Marginal Cost Curves Research Articles

Medium and Long-term Carbon Emission Projections and Emission Reduction Potential Analysis of the Lingang Special Area Based on the LEAP Model

Based on the existing statistical data of the Lingang Special Area in Shanghai and considering its future socio-economic development， industrial structure， and technological development， a LEAP-Lingang model was developed to analyze the evolution trends of energy demand and carbon emissions under the baseline scenario， low-carbon scenario， and enhanced low-carbon scenario. To enhance the prediction accuracy of the model， the Logistic population growth model was used to predict future population data， and the learning curve model was used to simulate the cost evolution trend of related carbon reduction technologies. In addition， an economic evaluation model for carbon reduction technologies was developed， and the economic costs and emission reduction potential of typical carbon reduction technologies were evaluated by drawing a marginal emission reduction cost curve. The results showed that under the enhanced low-carbon scenario， the renewable energy accounted for 69% of the primary energy consumption， and the electric energy accounted for 91% of the terminal energy demand in 2060. The Lingang Special Area could achieve carbon peak by 2030， and the carbon emissions in 2060 were predicted to decrease by 94% compared to that in the baseline scenario. In terms of contribution to emission reduction， clean energy substitution， industrial structure optimization， and terminal energy efficiency improvement played a key role in reducing carbon emissions near the port. In the medium term （until 2035）， they were predicted to contribute 35.1%， 27.3%， and 16.2% of carbon emissions， respectively， and in the long term （until 2060）， they should contribute 50.6%， 8.75%， and 7.7% of carbon emissions， respectively. Regarding specific carbon reduction technologies， hydrogen power generation； water electrolysis for hydrogen； and carbon capture， utilization， and storage （CCUS） technology were of great significance for achieving net-zero emissions， but the costs of emission reduction were relatively high. The research results can provide ideas and references for the low-carbon and green development of the Lingang Special Area and related areas.

Prices versus quantities in forest regulation

We revisit an unanswered and yet critical question in forest policy design: does a price or quantity instrument achieve a better social outcome when the government does not have perfect information. This is a common question in environmental regulation, but in the forest policy literature an equivalence between these instruments has historically been presented, albeit under perfect information. In the forestry case one might be tempted to simply defer to Weitzman (1974), who derived rules for prices versus quantity policy choices when either marginal abatement costs or marginal benefits of polluting emissions are unknown to the policy maker. These rules may not be transferrable to the forestry problem, however. We develop a framework of marginal costs and benefits based on a standard rotation model, showing that uncertainty leads to (very) different results than in the emissions literature. For example, we find that the slopes of marginal costs and benefits and the difference between the expected values of uncertain parameters and their realizations matter differently for the forest policy case. We also find that symmetric over- and under-estimation around true parameter values can result in asymmetric changes in marginal cost curves. Most importantly, we find that even the size of this difference now matters to the price versus quantity policy choice. Our results both draw into question whether Weitzman rules simply apply to forest resources, and they suggest that our new approach should be used for evaluating alternative forestry policies to achieve public goods goals.

A LifeCycle Analysis and Economic Cost Analysis of Corrugated Cardboard Box Reuse and Recycling in the United States

Manufacturing of a product such as a corrugated cardboard box (CCB) includes the extraction of a variety of raw materials in addition to supply chain efforts to get the raw materials to the industry. Conducting a LifeCycle Assessment (LCA) gives the carbon emission of each phase of the product and a quantitative estimate of the overall product carbon footprint and its effect on the environment. This gives impetus to recommendations for improving the phases of the lifecycle to minimize carbon emissions. The proposed waste management method in this paper is the “reuse” method instead of recycling or landfilling the CCB and, in so doing, focusing only on reducing carbon emissions in the manufacturing phase. The paper examines if the incremental cost of reusing the CCBs is less than the environmental and economic cost of reducing the extraction and supply chain of raw materials. This paper uses LCA to evaluate the carbon emission in each phase of the lifecycle of a typical 1 kg corrugated cardboard box in the United States. Carbon emission for the proposed “reuse” phase is also calculated, and the results are compared. This paper also explores the economic feasibility of the proposed “reuse” method that incentivizes the general population to reuse the CCBs instead of recycling or landfilling them. Economic tools such as willingness-to-pay vs. marginal cost curves and benefit-cost analyses are used to evaluate economic feasibility. The results indicate that the “reuse” method for CCBs is economically and environmentally feasible. It also supports the approach of using analytics, economics, and LCA to create a model that can be used for other products and processes as an evaluative process to determine if businesses can benefit from the reduction (or removal) of material extraction costs from the supply chain.

