Threshold Pricing Research Articles

The Valuation of Contract Deposit and Purchase Price

This paper evaluates the deposit and purchase pricing of purchase contracts in a risk-neutral framework. First, we determine the fair deposit price of a single-installment purchase contract based on theoretical modeling and numerical analysis. Second, the buyer’s threshold pricing in dual-installment and multi-installment contracts is investigated under the framework of compound options. Lastly, the pricing behavior of deposits and purchases is further analyzed using a simultaneous equations modeling framework.

Does Cost-Effectiveness Analysis Overvalue Potential Cures? Exploring Alternative Methods for Applying a “Shared Savings” Approach to Cost Offsets

ObjectivesTo evaluate alternative methods to calculate and/or attribute economic surplus in the cost-effectiveness analysis of single or short-term therapies. MethodsWe performed a systematic literature review of articles describing alternative methods for cost-effectiveness analysis of potentially curative therapies whose assessment using traditional methods may suggest unaffordable valuations owing to the magnitude of estimated long-term quality-adjusted life-year (QALY) gains or cost offsets. Through internal deliberation and discussion with staff at the Health Technology Assessment bodies in England and Canada, we developed the following 3 alternative methods for further evaluation: (1) capping annual costs in the comparator arm at $150 000 per year; (2) “sharing” the economic surplus with the health sector by apportioning only 50% of cost offsets or 50% of cost offsets and QALY gains to the value of the therapy; and (3) crediting the therapy with only 12 years of the average annual cost offsets or cost offsets and QALY gains over the lifetime horizon. The impact of each alternative method was evaluated by applying it in an economic model of 3 hypothetical condition-treatment scenarios meant to reflect a diversity of chronicity and background healthcare costs. ResultsThe alternative with greatest impact on threshold price for the fatal pediatric condition spinal muscular atrophy type 1 was the 12-year cutoff scenario. For a hypothetical one-time treatment for hemophilia A, capping cost offsets at $150 000 per year had the greatest impact. For chimeric antigen receptor T-cell treatment of non-Hodgkin’s lymphoma, capping cost offsets or using 12-year threshold had little impact, whereas 50% sharing of surplus including QALY gains and cost offsets greatly reduced threshold pricing. ConclusionsHealth Technology Assessment bodies and policy makers will wrestle with how to evaluate single or short-term potentially curative therapies and establish pricing and payment mechanisms to ensure sustainability. Scenario analyses using alternative methods for calculating and apportioning economic surplus can provide starkly different assessment results. These methods may stimulate important societal dialogue on fair pricing for these novel treatments.

Price Is Right: Exploring Prescription Drug Coverage Barriers for Irritable Bowel Syndrome Using Threshold Pricing Analysis.

Prescription drug costs exert profound effects on commercial insurance coverage and access to effective therapy. We aimed to assess threshold pricing to achieve budget neutrality of FDA-approved drugs treating irritable bowel syndrome from an insurance perspective, based on cost-savings resulting in decreased healthcare utilization through effective disease management. We constructed a decision-analytic model from an insurance perspective to assess the budget impact of IBS prescription drugs under usual insurance coverage levels in practice: (1) unrestricted drug access or (2) step therapy in a primary care population of middle-age, care-seeking IBS patients. Budget-neutral drug prices were then calculated which resulted in $0 budget impact to insurers with a short-term, one-year time horizon. If used according to FDA labeling, IBS-D drugs cost between $4778 and $16,844 per year and IBS-C drugs cost between $4319 and $4955 per year. These drug costs often exceed insurance expenditures of $6999 for IBS-D and $3929 for IBS-C if left untreated. Therefore, for drugs to have $0 budget impact to insurers, their prices would need to be discounted 36.7-74.2% for IBS-D drugs and 59.3-82.5% for IBS-C. IBS drugs are already priced to support step therapy "failing one of several common, inexpensive IBS treatments with a responder rate > 30-40%," reflecting the subpopulation with more severe disease and greater healthcare costs. Broader prescription drug coverage for patients failing common, inexpensive IBS treatments to which at least 30-40% of patients would typically respond appears warranted to enable gastroenterologists to offer personalized approaches targeting specific mechanisms of this heterogeneous disease.

An intelligent social-based method for rail-car fleet sizing problem

Freight rail transport is already among the safest and sustainable modes to transport goods, however the rail portion of the overall freight transport market as compared with road transport is small. The utilization of rail-car fleet under limited yard capacity to transport goods is a complex managerial problem in the freight rail network. Rail-car fleet is one of the main capital resources in the railroad industry. Hence, rail operators focus to minimize the size of rail-car fleet. We propose a novel approximation queuing model for the non-myopic dynamic rail-car fleet sizing problem with the objective of maximizing social welfare that improves the utilization of rail freight cars. A Markov decision process (MDP) is proposed to determine an optimal trade-off between the number of rail freight cars and the costs of empty rail-car allocation. A connection between an equilibrium-joining threshold and dynamic pricing policy is also studied where effective customers will join the queue based on their willingness to pay. Our simulation results show that the proposed non-myopic rail-car feet sizing policy improves the average social welfare by 27% compared to the myopic case.

