Consideration of optimal commodity storage with different discount rates. Finding that, even with a lower discount rate than private storage, optimal government-financed storage may not narrow price fluctuations compared with optimal privately financed storage because a government has to choose a probability of buffer stock failure greater than zero to economize on storage costs that could conceivably become very large. There is no presumption that government financed storage would be larger, with narrower intervention bands and more stable prices, than with privately-financed storage. The welfare enhancing effect of government financed storage compared to private storage is therefore indeterminate.

The rapid growth of renewable solar and wind energy necessitates extensive, long-term energy storage solutions to stabilize the electric grid and address the intermittent nature of these sources. In the absence of cost-effective long-duration, large-scale (LDLS) energy storage, there is a risk of increased disruptive blackouts and brownouts as intermittent energy sources approach 50% of electricity generation. Our analysis underscores volumetric energy density as a pivotal determinant in LDLS energy storage solutions, which is particularly crucial during periods of diminished renewable resource availability, such as the rainy season. Despite emphasis on conventional electric batteries and mechanical storage technologies such as compressed air and pumped hydro for LDLS, their costs pose a significant obstacle to widespread adoption, especially in emerging economies. In this study, we present a groundbreaking approach to LDLS: on-demand electricity generation from carbon-neutral renewable oil, known as "green oil," leveraging Reliance’s innovative catalytic hydrothermal liquefaction (R-CAT-HTL) technology. Our investigation evaluated two distinct sources of green oil production: organic waste streams (e.g., municipal solid waste, agricultural-waste, etc.) and on purpose production of algal biomass. We demonstrate that burning renewable green oil to produce electricity offers a cost-effective solution for large-scale (GWh) long-duration (many days) energy storage, ensuring the stability, reliability, and resiliency of the electric grid. We also demonstrate that minimum 14 days, ideally 30 days energy storage is needed for continuous uninterrupted service, especially critical for manufacturing facilities. Through a meticulous levelized cost of storage (LCOS) analysis comparing green oil with other LDLS technologies reported in literature, we demonstrate the cost effectiveness of green oil. In this model, green oil serves as stored energy, functions akin to a battery and is efficiently converted into electricity through conventional reciprocating engines or next-generation more efficient turbines. Our findings suggest that green oil derived from diverse organic sources is the most economically viable option for GWh-scale storage, particularly when storage requirements extend beyond a single day. This research thus presents a transformative cost-effective solution to the pressing challenge of LDLS energy storage, accelerating a sustainable and resilient energy future.

In light of the events of 2020 and 2022, this study aims to examine the co-movements between the capital markets of the Netherlands (AEX), France (CAC 40), Germany (DAX 30), the United Kingdom (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Russia (IMOEX), and spot prices of crude oil (WTI), silver (XAG), gold (XAU), and platinum (XPT) from January 1, 2018 to December 31, 2022. The purpose of this analysis is to answer the following research question: (i) Did the events of 2020 and 2022 increase the shocks between stock markets and WTI, XAG, XAU, and XPT prices? The findings indicate that time series do not follow a normal distribution and are stationary. In response to the question of investigation, we found that during the Tranquil period, it was possible to verify the existence of 28 causal relationships (out of 110 possibilities). During the stress period, there was a very significant increase in the number of causal relationships between the market pairs under analysis (62 causal relationships out of 110 possibilities), including a relative increase in the influence of commodities on capital markets and capital markets on commodities. These findings show that during the events of 2020 and 2022, capital markets and commodities significantly accentuated their co-movements among themselves, indicating that alternative markets such as WTI, XAG, XAU, and XPT do not provide safe-haven properties. These results have implications for portfolio diversification during times of global economic uncertainty.

