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Noise pollution has detrimental negative externalities which Scholars have attempted to evaluate the noise externalities economically, but environmental pricing has not been considerably applied to assess economically noise pollution. The present research aims to quantify the economic cost of noise pollution using the environmental pricing framework proposed by the Delft University. To realize environmental pricing frameworks, this study estimates the costs of noise pollution in the area of Tehran metropolitan. The study attempts to apply the environmental prices framework to local conditions with the assistance of GDP and Gini coefficient. The results demonstrate that the Localized Environmental Prices (LEP) mechanism is capable of internalizing environmental prices. The research indicates that LEP demonstrates the significance of noise pollution necessity to reduction. The results of present investigation show that the sum of environmental prices for noise pollution at Tehran is 56271911 €/year. It also offers a useful foundation for planners and policymakers to make more rational decisions. [ABSTRACT FROM AUTHOR]

We propose a general approximation method for the determination of optimal trading strategies in markets with proportional transaction costs, with a polynomial approximation of the residual value function. The method is exemplified by several problems, from optimally tracking benchmarks and hedging the log contract to maximizing utility from terminal wealth. Strategies are also approximated by practically executable, discrete trades. We identify the necessary trade-off between the trading frequency and trade size to ensure satisfactory agreement with the theoretically optimal, continuous strategies of infinite activity. [ABSTRACT FROM AUTHOR]

Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of model that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we deal with the post optimality solution, or what is known as sensitivity analysis using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model will change the problem of linear programming and will affect the optimal solution. Therefore, we need a method that helps to stand on the impact of changing these constants on the optimal solution that has been reached. General concepts about the binary model and some related theories have also been addressed. By analyzing the sensitivity, we rely on real data for a company that transports crude oil and its derivatives. The mathematical model is formulated for it and the optimal solution is reached using the software. Ready-made sop WINQSB and then calculate the shadow price values for the binding constraints, in addition, linear programming under the fuzzy environment is reviewed, and a new method based on the prime numbers is used to solve the fuzzy parameters model. [ABSTRACT FROM AUTHOR]

Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a naïve shadow price ansatz for maximizing long-term returns, given average volatility yields a strategy that is, for small bid–ask spreads, asymptotically optimal at the third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at the fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices. [ABSTRACT FROM AUTHOR]

Price knowledge is a key antecedent of many consumer judgments and decisions. This article examines consumers' ability to form accurate beliefs about the minimum, the maximum, and the overall variability of prices for multiple product categories. Eight experiments provide evidence for a novel phenomenon we call dispersion spillover : Consumers tend to overestimate price dispersion in a category after encountering another category in which prices are more dispersed (vs. equally or less dispersed). Our experiments show that this dispersion spillover is consequential: It influences the likelihood that consumers will search for (and find) better prices and offers, and how much consumers bid in auctions. Finally, we disentangle two cognitive processes that might underlie dispersion spillover. Our results suggest that judgments of dispersion are not only based on specific prices stored in memory and that dispersion spillover does not simply reflect the inappropriate activation of prices from other categories. Instead, it appears that consumers also form "intuitive statistics" of dispersion: Summary representations that encode the dispersion of prices in the environment but that are insufficiently category specific. [ABSTRACT FROM AUTHOR]

Purpose: Improving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions. Design/methodology/approach: Rice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences. Findings: Ugandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya. Originality/value: The study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples. [ABSTRACT FROM AUTHOR]

We propose a general approximation method for the determination of optimal trading strategies in markets with proportional transaction costs, with a polynomial approximation of the residual value function. The method is exemplified by several problems, from optimally tracking benchmarks and hedging the log contract to maximizing utility from terminal wealth. Strategies are also approximated by practically executable, discrete trades. We identify the necessary trade-off between the trading frequency and trade size to ensure satisfactory agreement with the theoretically optimal, continuous strategies of infinite activity.

