Marginal Cost Functions Research Articles

Can the expansion of market size increase firm markup? Evidence from China

ABSTRACT Traditional international trade theory suggests that a larger market size leads to more intense competition, thereby reducing firm markup. However, this conclusion does not hold in our research. Based on the theoretical model constructed by Melitz, this paper makes the following extensions: First, introducing the cost-saving effect outside of the competitive effect discussed in traditional international trade theory. Second, introducing a specific marginal cost function, which deepens the analysis of the operating mechanism. What’s more, earlier models focused solely on the market size of the industry itself (the target industry), whereas our analysis also takes into account the impact of the market size of its upstream and downstream industries. Our model indicates that the impact of market size on firm markup depends on the relative magnitude of the competitive effect and the cost-saving effect. With firm cost following a Pareto distribution, the expansion of market size leads to an increase in firm markup. In addition, this paper presents a spatial econometric model using industrial firms’ data from China. The results indicate that the promoting effect of market size on firm markup is more prominent among top-tier firms, state-owned firms, low export intensity firms, and firms in technology intensive industries.

Calibration of Grid Models for Analyzing Energy Policies

Intermittent forms of renewable energy destabilize electricity grids unless adequate reliable generating capacity and storage are available, while instability of hybrid electricity grids and cost fluctuations in fossil fuel prices pose further challenges for policymakers. We examine the interaction between renewable and traditional fossil-fuel energy sources in the context of the Alberta electricity grid, where policymakers seek to eliminate coal and reduce reliance on natural gas. We develop a policy model of the Alberta grid and, unlike earlier models, calibrate the cost functions of thermal generation using positive mathematical programming. Rather than employing constant average and marginal costs, calibration determines upward sloping supply (marginal cost) functions. The calibrated model is then used to determine an optimal generation mix under different assumptions regarding carbon prices and policies to eliminate coal-fired capacity. Results indicate that significant wind capacity can enter the Alberta grid if carbon prices are high, but that it remains difficult to eliminate reliable baseload capacity. Adequate baseload coal and/or natural gas capacity is required, which is the case even if battery storage is allowed into the system. Further, significant peak-load gas capacity will also be required to backstop intermittent renewables.

Interest rate pass-through and cost channel of monetary policy: Evidence from minimum distance estimation of DSGE model for Pakistan

Understanding the monetary policy transmission mechanism is pivotal for the design of an effective monetary policy. In this regard, the coexistence of interest rate and cost channel of monetary policy has raised important implications for the conduct of monetary policy. This article estimates a New Keynesian model to quantify the strength of interest rate and cost channel by estimating retail rate stickiness and share of firms considering interest rate in their marginal cost function. It examines the extent of interest rate pass-through and cost channel for exogenous monetary policy shock and endogenous movement in official rate arising due to other financial, nominal, and real shocks in the economy. The trade-off between the degree of pass-through and cost channel of monetary policy has also been examined. The minimum distance estimation of the Dynamic Stochastic General Equilibrium (DSGE) model has confirmed that the degree and nature of interest rate pass-through depend on the nature of shock hitting the economy and the cost channel exists only for monetary and financial shocks. A weak trade-off also exists between the degree of pass-through and cost channel of monetary policy. The study recommends that coordination between central banks and financial and non-financial firms is essential for effective stabilization through monetary policy.

우리나라 하수도 공기업 지속가능성 평가

As local governments' finances become poor, questions are being raised about the sustainability of the sewage business since Korea's sewage rates are very low. Due to the short-term characteristics of public officials and the short-term characteristics of elected officials whose desire to achieve their election-related commitments, there is a high possibility that local governments will not be able to invest a lot of resources for preemptive response and maintenance of sewage projects based on systematic and rational long-term plans. This study applies the Altman Z-Score, which can identify the signs of bankruptcy of private companies, and examines the trend of the sewage business where the deficit accumulates because of low rates and the amount of general account support is increasing. It was revealed that the realization of sewage rates to cost is important in that the increase in sewage rate revenue can significantly increase the Altman Z-Score Next, this study shows that voluntary efforts, financial support, and rate realization to cost have important influences on the Altman Z-Score. Finally, the total cost function, average cost function, and marginal cost function were estimated using the annual treatment amount and the population of the sewage treatment area as independent variables. This study insists that high-level (or provincial level) local governments should take the long-term responsibility of the sewerage business in order to allocate adequate resources for preemptive response and maintenance of sewage projects based on systematic and rational long-term plans.