Gravity Energy Storage (GES) systems are recently being considered as a viable solution for storing intermittent renewable energy power, specifically in high curtailment zones. While a few studies have analyzed the material costs of GES systems, there is a paucity of literature on analyzing the socioeconomic costs of GES systems. This study analyzes the location-dependent costs of GES plants using a multi-factor spatial parameterization model for evaluating the existence of a point of minimum cost in a suburban mountainous geography. A case study of 500x500 points in a 50x50km2 area in the suburban area of Fukuoka city in Japan is performed. It is found that the cost of material transportation and transmission is more dominant in determining the position of an optimal cost location than factors of excavation and land costs. The position of the minima is also related to the principal urban area in that the line connecting the Center Business District (CBD) and suburban flat areas (line 1) is where the potential minima lie. The intersection point of an orthogonal to the line connecting the CBD with a substation nearest to the flat area with line 1, is the potential zone of minima location. The findings of this study are critical for urban energy planners and reveals how socioeconomic cost factors can aid in geolocation a suitable GES installation site.

The presence of electrical harmonics in low voltage networks causes many problems for customers, the most important of which is the decrease in the power quality beyond the permissible limits, which leads to a decrease in voltage for long periods, a decrease in power factor and a large losses in the electrical network due to the deformation of the electric waveform of voltage and current. The aim of this paper is to design an optimal passive filter and its optimal location to suppress the harmonic distortion in the distribution system that results from nonlinear loads. This filter will use single objective functions and multi objective functions that will minimize the proposed filter cost, the real power losses, total harmonic distortion "THD" and individual harmonic distortion "IHD". This will be done under the equality constraint of power balance and some inequality constraints such as filter parameters limits, quality factor limits, voltage limits, harmonic distortion limits. The optimal passive filter parameters and location will be calculated using the modern optimization techniques such jellyfish optimization technique. IEEE 33 bus radial system will be used for demonstrating results obtained by the proposed method.

The paper addresses the alternative policy options available to address the question of lives versus livelihood in an SIRD model augmented with a macroeconomic structure. An important contribution of the paper lies in designing the policy of lockdown dependent on the extent of the constraint on the health facilities. The paper supplements the literature with a less stringent version of the lockdown policy, viz. soft lockdown policy which is shown to be more attractive from a public policy standpoint and has actually been practised in many countries across the globe during the recent pandemic. Finally, the optimal policy derived on the basis of the level of lockdown and adjustment of the binding constraint on health facilities depends on the objective of policy makers contingent on the relative weights of lives versus livelihood.

In reality firms most often face negatively sloped demand curves. Then, for a given level of consumers’ surplus, levies on prices yield higher fiscal revenues than specific duties. Therefore, according to the prevailing view, the switch from unit to ad valorem taxation is supposed to generate more welfare; some even speak of an associated Pareto-improvement. However, this is not true because taxing prices merely transfers profits to the Treasury, while total rent remains unaffected. Since excise duties diminish the welfare gain in comparison with untaxed trade, an appropriately designed income tax allows all parties to benefit. Sales should be taxed only exceptionally.

Economy has various stages which have been described as economic cycle and due to that the circulatory movement observed, some have faster cycle some have longer cycle which depends on numbers of factors and from that inflation is an important segment. Various terms have been described for inflation, in simple meaning when price of different commodities have been raised compared to previous stage due to depreciation of currency having lesser purchasing power. Perception of people towards inflation and its impact is the main crux of the study, because how the people think about technical terms is vital matter. The present study is based on primary data collected from 277 respondents through questionnaire from the Gujarat state India. The perception has been analysed from four statement have been asked in Lickert’s five scale form. The one-way ANOVA has been used to test the hypotheses and it has been found from that in first statement regarding price of commodity once increase then it will not decrease due to inflation has significant difference with place, education and age of the respondents and in rest three statement no significant differences have been observed.

This paper provides an overview of the existing literature on the use of artificial intelligence (AI) in various fields, including economics, finance, mining, manufacturing, and innovation. The paper identifies the drivers and effects of AI deployment in the context of innovation and highlights the challenges and opportunities that arise from the use of AI. The studies reviewed in this paper cover various topics related to forecasting, including the impact of AI on professional skills, hybrid forecasting techniques for predicting commodity prices, and novel deep reinforcement learning algorithms for crude oil price forecasting. The paper’s contribution lies in its systematic and comprehensive approach to reviewing the literature, which allows for a better understanding of the impact of AI on various fields and the identification of strategies to address the challenges that arise from its deployment.

