Rebate Levels Research Articles

Theoretical study on demand-side management to reduce imbalance between electricity supply and demand

The gap between electricity supply and demand, which is the electricity imbalance, can have negative economic impacts on retail electricity suppliers. This paper presents a methodology for designing demand response (DR) programs while mitigating the negative impacts. The DR programs require the retailers to set target electricity consumption and prices of economic incentives for customers who cooperate with the DR programs. First, the target electricity consumption is determined by solving a problem of social welfare maximization in which the objective function is the sum of economic surplus of the retailers and their customers and impacts of electricity imbalance. The optimal electricity prices or the optimal rebate levels are then calculated under the principle that rational customers act to maximize their economic surplus. Through numerical simulations, the authors confirmed that the proposed methodology mitigated the impacts of electricity imbalance. Meanwhile, results of the numerical simulations showed that in practical situations, there were cases where the retailers unable to reduce the electricity imbalance profitably. Therefore, the authors additionally discuss ways to assess the electricity imbalance, which motivates the retailers to reduce the imbalance, in such cases.

Analyzing consumers' willingness to purchase energy-efficient appliances in response to energy price changes: Case study of South Korea

This study investigates how changes in energy prices and payback periods can quantitatively change the level of energy efficiency investment. Using the contingent valuation method (CVM) and survey data from 2392 respondents in South Korea, we estimate consumers' acceptable payback period when they are willing to purchase four different types of home appliances: TVs, air conditioners, dehumidifiers, and air purifiers. The average of acceptable payback periods is six to seven years, which corresponds to the probability for consumers to purchase high-efficiency appliances ranging from 47% to 48%. Based on the estimated results, we simulate the purchase probability of high-efficiency appliances in response to changes in energy prices and payback periods. Overall, our findings indicate that consumers are highly sensitive to energy prices in adopting high-efficiency appliances. Therefore, incentive or rebate levels of energy efficiency programs needs to be adjusted according to changes in energy prices.

PD14-07 TRENDS IN MEDICARE PART D SPENDING ON MIRABEGRON AND IMPLICATIONS OF THE INFLATION

You have accessJournal of UrologyCME1 Apr 2023PD14-07 TRENDS IN MEDICARE PART D SPENDING ON MIRABEGRON AND IMPLICATIONS OF THE INFLATION REDUCTION ACT OF 2022 Brittany Berk, Elodi Dielubanza, and Thomas Hwang Brittany BerkBrittany Berk More articles by this author , Elodi DielubanzaElodi Dielubanza More articles by this author , and Thomas HwangThomas Hwang More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003261.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Mirabegron, a beta-3 adrenergic agonist indicated for the treatment of overactive bladder, is one of the costliest drugs for Medicare. In 2022, the US Congress enacted the Inflation Reduction Act, which for the first time allows Medicare to negotiate the price of certain costly drugs for Part D beneficiaries. This study analyzed trends in Part D spending on mirabegron and assessed the potential impact of the Inflation Reduction Act. METHODS: We obtained wholesale acquisition costs for mirabegron from Truven Health Micromedex as of October 2022; total Medicare Part D and per-beneficiary spending and utilization for 2016-2020 from Medicare’s 2020 Drug Spending database; estimated total rebates from SSR Health; and inflation data from Bureau of Labor Statistics. We calculated the nominal and inflation-adjusted change in prices for mirabegron since its launch in 2012, as well as the change in total Medicare Part D expenditures on the drug from 2016-2020. Finally, we compared estimated rebates in 2020 with minimum statutory discounts for negotiation-selected products under the Inflation Reduction Act. RESULTS: In 2020, Medicare Part D spending on mirabegron was $1.7 billion, ranking it among the top 10 likely negotiation-eligible drugs for Medicare under the Inflation Reduction Act in 2026. Part D spending on mirabegron increased by 3.37-times from 2016 ($518.6 million) to 2020. After accounting for estimated rebates, Part D net spending on mirabegron increased by an estimated 123.5% from 2016-2020. Since market launch in 2012, the wholesale acquisition cost for mirabegron has increased by 106.1% unadjusted and 68.9% on inflation-adjusted basis. Under the Inflation Reduction Act, the minimum statutory discount for mirabegron would be 25% if selected for negotiation in 2026, compared to an estimated total rebate level in 2020 of 65%. CONCLUSIONS: Medicare gross and net spending on mirabegron has grown significantly over the past decade, partly due to rapid price increases. Mirabegron may be one of the first medications (overall and for urology) selected for pricing negotiations under the Inflation Reduction Act. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e415 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Brittany Berk More articles by this author Elodi Dielubanza More articles by this author Thomas Hwang More articles by this author Expand All Advertisement PDF downloadLoading ...

