Shadow Prices Research Articles

Prediction of metabolite-protein interactions based on integration of machine learning and constraint-based modeling.

Metabolite-protein interactions play an important role in regulating protein functions and metabolism. Yet, predictions of metabolite-protein interactions using genome-scale metabolic networks are lacking. Here, we fill this gap by presenting a computational framework, termed SARTRE, that employs features corresponding to shadow prices determined in the context of flux variability analysis to predict metabolite-protein interactions using supervised machine learning. By using gold standards for metabolite-protein interactomes and well-curated genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, we found that the implementation of SARTRE with random forest classifiers accurately predicts metabolite-protein interactions, supported by an average area under the receiver operating curve of 0.86 and 0.85, respectively. Ranking of features based on their importance for classification demonstrated the key role of shadow prices in predicting metabolite-protein interactions. The quality of predictions is further supported by the excellent agreement of the organism-specific classifiers on unseen interactions shared between the two model organisms. Further, predictions from SARTRE are highly competitive against those obtained from a recent deep-learning approach relying on a variety of protein and metabolite features. Together, these findings show that features extracted from constraint-based analyses of metabolic networks pave the way for understanding the functional roles of the interactions between proteins and small molecules. https://github.com/fayazsoleymani/SARTRE.

Does foreign direct investment promote environmental performance: An investigation on shadow prices of pollutants

The shadow prices, or marginal abatement cost, of pollutants is a useful measure of environmental performance. Unlike much of the previous studies focusing on only one kind of pollutants, this paper applies the (multiplier) by-production approach to measure the shadow prices of carbon emission, sulfur emission, and dust. The case of regional economies in China is considered. As the foreign direct investment may have an impact on the environmental performance, a spatial Durbin model is utilized to identify the impact of foreign direct investment on the shadow prices of pollutants. The results show that the shadow prices of all three pollutants have been increasing over time which indicates the environmental performance of China has been improving. Moreover, the spatial regression results imply that both foreign direct investment and technology export volume positively impact the shadow price of pollutant emissions across the provinces of China.

Assigning Shadow Prices to Synthetic Inertia and Frequency Response Reserves From Renewable Energy Sources

Modern electricity grids throughout the world, particularly in islands such as Great Britain, face a major problem on the road to decarbonisation: the significantly reduced level of system inertia due to integration of Renewable Energy Sources (RES). Given that most RES such as wind and solar are decoupled from the grid through power electronics converters, they do not naturally contribute to system inertia. However, RES could support grid stability through appropriately controlling the converters, but currently no market incentives exist for RES to provide this support. In this paper we develop a methodology to optimally clear a market of ancillary services for frequency control, while explicitly considering the participation of grid-forming and grid-following inverter-based technologies. We propose a mathematical framework that allows to compute shadow prices for ancillary services offered by a pool of diverse providers: synchronous and synthetic inertia, enhanced frequency response (e.g. from curtailed RES) and traditional primary frequency response (e.g. by thermal generators). Several case studies are run on a simplified Great Britain system, to illustrate the applicability and benefits of this pricing scheme.

The accuracy of benefit-cost analysis for transport projects supported by the Asian Development Bank

This paper analyses the accuracy of Benefit-Cost Analysis (BCA) of transport projects financed by the Asian Development Bank (ADB). Ex post evaluation of BCAs outside Europe and North America has been largely missing from the current literature. This study covers 59 roadway projects in developing countries funded by ADB and examines the accuracy of BCA results through four dimensions: frequency, magnitude, correlation, and tendency. We found that under an average project completion rate of 95.33%, the average construction cost overrun for 59 roadway projects is 10.71%, equivalent to USD 71.4 million. Grounded on 23 projects disclosing detailed economic analysis, we discovered a systematic tendency to understate both the present values of cost (18 out of 23 projects) and the present values of future economic benefits (13 out of 23 projects) in ex ante BCA. Furthermore, more than half of projects (25 out of 47) underestimated EIRR, and about 52.17% of them (12 out of 23) understated NPV. Since the underestimation of economic benefits is too small to counterbalance the underestimation of costs, the project EIRR is on average 5.4% lower than the initial expectation. Moreover, we discussed ADB’s choice of the social discount rate, shadow price, and counterfactual base scenarios, which significantly influence the accuracy of BCA results and the reliability of decision-making grounded on BCA results. Lastly, the causes of cost overruns and benefits underestimations were analyzed.