Motivated by the Blackorby-Schworm (1993) observation that market outcomes may differ from those originating in market-actor optimization, this paper claims that the number of banks in the market is larger than the number justified by bank profit maximization alone or in combination with bank depositor welfare maximization. This claim is made within the context of bilateral monopoly banks and intertemporal utility maximization by bank depositors. The basic policy implication towards bank population rationalization is a minimization of the deviation away from the optimal interest rate margin at every stage of the business cycle. It is meant to be an acyclical policy though the target of optimal bank population is attainable by active countercyclical policy as well. The nature of this policy issue makes the use of macroprudential measures imperative, jointly perhaps with a fiscal-monetary policy mix. A dynamic version of the model in a Cournot environment is akin to the modeling of Minsky's hypothesis of financial fragility.

In this paper, we develop a model in which a monopolistic firm manufactures and sells a digital product, by incorporating digital rights management (DRM), quality degradation of pirated products, and government copyright enforcement into the consumer’s utility function. We determine the monopolist’s optimal pricing strategies and the appropriate DRM protection level through mathematical deduction. Our results show that when the government copyright enforcement is moderate and the quality of pirated products is relatively high, implementing a DRM system is optimal for the monopolist. However, in most other cases, DRM-free is better for the monopolist. This result may explain why DRM is not very popular in some industries. Our results suggest that choosing the right price, focusing on content innovation, and weakening DRM protection may be a better strategy for firms now. The results also indicate that DRM-free may be more prominent in the digital music industry than in the software and video games industries.

In this paper, a portfolio analysis is carried out using the Sharpe ratio to identify the optimal market portfolio. The measure of investment performance with a Sharpe ratio is compared to results obtained with bootstrapped resamples of the Sharpe ratio. The results indicate that the choice of the market portfolio is highly affected by the uncertainty regarding the estimation of the expected returns and the variance-covariance matrix between the returns, that is, the estimation risk associated with these parameters.

Objective: The paper, specifically examines whether the recently formed Regional Comprehensive Economic Partnership (RCEP) can potentially facilitate minimising the constraints to renewable energy goods exports at the regional level in Asia. Data, Methodology and Findings: Using the panel data from 11 RCEP members from 2006 to 2014, this study has applied the ‘meta frontier stochastic gravity frontier’ methodology and confirms that the establishment of RCEP has the potential to improve trade in renewable energy commodities within the RCEP region. Policy Implications: The policy implication is that when countries work together, it will lead to enormous benefits for national, regional, and worldwide prospects of a more sustainable energy future. Practical Policy Implications: In terms of practical policy implications, the developed RCEP member countries should actively engage in promoting R&D activities and protecting intellectual property rights concerning renewable energy production, which are essential for countries to integrate with the world market and to lift the export frontiers of both the developed and developing RCEP member countries to reach the unrestricted export of renewable energy technology.

Following the seminal paper on Optimum Currency Areas (OCA) by Mundell (1961) a wealth of literature has been published on the business cycles synchronisation and its main determinants. This work provides a systematic review of this research field both at country-level synchronization and regional level. The paper aims to evaluate the contribution of the related literature’s methodologies to the measurement of the business cycle and the estimation of the level of synchronization. The discussion of the collected papers is expected to substantially assist researchers, practitioners, and policy makers keen to employ themselves in the area of business cycles synchronisation.

Non-compliance with tax obligations, particularly by wealthy taxpayers and large corporations, continues to represent a source of social injustice that fuels social instability, especially in developing countries. Understanding the strategies of tax evasion and avoidance is of critical importance. This article highlights five main strategies used by large corporations and wealthy taxpayers to avoid taxes, including tax havens, the underground economy, aggressive tax optimization, alternative financial markets, and crypto currencies. We also propose several actions to tackle global tax non-compliance, including prevention, peer reporting, active monitoring of compliance indicators and inter- national cooperation. These actions can be combined to achieve optimal results in reducing tax evasion and avoidance.

