Measuring benefits from spatially-explicit surface water quality improvements: The roles of distance,scope, scale,and size

Programs to improve water quality do not improve all water bodies equally. Evaluation of the benefits of such programs must account for where improvements occur and the relative magnitude of improvements that occur in different places. This study uses a choice experiment survey to explore how the value to a household of a surface water quality improvement varies as a function of (i) the distance between the household and the affected streams and rivers, (ii) the degree to which the quality of the water has been improved, (iii) how many stream and river miles have been improved, and (iv) the sizes of the affected streams and rivers. Results show evidence that value declines with distance in an approximately linear way, weak evidence that large rivers are worth more than small rivers, and no evidence that willingness-to-pay is nonlinear in either the degree of water quality improvement or the number of stream miles improved. These results indicate that it may be defensible in applied work to value small, spatially-explicit water quality improvement projects independently and then sum over projects.     

Stock replenishment policies for a vendor-managed inventory in a retailing system

Using Vendor Managed Inventory (VMI), the vendor determines the replenishment decisions at the location of buyers (retailers). This strategy is used primarily for handling demand fluctuations stemming from the Bullwhip effect, leading the system to prevent from holding excessive inventory that result in a reduction in the overall cost of the supply chain. The main advantages of VMI for vendors are higher levels of accessibility to inventory information and more direct contact with the customers. Similarly, VMI has some pros for the buyers, such as shared risk with upper levels of supply chain and reduction in their holding costs of inventory. In this paper, a vendor-managed inventory system is developed containing one vendor and two buyers in which the main assumption is that back-ordering and lost sales are permitted. In this system, (r, Q) and (R, T) replenishment policies are compared according to their performances to see which one performs more cost-efficiently when partial back-ordering is allowed. In accordance, mathematical models utilizing (r, Q) and (R, T) replenishment policies are developed, and algorithms for deriving the optimal replenishment decision variables are proposed. Moreover, significant differences between the two replenishment policies are discussed. The main finding obtained by this research is that when shortage is permitted, both (r, Q) and (R, T) replenishment policies under VMI have pros and cons in different contexts.     

Relief aid stocking decisions under bilateral agency cooperation

We aim to quantify the benefits of cooperation between humanitarian relief agencies in terms of stocking decisions. We consider two agencies that stock the same type of relief item at different locations prone to individual disaster risks and agree to transship the shortage amount from available stocks in case of a disaster. We incorporate the disaster risk to the Newsvendor model by conditioning the stock quantity decisions on the event that a major disaster occurs within the lifetime of the stocked relief item. We optimize the stock quantity for each agency in response to the other's quantity and compute a Nash Equilibrium solution numerically. We apply this game theoretic approach to the case of earthquake preparedness in Istanbul to optimize the stocking decisions of an agency for shelter units in cooperation with another agency. We investigate the characteristics of the solutions under various parameter settings and identify cases in which cooperation may be beneficial to one or both of the agencies.     

Incorporating price elasticity in financial forecasting models: From theory to practice and implementation

The authors use a capital budgeting example to show students how to incorporate price elasticity into financial analysis as an application of what students learn in their microeconomics course. They present simple as well as more advanced price-quantity relationships, and using various “what-if” scenarios; the authors show how risk analysis can be used to improve revenue projections and valuation models. A project analysis example is employed to illustrate results for negative predictive value and IRR based on three models of price elasticities across a range of potential product pricing. Students are then encouraged to replicate and create similar models, helping them improve their vital Excel and financial modeling skills.     

Good jump,bad jump,and option valuation

I develop a new class of closed‐form option pricing models that incorporate variance risk premium and symmetric or asymmetric double exponential jump diffusion. These models decompose the jump component into upward and downward jumps using two independent exponential distributions and thus capture the impact of good and bad news on asset returns and option prices. The empirical results show that the model with an asymmetric double exponential jump diffusion improves the fit on Shanghai Stock Exchange 50ETF returns and options and provides relatively better in‐ and out‐of‐sample pricing performance.     

Markets under the Microscope: Making Scientific Discoveries Valuable through Choreographed Contestations

This paper breaks new ground by revealing and conceptualizing the marketization of science as a process that transforms scientific discoveries and markets through a series of choreographed contestations: moments of valuation that occur when different social worlds collide. We follow a scientific discovery, from the moment it entered an incubator, to uncover how valuation practices and market devices enact and contest diverse social values (i.e., what is worth doing) to generate economic value (i.e., what is worth paying for) at the science‐market‐entrepreneurship nexus. In contrast with commercialization of science studies that focus on institutional arrangements, this study explicates the practices and devices used by multiple market actors to transform a scientific discovery into a marketable object. In so doing, we characterise choreographed contestations and the mechanisms through which they operate to explain how specific valuations are performed to work out innovative next steps that unfold the marketization of science.     

A Note on a Framework for Valuation Ratios Based on Fundamentals*

Valuation ratios divide stock price by accounting metrics such as earnings, earnings growth, and book value. This study adapts the general valuation framework in Ohlson and Juettner-Nauroth (2005) and Ohlson (2005) to present a unified approach for developing valuation ratios based on fundamentals, referred to as fundamental valuation ratios. One starts with a valuation model that is driven by an accounting metric a and its abnormal growth, then divides the valuation model by a to get a fundamental valuation ratio. For any valuation ratio, one can find a corresponding fundamental valuation ratio, as long as the valuation model is based on the same metric a as the valuation ratio denominator.     

Bitcoin price and its marginal cost of production: support for a fundamental value

This study back-tests a marginal cost of production model proposed to value the digital currency Bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of production plays an important role in explaining Bitcoin prices, challenging recent allegations that Bitcoins are essentially worthless. Even with markets pricing Bitcoin in the thousands of dollars each, the valuation model seems robust. The data show that a price bubble that began in the Fall of 2017 resolved itself in early 2018, converging with the marginal cost model. This suggests that while bubbles may appear in the Bitcoin market, prices will tend to this bound and not collapse to zero.     

The impact of RFID adoption on donor subsidy through for-profit and not-for-profit newsvendor: Implications for Indian Public Distribution system

Subsidy programs are sponsored by government and international agencies to improve affordability and accessibility of food and health products for socially deprived community. Although the donors in such programs allocate substantial resources to fund subsidies, a lot of it is wasted due to the inefficiency in the system arising out of product shrinkage and misplacement. This study analyzes the impact of private participation and advanced technology like RFID adoption on the donor subsidy under target consumption level. We formulate the problem as a donor funding the subsidy program through for-profit/not-for-profit newsvendor and compare the equivalent subsidy per consumption with and without RFID. We perform numerical analysis, collecting data from the public distribution system of India, and the results indicate that, unless the for-profit firm operates under a substantially reduced level of shrinkage and misplacement, the donor should always prefer a not-for-profit firm for program implementation. We also observe that among all the scenarios, a not-for-profit firm with advanced technology like RFID requires minimum donor subsidy to generate the target expected consumption.