Research on a Day-Ahead Grouping Coordinated Preheating Method for Large-Scale Electrified Heat Systems Based on a Demand Response Model

In recent years, the increasing winter load peak has brought great pressure on the operation of power grids. The demand response on the load side helps to alleviate the expansion of the power grid and promote the consumption of renewable energy. However, the response of large-scale electric heat loads to the same electricity price curve will lead to new load peaks and regulation failure. This paper proposes a grouping coordinated preheating framework based on a demand response model, which realizes the interaction of information between the central controller and each regulation group. The room thermal parameter model and the performance map of the inverter air conditioner/heat pump are integrated into the demand response model. In this framework, the coordination mechanism is adopted to avoid regulation failure, an edge computing structure is applied to consider the users’ preferences and plans, the grouping and parallel computing structure is proposed to improve the computing efficiency. Users optimize their heat load curves based on a demand response model, which can consider travel planning and ensure user comfort. The central controller updates the marginal cost curve based on the predicted scenario set to coordinate the regulation groups and suppress the new peaks. The simulation results show that the proposed method can promote the consumption of renewable energy through coordinated preheating and reduce the system energy consumption cost and user bills. The parallel computing structure within the regulation group also ensures the computing efficiency under large-scale loads.

How competitive is the Syrian banking sector? Empirical evidence from ‘pre/post’ war Syria

AbstractThis paper investigates the degree of market power in the Syrian banking sector over the period 2005–2016 where research on competitive conditions does not exist. The degree of competitiveness is assessed based on the revenue elasticity to input prices approach and is related to a set of market indicators. To test whether the Syrian crisis has altered the competitive conditions over the years of the sample, I divide the full sample into two subsamples, namely the pre‐crisis years (2005–2012) and the crisis years (2013–2016). The results suggest that banks in Syria earn their interest and total revenue under conditions of monopoly. I find that the trend of market structure—characterized by a monopoly—in the pre‐crisis years continues over crisis years. My findings provide robust evidence that a collusive behaviour among banks is in operation in the banking sector of Syria. The difficult penetration into/exit from the market has led to the existence of a profit‐curb mechanism for the Syrian banks, hence, an upward shift in the marginal cost curve will be associated with a reduction in revenue as a result of the optimal condition for these banks which act as monopolists.

Marginal Cost Curves for Decarbonizing the European Cement Industry

Marginal Cost Curves for Decarbonizing the European Cement Industry

Demand, Supply And Markup Fluctuations

Abstract Markup cyclicality has been central for debating policy effectiveness and understanding business cycle fluctuations. However, measuring the cyclicality of markups is as important as understanding the microeconomic mechanisms underlying that cyclicality. The latter requires measurement of firm-level markups and separating supply from demand shocks. We construct a novel dataset with detailed (multi-) product-level prices for individual firms. By estimating a structural model of supply and demand, we evaluate how companies adjust prices and marginal costs as a response to shocks. We find that price markups respond positively to supply shocks and negatively to demand shocks. The mechanism explaining the observed markup behaviour is the same for both shocks: incomplete pass-through of changes along the marginal cost curve to price adjustments. These observed price and output responses are consistent with dynamic demand considerations. Finally, we use our estimated shocks to show how aggregate markup fluctuations in the sample period are mostly explained by aggregate demand shocks.