Fee versus royalty licensing in a Cournot duopoly with increasing marginal costs

AbstractWe consider a symmetric homogeneous Cournot duopoly operating under increasing marginal costs. One of the firms owns a patented superior technology that reduces the intercept of the marginal cost function. We compare the incentives of the insider patentee to license the technology to the rival firm either through a fixed fee or through a royalty. We obtain that royalty licensing does not necessarily dominates in our setting: when decreasing returns are important, a royalty is superior only for small enough innovations, whereas a fixed fee is chosen for large innovations. Aditionally, we show that our model is able to replicate the results in Wang (2002), which analyzes the same question in a differentiated duopoly with constant marginal costs.

Estimating empirical marginal adjustment cost function: a power series approach

Estimating empirical marginal adjustment cost function: a power series approach

A Dynamic Task Allocation Algorithm for Heterogeneous UUV Swarms.

Aiming at the task allocation problem of heterogeneous unmanned underwater vehicle (UUV) swarms, this paper proposes a dynamic extended consensus-based bundle algorithm (DECBBA) based on consistency algorithm. Our algorithm considers the multi-UUV task allocation problem that each UUV can individually complete multiple tasks, constructs a “UUV-task” matching matrix and designs new marginal utility, reward and cost functions for the influence of time, path and UUV voyage. Furthermore, in view of the unfavorable factors that restrict the underwater acoustic communication range between UUVs in the real environment, our algorithm complete dynamic task allocation of UUV swarms with optimization in load balance indicator by the update of the UUV individual and the task completion status in the discrete time stage. The performance indicators (including global utility and task completion rate) of the dynamic task allocation algorithm in the scenario with communication constraints can be well close to the static algorithm in the ideal scenario without communication constraints. The simulation experiment results show that the algorithm proposed in this paper can quickly and efficiently obtain the dynamic and conflict-free task allocation assignment of UUV swarms with great performance.

Нелинейные задачи Канторовича с параметром

We consider nonlinear Kantorovich problems with marginal distributions and cost functions depending measurably on a parameter and prove that there exist optimal transportation plans that are also measurable with respect to the parameter. Unlike the classical linear Kantorovich problem of minimization of the integrals of a given cost function with respect to transportation plans, we deal with nonlinear cost functionals in which integrands depend on transportation plans. Dependence of cost functions on conditional measures of transportation plans is also allowed.

Market Power and the Incentive to Innovate: A Return to Schumpeter and Arrow

Using a simple linear demand and marginal cost function, we demonstrate that both competition and monopoly have incentives to innovate since this increases their profit levels. However, our results show that perfect competition is more motivated to innovate since the increase in the profit is greater with the same cost reduction and the same innovation. We also conclude that a more drastic innovation brings greater rent to the monopolist and reduces the advantages of perfect competition over monopoly. It could be presumed that monopoly firms would be attracted to more substantive innovations rather than non-drastic ones.

Real-Time Distributed Economic Dispatch Adapted to General Convex Cost Functions: A Secant Approximation-Based Method

The increasing penetration of distributed energy resources (DERs) in power systems has aroused interest in distributed economic dispatch (DED). While quadratic cost functions are usually adopted, those of DERs are not necessarily quadratic in practice. Existing distributed algorithms perform unsatisfying convergence rates under nonquadratic cost functions. Therefore, this article proposes a secant approximation-based method (SAM) for general convex cost functions to achieve efficient convergence. The marginal cost functions are represented by linear functions in particular price intervals. With a dynamic ratio consensus (DRC) approach, the DERs with linear marginal cost functions can rapidly reach price consensus. The approximated prices can, in turn, determine new price intervals, which are narrower and more accurate.Case studies based on real-world data verify the improved convergence rate under general convex cost functions and exhibit growing performance in larger-scale cases. The proposed algorithm can be applied to DED in systems with high penetration of DERs and massive agents with general convex cost functions.