This article investigates the contribution of farmers' working conditions to production efficiency under state-contingent production uncertainty. Directional distance function is used to estimate efficiency scores and input shadow prices for 180 Spanish crop farms in 2015. Results suggest that shadow prices vary considerably between the different states of nature, suggesting why incorporating the stochastic production specification is important. The present study provides evidence of the important contribution of working conditions to technical efficiency. Thus, improved working conditions have the potential to help farms to progress toward sustainable agriculture. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the optimization level of a dairy production unit (DPU) through a mathematical programming model (MP). It is expected that by maximizing net income by at least 10%, the DPU will be more profitable than without optimized management. Design/Methodology/Approach: The analysis was carried out under the economic approach of agricultural production, taking into consideration 11 decision variables in the objective function (OF), which was subject to 20 constraints. The variables were based on the requirements of the demand for dairy by-products, using technical coefficients (input-output coefficient). Excel® Solver® was used to develop the sensitivity report and to analyze the shadow prices and reduced costs. Results: Three scenarios were modeled. Between the first and third scenario, the income increased to $58,000.00 (41.02%). Between the second and third scenario, the income increased to $63,840.00 (46.16%). Study Limitations/Implications: Dairy food processing is an important industry in the economies of the world. Findings/Conclusions: Panela cheese recorded the highest shadow price ($72.85), which indicates that the DPU should concentrate on this type of dairy product. In conclusion, the optimization of the DPU guarantees the efficient use of scarce resources and therefore generates a higher profit. [ABSTRACT FROM AUTHOR]

In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challenges are triggered by complex interactions between high demand, low renewable availability, electricity transmission constraints and storage dynamics. We show these challenges cannot be rigorously understood from an exclusively power systems, or meteorological, perspective. We propose a new method that uses electricity shadow prices—obtained by a European power system model based on 40 years of reanalysis data—to identify the most difficult periods driving system investments. Such difficult periods are driven by large-scale weather conditions such as low wind and cold temperature periods of various lengths associated with stationary high pressure over Europe. However, purely meteorological approaches fail to identify which events lead to the largest system stress over the multi-decadal study period due to the influence of subtle transmission bottlenecks and storage issues across multiple regions. These extreme events also do not relate strongly to traditional weather patterns (such as Euro-Atlantic weather regimes or the North Atlantic Oscillation index). We therefore compile a new set of weather patterns to define energy system stress events which include the impacts of electricity storage and large-scale interconnection. Without interdisciplinary studies combining state-of-the-art energy meteorology and modelling, further strive for adequate renewable power systems will be hampered.

In this paper, we deal with linear production planning problems in which multiple firms jointly produce some goods. Owen (Math Program 9:358–370, 1975) presents an allocation scheme for the joint profit of the firms through the cooperative game defined by formulating linear programming problems for obtaining optimal production planning. However, since the values of the resources are measured by the shadow prices which are the optimal dual solution to the linear programming problem for the grand coalition, the excess resources in the grand coalition have no value, and players receive no payoff for the excess resources possessed. Moreover, even when some coalitions cannot be formed, the Owen solution does not change and it is not affected by such situations because it is calculated using the optimal dual solution in the linear production planning problem only for the grand coalition. To cope with these difficulties, we revise the definition of the linear production game by introducing a characteristic function taking into account not only the maximized profit but also the value of the excess resources. To the revised linear production game, we introduce a solution concept with the following favorable aspects. (i) The shadow prices of the resources for all coalitions are utilized for calculating the payoffs of the players. (ii) When some coalitions cannot be formed, such situations are appropriately reflected in the payoffs. (iii) The proposed payoff vector is in the core of the revised linear production game. To demonstrate these properties, we give the numerical examples, and calculate the corresponding proposed payoff vectors. Finally, we give an axiomatic characterization of the proposed solution concept. [ABSTRACT FROM AUTHOR]

The miserable failure of the enforced strategy for moving from the former economic regime towards market economy through applying the flawed neoliberal economic policies during the period (2003-2023), necessitates radical change of public investment criteria for utilizing public ownership of oil wealth in order to ensure optimal economic production, and to finance public investment projects necessary to achieve the targeted growth of production sectors and improving the deteriorated public services. The paper aims to identify the conditions required for optimal production and assess the real economic cost of utilizing oil wealth, as well as regulate the foreign exchange rate's accordingly, through a proposed model of dual central economic planning and competitive market mechanism. [ABSTRACT FROM AUTHOR]

This study applies the wellbeing valuation approach to sport participation and volunteering using data from the German Socio-Economic Panel. Linear regression results show that sport and volunteering hours increase satisfaction with life, health, work, income, and leisure, but with diminishing returns in most models. In a seemingly unrelated regression, some of these effects turn insignificant. The instrumental variable estimates show causal impacts of sporting hours on all wellbeing measures, while volunteering only impacts health satisfaction. The monetary values vary depending on the type of wellbeing measure and estimator, indicating that future studies should consider the employed measures and estimators. [ABSTRACT FROM AUTHOR]