The Shadow Price of Capital: Accounting for Capital Displacement in Cost Benefit Analysis

The Shadow Price of Capital: Accounting for Capital Displacement in Cost Benefit Analysis

Linearizing Bilinear Products of Shadow Prices and Dispatch Variables in Bilevel Problems for Optimal Power System Planning and Operations

This work presents a method for linearizing bilinear terms in the upper level of bilevel optimization problems when the bilinear terms are products of the primal and dual variables of the lower level. Bilinear terms of this form often appear in energy market optimization models where the dual variable represents the market price of energy and the primal variable represents a generator dispatch decision. Prior works have linearized such bilinear terms for specific problems. This work is the first to demonstrate how to linearize these terms in the most general case and the conditions required to perform the linearization for bilevel problems with integer or continuous variable in the upper level. The method is provided in an open source Julia module that allows researchers to write their bilevel programs in an intuitive fashion.

The Net Benefits and Residual Cost from U.S. Border Management of the Initially Inadmissible

AbstractBorder management is a government activity affecting immigration and the economy. Benefit–cost and equivalent decision analyses are used to evaluate U.S. border management for 2017. Controversial issues arise. Among these are the issue of standing and the values of asylum, a criminal career, child custodial care, foreign deaths, fiscal and labor market effects, and distributional weighting. Sixteen unique shadow prices (imputed marginal value) are computed. Those shadow pries are combined with proportions and levels of border management outcomes. The aggregate result is not only a large expected present value net benefit per year from managed outcomes of $46.6 billion but also a large residual unmanaged annual cost of $23.7 billion. Significant uncertainty exists, but estimated net benefits remain positive.

Alternative risk measurement for the banking system and its nexus with economic growth

Scientific and reasonable evaluation of bank performance can help them conduct business management and decision-making, while most research ignore using the shadow price of undesirable outputs to evaluate banking performance. This study introduces a dual formulation of network data envelopment analysis to evaluate the shadow price of non-performing loans, which could be regarded as a novel measure of potential financial risk. We further investigate the tradeoff between economic growth and financial risk from micro and macro perspectives. Our results show that the financial risk of city commercial banks and joint-stock banks is higher than that of the big four state-owned and policy banks. Our research proves that economic growth influences the risk levels of banks directly and indirectly. More specifically, our study confirms that economic growth can reduce the bank's risk by reducing the bank's loan capital ratio as an intermediary path, that an increase in the capital adequacy ratio has a positive effect on the bank's risk.

Thermodynamic analysis and operation investigation of a cross-border integrated energy system based on steam Carnot battery

With the booming development of industrial parks in southern Belt and Road (B&R) countries, the demand for energy carriers such as electricity and steam grows rapidly. One key aspect of B&R initiative is to promote cross-border energy cooperation in these countries. However, this region has abundant renewable energy resources, while the electricity and steam supply required in industrial processes is insufficient. This paper proposes a cross-border integrated energy system (IES) based on Carnot battery technology. A steam Carnot battery (SCB) is designed based on phase change material with water/steam as the working fluid. This paper establishes thermodynamic model of the proposed IES and evaluates its performance. Based on a field investigation in a real cross-border China-Myanmar industrial park, this paper designs the corresponding IES and studies SCB’s impact on IES daily operation. A baseline IES having an electric battery is also proposed to facilitate the comparison. The result shows that IES based on SCB reduces 28.57% operating cost, 43.49% carbon emission, and 16.49% city grid electricity consumption compared with the baseline. This means electro-thermal complementarity is an essential feature of SCB in IES. Furthermore, shadow price approach is adopted to analyze the impact of SCB in IES with the development of the industrial park. Renewable electricity output and peak-valley ratio have high shadow prices. The operating cost of IES based on SCB is highly affected by the percentage of renewable energy introduction and pricing market, making it a promising choice in this region known for redundant hydropower. Although electricity storage capacity and SCB’s roundtrip efficiency have less impact on cost reduction, they can reduce carbon emission for IES. This study provides a new perspective for constructing the energy system in B&R initiative areas.

Input-output planning and information

In this paper, we show how socialist planning can be based on input-output data. We argue that the information required for this can be obtained by a central planning agency and thus dismiss Hayek’s information argument against socialism. We further show how economic planning can be made responsive to consumer demand through a feedback control mechanism. Output targets of products would be adjusted in response to observed consumer demand or based on predictions about future demand. Planners can use machine learning to make more accurate forecasts. The valuation of goods plays an important role in the feedback control mechanism. The values of goods can either be measured by the labour time necessary for their production (labour values) or through shadow prices based on linear programming.

Nonparametric shadow pricing of non-performing loans: a study of the Chinese banking sector

Nonparametric shadow pricing of non-performing loans: a study of the Chinese banking sector

Is the technical efficiency green? The environmental efficiency of agricultural production in the MENA region

There is widespread recognition of the global environmental impact of agricultural production on greenhouse gas emissions, but evidence is sparse regarding the impact in the Middle East and North Africa (MENA) region. In this study, we treat agricultural emissions as an undesirable output from agricultural production and apply the directional distance function to measure environmentally-adjusted technical efficiency, defined as environmental efficiency in agricultural production, in six countries in the MENA region (Algeria, Egypt, Israel, Jordan, Morocco, Tunisia) during the period 1980–2016. The results show that all six countries have clear scope to improve their environmental efficiency. Agricultural production is greener in Jordan and Israel, while environmental efficiency is currently lowest in Egypt and Morocco. Estimated relative shadow price of agricultural emissions is −1.002, implying that the ‘cost’ of removing agricultural emissions is almost equal to the value of producing one unit of good output. These findings suggest there is a trade-off between agriculture emissions and production, which should be considered in efforts to enhance the sustainability of agricultural production in the MENA region.

