Demand Curve Research Articles

Estimates of Equivalence scale for Iranian Households

Despite its vast natural resources of oil, gas and minerals (mining), dealing with the problem of poverty  and inequality  is a serious challenge for policy makers. This challenge becomes increasingly acute as the authorities succumb, inevitably, to pressures to liberalise the economy by implementing free market principles and similar reforms. The welfare system in the Islamic Republic of Iran is quite complex with various governmental, non-governmental and para-governmental welfare organizations operating side by side. The Subsidy Targetization Act was the biggest of its kind in the history of the Islamic Republic, and that it is bound to affect the well-being of a large proportion of the population, it is rather surprising that it was introduced in such haste and without thorough planning. An equivalence scale is a measure of the cost of living of a household of a given size and demographic composition relative to the cost of living of a reference household when both households attain the same level of utility or standard of living (Lewbel and Pendakur, 2006). The method of calculating the equivalence scale is based on the Engel curve which can be argued to be a specific, restricted, representation of the Marshallian demand curve where prices are held constant and demand varies with income. We have argued, as an example of application of this approach, that this approach provides a more efficient and equitable way of compensating the consumers for the impact of the removal of price subsidies.

Optimisation of regional energy demand networks based on flexible load model

The existing literature on integrated energy station-grid planning studies focuses on configuration planning. Therefore, a multi-objective hybrid particle swarm algorithm is used in this paper to solve a multi-objective optimisation model and combines a multi-indicator evaluation method based on evidence-based reasoning to select the solution with the highest evaluation value from multiple candidates (Pareto solution set) as the optimal solution. The optimal planning solution is selected from multiple candidates (Pareto solution set) by a multi-indicator evaluation method based on evidence-based reasoning, and the effectiveness of the proposed model is verified utilizing an example. The customer participation demand response optimises the demand curve by adjusting the flexible load, reduces the system operation cost and investment construction cost, and maximises the economic, environmental and reliability benefits of the integrated regional energy station grid.

Is the price elasticity of demand asymmetric? Evidence from public transport demand

Demand is frequently found to react differently to price increases than to price decreases. This finding is usually attributed to psychological phenomena such as loss aversion or to the different pace with which price changes become known to potential buyers leading to a kinked demand curve. This kink is often invoked in explaining why prices are sticky, especially in the downward direction. We analyse the presence of and the causes for asymmetric price elasticities of demand for the London Underground. Studying public transport demand offers unique advantages: the service cannot be stored and must be consumed at the point of purchase, and the consumption of public transport cannot be preponed or postponed. During the period that we study some nominal fares on the network have increased while others have decreased, offering a unique opportunity to observe price elasticities for both cases. Comparing changes in price elasticities after a price decrease to changes after a price increase, we find that demand is more sensitive to price increases than to decreases (by 0.5 to 1.0 percentage points). We also find that loss aversion contributes to this asymmetry at least on the intensive margin of transport demand.

Ask a Local: Improving the Public Pricing of Land Titles in Urban Tanzania

Abstract Information on willingness-to-pay is key for public pricing and allocation of services but not easily collected. Studying land titles in Dar-es-Salaam, we ask whether local leaders know and will reveal plot owners' willingness-to-pay. We randomly assign leaders to predict under different settings then elicit owners' actual willingness-to-pay. Demand is substantial, but below exorbitant fees. Leaders can predict the aggregate demand curve and distinguish variation across owners. Predictions worsen when used to target subsidies, but adding cash incentives mitigates this. Finally, we demonstrate that leader-elicited information can improve the public pricing of title deeds, raising uptake while maintaining public funds.

Do uninformed traders move prices? Evidence from the Bank of Japan's ETF purchasing program

AbstractUsing the Bank of Japan (BoJ) ETF purchasing program as an exogenous shock to stock demand, we find that stocks with a higher BoJ demand experience higher positive abnormal returns on BoJ ETF purchase dates, which only partially revert in the long term. Our findings support the hypothesis that stocks have a downward‐sloping demand curve, implying that uninformed traders can cause a permanent shift in price.

