPLI provides regulators and managers with a quantitative tool to measure market power across donor and client markets. Future research avenues include empirical validation and applications to nonprofit governance and stakeholder management.

Long-term care facility networks in Canada face significant challenges in balancing demand and capacity, a problem exacerbated by rising demand. In other words, the growing elderly population is escalating the need for long-term care resources. To address this issue, this study proposes a Mixed-Integer Linear Programming model based on the current standing of the long-term care system in Ontario, a representative case for considering varied patient supports. The proposed model simultaneously optimizes the timing and location of constructing new long-term care facilities while dynamically adjusting each facility's capacity, including human resources and beds. Moreover, patient assignments are optimized based on their demand region, gender, language, and age group over a finite time horizon. The model incorporates multiple constraints to accommodate patients' gender and language, addressing language barriers, alleviating feelings of loneliness, and aligning with Canada's commitment to inclusive care. Additionally, it considers patient journeys by incorporating age groups and assigning patients from different demand regions in an equitable manner through the geographical equity constraint. To validate our proposed model, we conduct a case study on the existing network in Hamilton, Ontario. An extensive set of numerical analyses is executed to provide insights into the problem. Most importantly, the results demonstrate that the model effectively optimizes facility placement and patient allocation while significantly reducing un-assignment and misassignment rates. Specifically, the results indicate that over 88% of patient demand can be accommodated annually throughout a five-year planning horizon. In addition, patients can be assigned based on language and gender with marginal additional costs. Lastly, operational costs constitute the largest share of total expenditures, whereas misassignment costs account for the smallest proportion.

ABSTRACT This article estimates the external marginal costs of traffic accidents for light and heavy vehicles. We use microdata covering the Swedish national road network from 2004 to 2012. We estimate the risk elasticities for heavy and light vehicles by applying a set of count data models that explain how the number of fatalities, and of severely and slightly injured individuals, changes in response to changes in traffic flows. We analyse the impact of observed and unobserved heterogeneity by applying a range of different model specifications. The weighted average of the external marginal costs for light and heavy vehicles is computed for the full road network, taking into account the degree of risk internalization by vehicle type. The preferred model yields an external marginal cost of 0.28 € cents per vehicle-kilometre (vkm) for light vehicles, and this result is robust across specifications. The estimates for heavy vehicles are more sensitive to the model specification; including or excluding traffic flows of light vehicles has a substantial effect. Our preferred estimate for the external marginal cost of heavy vehicles is 2.36 € cents per vkm. We find negative risk elasticities for both light and heavy vehicles.

Abstract In several markets, retailers consider volume (size) as a crucial factor for competitiveness; this is driven, for example, by volume rebates from suppliers or technological economies of scale. This indicates that the retailers face decreasing marginal costs. We show that such economies of scale may imply that prices become strategic substitutes and that this has profound effects on firms’ behavior. A retail chain that controls several stores in the same market may prefer decentralized pricing rather than centralized pricing. This preference arises because a multi-store chain that employs centralized pricing essentially commits to setting higher prices than it otherwise would. If prices are strategic substitutes, the rivals of a multi-store chain would then, to the detriment of the chain stores, respond by reducing their prices. If this effect is sufficiently strong, centralized pricing will be unprofitable for a multi-store chain.

ObjectiveTo quantify the costs associated with a stepped model of depression care—Integrated Chronic Care Clinics-Depression Module (IC3D)—in rural Malawi.DesignCross-sectional cost analysis.SettingIntegrated chronic care clinics (n=14) throughout Neno District, Malawi.InterventionsThe stepped model of depression care provided behavioural therapy (Problem Management Plus (PM+)) to adults (aged 18+) with moderate depression and joint PM+ and antidepressant therapy (ADT) to those with moderate-to-severe and severe depression. The model incorporated two cost-saving features: treatment was integrated into existing chronic care services within the health system, and PM+ was group-based rather than one-on-one.Primary and secondary outcome measuresWe conducted time-driven activity-based costing to quantify the marginal economic cost of implementing PM+ and ADT, inclusive of training and supervision. We measured all costs in 2025 US dollars and quantified costs from a societal perspective—including human resources, infrastructure, equipment, consumables, indirect costs and opportunity costs.ResultsThe marginal cost of PM+ was $90 per patient treated for five sessions over 2 months, while ADT was $138 for eight sessions over 8 months. In both instances, human resources (45% from PM+, 52% for ADT) and consumables (30% for PM+, 31% for ADT) represented primary health system cost drivers. In the first year of implementation, 15 002 depression screenings were conducted, 724 adults were evaluated with a diagnostic tool and 398 adults subsequently received care: 263 received PM+ alone, 31 received ADT alone and 104 received both PM+ and ADT. The total cost of introducing operations throughout Neno District was $62 806.ConclusionsThese findings indicate that integrating depression care services into the Malawian health system is financially feasible and successfully reached many individuals with major depressive disorder.Trial registration numberNCT04777006.

Methane abatement in Malaysia’s upstream oil and gas sector: A marginal cost analysis for supporting long-term energy transition

Abstract This perspective examines trade-offs in designing residential electricity rates that improve economic efficiency while ensuring feasible and distributionally favorable outcomes. We analyze rate structures across three key dimensions: improving economic efficiency by reflecting social marginal costs; ensuring affordability, technology access, and residual cost recovery; and simplicity in customer understanding and implementation. While real-time pricing based on social marginal costs is the most economically efficient choice, intermediate approaches like time-of-use rates or critical peak rates may better balance competing objectives. We recommend that decision-makers (1) move towards pricing environmental externalities in time-varying electricity rates, (2) introduce time-varying rates with predictable price periods gradually, (3) expand access to flexibility enabling technologies for low-income customers, and (4) carefully design fixed charges for residual cost recovery to avoid distributionally regressive impacts. These findings are particularly relevant as utilities nationwide consider rate reforms to support electrification while maintaining ratepayer affordability.