Estimating Empirical Marginal Adjustment Cost Function - A Power Series Approach

Estimating Empirical Marginal Adjustment Cost Function - A Power Series Approach

Marginal Uncertainty Cost Functions for Solar Photovoltaic, Wind Energy, Hydro Generators, and Plug-In Electric Vehicles

The high penetration of renewable sources of energy in electrical power systems implies an increase in the uncertainty variables of the economic dispatch (ED). Uncertainty costs are a metric to quantify the variability introduced from renewable energy generation, that is to say: wind energy generation (WEG), run-of-the-river hydro generators (RHG), and solar photovoltaic generation (PVG). On other side, there are associated uncertainties to the charge/uncharge of plug-in electric vehicles (PEV). Thus, in this paper, the uncertainty cost functions (UCF) and their marginal expressions as a way of modeling and assessment of stochasticity in power systems with high penetration of smart grids elements is presented. In this work, a mathematical analysis is presented using the first and second derivatives of the UCF, where the marginal uncertainty cost functions (MUCF) and the UCF’s minimums for PVG, WEG, PEV, and RHG are derived. Further, a model validation is presented, considering comparative test results from the state of the art of the UCF minimum, developed in a previous study, to the minimum reached with the presented (MUCF) solution.

The Song Remains Not the Same: Correlated Intercept and Slope Uncertainties Matter to Prices versus Quantities

Weitzman’s “relative slope rule” (RSR) is a rule of thumb for determining the relative efficiency of quantity versus price instruments to regulate firms under asymmetric information. This rule identifies the more efficient instrument based on the relative slopes of the marginal benefit and cost functions. The RSR relies on three key assumptions: the unknown cost and benefit functions are well represented by second-order approximations, the regulator’s uncertainty is confined to the intercepts of the linearized marginal functions, and these intercepts are not correlated. Subsequent work has adopted these assumptions as the default case and found the RSR to be robust, although Malcomson showed the RSR may break down when the marginal cost function’s intercept and slope are both uncertain and correlated. We provide theoretical support for the presence of this correlated uncertainty and, using numerical examples, show the relative slope rule may be in error in this setting.

Marginal damage cost functions for particulate organic carbon loading from open-net pen salmon farms in British Columbia, Canada

Increasing production of salmon open-net pen culture has raised concerns about the negative impact of this aquaculture technology on the marine environment. In British Columbia (BC), Canada, benthic deposition of organic nutrients (faeces and waste feed) is identified as a potential source of localized environmental degradation from salmon farming. In this paper, we develop a marginal damage cost function to provide a quantitative monetary measure for potential environmental impacts of simulated salmon farms, representative of typical BC net pen sites. The development of the functions is done by integrating the outputs of a discrete choice experiment (DCE) with the results of an organic deposition model (NewDEPOMOD). The resulting relationships can be used to find efficient policies and sustainable operation strategies that balance salmon production with the external cost to the marine environment.

Kantorovich problems and conditional measures depending on a parameter

We study measurable dependence of measures on a parameter in the following two classical problems: constructing conditional measures and the Kantorovich optimal transportation. For parametric families of measures and mappings we prove the existence of conditional measures measurably depending on the parameter. A particular emphasis is made on the Borel measurability (which cannot be always achieved). Our second main result gives sufficient conditions for the Borel measurability of optimal transports and transportation costs with respect to a parameter in the case where marginal measures and cost functions depend on a parameter. As a corollary we obtain the Borel measurability with respect to the parameter for disintegrations of optimal plans. Finally, we show that the Skorohod parametrization of measures by mappings can be also made measurable with respect to a parameter.

Variational Inequality and Distributed Learning for a Bidding Game in Electricity Supply Markets

This study uses a game-theoretic analysis of bid-based electricity supply market equilibrium. Electricity supply markets are modeled as strategic interactions of bidders that supply electric power to the market and the bidders’ pure strategies are the cost function parameters of power generation. We demonstrate that the resultant bidding game is a convex game and has a unique pure-strategy Nash equilibrium (PNE) when the bid-cost functions are parameterized by marginal costs of power generation. The PNE of the power-supply bidding game is reformulated in terms of a variational inequality and as a fixed-point of a recursive mapping. We propose two distributed learning algorithms and their variations with convergence analysis to compute a PNE. Three types of measures are proposed and analyzed for quantification of inefficiency due to falsified bidding actions corresponding to the marginal cost function parameters of supply-market participative generators. A numerical case study with a 26-bus power network is presented to illustrate and demonstrate our results.

