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This study proposes a novel distributed energy trading market model with a value distribution mechanism to optimize the allocation and transactions of distributed energy resources (DERs). The framework incorporates a direct load management approach via an electricity aggregator agent, simplifying market processes and reducing transaction costs. A Nash bargaining model is employed to design a fair and efficient value distribution mechanism, promoting equitable benefit allocation among participants. The model integrates stochastic programming to account for uncertainties in real-time load and DER output, enhancing its robustness and applicability in real-world scenarios. The proposed mechanism quantifies each DER's contribution using a market value contribution rate, serving as a foundation for the Nash bargaining model. This approach ensures individual rationality for both the aggregator and DERs while maximizing overall system benefits. Case studies validate the model's effectiveness, demonstrating improvements in resource utilization and fair benefit allocation. This research contributes to the advancement of distributed energy markets, offering valuable insights for designing efficient and equitable market structures, ultimately promoting grid stability, renewable energy adoption, and the development of more sustainable and flexible energy systems. [ABSTRACT FROM AUTHOR]

Amidst the global energy crisis in 2022, the Spanish and Portuguese governments introduced a subsidy to natural gas ("the Iberian exception"), attempting to lower the wholesale electricity market prices, with the understanding that gas-fired-combined cycle gas turbines (CCGTs) are price-setting technologies most of the time, directly or indirectly. The subsidy succeeded in lowering the market price but induced several other effects, such as (1) the increase in cleared energy in the Spanish market (mostly produced with gas), (2) the bias in the import/export cross-border position between Spain and France (Spain became a net exporter to France immediately), or (3) the consequent increase in congestion rents, which serve to lightly finance the subsidy, among other effects. This paper provides a framework for clustering the different effects based on the market participation phases: the subsidy, the market bidding, the market results, and surplus and rents. Moreover, this paper builds on the theoretical market models, with and without subsidies, and with and without cross-border exchanges. Based on the real market bids, the subsidies, and the generators' data, we reconstruct the supply and demand curves and simulate the counterfactual market scenarios in order to illustrate and quantify the effects. We highlight the quantification of the theoretical effect of the transfer of rents, from non-fossil to fossil fuel producers, induced by the gas subsidy. [ABSTRACT FROM AUTHOR]

This study proposes a novel distributed energy trading market model with a value distribution mechanism to optimize the allocation and transactions of distributed energy resources (DERs). The framework incorporates a direct load management approach via an electricity aggregator agent, simplifying market processes and reducing transaction costs. A Nash bargaining model is employed to design a fair and efficient value distribution mechanism, promoting equitable benefit allocation among participants. The model integrates stochastic programming to account for uncertainties in real-time load and DER output, enhancing its robustness and applicability in real-world scenarios. The proposed mechanism quantifies each DER’s contribution using a market value contribution rate, serving as a foundation for the Nash bargaining model. This approach ensures individual rationality for both the aggregator and DERs while maximizing overall system benefits. Case studies validate the model’s effectiveness, demonstrating improvements in resource utilization and fair benefit allocation. This research contributes to the advancement of distributed energy markets, offering valuable insights for designing efficient and equitable market structures, ultimately promoting grid stability, renewable energy adoption, and the development of more sustainable and flexible energy systems.