Policy Optimization Using Semiparametric Models for Dynamic Pricing

ABSTRACT In this article, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one at a time, and only a binary response indicating success or failure of a sale is observed. Our model setting is similar to the work by? except that we expand the demand curve to a semiparametric model and learn dynamically both parametric and nonparametric components. We propose a dynamic statistical learning and decision making policy that minimizes regret (maximizes revenue) by combining semiparametric estimation for a generalized linear model with unknown link and online decision making. Under mild conditions, for a market noise cdf F ( · ) with mth order derivative ( m ≥ 2 ), our policy achieves a regret upper bound of O ˜ d ( T 2 m + 1 4 m − 1 ) , where T is the time horizon and O ˜ d is the order hiding logarithmic terms and the feature dimension d. The upper bound is further reduced to O ˜ d ( T ) if F is super smooth. These upper bounds are close to Ω ( T ) , the lower bound where F belongs to a parametric class. We further generalize these results to the case with dynamic dependent product features under the strong mixing condition. Supplementary materials for this article are available online.

Measuring the welfare cost of asymmetric information in consumer credit markets

Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show how exogenous variation in interest rates can be used to estimate borrower demand and lender cost curves and recover implied welfare losses. While asymmetric information generates large equilibrium price distortions, we find only small overall welfare losses, particularly for high-credit-score borrowers.

Sport tickets pricing strategy with home team's crowd effect

AbstractThis paper investigates the impact of the crowd effect and financing constraints on pricing strategy by constructing an intertemporal model and introducing the crowd effect into a monopolistic home team's decision‐making framework. The results demonstrate that a stronger crowd effect and a larger depreciation rate are always beneficial to the expected profits of the home team and the home team may price along the inelastic portion of the static demand curve in periods 1–3, as long as the expected deferred marginal revenue and the additive price from the performance of the preceding match are sufficiently large.

The CO2 cost pass-through in nonlinear emission trading schemes

In this paper, we theoretically study the issues that how nonlinear structures of energy market affect CO2 costs of energy firms being passed through to energy prices in emission trading schemes. We set up oligopoly models to investigate CO2 cost pass-through under different emission right allocations, characterize analytic derivations of CO2 cost pass-through rates and then explore the connections between CO2 pass-through rates and nonlinear market structures. Our findings suggest that the CO2 cost pass-though rates are not only dependent on the elasticities of energy demand and supply, but largely determined by the convexity of demand curve and the competition intensity of energy market. More importantly, an economic curiosity (CO2 cost pass-through overshifting) is also observed in the emission trading schemes under suitable market conditions. The existence of CO2 cost pass-through overshifting provides regulators and policy makers important information that the emission trading schemes are at the risk of imperfect competition and may require further policy adjustments.

A comparison of reinforcing effectiveness and drug-seeking reinstatement of 2-fluorodeschloroketamine and ketamine in self-administered rats.

2-Fluorodeschloroketamine (2F-DCK), a structural analog of ketamine, has been reported to cause impaired consciousness, agitation, and hallucination in abuse cases. It has similar reinforcing and discriminative effects as ketamine. However, the reinforcing efficacy and drug-seeking reinstatement of this analog have not been clarified to date. In this study, the effectiveness of 2F-DCK and ketamine was compared using a behavioral economics demand curve. The reinstatement of 2F-DCK- and ketamine-seeking behaviors induced by either conditioned cues or self-priming was also analyzed. Rats were intravenously self-administered 2F-DCK and ketamine at a dose of 0.5 mg/kg/infusion under a reinforcing schedule of fixed ratio 1 (FR1) with 4 h of daily training for at least 10 consecutive days. The elasticity coefficient parameter α and the essential value of the demand curve in the two groups were similar. Both groups of rats showed significant drug-seeking behavior induced either by conditional cues or by 2F-DCK and ketamine priming. Moreover, the α parameter was inversely related to the degree of reinstatement induced by cues or drug priming in both groups. In total, the expression levels of brain-derived neurotrophic factor (BDNF) and phosphorylated cAMP response element-binding protein (p-CREB) in the nucleus accumbens in both extinguished and reinstated rats were significantly lower than those in the control. The expression of total Akt, glycogen synthase kinase (GSK)-3β, mammalian target of rapamycin (mTOR), and extracellular signal-related kinase (ERK) also decreased, but p-Akt, p-GSK-3β, p-mTOR, and p-ERK levels increased in both extinguished and reinstated rats. This is the first study to demonstrate that 2F-DCK has similar reinforcing efficacy, effectiveness, and post-withdrawal cravings as ketamine after repeated use. These data suggest that the downregulation of CREB/BDNF and the upregulation of the Akt/mTOR/GSK-3β signaling pathway in the nucleus accumbens may be involved in ketamine or 2F-DCK relapse.

Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings

Building upon prior research that highlighted the need for standardizing environments for building control research, and inspired by recently introduced challenges for real life reinforcement learning (RL) control, here we propose a non-exhaustive set of nine real world challenges for RL control in grid-interactive buildings (GIBs). We argue that research in this area should be expressed in this framework in addition to providing a standardized environment for repeatability. Advanced controllers such as model predictive control (MPC) and RL control have both advantages and disadvantages that prevent them from being implemented in real world problems. Comparisons between the two are rare, and often biased. By focusing on the challenges, we can investigate the performance of the controllers under a variety of situations and generate a fair comparison. As a demonstration, we implement the offline learning challenge in CityLearn, an OpenAI Gym environment for the easy implementation of RL agents in a demand response setting to reshape the aggregated curve of electricity demand by controlling the energy storage of a diverse set of buildings in a district. We use CityLearn to study the impact of different levels of domain knowledge and complexity of RL algorithms and show that the sequence of operations (SOOs) utilized in a rule based controller (RBC) that provides fixed logs to RL agents during offline training affect the performance of the agents when evaluated on a set of four energy flexibility metrics. Longer offline training from an optimized RBC leads to improved performance in the long run. RL agents that train on the logs from a simplified RBC risk poorer performance as the offline training period increases. We also observe no impact on performance from information sharing amongst agents. We call for a more interdisciplinary effort of the research community to address the real world challenges, and unlock the potential of GIB controllers.

A Model of Optimal Production Planning Based on the Hysteretic Demand Curve

The article considers a hysteretic model of consumer behaviour in mono-product markets. Demand generation with regard to an individual consumer is modeled using a non-ideal relay with inverted thresholds. Therefore, the sales rate is defined as an analogue of the Preisach converter. The article considers the problem of the optimal production, storage, and distribution of goods, taking into account the hysteretic nature of the demand curve. The problem is reduced to a non-classical optimal control problem with hysteretic non-linearities. The latter is solved using Pontryagin’s maximum principle. The adopted economic model is based on the binary relationship of consumers to the product: the product is bought or the product is not bought. Transitions between these states are determined within the framework of our model only by the price of the goods; therefore, only the operator of a non-ideal relay can accurately describe such a dependence. The article presents the results of computational experiments illustrating the theoretical assumptions.

Open modeling of electricity and heat demand curves for all residential buildings in Germany

Energy system modeling has been following the energy transition to investigate challenges and opportunities of future energy systems on all grid levels. Necessary input for sector-coupled energy system models are residential electricity and heat demand curves. The increasing importance of distribution grids and their modeling requires demand profiles in high spatial resolution.This paper presents a method to assign pre-generated electricity and heat demand curves to georeferenced residential buildings in Germany. We aim at overcoming fundamental shortcomings of the Standard Load Profiles and enable new possibilities for the modeling of distribution grids. Our approach provides a large variety in residential load profiles which spatially correspond to official socio-demographic data. All used input data sets as well as implemented methodology and the resulting profiles are publicly available under open source and open data licences to enable further use. Our results are validated on different aggregation levels as well as compared and discussed with the commonly used Standard Load Profiles.