This paper investigates the implementation of negligence rules when the negligent act constitutes a hidden action in the sense of principal–agent theory and where the available evidence is generated by a signal. Any liability rule exclusively based on the available evidence comes with an incentive threshold. Agents with cost savings from the negligent act above this threshold commit the negligent act whereas the others do not. In a first step, liability rules are examined that implement a given incentive threshold at minimum error costs. As this is a linear programming problem, the present paper makes heavy use of duality theory. The multiplier of the incentive constraint if understood as shadow price allows for an intuitive explanation of the results. As a second step, a comparative statics analysis with respect to the incentive threshold is provided. Surprisingly enough, the relation between the threshold and minimum error costs need not be monotonic. • Implementing negligence rules when precaution choice remains hidden to courts. • Minimizing type I and II errors by making use of linear programming technique. • The shadow price for incentive constraint supports intuition for the optimal rule. • Imposing liability at evidence with high likelihood ratios can be optimal. • Non-monotonic relationship between total error costs and the incentive threshold. [ABSTRACT FROM AUTHOR]

Prices and the allocation of resources are essential components of efficient markets. Yet due to market failures or other imperfections, observed prices, and the allocation of resources can diverge from socially optimum equilibria, misinforming private and public decision making and distorting welfare. In this study, we present a two‐step framework for valuing market inefficiencies and the foregone monetary value from disequilibrium. Specifically, we measure the degree that observed prices and quantities diverge from equilibrium and capture this divergence in terms of foregone revenue impacts. Empirically, we illustrate this framework using Indian agricultural data, where we estimate that on average and over the study period this particular market has been underpriced and overproduced compared to the estimated efficient equilibrium. The potential additional gains in value to Indian agriculture from correcting this market disequilibrium ranges from $11 billion USD to $75 billion USD depending on the degree of disequilibrium and the adjustment level. [ABSTRACT FROM AUTHOR]

This paper studies the online scheduling of shared autonomous electric vehicle (SAEV) fleets. The study includes charging management, routing and rebalancing strategies for SAEVs to serve the trip demands in the coupled power and transportation network (PTN). It aims to minimize the total social cost of PTN. The difficulty lies in how to deal with time-varying trip demands with the time-coupled SAEV scheduling and PTN operation considered. To address this challenge, for the first time, we propose a novel framework named the shadow-price deep reinforcement learning (shadow-price DRL), which combines the rigorous PTN operation model and the data-driven model-free DRL-based algorithm. Within the shadow-price DRL, the policy neural network adaptively learns the system dynamics and imposes its actions on the online SAEV scheduling problem as the dynamic shadow prices. By doing so, the SAEV schedule will be determined in the online manner. In addition, the connection between the proposed framework and Lagrangian Relaxation method is discussed, which illustrates the principles and effectiveness of the proposed method. The case studies include the practical Xi’an city which verifies the effectiveness of the shadow-price DRL and illustrates its significant superiority over the safe DRL and model predictive control (MPC) based methods. [ABSTRACT FROM AUTHOR]

The share of home‐cooked food in the diet of UK households declined from the 1980s. This was contemporaneous with a decline in the market price of ingredients for home cooking relative to ready‐to‐eat foods. We consider a simple model of food consumption and time use that captures the key driving forces behind these apparently conflicting trends. We show that observed behaviour can be rationalised by the fact that the shadow price of home‐cooked food, which accounts for the fact that cooking takes time, has risen relative to the price of ready‐to‐eat food, due to the increase in the market value of time of secondary earners. We discuss the implications for policies that aim to encourage healthier diets. [ABSTRACT FROM AUTHOR]

Evaluating shadow prices is critical in devising environmental regulatory policies for pollutants. Compared to traditional frontier estimation methods, this paper uses a recently developed data-driven approach named convex quantile regression, taking both the noise and inefficiency into account and estimating the shadow prices locally. This paper is the first work applying convex quantile regression to jointly evaluate shadow prices of CO2, SO2, and NOx produced by U.S. coal power plants from 2010 to 2017. During this period, five major regulatory provisions were implemented for U.S. coal power plants. We find that the shadow prices of CO2, SO2, and NOx increased from 2010 to 2017. The increase in the shadow price of CO2 is mainly due to the increase in electricity prices, while the increase in shadow prices of SO2 and NOx is mainly due to the successful emission reductions. Moreover, the results show that the CSARP and CSARP Update have significantly increased the shadow prices of SO2 and NOx. However, the relatively lower market allowance prices compared to the shadow prices indicate that society could benefit more if the government could increase the market prices of the pollutants to be more close to the shadow prices. [ABSTRACT FROM AUTHOR]