The subject under analysis pertains to the research field of semi-strong informational efficiency, which is established when the autocorrelation coefficient of stock prices during the event period being analyzed is zero. This indicates that stock price fluctuations before and after the mergers and acquisitions (M&A) event occur randomly. If the release of new information regarding mergers and acquisitions is followed by abnormal returns before or after the M&A event, then semistrong efficiency is not confirmed. There is a notable movement in stock prices one day prior to the official announcement of mergers and acquisitions, followed by a significant reverse movement for several subsequent days. This fluctuation in returns, along with market movements, exceeds 11% over a 10-day period. The day of the event is considered to be the day when the Board of Directors’ decision regarding the acquisition is made public. Firstly, we highlighted the purpose of the event study, namely, to identify the „residuals” of returns between actual returns (R_it) and expected returns during the period when M&A information was publicly disseminated. Furthermore, we reviewed elements of the literature that addressed event studies in general, with a focus on the impact of M&A on the capital market in particular. Subsequently, we outlined the research methodology and hypotheses, and the models used to identify return residuals. For analyzing the impact of M&A on market reactions, we used the market model and the Capital Asset Pricing Model (CAPM). Our empirical study estimates the impact on the stock price of Transilvania Bank resulting from the acquisitions of Volksbank Romania and Bancpost. Finally, we analyzed the impact of the merger between the Bucharest Stock Exchange (BVB) and SIBEX Sibiu. This paper offers a thorough empirical analysis of the economic advantages received by shareholders of acquiring companies after mergers and acquisitions. Our research findings show that, in general, acquiring firms yield positive abnormal returns. This stands in contrast to much of the existing literature, which indicates that, on average, there are losses (although not always statistically significant) associated with merger and acquisition transactions in developed countries.

Since FY2015, the Ministry of Economy, Trade and Industry (METI) and the Tokyo Stock Exchange (TSE) have jointly been selecting the excellent Japanese firms for their efforts for IT utilization as "Competitive IT Strategy Companies." This paper investigates and examines stock market reaction to the announcement of the selected Competitive IT Strategy Companies. We use an event study methodology with a market model on a sample selected in FY2018. Our empirical analysis shows a few reactions in stock returns around the event day. The cumulative average abnormal return (CAAR) during the event period [-5,0] is significantly positive at the 10% level. This result indicates that the stock market reaction may have started prior to the 2018's announcement date. The findings suggest that this study demonstrates the effectiveness of public policy program by METI and TSE, and assists investors in making wise decisions before reacting to the announcement of this annual program. [ABSTRACT FROM AUTHOR]

Multiple considerations must be evaluated with a new acquisition or license in biopharmaceutical business development. This case utilizes a fictional company, XYZ Biotech, to illustrate the quantitative considerations in evaluating an antibody-drug combination product in the metastatic breast cancer (mBC) space. The steps shown in this case also include the development of a market model to define the potential size of the market opportunity, a weighted benefit pricing model to evaluate the present price, and a net present value model to estimate projections from the product. The case also engages multiple qualitative considerations as part of the discussion section. It concludes by offering several nuanced questions at the end to stimulate discussion around the analysis, probe additional considerations needed for a business case, and analyze what other elements or issues would drive a decision. In the appendix is a short case summary of key facts for participants to develop solutions and share in class before reviewing the case narrative. [ABSTRACT FROM AUTHOR]

The study examined the effectiveness of the signaling theory and the efficient market hypothesis in Nigeria during the period of the COVID-19 pandemic which has been an underexplored investigation in the Nigerian capital market. The broad objective of the study was to assess how earning announcements could affect the stock prices of deposit money banks in Nigeria. Specifically, the study sought to analyse the trend of stock prices and examine the reactions of stock prices of quoted DMBs to earnings announcements during a pandemic period in Nigeria. The study employed secondary data from daily closing stock prices of 13 selected banks and the All Share Index (ASI) between 2019 and 2020, sourced from the Nigerian Stock Exchange. The Log-in model, Event-study methodology and the Augmented Dickey-Fuller (ADF) test were used to analyse the data. The eventstudy methodology employed the market model to estimate the expected returns and abnormal returns during the event window. For the weak form of the market efficiency test, ADF was used to test for the presence of unit roots in the time series. Findings from the study showed that 69.23% of banks' stocks in the Nigerian capital market had negative growth, while 30.77% had positive growth during the period. That abnormal returns around announcement days were not statistically significant as abnormal returns of banks that announced an increase or decrease in earnings were -0.01007 (- 0.00533) with t-stat values of -0.30355 (-0.16428) respectively. The implication of the findings is that investors could not earn cumulative abnormal returns during the event window and the abnormal returns of most of the banks had an inverse relationship with earnings announcements. Based on these findings, the study recommended, amongst others, that investors should avoid mispriced stocks while investing in index funds in order to earn market average returns and that regulatory authorities should monitor banks listed on the Nigerian stock exchange to guard against abuse of insider information to the detriment of investors. [ABSTRACT FROM AUTHOR]

