Shadow Value Research Articles

OPTIMIZING ROYALTY PAYMENTS FOR MAXIMUM ECONOMIC BENEFIT: A CASE STUDY UTILIZING MODIFIED SHOOTING AND DISCRETIZATION METHODS

This research delves into the application of the modified shooting method for the numerical resolution of non-standard optimal control (OC) problems. More precisely, it concentrates on scenarios where the final state value component remains unknown and unconstrained, leading to a non-zero final shadow value or costate variable. Moreover, the objective function involved a piecewise royalty function, which poses a challenge due to its lack of differentiability within a specific time interval. Consequently, the novel modified shooting method was employed to ascertain the elusive final state value. The model’s differentiability is maintained throughout by adopting a continuous hyperbolic tangent (tanh) approximation. In addition, the construction of the Sufahani-Ahmad-Newton-Golden-Royalty Algorithm (SANGRA) and Sufahani-Ahmad-Powell-Golden-Royalty Algorithm (SAPGRA) was accomplished using the C++ programming language to formulate the problem. The outcomes of these algorithms, satisfying the criteria for optimality, were juxtaposed with non-linear programming (NLP) techniques such as Euler and Runge-Kutta, aside from Trapezoidal and Hermite-Simpson approximations. This groundbreaking discovery carries extensive practical implications as it propels the field forward and ensures the application of contemporary problem-solving methodologies. Moreover, the study underscores the significance of fundamental theory in effectively tackling current economic challenges.

Should macroprudential policy be countercyclical?

This paper investigates the influence of possible bank default and bank leverage constraints on monetary and macroprudential policy prescriptions. We build a New Keynesian model with banks that channel funds from households to firms. Banks face endogenous leverage constraints and are subject to costly default. We calibrate our model to the US economy and show that in the decentralized equilibrium, banks borrow more than the socially efficient level. A macroprudential policy that limits bank leverage reduces the risk of bank default and improves long-run welfare. In the short run, a “macroprudential-flavored” monetary policy can reduce financial propagation by affecting bank shadow values, while countercyclical capital regulation is effective for stabilizing bank leverage. While both policies are effective, our study shows that introducing countercyclicality to bank capital regulation achieves little welfare improvement if monetary policy is already used to mitigate financial acceleration. The jointly optimal policies suggest that policymakers should assign countercyclical macroprudential roles to monetary policy, and bank capital regulation should focus on the desired level of prudence.

Short-term energy scenario of district energy system using optimised renewable energy mix with and without energy storage

The study proposes a multi-objective, multi-node optimisation model for the district energy system to achieve high renewable energy share by 2030. A combined analysis is conducted to reduce total system cost, carbon footprint; and satisfy inertia and flexibility requirements of integrated renewable energy system of the considered district. An hourly deterministic tool, Flextool, developed by IRENA, is used for analysis. Multiple scenarios are analysed to identify an optimal capacity expansion plan. The interaction between various energy generation units while meeting hourly energy demand is studied. The flexibility issues concerned with high VRE (Variable renewable energy) integration expected in the future energy grid are identified, and the effect of battery storage on curtailment is evaluated. The maximum VRE absorption capacity of the district is examined, and the shadow value is calculated for all considered scenarios. It is concluded that the district energy system could achieve 52% renewable energy share, zero loss of load and minimum curtailment in 2030 with adequate policy interventions. If the recommended investment pattern is followed, carbon intensity will reduce from 10.729 g/kWh to 6.70 g/kWh and 6.02 g/kWh without and with battery storage systems. The application of battery storage as a flexibility solution resulted in a significant reduction in curtailments. The study demonstrated that Flextool is a competent flexibility assessment tool which provides comprehensive support to optimise capacity expansion and system operations.

Droughts, Deluges, and (River) Diversions: Valuing Market-Based Water Reallocation

This paper develops and applies a method to value water trading on a river network. The framework relies on regulatory variation in diversion caps to identify production functions for irrigated farms, then uses the estimated shadow values to assess the market’s reallocation. I apply this framework to the largest water market in human history, located in southeastern Australia. Observed water trading increased output by 4–6 percent from 2007 to 2015, equivalent to avoiding an 8–12 percent uniform decline in water resources. Reallocation and average surplus both increase substantially during drought, implying that water markets can be most valuable when climatic variability is most severe. (JEL D23, D24, Q12, Q15, Q25, Q54)

The Shadow Values of Soil Hydrological Properties in the Production Potential of Climatic Regionalization of the Czech Republic