Resumen: Objetivo: El objetivo de este trabajo es demostrar que es posible monetizar el valor social que genera un hospital y que con su análisis podemos establecer una perspectiva diferente para analizar la eficiencia del gasto público.Método: Utilizando el método del caso se ha seleccionado un hospital público en España. Es idóneo por dos razones: primero, porque su actividad es pequeña y esto facilita el diálogo con los stakeholders; y segundo, como es un hospital de carácter residencial, permite realizar una experiencia de aproximación de la contabilidad social en hospitales sencilla, modificable y que es posible testar.Resultados: Se establece la traducción monetaria de la actividad de un hospital, incluyendo la parte social de las transacciones económicas (mercado), las variables que no han supuesto transacción económica, pero han sido percibidas y valoradas por los stakeholders (no mercado), y la satisfacción de los stakeholders (emocional). Este valor socioemocional asciende a aproximadamente 60 millones de euros anuales para el periodo de 2013 a 2017.Conclusiones: El valor social generado para los stakeholders, y su monetización, permiten gestionar de forma más eficiente las decisiones hacia el propósito social de los hospitales públicos. En concreto, el índice de valor social añadido puede ser una herramienta para la eficiencia social del hospital, ya que se establece cuánto valor social genera a partir de la financiación pública que le han asignado. Así, la disminución de este valor en los últimos años denota un problema que, sin este análisis con perspectiva social y desde los stakeholders, no podría haberse detectado. Abstract: Objective: The objective of this paper is to demonstrate that it is possible to monetize the social value generated by a hospital and use it to establish a different perspective to analyze the efficiency of public spending.Method: A public hospital in Spain was selected using the case method. It is suitable for two reasons; first, the hospital activity is small and therefore dialogue with stakeholders is easy; and second, as it is a hospital of a residential nature, it allows an easy, modifiable and testable approximation of social accounting in hospitals.Results: It establishes the monetary translation of the activity of a hospital, including the social part of the economic transactions (market), the variables that have not been created based on economic transaction, but have been perceived and valued by the stakeholders (not market), and the satisfaction of the stakeholders (emotional). This socio-emotional value amounts to approximately 60 million Euros per year from 2013 to 2017.Conclusions: The social value generated for the stakeholders, and its monetization, allows more efficient management of decisions towards the social purpose of public hospitals. In particular, the social value added index can be a tool for the social-efficiency of hospitals, as it establishes how much social value it generates from the public funding allocated to it. Thus, the decline in this value in recent years denotes a problem that, without this analysis with a social perspective and from the stakeholders, could not have been detected.

We develop a distribution‐adjusted welfare measure that aggregates income, unemployment, and longevity using individual weights that reflect heterogeneous preferences. The measure is implemented for 28 OECD countries for 2008–2013 to gauge the welfare effects of the Great Recession. Estimated shadow prices of one percentage point of unemployment and one year of longevity average 3.1 percent and 5.7 percent of household income, respectively. We find that the rate of GDP growth poorly reflects the social cost of the Great Recession. On average, GDP per capita stagnated across OECD countries between 2008 and 2013 while living standards of poor households fell by 5.3 percent annually. [ABSTRACT FROM AUTHOR]

Streptomyces clavuligerus (S. clavuligerus) has been widely studied for its ability to produce clavulanic acid (CA), a potent inhibitor of β-lactamase enzymes. In this study, S. clavuligerus cultivated in 2D rocking bioreactor in fed-batch operation produced CA at comparable rates to those observed in stirred tank bioreactors. A reduced model of S. clavuligerus metabolism was constructed by using a bottom-up approach and validated using experimental data. The reduced model was implemented for in silico studies of the metabolic scenarios arisen during the cultivations. Constraint-based analysis confirmed the interrelations between succinate, oxaloacetate, malate, pyruvate, and acetate accumulations at high CA synthesis rates in submerged cultures of S. clavuligerus. Further analysis using shadow prices provided a first view of the metabolites positive and negatively associated with the scenarios of low and high CA production. [ABSTRACT FROM AUTHOR]