Amidst the global energy crisis in 2022, the Spanish and Portuguese governments introduced a subsidy to natural gas (“the Iberian exception”), attempting to lower the wholesale electricity market prices, with the understanding that gas-fired-combined cycle gas turbines (CCGTs) are price-setting technologies most of the time, directly or indirectly. The subsidy succeeded in lowering the market price but induced several other effects, such as (1) the increase in cleared energy in the Spanish market (mostly produced with gas), (2) the bias in the import/export cross-border position between Spain and France (Spain became a net exporter to France immediately), or (3) the consequent increase in congestion rents, which serve to lightly finance the subsidy, among other effects. This paper provides a framework for clustering the different effects based on the market participation phases: the subsidy, the market bidding, the market results, and surplus and rents. Moreover, this paper builds on the theoretical market models, with and without subsidies, and with and without cross-border exchanges. Based on the real market bids, the subsidies, and the generators’ data, we reconstruct the supply and demand curves and simulate the counterfactual market scenarios in order to illustrate and quantify the effects. We highlight the quantification of the theoretical effect of the transfer of rents, from non-fossil to fossil fuel producers, induced by the gas subsidy.

Health Information Exchange (HIE) network allows securely accessing and sharing healthcare-related information among healthcare providers (HCPs) and payers. HIE services are provided by a non-profit/profit organizations under several subscription plans options. A few studies have addressed the sustainability of the HIE network such that HIE providers, HCPs, and payers remain profitable in the long term. However, none of these studies addressed the coexistence of multiple HIE providers in the network. Such coexistence may have a huge impact on the behavior of healthcare systems in terms of adoption rate and HIE pricing strategies. In addition, in spite of all the effort to maintain cooperation between HIE providers, there is still a chance of competition among them in the market. Possible competition among service providers leads to many concerns about the HIE network sustainability and behavior. In this study, a game-theoretic approach to model the HIE market is proposed. Game-theory is used to simulate the behavior of the three different HIE network agents in the HIE market: HIE providers, HCPs, and payers. Pricing strategies and adoption decisions are optimized using a Linear Programming (LP) mathematical model. Results show that the relation between HIEs in the market is crucial to HCP/Payer adoption decision specially to small HCPs. A small change in the discount rate proposed by a competitive HIE provider will highly affect the decision of HCP/payers to join the HIE network. Finally, competition opened the opportunity for more HCPs to join the network due to reduced pricing. Furthermore, collaborative HIEs provided better performance compared to cooperative in terms of profit and HCP adoption rate by sharing their overall costs and revenues. [ABSTRACT FROM AUTHOR]

Network slicing (NS) has emerged as a promising solution that enables network operators to slice network resources such as spectrum and bandwidth to adapt to different beyond 5G scenarios. This allows new operators to enter the market: the infrastructure provider (InP), who owns the infrastructure, and the mobile virtual network operator (MVNO), who may purchase a resource slice from the InP to provide a specific service to their end-users. To better deal with the resource allocation problem, efficient algorithms and methods have been done such as the auction model, bidding method, and game theory. This paper presents an upper-tier resource allocation based on game theory. This mechanism considers a single base station (BS) and multi MVNOs-users that share aggregated bandwidth radio access networks to maximize utilized BS resources. The proposed method takes both the bandwidth utilization of BS and the service requirements of MVNO users. Accordingly, the Game Theory solution takes two contradictory objectives: the InP aims to maximize its revenue while the MVNOs want to serve their users by paying the minimum amount. We prove that our proposal achieves an optimal solution from both InP and MVNOs' in terms of revenue and quality of service. [ABSTRACT FROM AUTHOR]