Research on Water Rights Trading and Pricing Model between Agriculture and Energy Development in Ningxia, China

The contradiction between the supply and demand of water resources has become increasingly prominent, and water rights trading is an effective approach to increase the efficiency of water resource utilization and allocation so as to achieve sustainable use of water resources. Current transferring cost and price in China are both underestimated, taking into account the construction and maintenance fee of water conservation project and the irrigation risk compensation fee but ignoring the renovation and reconstruction fee of water conservation projects, and the compensation fee for farmers. This paper takes assignee rights, assignee capacity, and compensation to third parties into comprehensive considerations in Ningxia Hui Autonomous Region, where the contradictions between water, energy and food are most prominent in China. Tradable water use rights were analyzed based on a water transfer pricing model. The results show that there is an obvious negative correlation between shadow water price and water usage, and the shadow price of water resources is between 10.91 and 40.52 CNY/m3, which is an optimal solution under the constraint of water usage from 6.65 to 7.03 billion m3. The reasonable water transfer price is 10.91 CYN/m3, of which the earning of the agricultural assignor was 5.96 CNY/m3. This price guarantees the interests of the assignee and is also affordable to the assignee. This research provides a specific calculation method for the transfer pricing of water rights under non-market conditions, which is of important theoretically and has practical significance.

Land use changes and economic effects of alternative fertilizer policies: A simulation analysis with a bio-economic model for a Tank Village of Sri Lanka

CONTEXTUntil May 2021, the policy regime of the Government of Sri Lanka was to import and provide chemical fertilizer at subsidized rates to small-holder farmers. On May 6, 2021, the government imposed a ban on import of chemical fertilizers and subsidy was directed to organic fertilizers. Due to heavy protests by the farming community, the import ban was lifted in November 2021. By that time, fertilizer prices in the world market had sharply escalated making chemical fertilizers quite an expensive source of nutrients. OBJECTIVEThe objective of this paper is to assess the implications of different fertilizer policy scenarios on land use, profitability, shadow prices of resources, and environmental damages in paddy, maize and vegetable- based cropping systems in the Dry Zone of Sri Lanka. METHODA bio-economic model was developed and simulated for five policy scenarios for the Mahakanumulla tank village in the Dry Zone of Sri Lanka demonstrating (i) conventional agriculture, (ii) enhanced availability of organic fertilizers, (iii) removal of subsidy on chemical fertilizers, (iv) premium prices for chemical fertilizer free produce, and (v) a composite shock accommodating (ii), (iii) and (iv) above. The above simulations were run “with” and “without” water constraints to depict tank village systems and similar systems under major irrigation schemes respectively under varying limits of chemical fertilizers. Paddy, maize and vegetable, cultivated using two technologies, i.e., intensive use of chemical fertilizers and intensive use of organic fertilizers, were taken as decision variables. RESULTS AND CONCLUSIONSThe results of the analysis showed that under the conventional agriculture scenario, paddy and maize cultivation was the preferred choice for profit maximizing farmers in the tank village. When chemical fertilizers were restricted, farmers abandoned paddy and maize cultivation. Chemical fertilizers were available in sufficient quantities, even without a subsidy, profits reduce only by 13.56%. Maximum returns from crop cultivation were reaped when chemical and organic fertilizers were available in sufficient quantities and a premium price for products cultivated with organic fertilizers is secured. The cost of restricting chemical fertilizer application is severe in agricultural systems where water is abundant. SIGNIFICANCEA policy environment that secures markets for chemical fertilizer free food products is needed to make cropping systems more financially and environmentally sustainable. Stringent restrictions on quantity limits on chemical fertilizers use can affect profitability of cropping systems with no significant gains in environmental quality.

Local rationality

A new behavioral concept, local rationality, is developed within the context of a simple heterogeneous-agent model with incomplete markets. To make savings decisions, agents forecast the shadow price of asset holdings. Absent aggregate uncertainty, locally rational agentsforecast shadow prices rationally, and thereby make optimal state-contingent decisions. They use adaptive learning to extend their forecasts to accommodate aggregate uncertainty. Over time the state evolves to an ergodic distribution near the economy’s restricted perceptions equilibrium. In a partial equilibrium environment we develop intuition for locally rational decision making, documenting an important hysteresis effect. General equilibrium dynamics are examined via a calibration exercise. Calibrated representative-agent RBC models induce low consumption volatility relative to the data. Extending the model by either incorporating adaptive learning or heterogeneous agents fails to alter this conclusion. Via the hysteresis effect, local rationality, which interacts heterogeneity and adaptive learning, significantly improves the model’s fit along this dimension.