In many countries, bus operators are private companies whose service has been leased by government agencies. These agencies develop service compliance indices or measures to keep track of factors such as passenger satisfaction, frequency, and regularity but do not necessarily include the objectives of the operators in the assessment. In this paper, we used slack-based measure data envelopment analysis (SBM) to investigate whether it is possible for a bus operator to be efficient (from a private perspective) and match required standards of frequency and regularity. In doing so, data collected from two major bus operators in Santiago, Chile has been used comprising 99 services. The results show that when private objectives, namely revenues, are included in the analysis, bus operators do not necessarily seek to improve the regularity of their service. Moreover, it was found that some bus services are on the efficient frontier while keeping low performance measure standards. Using the shadow prices of the models, it was also found that improving the performance measures will be hard for many bus services unless there is a significant change in factors that are not under control of the operators (i.e., number of stops, length of the route, etc.). This shows the difficulty of correctly aligning the private objectives of operators with agencies’ objectives.

To achieve green development, the Chinese government has taken a number of steps to reduce pollution. Several provinces of China thereby are implementing pilot pollution emission trading schemes. However, problems remain before establishing a nationwide pollution emission trading system, i.e., at what price do polluters acquire another emission allowance in the stage of initial quota allocation. In this context, shadow prices of emissions could provide the policymakers important information for the allowance prices. Besides, environmental protection policies often result in the reduction of several pollutants simultaneously. Thus, considering the provincial and sectoral significant differences in China, this paper employs a nonparametric output distance function approach including multiple undesirable outputs to estimate shadow prices of S O 2 and N O x at national level, provincial level and sectoral level. Our results suggest that multiple pollutants should be taken into account and shadow prices should be set differently at national, provincial and sectoral levels. [ABSTRACT FROM AUTHOR]

This paper analyses the evolution and policy drivers of the productivity of farmers’ human capital in EU agriculture from 1986 to 2010. The empirical analysis employs farm data sourced from the Farm Accountancy Data Network Standard Results as well as Eurostat’s information on farm holders’ educational-attainment levels. Productivities of human capital are measured by the shadow prices for three levels of educational attainment of farm family labour, computed using Data Envelopment Analysis with variable returns to scale, and related to a Malmquist index of total factor productivity and to selected policy variables. The results indicate that productivities of farmers’ human capital trend upwards and are positively associated with rural development payments.

Pollution cost is an important variable in the calculation of Green GDP, which is an indicator of economic development under the green economy concept. This paper relies on the SFA to estimate the cost of air and water pollution in Thailand. During the past 20 years, Thailand has been subject to an average pollution cost of about 2,209,936 million baht ($63,141 million). The average air pollution cost is about 827,383.11 million baht ($23,640 million) and average water pollution costs approximately 1,382,552.84 million baht ($39,501 million). This study also confirms that the pollution problems affecting health, quality of life, and human capital are worsening. Therefore, the government should take the necessary measures through regulations and strict penalties to control pollution. It should also raise awareness of the long-term impact of pollution on human capital and economic development. [ABSTRACT FROM AUTHOR]

This paper analyses the evolution and policy drivers of the productivity of farmers' human capital in EU agriculture from 1986 to 2010. The empirical analysis employs farm data sourced from the Farm Accountancy Data Network Standard Results as well as Eurostat's information on farm holders' educational-attainment levels. Productivities of human capital are measured by the shadow prices for three levels of educational attainment of farm family labour, computed using Data Envelopment Analysis with variable returns to scale, and related to a Malmquist index of total factor productivity and to selected policy variables. The results indicate that productivities of farmers' human capital trend upwards and are positively associated with rural development payments. [ABSTRACT FROM AUTHOR]

We employ parametric forms of directional distance functions to obtain shadow prices of bank equity capital for listed and unlisted banks. We exploit cost, revenue and profit maximisation as the optimisation criteria to derive pricing rules, which allow us to find shadow prices for both inputs and outputs by explicitly accounting for the bank's capital structure choices and hence risk-taking behaviour. We show how knowledge of one input price can be used to price outputs and how knowledge of one output price can be used to price inputs along with information on input and output quantities. We also show how information on total cost or revenue can be used to shadow price inputs and outputs, respectively. We obtain some striking results highlighting the perils of overambitious balance sheet expansions supported by excessive leverage. More specifically, we show that shadow prices for equity capital had reached abnormally high levels in the years leading up to the subprime crisis in the US indicative of excessive risk-taking behaviour. [ABSTRACT FROM AUTHOR]

Shadow prices guide farmers' resource allocations, but for subsistence farmers growing traditional crops, shadow prices may bear little relationship with market prices. We econometrically estimate shadow prices of maize using data from a nationally representative survey of rural households in Mexico. Shadow prices are significantly higher than the market price for traditional but not improved maize varieties. They are particularly high in the indigenous areas of southern and southeastern Mexico, indicating large de facto incentives to maintain traditional maize there.