Focusing on the hedging-stock pricing research landscape, this research investigates the role of different futures hedging instruments, namely oil futures, gold futures, and VIX futures and the effect of net hedging benefits by employing them on oil price risk exposure to Asia- Pacific airline firms’ stock returns using the hedging-stock pricing model. This research examines 22 Asia-Pacific airline firms’ stock returns behaviour with monthly frequency data from 2010 to 2019. A complementary analysis approach using the fixed effect panel and quantile regressions are used to analyse the research model. The findings confirm the negative effects of oil price risk and the benefits of hedging oil price risk on airline stock returns, and the superiority of gold futures over oil futures and VIX futures as effective hedging instruments. The findings provide hedging insights to investors to manage equity investment against oil price risk. In the academic context, little is known about the benefits of cross-commodity hedging to reduce risk in equity investment and this work advances the hedging- stock pricing research. This research confirmed pairing of gold futures-airline stock produces an effective hedge. The equity investors could use cross-hedging strategy to enhance airline stock investment portfolio returns.

In wireless communication networks, the stock of spectrum, computing, storage and other resources at the edge was limited.The traditional decentralized and exclusive resource allocation resulted in weak resource reuse capability and low utilization rate.At the same time, it was difficult to ensure the fairness of resource sharing in the traditional resource scheduling process due to the lack of trust between the owners.First, a double auction model of computing and wireless communication resource joint management based on blockchain was proposed.In the model, a resource market was established, in which resource buyers and sellers allocated resources through double auctions.Secondly, blockchain was used to store the resource information of buyers and sellers to solve the mutual trust problem of all parties in the network.Finally, the experimental simulation was carried out to verify that the proposed model effectively improved the system performance and resource utilization efficiency.

Sweden historically pioneered many aspects of a modern market economy, hosting the first known share company, the first European credit notes, and the first central bank. Anders Chydenius's booklet Den nationella vinsten (The National Gain) was printed in 1765, 11 years before Adam Smith's The Wealth of Nations. Sweden was early in extending to women the rights to pursue professions and own businesses. Today, Sweden and its Nordic neighbours evince an unusual combination of high taxes and some of the freest economies in the world. Another characteristic feature is long‐standing trust, which facilitates investment and cooperation. It also allows for decentralised decision‐making, a characteristic feature of Nordic business management. Sweden's unusual high‐trust culture significantly affects economic activity. [ABSTRACT FROM AUTHOR]

In this paper, an empirical study has been conducted to document the effects of US sector-specific sanctions on publicly-traded firms listed on the Tehran Stock Exchange. The withdrawal of the US from JCPOA on May 8th, 2018 is considered the main event, and the GARCH (1, 1) model has been utilized along with the OLS estimation of a market model for the estimation of abnormal returns within 11 working days following the event. A multifactor statistical model of expected returns is also considered for controlling the potential effects of the changes in the foreign exchange rate and the risk-free rate of return on the abnormal returns of different firms. The potential effect of size, profitability, and leverage for each firm on the relationship between cumulative abnormal returns and being the target of sector-specific sanctions has been controlled. The results showed that the withdrawal of the US from JCPOA induces a two-day cumulative abnormal return of about -1% for the firms which operate in industries targeted by US sectoral sanctions compared to non-target firms. The effect remains significant for about two weeks. Similarly, the effect of Trump's victory in the presidential election in 2016 on targeted firms is estimated to be significant. Other events in which Trump has speculated about the chance of withdrawal from the JCPOA have no significant effect on the stock market.

Large-scale integration of new energy presents higher demands on power system regulation capacity. In order to give full play to the regulation function of split shaft gas-steam combined cycle units， it is urgent to explore and establish a safe， reliable， and stable power spot market participation mechanism. Firstly， the characteristics and applicability of different market mechanisms for split-shaft gas turbines at home and abroad are compared and analyzed. Secondly， a mechanism based on independent modeling for split-shaft gas turbines participating in power spot market according to the experience of power market construction in Zhejiang province is introduced in detail. The split-shaft gas turbines are modeled separately， and steam turbine output is determined by the gas turbine output， which puts an end to the dependence relationship between the gas turbines and steam turbines. The gas turbine bid is incorporated into the objective function， and the ratio of gas turbine and steam turbine output is incorporated into the constraint conditions， which solves the problem of the variable operation mode of split-shaft gas turbines. Then the measured data of Zhejiang spot market is analyzed to verify the rationality of the model design， control， and income index results. Finally， experience is summarized and provided for diversified generation entities to participate in mechanism design in the spot market.