An efficient reliability assessment approach for multiple energy systems based on shadow price

This paper presents a new efficient reliability assessment method for multiple energy systems (MES) based on shadow price (SP). The coupling and interaction of multiple energy flows are quantitatively described by the energy hub (EB) model. The shadow price theory can accelerate the calculations of optimal load shedding in the reliability assessment for MES. Large numbers of system states are generated by the fluctuations of renewable energy generation. These numerous system states can be evaluated by the shadow price theory instead of cumbersome optimization computations. The case study shows that the proposed SP approach can greatly improve the efficiency of MES.

Monetary valuation of unsorted waste: A shadow price approach

Improving the management of municipal solid waste (MSW) is fundamental to promote circular economy and sustainability. Unsorted waste involves negative environmental impacts which often are ignored in economic feasibility studies due to its difficult valuation. In this study the shadow price of unsorted waste using the directional distance function was estimated. This methodological approach also allowed us to compute eco-efficiency scores of a set of municipalities in the provision of MSW services. The empirical application focused on a sample of 119 Chilean municipalities. The results showed that the average shadow price of unsorted waste was 297.66 €/ton which means that the environmental cost of left waste as unsorted was 297.66 € per ton. A regression tree model illustrated that population density, tourism intensity and the generation of waste per capita significantly influenced the shadow price of unsorted waste. Moreover, it was illustrated that Chilean municipalities were very inefficient in the management of MSW since the average eco-efficiency score was 0.272. The findings from this study reveal that additional and alternative policies should be adopted to improve the management of MSW and increase its recycling rate.

What Are People Willing to Pay for Social Sustainability? A Choice Experiment among Dutch Consumers

A relatively large number of studies has shown that consumers are willing to pay more for products that are certified as being environmentally or socially responsible, but most of these studies focus on the willingness to pay (WTP) for environmental benefits, while insights into the WTP for social benefits are limited. More research in this area will shed light on consumer choices and help policymakers to better direct the food industry toward social sustainability. In this paper, we carry out a Discrete Choice Experiment among Dutch consumers to measure consumer WTP for five social sustainability benefits; (1) no child labor; (2) liveable wage and safe working environment; (3) project for the education of workers; (4) equal wages for men and women; and (5) freedom to join a trade union. The novelty of our research in comparison with previous studies is that we aim to differentiate the WTP for various social standards instead of estimating an overall WTP for fair-trade labels. In addition to average price premiums per social standard, our latent class models also give insight into heterogeneity in WTP, or more specifically, stated price premiums by different groups (or market segments) in society. The results suggest that substantial price premiums for social sustainability benefits may exist, which currently are not reflected in food prices. Including price premiums for market products that fully incorporate societal costs of those products, so-called true prices or shadow prices, will decrease consumer demand for less-sustainable products and will lead to a fairer and more sustainable economic system. Our results also show that the price premiums may vary substantially between the various categories of social sustainability benefits and across products and market segments. Further research on assessing the motivations behind consumer choices for more-sustainable products is crucial here, especially for campaigns aimed at enhancing their market shares.

Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period.

This paper is a case study of the impact of CO2 emissions target setting. We empirically investigate the targets set during the Kyoto Protocol period using a convex nonparametric least squares system, quantile regressions, and a comprehensive data set of 125 countries. Our findings reveal CO2 marginal abatement costs, which: (1) are significantly higher for target setting countries; (2) increase over the sample period; (3) and are an order of magnitude greater than the prevailing emissions pricing mechanisms. The results provide insights into the consequences of policies to curb unwanted by-products in a regulated system and shed light on the price efficiency of carbon markets. Furthermore, we contribute to the debate on emission reduction standard-setting and highlight the importance of shadow price estimates when regulating market instabilities in an emission trading scheme.

Pricing real-time stochastic storage operations

Pricing storage operation in the real-time market under demand and generation stochasticities is considered. A scenario-based stochastic rolling-window dispatch model is formulated for the real-time market, consisting of conventional generators, utility-scale storage, and distributed energy resource aggregators. We show that uniform pricing mechanisms require discriminative out-of-the-market uplifts, making settlements under locational marginal pricing (LMP) discriminative. It is also shown that the temporal locational marginal pricing (TLMP) that adds nonuniform shadow prices of ramping and state-of-charge to LMP removes the need for out-of-the-market uplifts. Truthful bidding incentives are also established for price-taking participants under TLMP. Revenue adequacy and uplifts are evaluated in numerical simulations.