Integrated Approach for Sectoral Carbon Drawdown Solutions

Sectoral contributions of greenhouse gas (GHG) emissions are at the heart of the climate debate. Carbon drawdown solutions from different sectors (e.g. energy, land, urban infrastructure, and industrial systems) will play significant roles in mitigating climate change in the coming decades. This work identifies the feasible carbon drawdown solutions to support GHG emissions reduction paths globally. These solutions should meet both economic constraints and carbon emissions targets. This work develops a novel approach that integrates Carbon Emission Pinch Analysis (CEPA), the Best-Worst Method (BWM), and Cost-Benefit Analysis (CBA). For each sector, BWM is used to evaluate the performance of reduction solutions and identify their priority weights. Then, CBA is used to rank the options further. Finally, CEPA combines with the Marginal Emission Reduction Cost Curve to find the final mix to meet carbon reduction targets and investment costs. The results prioritize global carbon drawdown potentials for the power (186.4 Gt CO2-eq), construction (97.9 Gt CO2-eq), industry (23.8 Gt CO2-eq), transportation (20.2 Gt CO2-eq), food, agriculture, and land use (2.5 Gt CO2-eq) sectors. Based on these results, this work presents an optimal path for carbon drawdown.

The impact of water conservation regulations on mining firms: A stochastic control approach

Large water demands by the mining industry are of increasing concern around the world. The cost of a specific water management regulation is studied for an oil sands mining operation in Canada, where restrictions on water withdrawals vary with fluctuations in the river. A stochastic optimal control problem is formulated for a firm choosing production, water use, and the timing to build a water storage facility, under conditions of uncertain oil prices and uncertain water withdrawal limits. As no closed form solution is available, a stochastic dynamic programming approach is implemented to determine the difference in value and optimal controls for the oil-producing asset, with and without water restrictions. The cost of the restrictions is estimated to be quite small given historical river flow conditions, while cost is shown to increase under drier conditions. A long run marginal cost curve is developed showing the cost of increasing restrictions given expectations about future river conditions and oil prices.

Returns to Scale in Residential Construction: The Marginal Impact of Building Height

AbstractWe estimate the marginal cost and break‐even rent of developing multifamily apartment buildings in the 50 largest cities in the United States using a novel data set of required construction inputs of standardized assemblies. We find nonlinearities in the marginal cost curve at the fourth and eighth stories that directly impact a developer's returns to scale with respect to height. This curve allows us to identify a developer's maximum willingness to pay for land for each building height, which we then compare to existing single‐family land prices to determine whether new multifamily development will occur. The analysis concludes by simulating the impact of height regulations on break‐even rents of new supply. We find that height regulation often has large, negative effects on housing affordability, with increasing magnitudes for more expensive land markets.

The Economics of Water Conservation Regulations Under Uncertainty: An Application to Alberta’s Lower Athabasca River Region

Large water demands by the mining industry are of increasing concern around the world. The cost of a specific water management regulation is studied for an oil sands mining operation in Canada, where restrictions on water withdrawals vary with fluctuations in the river. A stochastic optimal control problem is formulated for a firm choosing production, water use, and the timing to build a water storage facility, under conditions of uncertain oil prices and uncertain water withdrawal limits. As no closed form solution is available, a stochastic dynamic programming approach is implemented to determine the difference in value and optimal controls for the oil-producing asset, with and without water restrictions. The cost of the restrictions is estimated to be quite small given historical river flow conditions, while cost is shown to increase under drier conditions. A long run marginal cost curve is developed showing the cost of increasing restrictions given expectations about future river conditions and oil prices.

Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China

As China ramped-up coal power capacities rapidly while CO2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China.

Economies of scale and international business cycles

This paper incorporates sloping marginal cost curves and their variations across industries into an open macro model, motivated by the fact that industries’ output, imports, and exports are more procyclical when their economies of scale arise from sloping marginal cost curves rather than fixed costs. The model, consistent with the data, delivers endogenous within-firm interdependence across markets and export gains/losses, which reproduce observed industrial business cycle patterns as well as more correlated aggregate business cycles across countries. The findings highlight the importance of marginal cost structures in international business cycle research.

Heterogeneous labour market response to monetary policy: small versus large firms

We study the effects of monetary policy shocks on the growth rates of hiring, employment and earnings of new hires across firms of different sizes. We find that contractionary and expansionary monetary policy shocks have different effects on hiring and employment growth for small and large firms. Relative to large firms, small firms are less responsive to contractionary monetary policy shocks while they are more responsive to expansionary shocks. We also find that, as a consequence of monetary policy shocks, the earnings of new hires changes, and this wage effect depends on the sign of the shock and the size of the firms. We use a heterogeneous firm model with a working capital constraint, an upward sloping marginal cost curve and a financial accelerator effect, and augment it with the wage effect. We find that our empirical results are consistent with the model as long as the combined effect due to varying steepness of the marginal cost curve and the wage effect is stronger than the financial accelerator channel.