Methodology for characterization and planning of electricity demand in an isolated zone: Mitú Approach

This paper aims a model for the characterization and planning of electricity demand in isolated networks when there is no information from the measurement system, a typical scenario in the Colombian Non-Interconnected Zone. This research is based on Arvidson method of the publication entitled: "Diversified demand method of estimating residential distribution transformer loads". This study proposes consumption indices for typical household appliances based on a statistical analysis of load censuses. Then, a timely contrast is made between the curves of the Arvidson study and the generation curves of the isolated network because there is no direct measurement in the end-users and by macrometers associated with the transformers. With this information, we proceed to complement the validated Arvidson curve with its own index; this index allows the proposed curve to be readjusted to a similar curve, per unit, with the generation profile. The main contribution is to propose a new factor, in order to, contextualizes and diversifies the Arvidson method to specific case studies to building daily electricity demand and diversified demand curves as tools for planning the electrical system and managing the electrical infrastructure.

Requirements for New Grid Codes: A Review in Spain & Portugal

To continue to make successful progress towards the achievement of net zero emissions by 2050, a significant number of new facilities based on renewable technologies must continue to be deployed at large scale. However, the integration of large capacities of renewable generation sources into power systems leads to a series of challenges that must be urgently addressed. On the one hand, the intermittent character of renewable resources may lead to imbalances between generation and demand curves, and on the other hand, transmission and distribution system operators will have to carefully consider the impact of reduced power system inertia due to the increase in the number of renewable power plants. Under this framework, stricter technical requirements will be demanded to new power plants that will be integrated into the grid to guarantee quality of electricity supply. These requirements are included within increasingly modern and up-to-date network connection -or gridcodes. Thus, grid codes have a significant role to play in the years to come towards the transition of a more sustainable future, and therefore this paper presents an overview of two grid codes for connecting new generation units across Europe, focusing on the current situation of Iberia. A special emphasis is given on the detailing of certain grid code requirements based on a comparison between the Portuguese and the Spanish grid codes, together with few highlights on the operational procedures for connecting new generation units on both regions.

The Effects of bride price on the Chinese marriage market

This paper will mainly focus on the marriage market of China and how bride price affects it through diverse methods like analyzing the amount of bride price in different parts of China, using the economics models including demand and supply curve and the indifference curves to figure out whether bride price will affect the marriage rate, and finally developing a theory to depict a females’ psychological and economics evaluation on whether a male is worth marrying. The author finds that if the bride price is too high, then it will negatively affect the marriage rate. The bride price will also affect some of the females’ decisions in choosing their lifestyles. However, for more educated women, the theory suggests that the bride price is no longer the most important factor in their marriage decision.

Energy Analysis of a NZEB Office Building with Rooftop PV Installation: Exploitation of the Employees’ Electric Vehicles Battery Storage

Near zero energy buildings are increasing worldwide, exploiting low-carbon technologies in heating and electricity self-production. Commercial buildings are increasingly considered as candidates for the installation of smart micro-grids, which may profit from the added storage capacity of the batteries of employees electric vehicles, stationed during daytime in their charging lots. Smart exploitation of the interaction of these electricity sources and sinks may prove essential to address the complex electricity network demand patterns in today’s fast changing energy mixture. The interaction of an efficient office building’s energy system with a big rooftop photovoltaic installation and the aggregate storage capacity of 40 electric cars that are connected in the building’s charging lots is studied by means of transient simulation in TRNSYS environment. The 18-zone building’s heating, ventilation, and air conditioning system, the cars’ batteries, and photovoltaic systems’ interactions are analyzed on a monthly, seasonal, and hourly basis, against the respective demand curves of the Greek network. The results suggest that the specific system’s size may profitably support the operation of a smart micro-grid. The total annual electricity consumption of the building is computed to reach 112,000 kWh, or 20 kWh/m2y. The annual electricity needs of the 40 electric cars, amounting to 101,000 kWh, can be fully met with 30% of the photovoltaic electricity production. Thus, the building becomes a net exporter of electricity to the network, with maximum exported electricity occurring daily between 12:00 and 14:00, which is favorable to meeting the demand curve. Thus, the establishment of smart micro-grids in commercial buildings with large rooftop photovoltaic panels’ capacity and a significant number of electric cars in the employees’ car fleet is quite effective in this direction.