The Czech Republic uses a dual system of agricultural land prices, namely the formal/official price—for tax purposes—and the market price in the case of a standard sale or purchase of farmland. This paper focuses on the construction of an econometric model to quantify the influence of soil hydrological characteristics on the production potential in a given climatic region. It also focuses on the use of this model for the determination of the official price of agricultural land, which is expressed on the basis of the code of the evaluated soil-ecological unit (ESEU) and based on defined soil characteristics. The pricing itself is based on the production potential of the land, which in practice is very important for spatial planning, as it determines the classes of agricultural land protection with regard to the possibility of setting aside agricultural land for non-productive purposes or for drawing subsidies for less favourable areas. In this context, the non-productive functions of agricultural land are also frequently discussed, especially its retention, which plays a very important role in the currently changing climatic conditions. There are a number of studies on soil retention, and numerous approaches to measuring it, but none of them address its impact on production potential and thus on the price of land. For this reason, this paper focuses on defining the influence of the retention of the main soil units (defined for the conditions of the Czech Republic) on production potential. For this definition, SUR models are used, where the endogenous variable is expressed as production potential and the exogenous variables include the basic soil characteristics such as grain size, porosity, hydrological component of the soil, and retention. The obtained outputs show both the high explanatory power of the model and the adequate parametric significance of most variables, which provides sufficient support for the use of the results in practice. In addition, the estimated models across all climatic regions are consistent with substantively logical assumptions about the link between production potential and soil hydrological properties, which secondarily demonstrates their applicability in practice, especially for state administration, but also for local government in the sense of municipalities, cities, and other organizational units.

On the Predictive Value of the (Shadow) Real Interest Rate for the Realized Volatility of Gold-Price Returns

We use a quasi-out-of-sample forecasting experiment to study the predictive value of a short-term real interest rate for the volatility of gold-price returns. To this end, we use monthly U.S. data for the sample period from 1990/1 to 2022/2, and we study a standard effective-federal-funds-based real interest rate as well as a shadow real interest rate, which accounts for the recent extended zero-lower-bound period. We find that the real interest rate has predictive value for the subsequent realized volatility, and this predictive value turns out to be stronger in several specifications of our forecasting experiment for the shadow real interest rate than for the standard real interest rate. We evaluate the predictive value of forecasts in terms of an asymmetric loss function. Because gold is considered as a safe-haven asset, our results provide some important implications for portfolio decisions of investors.

A machine learning framework for identifying influenza pneumonia from bacterial pneumonia for medical decision making

Accurately identifying viruses from bacteria determine the therapy and outcome of patients suffering from pneumonia. This study focuses on exploring the capability of machine learning techniques in detecting the well-known influenza virus pneumonia from bacterial pneumonia based on the key variable quantity of blood tests and computer tomography (CT). In this study, we propose an improved Harris hawk’s optimization (GSHHO) based on the Gaussian mutation mechanism and simulated annealing method, and then combine GSHHO with Fuzzy k-nearest neighbor (FKNN) to form a GSHHO-FKNN machine learning model, GSHHO-FKNN. The experimental results have demonstrated that the proposed GSHHO-FKNN has identified that ground grass opacity (GGO) and bronchovascular bundle were distinctive CT phenomenon of influenza pneumonia. Furthermore, the number of procalcitonin (PCT) and white blood cells (WBC) in the cases of influenza pneumonia were notable from those in the cases of bacterial pneumonia. In addition, an interesting result was that the absolute value of eosinophils, platelet and flake shadow in influenza pneumonia cases was more abnormal than those of bacterial pneumonia cases. It proved that the GSHHO-FKNN model was an effective method for discriminating influenza pneumonia from community acquired pneumonia, leading to accurate diagnosis against pathogenic microorganisms.

Objective Evaluation of CT Imaging in the Treatment of Lumbar Disc Herniation.

The value of CT imaging in evaluating the efficacy of percutaneous transforaminal endoscopic discectomy (PTED) in the treatment of lumbar disc herniation (LDH) is explored. A total of 105 patients with LDH admitted to our hospital from March 2018 to September 2019 are selected for treatment with PTED, and all patients undergo CT examination before and after surgery. The CT imaging parameters (CT value of spinal canal soft tissue shadow, maximum back shift distance, longitudinal axis length, and intervertebral space height) before and 1 week after operation, the Japanese Orthopaedic Association (JOA) scores before and 6 months after the operation are compared, and the excellent and good rate of the operation effect is calculated. The correlation between JOA score and CT imaging parameters are analyzed by Pearson correlation method. The experimental results prove that PTED is effective in treating LDH. CT imaging can quantitatively measure the data of herniated intervertebral discs to clarify the recovery of the compressed dural sac and nerve roots, and the results are highly consistent with JOA score, which can be used as PTED objective evaluation method for the treatment of LDH.