Calculation Method for Electricity Price and Rebate Level in Demand Response Programs

Demand response programs (DRs) can be implemented with less investment costs than those in power plants or facilities and enable us to control power demand. Therefore, they are highly expected as an efficient option for power supply–demand-balancing operations. On the other hand, DRs bring new difficulties on how to evaluate the cooperation of consumers and to decide electricity prices or rebate levels with reflecting its results. This paper presents a theoretical approach that calculates electricity prices and rebate levels in DRs based on the framework of social welfare maximization. In the authors’ proposal, the DR-originated changes in the utility functions of power suppliers and consumers are used to set a guide for DR requests. Moreover, optimal electricity prices and rebate levels are defined from the standpoint of minimal burden in DRs. Through numerical simulations and discussion on their results, the validity of the authors’ proposal is verified.

Negotiation Decision between Manufacturer and System Operator on the Electric Energy Demand Response Program

In the electricity market, the imbalance issues between the demand and supply have been an ongoing challenge, especially during the on-peak period. Generally, the system operator adopts the demand response programs: the price-based and incentive-based program, to promote the manufacture decrease the demand during the on-peak period. However, as the manufacturer’s consumption pattern varies from the load curtailment strategy to the load deferral strategy, the system operator should set appropriate price or rebate levels to face the manufacturer’s different choices. The manufacturer announces the portion of on-peak demand for demand response program as well as the choice of the energy consumption patterns in advance. Moreover, the system operator (she) decides the price or rebate level accordingly. To analyze the negotiation process, we formulate a Stackelberg game, where the manufacturer, acting as the leader and the system operator is the follower. The results show that the incentive-based program is more useful to promote the manufacturer to provide a higher portion to the demand response program. However, no dominated program ensures higher profit for the system operator or the less cost for the manufacturer. So, it is the unit shifting cost and customer’s sensitivity to the rebate level that determines the system operator’s preference.

Strike while the rebate is hot: Savvy consumers and strategic technology adoption timing

The California Solar Initiative (CSI) rebate program disbursed more than two billion dollars in incentives to install solar photovoltaics (PV) over roughly a decade while “stepping-down” rebate levels as installed capacity goals were reached. The exact dates (i.e., timing) of the stepdown events were not known, yet recent analyses find evidence of an “announcement effect” wherein consumer adoption is “pulled-forward” across these stepdown events. We analyze unique data from our recent household-level survey on the decision-making process for 194 of these very consumers within a narrow window of eight CSI rebate stepdown events, comparing the decision-making processes of pulled-forward consumers to their counterparts that adopt just after a rebate stepdown.We find evidence that a subset of pre-stepdown adopters engage in more “savvy” decision-making behaviors from their post-stepdown counterparts, including strategic adoption timing. Given these behavioral differences, we conclude that future analyses should carefully consider aspects of individual decision-making processes as potential confounders and control for them if possible. Experience is identified as a potential pathway through which this non-negligible subset of adopters may gain the ability to execute savvy decision-making behaviors; future research should assess the degree to which policy implementation can explicitly leverage this pathway.