Call Auction-Based Energy Management System with Adaptive Subsidy and Dynamic Operating Reserve

According to the Paris agreement and the European climate law, carbon neutrality should be achieved by 2050. Therefore, the long-term planning of energy production and the development of green energy have become indispensable research topics in recent years. Due to the unstable production and high cost of green energy, the mechanisms of operating reserve and subsidy should be included in the energy management system. In this paper, we proposed a Call Auction-based Energy Management System (CAEMS) that manages energy using economic theories and dynamic control mechanisms. We use production theory to determine the amount of energy produced, which takes into account the market equilibrium price of supply and demand curves. Then, a dynamic operating reserve rate is designed and embedded in the demand curve to ensure energy stability. An adaptive and self-financing subsidy is proposed to gradually achieve the target energy distribution. Simulation results show that the CAEMS has outstanding improvements in convergence day (42% reduction), mean absolute error (MAE) of supply distribution (1.2% in each type), and extremely low MAE of operating reserve rate (3.2%) and failure rate (0.03%).

Decentralized prioritization of demand response programs in multi-area power grids based on the security considerations

The deregulation of electrical energy grids (EEGs) and surrogating the installation of bulk power plants with distributed generations such as wind energy sources, despite the score of advantages, bring new challenges for the secure operation of these EEGs for their operators. On the other hand, the deployment of demand response programs (DRPs) alongside the management of these multi-area EEGs (MEEGs) intensifies the complexity of the situation. In this paper, a method is proposed for the secure operation of MEEGs when DRPs are employed to incorporate the end-users in balancing the demand–supply chain. Moreover, the techno-economic impacts of fluctuating nature of wind energy sources are mitigated by coordinating them with energy storage systems (ESSs). To do so, a decentralized probabilistic DC-SCOPF model is developed for the operation of MEEGs with ESS-coordinated wind energy sources when several DRPs are deployed in their different areas. The decentralization of the model is performed based on the optimality condition decomposition (OCD) algorithm which results in a mixed-integer non-linear programming (MINLP) problem for each area of the MEEG. What is more; a priority list of DRPs in different areas of the MEEG is generated based on four criteria including the overall operational cost of the system, the number of critical contingencies as the security measure, the overall shed load, and the peak-to-valley ratio (PVR) of the daily demand curve. Numerical simulations are carried out on the New England 39-bus testbed and obtained results are discussed in depth.

Entrepreneurial Opportunity Revelation as the “Anti-Antenarrative”.

Discussions of entrepreneurial opportunity revolve around two competing constructions – opportunity as discovered vs. opportunity as created. Those in the discovered approach are predominantly in the Austrian Economics camp and postulate that entrepreneurs achieve opportunities through expertise or superior knowledge to spot gaps within the market place. Alternatively, created approached in entrepreneurial opportunity thrive in processual approaches, such as effectuation, bricolage, and even the awakening of social capital. Each of these orientations is nonetheless built upon different antenarratives. In the discovered approach, astute entrepreneurs are able to successfully navigate between competing antenarratives to select the “correct” choice, or that which emulates a more faithful interpretation of a supply and demand curve, or best approaches to a metaphysical source as shown in the undifferentiated individual ontology. In the created approach, entrepreneurs choose antenarratives embodied in personal networks, material objects, and preexisting knowledge to create new future oriented narratives as embodied in the differentiated individual ontology. Based on the selected antenarrative, actions occur such as new venture and organization formation.