Predictive value and prevalence of refractive edge shadow in diagnosis of ovarian dermoids.

To evaluate the diagnostic performance of refractive edge shadow in evaluation of ovarian dermoids compared to other benign adnexal masses. Ultrasound images of 139 patients with 154 dermoids, endometriomas, and hemorrhagic cysts were retrospectively reviewed by 3 radiologists blinded to final diagnosis. Ultrasound and clinical features were compared to pathology or follow-up ultrasound results as reference standard. Inter-reader agreements with free-marginal kappa and diagnostic performance were evaluated. The former was compared using Fisher's exact test or Mann-Whitney test with p < 0.05 to determine statistical significance. The study sample consisted of 154 lesions: 50 dermoids, 50 endometriomas, and 54 hemorrhagic cysts. Refractive edge shadow, homogeneous echogenic appearance, tip of the iceberg sign, mural echogenic nodule, echogenic shadowing focus, and dot-dash sign all were statistically significant across all readers for the diagnosis of dermoid. Prevalence of each feature in dermoids compared to other entities were as follows: refractive edge shadow (70% vs 8%; p < 0.001), homogeneously echogenic appearance (34% vs 2%; p < 0.001), tip of the iceberg sign (16% vs 1%; p < 0.001), mural echogenic nodule (38% vs 2%; p < 0.001), echogenic shadowing focus (13% vs 1%; p < 0.001), and dot-dash sign (44% vs 1%; p < 0.001). Refractive edge shadow had the highest sensitivity, negative predictive value, and accuracy among all ultrasound features associated with dermoids (70%, 86%, and 85%, respectively). Refractive edge shadow is a promising ultrasound feature for diagnosis of dermoids, with the highest diagnostic accuracy and prevalence compared to other previously described features associated with dermoids.

The access to CETA quotas: Extending CGE models with a market for quota licenses

Abstract We analyze the market dynamics that are caused by tariff-rate quotas, particularly the effects of quota license allocation between heterogeneous commodities at the tariff line level. The allocation is endogenously modeled with a mixed complementarity problem approach for the case of the Comprehensive Economic and Trade Agreement between Canada and the European Union. The model results are compared both with alternative models that resemble pre-existing approaches and with the real trade figures that have been collected since the trade agreement's implementation. Our analysis shows a bias toward more expensive commodities if the shadow value of a quota license manifests in a secondary license market. The same quota can thereby be binding to some commodities but not so for others. This feature of quotas can be crucial for policymakers who are concerned about price effects or who want to understand the effects of lumping together commodities of different quality in one quota.

COMBINING SUPERVISED AND UNSUPERVISED METHODS IN TOURISM VISITOR DATA

Combining supervised and unsupervised method can assist in the data analysis process. This research aims to apply a supervised method, i.e. Poisson regression, that is followed by an unsupervised method, namely cluster analysis of the visitors in a tourism dataset. The samples were taken 80 persons purposively from the visitors of the Flower Garden X in Serang Regency, Banten Province. The dataset consists of the number of visits, travel cost, income/ stipend per month, gender, age, distance from the place of origin, and perception, which is formed by 11 questions of facilities and services. The Poisson regression was applied in the 30, 40, and 50 bootstrap samples resulted in the perception as the significant features. Then, medoid-based cluster analysis, i.e. pam and simple k-medoids, in the perception dataset was applied. They compared simple matching and cooccurrence distances and were validated via medoid-based shadow value. It grouped the visitors into five clusters as the most suitable number of clusters. The combined methods of supervised and unsupervised provided the cleanliness as the important indicator. The improvement of the tourism object had to be focus on the cleanliness aspect.

Irrigation water use, shadow values and productivity: Evidence from stochastic production frontiers in vineyards

Increasing agricultural water use efficiency has the potential to contribute significantly to hydrological sustainability and to coping with increasing water scarcity. This paper focuses on the role of the quantity of irrigation water applied and irrigation method used in explaining output in wine grape farms. We applied propensity score matching to reduce potential selection bias from observables that might mediate in the choice of irrigation system. Stochastic Production Frontier models are then estimated for a sample of 371 Chilean wine grape growers. The results show that pressurized irrigation leads to higher production at all levels of water applied; however, at lower levels the impact on TVP is more pronounced. Shadow values calculated at observed output for pressurized and gravity systems are 0.026 USD m−3 and 0.033 USD m−3, respectively. Significant differences are found between low (0.046 USDm−3), medium (0.027 USD m−3) and high (0.018 USD m−3) levels of water applied. The average technical efficiency for the sample is 70.4% and there is no significant difference between growers using pressurized and gravity methods. Our findings suggest that irrigation water can be saved without compromising output, which has important implications for sustainability given that agriculture is the most water demanding sector in the world.