The Price of Substitute Technologies

BackgroundOnly a small share of new drugs is truly innovative; 85% to 90% of all new health technologies have little or no advantage over existing therapeutic alternatives. Health economic evaluations can be used to induce acceptable prices for new technologies through threshold pricing. ObjectiveThis work discusses a cost-effectiveness threshold (λ) to be applied to the price regulation of substitute technologies. MethodsConsidering that substitute technologies add only small marginal benefits in terms of innovation or ethical considerations to the system, it does not make sense to allow a loss of efficiency to list them. It has been postulated that the threshold calculated from opportunity costs (κ) represents its maximum possible value and that there must be a threshold (β) that maximizes consumer surplus. For a substitute technology to be listed, the cost of treatment associated with it must be lower than the cost of treatment of the incumbent technology added to the difference in effectiveness priced at the threshold. ResultsThere is no reason for us to believe that the oligopolistic pharmaceutical market is currently charging prices at the cost of production. That way, the cost-effectiveness ratio of the incumbent technology, when lower than κ, is shown through a deductive process to be a plausible estimate for λ that fulfills the objective of maximizing consumer benefit, granting producers a part of the combined surplus to stimulate research and development; that is, it would be between β and κ. ConclusionIn conclusion, the price of substitute technologies should be limited by the cost-effectiveness ratio of the incumbent technology.

An Evolutionary Game Theory Approach for Joint Offloading and Interference Management in a Two-Tier HetNet

In this paper, we present a price-based approach for offloading macro users to small-cells in a two-tier heterogeneous network (HetNet). We have constructively exploited the small-cell density in a HetNet to harness offloading opportunities for macro users (MUs), the goal of which is to solve two problems simultaneously. It aims to shun the MUs, who have a lower received data rate due to the interference perceived from the small-cell tier. The scheme also fends off congestion in a macrocell, by offloading macro users to the small-cell tier. We have proposed a novel threshold pricing scheme, which a macrocell adopts, with a view to influencing low data rate MUs to join a small-cell network. Small-cell networks also charge a price, which includes an access price and an interference compensation price, proportional to the number of MUs who choose the small-cells instead of the macrocellular network. We assume that the small-cells adopt existing cell range expansion techniques to accommodate MUs. We formulate an evolutionary game to model and analyze the behavioral dynamics of the large number of MUs under the proposed pricing strategies of both networks. Replicator dynamics is used to find the evolutionary equilibrium of the evolutionary game. Sequentially, we provide the proof of the existence, uniqueness and stability of the evolutionary equilibrium through extensive analysis. Numerical results are provided to demonstrate that the proposed pricing strategies are able to shape the network dynamics by fine-tuning the rate-threshold and price. The ability to control the macrocell population share by itself with an application of the proposed pricing scheme remains the prime contribution of this paper.

Game Theoretic Design of MAC Protocols: Pricing Versus Intervention

In many wireless communication networks a common channel is shared by multiple users who must compete to gain access to it. The operation of the network by self-interested and strategic users usually leads to the overuse of the channel resources and to substantial inefficiencies. Hence, incentive schemes are needed to overcome the inefficiencies of non-cooperative equilibrium. In this work, we consider a slotted-Aloha-like random access protocol and two incentive schemes: pricing and intervention . We provide some criteria for the designer of the protocol to choose one scheme between them and to design the best policy for the selected scheme, depending on the system parameters. Our results show that intervention can achieve the maximum efficiency in the perfect monitoring scenario. In the imperfect monitoring scenario, instead, the performance of the system depends on the beliefs of the different entities and, in some cases, there exists a threshold for the number of users such that, for a number of users lower than the threshold, intervention outperforms pricing, whereas for a number of users higher than the threshold pricing outperforms intervention.

The Impact of Regulatory Change on Retail Pricing: The New York State Milk Price Gouging Law

This study examines the causal effect of a change in administration of the New York State milk price gouging law on retail milk prices. Specifically, we focus on the November 2008 shift from a threshold pricing policy that consisted of monthly announced prices to a fixed margin policy. Using a regression discontinuity approach, we find lower prices and thus increased consumer welfare for retail milk purchasers in New York State. Furthermore, the change in application of the law may have eliminated previously hypothesized coordination in pricing by retailers through a more competitive retail milk environment.