This study evaluates the environmental impact of current apple cultivation practices in Flanders, Belgium. It evaluates integrated production, the most common practice, and it compares this production method with conventional and organic production. The assessment was based on Farm Accountancy Data Network data from 2010 to 2012 for 64 farms in the region and a life cycle approach was used. The findings showed no significant improvement in environmental impacts for integrated farms compared to conventional farms and, even more, the former showed significantly higher average impacts per hectare for the categories ‘acidification’, and ‘non-renewable energy use’ in comparison with the latter. The organic production group showed higher average impacts per kilogram due to lower yields. Secondly, impacts related to the categories ‘acidification’, ‘eutrophication’ and ‘global warming potential’ were monetized based on the shadow price method in order to obtain external costs. Results show that external costs increase the production costs for integrated farming at least with 5%, both when these costs are expressed per kilogram and per hectare. However, the findings show a large variability in impacts and costs per farm. Farm-specific practices have therefore an important influence on the total environmental cost rather than production group-specific practices.

Background Public district hospitals (PDHs) in Tunisia are not operating at full plant capacity and underutilize their operating budget. Methods Individual PDHs capacity utilization (CU) is measured for 2000 and 2010 using dual data envelopment analysis (DEA) approach with shadow prices input and output restrictions. The CU is estimated for 101 of 105 PDH in 2000 and 94 of 105 PDH in 2010. Results In average, unused capacity is estimated at 18% in 2010 vs. 13% in 2000. Of PDHs 26% underutilize their operating budget in 2010 vs. 21% in 2000. Conclusion Inadequate supply, health quality and the lack of operating budget should be tackled to reduce unmet user’s needs and the bypassing of the PDHs and, thus to increase their CU. Social health insurance should be turned into a direct purchaser of curative and preventive care for the PDHs.

Purpose: The interpretation of differences between alternative systems in life cycle assessment (LCA) can be problematic when different impact categories point to different directions. Using shadow prices is one way to overcome this problem, as the results are expressed in a monetary value, making comparison easy for decision makers. However, for the International Reference Life Cycle Data System midpoint impact categories 'water depletion' and 'land use', the shadow prices were missing. In the current paper, these were derived from literature sources. Methods: Abatement-based shadow prices (Pa) were established from the costs of the abatement measures minus the additional benefits. The damage-based shadow price (Pd) was based on the economic damage per unit of impact. Damage to ecosystems or human health was not included, as monetary values were lacking. As a consequence, Pd is an underestimation. Pa prices for land use, based on soil organic carbon (SOC) depletion, were derived from the cost of abatement measures like adding organic matter to agricultural soil or changing tillage. The response of crop yield to SOC, for several countries and crops, was used for the Pd calculation. For water depletion, Pa was based on water saving measures and desalination techniques, and Pd was based on economic losses due to water unavailability. Results and discussion: The following shadow prices were found for SOC depletion: Pa of 0.10 € kg−1 SOC and Pd of 0.0286 € kg−1 SOC. For water depletion, Pa of 15.8 € m−3 eq. was based on replacing turf with less-water-consuming planting. The value of water for irrigation was the base for the Pd 5.17 € m−3 eq. Freshwater and SOC Pa values unexpectedly exceeded the Pd values. This originated partly from the methods used. Pd was established by averaging marginal costs, while Pa used the most expensive measure, and this may lead to Pa exceeding Pd. Furthermore, the damage-based Pd for SOC and water depletion was mainly based on crop yield, and other types of ecological or societal damage will exist. Including these damages that lacked reliable data will increase Pd. Conclusions: The shadow prices presented here are the first science-based global estimates. For LCA, the Pd values should preferably be used. The values are regarded as conservative estimates since only economic damage was included as other damages like ecological damage could not be monetised. The estimated shadow prices were derived for impacts where economic data is relatively scarce, and this limited the quality of the estimates. More extensive studies are needed to further improve the quality of the estimated prices. [ABSTRACT FROM AUTHOR]