Integrated graphical approach for selecting industrial water conservation projects

Sustainable water management is key to achieving sustainable development goals. Increasing water consumption prompts industrial plants to implement water conservation projects (WCPs) and improve the utilization efficiency of water resources. In this paper, we develop an integrated graphical method for the implementation of water conservation projects by considering both water-saving targets and investment costs with or without government subsidies. First, cost-benefit analysis for different projects is carried out. The unit water saving cost diagram is employed to rank the priority of implementation of each project. Then, the project combination that meets the expected water-saving goal is determined via water-saving pinch analysis. Finally, the water conservation potential and cost-benefit of the optimal project combination are estimated using the marginal cost curve diagram. Two scenarios are considered for the proposed graphical approach: with and without government subsidies. A chlor-alkali/polyvinyl chloride complex is used as an illustrative case study. The results indicate the proposed method can be used to screen out the feasible projects under the constraints of water-saving target and financial fund.

Benefit-cost analysis of water quality policy and criteria in the Delaware River

Abstract This research conducts a benefit-cost analysis of water policies to reach an optimal level of dissolved oxygen (DO) to meet year-round fishable water quality criteria in the Delaware River. A watershed pollutant load model is utilized to estimate marginal cost curves of water quality improvements to meet a more protective year-round fishable standard and annual benefits are defined to achieve future DO criteria in the Delaware River. The most cost-effective DO standard is 4.5 mg/L defined by the point where the marginal benefits of willingness to pay (WTP) for improved water quality equals the marginal costs of pollution reduction. This optimal criteria (4.5 mg/L) can be achieved at a cost of $150 million with benefits ranging from $250 to $700 million/year. While a future DO standard of 4.5 mg/L reflects an economically efficient level of water quality, this DO criteria is less protective than the level of 5–6 mg/L needed to protect anadromous fish such as the Atlantic sturgeon. The policy to reach a DO level of 6 mg/L (at 80% DO saturation) may be difficult to achieve at summer water temperatures that approach 30 °C in the Delaware River at Philadelphia.

What Does Financial Heterogeneity Say About the Transmission of Monetary Policy?

Do financial constraints determine the transmission of monetary policy? I examine this question using the staggered enactment of anti-recharacterization legislation as a source of exogenous variation in creditor rights that loosens firm financial constraints. Treatment effect estimates indicate constraints matter. A 25 basis-point expansionary monetary policy shock results in a 2 percentage-point higher investment growth among treated (unconstrained) firms, reflecting their flatter marginal cost curves for financing which amplifies responses to shifts in the marginal benefit curve. This relationship reverses during economic downturns when investment opportunities are scarce. I rationalize these findings in a static model with convex financing costs.

Canadian Regional Agriculture Model: PMP Applied to the Beef Sector in Canada

This paper describes the Positive Mathematical Programming (PMP), the method for calibrating models of agricultural livestock production and resource use by a nonlinear total cost function. The PMP method is applied to agricultural sectoral models to study changes in policy and market signals. The Canadian Regional Agriculture Model (CRAM) is a regional, multi-sectoral, comparative static, partial equilibrium, mathematical programming model developed and maintained by Agriculture and Agri-Food Canada (AAFC) since mid-eighties. The PMP process converts a linear model using flexibility constraints into a nonlinear model in the absence of the flexibility constraints. A component of CRAM is the beef sector. The elements of the set of total cost curves are defined as quadratic function in terms of the number of cows and calves in the beef production activities. The marginal cost curves were then approximated using the shadow values from linear programming solution with linear curves. Once the flexibility constraints were removed, the model automatically calibrates to the base year production levels. The results from four scenarios indicated the beef sector of CRAM could predict the impact of the scenarios on the size of beef herd. In Scenario 1 where cash costs were increased by 10 percent, the breeding herd size decreased from 3.73 percent in New Brunswick to 0.0 percent in Ontario and Quebec. In Scenario 2 where barley costs were decreased by 10 percent, the breeding herd size increased from 0 percent for British Columbia, Alberta, Ontario, Quebec, Prince Edward Island and Nova Scotia to 1.93 percent for New Brunswick. In Scenario 3 where carcass weight per beef cow could be increased by 10 percent, the increase in beef herd size ranged from 0 percent for Ontario and Quebec to 2.56 percent for New Brunswick. In Scenario 4 where world beef prices were increased by 10 percent increase in beef herd size ranged from 4.48 percent for Manitoba to 25.78 percent for New Brunswick.