The Impact of Make-Take Fees on Market Efficiency

Recently, stock exchanges have altered their trading fees to subsidize liquidity by offering “make” rebates for providing liquidity through limit orders and charging “take” fees for consuming liquidity via marketable orders, leading to debate regarding the impact of these fees on market quality. Using an exogenous experiment performed by NASDAQ in 2015, I employ difference-in-differences analysis on a matched sample and find that a decrease in take fee and make rebate levels leads to greater absolute pricing error and larger variance of mispricing, beyond that expected from widened bid-ask spreads, raising concerns for the SEC’s proposed decrease in fee limits.

Incentive pass-through for residential solar systems in California

This paper estimates the incentive pass-through rate for the two largest solar photovoltaic rebate programs in the U.S.: California Solar Initiative and its predecessor Emerging Renewables Program. We apply both a structural-modeling approach based on the conduct parameter and a reduced-form regression analysis using different fixed effects. Identification comes from rebate level stepwise changes within each of the three major electric utilities in California and different rebate levels across the utilities. The results from both approaches suggest an average pass-through rate of direct incentives of nearly 100%, though with minor regional differences among California counties. These results suggest a relatively competitive market and a smoothly operating subsidy program, at least from an incentive pass-through perspective.

A Design Method for Incentive-based Demand Response Programs Based on a Framework of Social Welfare Maximization

Demand response program (DR) is expected as one of the most effective alternatives to the traditional power supply-demand operations because it does not require additional investment in power plants and equipment. However, there is still room for discussion on setting of electricity price and rebate level with ensuring resources. This paper presents a pricing method for the DRs based on an idea of social welfare maximization. In the proposed method, decrement of the consumers’ comfort, which is caused by the DR cooperation, is calculated as the appropriate incentive payment. That is, the authors evaluate the negative consumer surplus, and convert it into the incentive payment in the DRs. Meanwhile, the limit of DR requirement is estimated in accordance with the resulting decrement of suppliers’ benefit. Through discussions on numerical results, usefulness of the authors’ proposal is verified.

Free riding and rebates for residential energy efficiency upgrades: A multi-country contingent valuation experiment

The cost-effectiveness of energy technology upgrade programs critically depends on free riding. This paper assesses ex ante the effects of free riding on the cost-effectiveness of a rebate program that promotes the adoption of energy-efficient heating systems, relying on contingent valuation choice experiments carried out through identical representative surveys in eight EU Members States. The analysis distinguishes between strong and weak free riders: strong free riders already plan to adopt a new heating system in the next five years; weak free riders decide to purchase once propositioned with an attractive technology package (and therefore do not require a rebate to adopt). The reservation rebates for incentivized adopters (those who decide to adopt because of a rebate) differ substantially across countries. On average, they amount to approximately 40% of the heating system's purchasing price, suggesting generally high opportunity costs for premature upgrades. The reservation rebate and weak free-ridership vary with income, risk and time preferences, and environmental identity. At a rebate level that corresponds to half the purchase price of the offered heating system, the estimated share of free riders exceeded 50% for most countries, with a typically higher share of weak free riders than strong free riders. Specific rebate cost estimates (in €/tCO2) differ considerably across countries, suggesting that cooperation can yield budgetary benefits.

Residential energy retrofits in a cooling climate

In this analysis we calculate the effect of energy retrofits in almost 500 homes in Austin, TX. We used measured daily energy use data (kWh/day) from before and after the homes received energy retrofits. These retrofits included attic insulation, new heating, ventilation, and air-conditioning (HVAC) systems, window screen/film, new windows, new ducts, and added duct insulation. We used a mixed effects regression model (with and without interaction terms) to identify the impact of each type of retrofit, as many homes received multiple measures. We used both utility rebates (to the homeowner) and total retrofit cost information to find the levelized avoided cost ($/kWh) of energy consumption to both the rebate issuing entity (in this case, Austin Energy – the local municipally owned electric utility) and the homeowner. Results indicate that, at current rebate levels, all “rebate costs” incurred by the utility are less than the average cost to procure energy on the wholesale market ($0.035/kWh). Thus the utility could make a profit by forgoing energy sales to local residential customers and instead selling into the market. Regression results show that increasing attic insulation, replacing older heating, ventilation, and air-conditioning (HVAC) systems, and replacing duct systems will most likely be cost effective for the homeowner at the current time, i.e. the costs are less than the current electricity rate (about $0.11/kWh), but replacing windows might not.