Balancing conservation and commerce: A shadow value viability approach for governing bycatch

The losses from extinction events are not well-known, making an expected net benefits approach to conservation problems difficult to implement. A viable control strategy instead focuses on limiting the risk of extinction to some acceptably low level at the least possible cost. Here we describe a shadow value viability approach for solving conservation problems with irreversible thresholds with dynamic programming. A social planner calculates the minimal (virtual) level of loss from extinction that would trigger sufficient action to avoid extinction with the desired confidence. The cost-effective policy then arises from acting as if the resulting shadow value is real. We demonstrate the method in a numerical application to the conservation of the Pacific leatherback turtle population, which co-mingles with the Pacific swordfish fishery. We show how the cost-effective outcome can be achieved among decentralized fishers by using the planner’s shadow value to set market-based instruments for managing turtle bycatch. This approach translates the species viability objective into economic terms so conservation and commercial harvest can be rationally integrated.

Environmental total factor productivity of agriculture in South Asia: A generalized decomposition of Luenberger-Hicks-Moorsteen productivity indicator

The agricultural total factor productivity (TFP) assessment is essential for providing intuition regarding factors involving productivity change. Integration of environmental aspects together with productive efficiency provides identification of factors for agricultural growth and environmental performance which anticipates foundation for the sustainable agricultural development. In a non-parametric framework, this paper establishes a modified directional by-production model to ensure the link between production and pollution-generating sub-technologies which offers more refined economic interpretations thereby proposing a unique shadow value of the pollution-generating inputs for the two sub-technologies. Further, a non-oriented generalized Luenberger-Hicks-Moorsteen (LHM) productivity indicator is adapted for the refined by-production model to measure the environmental TFP of agriculture sector in South Asia during 2000–2019. The environmental LHM-TFP decomposition accumulates both input and output changes yielding three mutually exclusive components, i.e. technical efficiency change, technological progress, and scale efficiency change. Moreover, the spatial evolution of agricultural carbon shadow price has been accessed during the study period. The policy implications suggest effective ways to improve the environmental TFP of agriculture in South Asia by strengthening technical efficiency advancements and optimizing economies of scale, promoting the coordinated development among countries for sustainable agricultural practices, and encouraging cleaner agricultural production for emissions reduction.

Fuel retention and erosion-deposition on inner wall cladding tiles in JET-ILW

The morphology of beryllium coatings on the Inconel inner wall cladding tiles after JET-ILW campaigns was determined. The focus was on: (i) fuel retention and its share in the overall fuel inventory; (ii) the change of the layer structure and composition. The study is motivated in the view of planned D-T operation in JET. Four tiles were examined: the initial not exposed; one exposed to two campaigns (ILW1-2) and two facing the plasma during ILW1–3. As determined with ion beam and microscopy methods, the initial Be layer (9.0 μm thick) contained up to 4–5 at.% of impurities, mainly H, O, C, Ni. In the exposed tiles, the impurity content increases to 14–26 at.% (up to 20 at.% O, 1.7 at.% C, 1.0 at.% N, 1.3 at.% Ni and under 0.1 at.% W). The surface composition indicates gettering of O and a long-term retention of N. The Be thickness on the tile exposed to ILW1–2 was between 7.6 and 9.7 μm, thus indicating erosion in some areas, while the thickness after ILW1–3 increased to 10–12 μm. The D content was in the range 1.2–3.4×1017 cm−2 after ILW1–2 and 3.2–10×1017 cm−2 after ILW1–3 on most of the analyzed area, but in the limiter shadow values up to 58 ×1017 cm−2 were measured. Taking into account the total area of the Be-coated inner wall cladding tiles, the lower limit of D inventory amounts to 5.3×1022 atoms corresponding to about 176 mg, i.e. somewhat greater than the amount determined on Be limiters. The formation and spalling-off of Be-O particles was revealed.

Multi-asset Noisy Rational Expectations Equilibrium with Contingent Claims

Abstract We study a noisy rational expectations equilibrium in a multi-asset economy populated by informed and uninformed investors and noise traders. The assets can include state contingent claims such as Arrow–Debreu securities, assets with only positive payoffs, options or other derivative securities. The probabilities of states depend on an aggregate shock, which is observed only by the informed investor. We derive a three-factor CAPM with asymmetric information, establish conditions under which asset prices reveal information about the shock, and show that information asymmetry amplifies the effects of payoff skewness on asset returns. We also find that volatility derivatives make incomplete markets effectively complete, and their prices quantify market illiquidity and shadow value of information to uninformed investors.