Online Pricing of Secondary Spectrum Access with Unknown Demand Function

We consider a wireless provider who caters to two classes of customers, namely primary users (PUs) and secondary users (SUs). PUs have long term contracts while SUs are admitted and priced according to current availability of excess spectrum. The average rate at which SUs attempt to access the spectrum is a function on the currently advertised price, referred to as the demand function. We analyze the problem of maximizing the average profit gained by admissions of SUs, when the demand function is unknown. We introduce a new on-line algorithm, called Measurement-based Threshold Pricing (MTP), that requires the optimization of only two parameters, a price and a threshold, whereby SU calls are admitted and charged a fixed price when the channel occupancy is lower than the threshold and rejected otherwise. At each iteration, MTP measures the average arrival rate of SUs corresponding to a certain test price. We prove that these measurements of the secondary demand are sufficient for MTP to converge to a local optimal price and corresponding optimal threshold, within a number of measurements that is logarithmic in the total number of possible prices. We further provide an adaptive version of MTP that adjusts to time-varying demand and establish its convergence properties. We conduct numerical studies showing the convergence of MTP to near-optimal online profit and its superior performance over a traditional reinforcement learning approach.

Load management for price-based demand response scheduling- a block scheduling model

Demand Response (DR) plays an important role in electricity market design, in both reducing utility's investment on peak generation and improving electricity bill savings and incen- tive payments earned by customers. Improved resource-efficiency of electricity production is achieved by closer alignment of elec- tricity pricing information with energy consumption behaviors. In this paper, a block scheduling model of load management for price-based Demand Response is presented under two different real-time pricing schemes: linear pricing scheme and threshold pricing scheme. For linear pricing, the problem is formulated as a convex optimization problem and the optimal demand response profile is given as a two-dimensional water-filling solution either with flat water levels or different water levels for different customers. From the perspectives of the customers as a whole or as selfish individuals, the demand-response computations lead to centralized or distributed optimizations, respectively. A trade-off strategy which attempts to balance these competing objectives is also provided. This trade-off strategy divides customers into local groups within which group-wise distributed optimization is performed to improve the overall performance so that the Price of Anarchy (PoA) is reduced. For threshold pricing, which might be more applicable in certain scenarios, detailed characterization of different optimal load profiles are given assuming a discrete load unit model. A search algorithm is also proposed to find the optimal load profiles for both constant and dynamic pricing threshold scenarios. The effect of dynamic pricing threshold on customers' electricity consumption behaviors is highlighted. Index Terms—Demand response (DR), real-time pricing, load management, two-dimensional water-filling, block scheduling.

Spot Pricing of Secondary Spectrum Access in Wireless Cellular Networks

Recent deregulation initiatives enable cellular providers to sell excess spectrum for secondary usage. In this paper, we investigate the problem of optimal spot pricing of spectrum by a provider in the presence of both nonelastic primary users, with long-term commitments, and opportunistic, elastic secondary users. We first show that optimal pricing can be formulated as an infinite horizon average reward problem and solved using stochastic dynamic programming. Next, we investigate the design of efficient single pricing policies. We provide numerical and analytical evidences that static pricing policies do not perform well in such settings (in sharp contrast to settings where all the users are elastic). On the other hand, we prove that deterministic threshold pricing achieves optimal profit amongst all single-price policies and performs close to global optimal pricing. We characterize the profit regions of different pricing policies, as a function of the arrival rate of primary users. Under certain reasonable assumptions on the demand function, we prove that the profit region of threshold pricing is optimal and independent of the specific form of the demand function, and that it includes the profit region of static pricing. In addition, we show that the profit function of threshold pricing is unimodal in price. We determine a restricted interval in which the optimal threshold lies. These properties enable very efficient computation of the optimal threshold policy, which is far faster than that of the global optimal policy.

The refinancing threshold pricing model: An economic approach to valuing MBS

Investigation of MBS prepayment data indicates that mortgagors have different interest rate levels, or thresholds, at which they exercise their option to prepay their mortgage. In order to properly value an MBS with heterogeneous mortgagors, Merrill Lynch has developed the Refinancing Threshold Pricing Model (RTP). The RTP model focuses on the refinancing decision of the mortgagor when pricing the mortgage pool. The model divides each pool into groups of mortgagors who share similar refinancing costs. Using market data, the RTP model endogenously determines both the implied costs that mortgagors face, as well as the proportion of the MBS pool in each refinancing cost group. In addition to determining pool value, the RTP model also calculates MBS duration, dP/dY and convexity. Comparison between RTP model values and actual market data reveals a strong correlation. The RTP has a wide range of applications, including valuing 15-year and 30-year conventional MBS; pricing interest-only (IO)/principal-only (PO) derivative MBS; determining new versus seasoned MBS price spreads; and valuing specific MBS pools.