Canadian Regional Agriculture Model: Positive Mathematical Programming Applied to the Beef Sector in Canada

This paper describes the Positive Mathematical Programming (PMP), the method for calibrating models of agricultural livestock production and resource use using a nonlinear total cost function. The PMP method is applied to agricultural sectoral models to study changes in policy and market signals. The Canadian Regional Agriculture Model (CRAM) is a regional, multi-sectoral, comparative static, partial equilibrium, mathematical programming model developed and maintained by Agriculture and Agri-Food Canada (AAFC) since mid-eighties. The PMP process converts a linear model using flexibility constraints into a nonlinear model in the absence of the flexibility constraints. A component of CRAM is the beef sector. The elements of the set of total cost curves are defined as quadratic function in terms of the number of cows and calves in the beef production activities. The marginal cost curves are then approximated using the shadow values from linear programming solution with linear curves. Once the flexibility constraints were removed, the model automatically calibrates to the base year production levels. The results from four scenarios indicated the beef sector of CRAM could predict the impact of the scenarios on the size of beef herd. In Scenario 1 where cash costs were increased by 10 percent, the breeding herd size decreased from 3.73 percent in New Brunswick to 0.0 percent in Ontario and Quebec. In Scenario 2 where barley costs were decreased by 10 percent, the breeding herd size increased from 0 percent for British Columbia, Alberta, Ontario, Quebec, Prince Edward Island and Nova Scotia to 1.93 percent for New Brunswick. In Scenario 3 where carcass weight per beef cow could be increased by 10 percent, the increase in beef herd size ranged from 0 percent for Ontario and Quebec to 2.56 percent for New Brunswick. In Scenario 4 where world beef prices were increased by 10 percent increase in beef herd size ranged from 4.48 percent for Manitoba to 25.78 percent for New Brunswick.

Canadian Regional Agriculture Model: Positive Mathematical Programming Applied to the Beef Sector in Canada

This paper describes the Positive Mathematical Programming (PMP), the method for calibrating models of agricultural livestock production and resource use using a nonlinear total cost function. The PMP method is applied to agricultural sectoral models to study changes in policy and market signals. The Canadian Regional Agriculture Model (CRAM) is a regional, multi-sectoral, comparative static, partial equilibrium, mathematical programming model developed and maintained by Agriculture and Agri-Food Canada (AAFC) since mid-eighties. The PMP process converts a linear model using flexibility constraints into a nonlinear model in the absence of the flexibility constraints. A component of CRAM is the beef sector. The elements of the set of total cost curves are defined as quadratic function in terms of the number of cows and calves in the beef production activities. The marginal cost curves are then approximated using the shadow values from linear programming solution with linear curves. Once the flexibility constraints were removed, the model automatically calibrates to the base year production levels. The results from four scenarios indicated the beef sector of CRAM could predict the impact of the scenarios on the size of beef herd. In Scenario 1 where cash costs were increased by 10 percent, the breeding herd size decreased from 3.73 percent in New Brunswick to 0.0 percent in Ontario and Quebec. In Scenario 2 where barley costs were decreased by 10 percent, the breeding herd size increased from 0 percent for British Columbia, Alberta, Ontario, Quebec, Prince Edward Island and Nova Scotia to 1.93 percent for New Brunswick. In Scenario 3 where carcass weight per beef cow could be increased by 10 percent, the increase in beef herd size ranged from 0 percent for Ontario and Quebec to 2.56 percent for New Brunswick. In Scenario 4 where world beef prices were increased by 10 percent increase in beef herd size ranged from 4.48 percent for Manitoba to 25.78 percent for New Brunswick.