Estimating farmers’ internal value of crop residues in smallholder crop-livestock systems: A South Asia case study

Crop residues (CR) are an important, internally produced resource with several uses on smallholder, mixed crop-livestock farms, including livestock feed, mulch, fuel and construction material. This study sets out to develop a method to estimate the internal shadow value of CR as feed and as mulch for smallholder households. The study uses a South Asia case study as illustration using data from a set of village and household surveys in three different sites. The estimated shadow prices were higher for CR as mulch than for CR as feed at all three sites. These results reject the null hypothesis that the estimated shadow price for CR as feed is greater than the shadow price for CR as mulch. Since the null hypothesis was formed based on observing household behavior, the rejection of the null hypothesis implies that there are other reasons to explain why more households use CR as feed versus as mulch.

Does the productivity J-curve exist in Japan?-Empirical studies based on the multiple q theory

Brynjolfsson, Rock, and Syverson (2021) argued that the standard TFP growth is low during an investment boom for new technology such as the IT revolution. As the new capital is operated and productivity improves, the shape of the movements in the standard productivity growth resembles a J-curve. However, when costs associated with investment for new technology are recognized as intangible investment - which is not counted in the conventional value added –, the revised TFP growth including these unmeasured intangibles show different movements from the standard TFP growth. Following Brynjolfsson, Rock, and Syverson (2021), we examine the gap between the standard TFP growth and the revised TFP growth. According to their theory, unmeasured intangibles are estimated by the gap between the shadow value and the price of investment goods. We obtain this shadow value of investment through an estimated parameter in each asset using listed firm-level data and revise the standard TFP growth rate. In the case of all industries, the standard TFP growth is overestimated in most years in the late 1990s and the 2000s, because the growth in intangible investment associated with measured investment is lower than measured capital accumulation rate. When we focus on the IT-intensive industries, we find the productivity J-curve in the late 1990s, at the early stage of the IT revolution, as indicated by Brynjolfsson, Rock and Syverson (2021).

Sustainable fisheries are essential but not enough to ensure well‐being for the world’s fishers

AbstractEffective fisheries management is necessary for the long‐term sustainability of fisheries and the economic benefits that they provide, but focusing only on ecological sustainability risks disregarding ultimate goals related to well‐being that must be achieved through broader social policy. An analysis of global landings data shows that average fishing wages in 36%–67% of countries, home to 69%–95% of fishers worldwide, are likely below their nationally determined minimum living wage (which accounts for costs of food, shelter, clothing, health and education). Furthermore, even if all fisheries in every country were perfectly managed to achieve their Maximum Sustainable Yield, a common sustainability target, average incomes of fishers in up to 49 countries—70% of fishers worldwide—would still not meet minimum living wages. Access to decent work and livelihoods are fundamental human rights, including for all fisherfolk around the world, and strategies to support their well‐being must therefore integrate a much wider set of perspectives, disciplines and institutions. Key first steps for fisheries researchers are to more fully recognize and estimate fisheries benefits to households—including income from women and/or alternative employment, unreported landings, or shadow values of subsistence catch—and to help identify and learn from economic equity outcomes in rebuilt fisheries around the world.

The application of medoid-based cluster validation in desirable dietary pattern data

A desirable dietary pattern (DDP) index is an index to measure the balance and variance of the nutrition intake of an individual. This index is composed of the calory values of protein, fat, and carbohydrates. Grouping individuals based on the DDP index is required to measure and improve an individual food security state. We took 14 individual purposively as samples to fill a set of DDP questioner. They were asked about their daily food consumption. They were grouped based on the DDP variables. A 3-dimensional plot showed that there were three to four clusters. Then, medoid-based partitioning algorithms, namely partitioning around medoids (PAM) and simple k-medoids (SKM), were applied in the data set. The inputted distances were generalized distance function to vary the distance options. The cluster results were then validated by medoid-based shadow value validation. This index was comparable to the 3-dimensional plot such that four clusters were opted as the most suitable number of clusters. The barplot of the cluster results showed that cluster 1 was characterized by an abundance of fat, while cluster 2 had very sufficient carbohydrates. Cluster 3 and 4 were two clusters with opposite characteristics where the former had a shortage of protein, fat, and carbohydrates, while the latter had an abundance of them.