An experimental investigation of bilateral oligopoly in emissions trading markets

Market power in emissions trading has been extensively investigated because emerging markets for tradable emissions permits, such as the European Union's Emissions Trading Scheme (ETS), can be dominated by relatively few large sellers or buyers. Previous studies on market power in emissions trading have assumed the existence of a subset of competitive players. However, a key feature of emissions trading markets is that emissions permits are often traded by a small number of large sellers and buyers. Using a laboratory experiment, our objective in this paper is to test the performance of an emissions trading market utilizing a double auction in a bilateral oligopoly. Our results suggest that the theoretical bilateral oligopoly models can better describe market outcomes of emissions trading. The effects of the slope of the marginal abatement cost function on market power in laboratory experiments are found to be consistent with those predicted by the theoretical bilateral oligopoly model. How market power is exercised depends on the curvature of the abatement cost function. If the marginal abatement cost function of buyers (sellers) is less steep than that of sellers (buyers), the price of permits is lower (higher) than that under perfect competition. This is because the market power of buyers (sellers) exceeds that of sellers (buyers). The price of permits is close to the perfect competitive price when all traders have the sameslope of the marginal abatement cost function.

Measures of industry productivity change: the case of thermal electricity generation in Chinese provinces 2000–2014

The typical textbook production theory for a single production unit, assuming substitution possibilities both ex ante and ex post between all factors of production, may not be so well suited for understanding structural change within industries characterised by embodied technical change and a significant presence of capital equipment that represents sunk cost. In the literature an industry function is often based on just aggregating micro-level data to the industry level, or scaling up an average production function, using at times quite sophisticated econometric techniques to estimate a parametric production function. However, entry and exit of plants, and embodied technological change at the micro or plant level drive the dynamics. The requirement of plant level data has severely restricted the use of the approach. However, the paper shows that such production function concepts can be applied to coal-fired electricity generation aggregated to the Chinese province level and still get valuable structural information for policy analysis. Development in total variable factor productivity (TVFP) and bias of technical change are estimated and illuminated using figures for isoquant maps, capacity regions in input coefficient space and average- and marginal cost functions for the provinces in China.

Cost function approach to water protection in forestry

Abstract The European Water Framework Directive (WFD) strongly emphasizes that all water polluting sectors must enhance the protection of water bodies in a cost-effective way. River Basin Management Plans need to be made to achieve a good environmental status for all water bodies by 2027 at the latest. This article examines three principal water protection measures used in forestry: buffer zones, overland flow fields and sedimentation ponds. We analytically develop marginal abatement cost functions for each of these measures and apply them numerically for the Finnish forestry. We find that the marginal abatement costs of nutrients using buffer zones in clear-cut mineral soil forests are very high, as they entail leaving financially mature and uncut trees. In contrast, the marginal costs of using overland flow fields in conjunction with ditch cleaning and clear-cutting in peatlands are very low. Furthermore, for sediments using overland flow fields as a water protection measure entails significantly lower abatement costs than does using sedimentation ponds in conjunction with ditch cleaning in peatland forests. A cost-effective solution in a river basin entails that the highest nutrient reductions are made in agriculture but that forestry also does its share. A cost-effective allocation of abatement measures entails that the proportions of the overall nutrient reduction are 3% (1%) in forestry and 97% (99%) in agriculture when the reduction target is set as 10% (30%).

Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics

A hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid solves its own economic dispatch problem through a distributed model predictive control approach that respects capacity limits and ramp-rate constraints of distributed generation. In the upper layer, the energy trading in the network of microgrids decides how to optimally trade the energy based on the marginal cost information from the lower layer in order to improve global optimization objectives, e.g., social welfare. In order to solve the trading problem, a consensus-based algorithm and a replicator dynamics algorithm are proposed assuming that the marginal cost function of the microgrid is known and linear. It is shown that both algorithms converge to the same solution, which is equivalent to the minimization of operation costs. The consensus-based algorithm is extended in order to tackle more general marginal cost functions and trading network constraints. Moreover, the effect of ramp constraints and network limits is studied. Simulations show the effectiveness of the proposed algorithms for three interconnected microgrids with different characteristics.