Environmental Taxes and the Choice of Green Technology

We study several important aspects of using environmental taxes to motivate the choice of innovative and “green" emissions‐reducing technologies as well as the role of fixed cost subsidies and consumer rebates in this process. In our model, a profit‐maximizing monopolistic firm facing price‐dependent demand selects emissions control technology, production quantity, and price in response to the tax, subsidy, and rebate levels set by the regulator. The available technologies vary in environmental efficiency as well as in the fixed and variable costs. Both the optimal policy for the firm and the social‐welfare maximizing policy for the regulator are analyzed. We find that the firm's reaction to an increase in taxes may be non‐monotone: while an initial increase in taxes may motivate a switch to a greener technology, further tax increases may motivate a reverse switch. For the regulator, we compare the social welfare achievable in the centralized system (which serves as an upper bound) to the highest level achievable under different classes of environmental policies. If the regulator is limited to a tax‐only policy, then when the regulator is moderately concerned with environmental impacts, the tax level that maximizes social welfare simultaneously motivates the choice of clean technology and closes the gap to the upper bound; however, both low and high levels of societal environmental concerns may lead to the choice of dirty technology and significant welfare losses as compared to the centralized case. Supplementing the environmental taxation with fixed cost subsidies and consumer rebates can eliminate this effect, expanding the range of parameters over which the green technology is chosen and often closing the welfare gap to the centralized solution.

Eliciting Coordination with Rebates

This article considers a mechanism based on rebates that aims at reducing congestion in urban networks. The framework helps select rebate levels so that enough commuters switch to modes that are under used. Indeed, getting a relative small number of drivers to switch to public transportation can significantly improve congestion. This mechanism is modeled by a Stackelberg game in which the transportation authority offers rebates, and participants factor them into the costs of each mode. A new Wardrop equilibrium arises when participants selfishly select one of the modes of transportation with the lowest updated costs. Rebate levels are chosen taking into account not only the potential reduction of the participants' cost, but also the cost of providing those rebates. Part of the budget for rebates may come from the savings that arise from the more efficient use of capacity. We characterize the Stackelberg equilibria of the game, and describe a polynomial-time algorithm to compute the optimal rebates for each mode. In addition, we provide tight results on the worst-case inefficiency of the resulting Wardrop equilibrium, measured by the so-called price of anarchy. Specifically, we describe the tradeoff between the sensitivity of the owner towards rebate costs and the worst-case inefficiency of the system.

Costs and benefits of a utility rebate program to promote compact fluorescent lamps in Brazilian households

This article presents results of the first utility-sponsored residential lighting rebate programs in Brazil. The costs of conserving electricity via this type of program as well as the impact on CFL sales resulting from different rebate levels are presented. The programs were held in three cities of the state of Sao Paulo and followed the same structure: the same information campaign, lamp products, number and type of vendors, and participation conditions. The results show that with higher rebate more lamps are sold per day, and the number of lamps sold per household and the total savings achieved increase. It was also noticed that the most affluent consumers have higher participation levels, and this applies to all rebate levels tested. In the present analysis rebate costs, administrative costs and all other program costs were included. The results show that the utility program was cost-effective at three rebate levels tested.

Choice of psychologist based on prior knowledge of fees and level of rebate

This study investigated the relationship between different levels of psychologists' fees and expectations of therapeutic outcome. Subjects were presented with a scenario concerning their need to seek therapy, and then asked to choose from four psychologists differing in amount of fee charged per session: no fee, $25, $35 or $45. The influence of real cost on choice was studied by using three groups of subjects differing in amount of health-fund rebate they could expect: nil, 50% or 100%. The “free” category was most favoured in each group but there was a significant trend towards payment for therapy as the amount of rebate increased. Few subjects, however, chose the highest fee, irrespective of rebate level. The relevance of the data to the issues of fees and rebates was discussed.