We offer an extensive analysis of the significance of information within the realm of Gaussian quadratic economies. We build upon the seminal papers of Morris and Shin (2002, 2007) and consider a signal game of incomplete information. Particularly, we question the suitability of partial transparency portrayed by fragmented information in addition to the private signal in terms of welfare effects. We can summarize our findings in two main points. First, fragmented information, in conjunction with a private signal, can reduce the reliance on public signals. Second, a conflicting effect arises between increasing full disclosure and increasing the precision of fragmented (semi-public) information when examining different complex scenarios, involving for example endogenous private information or imperfect correlated signals. For a critical threshold, an optimal communication strategy designed by fragmented information should be implemented whenever that kind of information is acquired at a high precision.

Bank capital requirements would entail large social costs if they made resource allocation suboptimal and banking services costly by unduly limiting the banks’ ability to lend. This paper considers three main factors that may make capital requirements relevant, namely, deposit insurance subsidies, stock valuation errors, and tax shields derived from debt financing. The theoretical model analyzes the combined effects of the three factors on the banks’ incentives to make fairly priced loans, which should also be socially optimal loans. A key finding is that the long-term cost of capital requirements is likely to be very small when deposit insurance is underpriced. Increased funding costs resulting from higher capital requirements are absorbed by shareholders of banks, rather than passed on to borrowers. Under some reasonable assumptions, higher capital requirements improve resource allocation by countervailing distortionary effects of deposit insurance subsidies. Short-term adjustment costs can still be large, but it should be relatively easy to mitigate the short-term effects.

We explore the connectedness and portfolio implications between Islamic and conventional bonds in global and GCC regions. We also compare which bonds performed better during our sample period. Unlike previous studies, we focus on Islamic bond markets compared to their conventional counterparts and highlight the GCC bonds (Islamic and conventional) in respect of global bonds. We apply the DCC-GJR-GARCH (1,1) method, the Sharpe ratio, and the portfolio implications strategy over the period from September 1, 2013, to February 23, 2022. Our time-varying results suggest that the relationship among all variables varies over time, but most of them are positive, suggesting that there are fewer diversification opportunities between Islamic and conventional bonds. Hedging and diversification benefits are found only in the limited period among these variables, especially between GCC bonds and global bonds, and global Sukuk and GCC Sukuk. The findings of risk-adjusted returns reveal that Islamic bonds outperform their conventional counterparts. Moreover, mixed results are found in the case of hedging costs, and the majority of the fund, based on optimal weights, should be invested in Islamic bonds. Our study endows investors and regulators in the global and GCC markets with new insights on how to shield their investments and the financial system from financial crises through a hedging strategy with Islamic finance.

In China, the land arrangement behavior of over 160 million rural-urban migrant workers is closely related to the optimal allocation of rural land resources and sustainable development of urban and rural areas. Although previous studies show that social capital affects migrant workers’ land arrangement behavior, few empirical studies reveal the relationship between them, and the corresponding interventions remain unclear. Using survey data collected in Henan Province, China, and a multinomial logit model, this study empirically analyzes the mechanism behind the impact of social capital on migrant workers’ land arrangement behavior from the perspective of social capital. Results illustrate that social capital has a significant impact on the land arrangement behavior of migrant workers. The behavior is significantly correlated with the scale of migrant workers’ urban social networks, the degree of urban social trust, and urban belonging. More social capital in urban areas indicates a higher tendency for migrant workers to abandon their land contracting rights and become permanent urban residents. This study reveals the mechanism of social capital affecting migrant workers’ land arrangement behavior and provides a reference for decision-making with respect to guiding migrant workers’ land management behavior for other countries facing similar social problems.