This study extends the literature on the capital structure by examining the effect of firm specific and macroeconomic factors on probability of default using 2385 firm year observations of Non-financial firms listed on Pakistan Stock Exchange (PSX) for the period 1998 to 2021. This is the first study that used a large dataset to analyze the default risk of Pakistani listed non-financial companies. This study follows Bharat and Shumway (2008) methodology to calculate expected default probability, which is a simplified version of the Merton (1974) structural default model. Fixed effect model has been used for data analysis. The empirical results of firm specific variables show that growth, operating cash flow ratio, liquidity, and performance is negatively related with the probability of default while leverage and tangibility of assets are positively related with the probability of default. Size of the company has no relationship with the probability of default. Macroeconomic variables economic conditions measured by GDP growth rate and index return have negative while short term interest rate have positive impact on probability of default. This study may be beneficial to the managers of non-financial companies since it may help them become more aware of the consequences of default risk and may also help them build effective policies linked to managing default risk. The board of directors of non-financial companies can extract valuable information from this study which is required to conduct control measures related to default risk management. The study excluded financial firm because those have different capital structure as compared to non-financial firms. Further studies can also investigate the effect of firm-specific factors and macroeconomic factors in different sectors to check is there any difference in results on sector basis. [ABSTRACT FROM AUTHOR]

Purpose – The authors examine the impacts of corporate announcements on stock returns during the pandemic stress. Design/methodology/approach – The authors employ the event study methodology with the market model on a sample of 90 events (announcement and ex-date). Findings – The authors find that all the corporate announcements do not impact the stock returns in a similar pattern. While the bonus announcement, ex-bonus and ex-split events led to positive significant abnormal returns on the event date, the rights issue and stock-split announcements failed to influence the stock returns. The findings suggest that before making such announcements, the corporates should wait until the market recovers because even the positively impacting events result in negative market responses during pandemic stress. Practical implications – This study will guide the policymakers to stimulate share prices during such pandemics with the help of various corporate announcements. The investors will be assisted in understanding the stock market mechanism and making wise decisions before reacting to corporate actions during a pandemic or emergency period. While the policymakers are concerned with influencing the share prices, the investors are concerned with the composition of the risk-return parameters in their portfolio. This study will act as an essential investment tool for both. Originality/value – To the best of the authors’ knowledge, the authors conduct the first-ever study to examine the impacts of corporate announcements during a pandemic stress period that significantly contributes to the literature. The authors examine the announcement effects in India and accurately anticipate that this study will be a pioneer in this field. This study also paves the way for future researches in this area.

This paper is concerned with the multivariate extended skew-normal [MESN] and multivariate extended skew-Student [MEST] distributions, that is, distributions in which the location parameters of the underlying truncated distributions are not zero. The extra parameter leads to greater variability in the moments and critical values, thus providing greater flexibility for empirical work. It is reported in this paper that various theoretical properties of the extended distributions, notably the limiting forms as the magnitude of the extension parameter, denoted τ in this paper, increases without limit. In particular, it is shown that as τ→−∞, the limiting forms of the MESN and MEST distributions are different. The effect of the difference is exemplified by a study of stockmarket crashes. A second example is a short study of the extent to which the extended skew-normal distribution can be approximated by the skew-Student.

Purpose - With a sample of 22 banks, this study examines the significance of the news contents about the privatization of two public sector banks in India. New information does impact the stock markets. This study provides evidence on how the privatization of public sector banks impacted the returns of the Indian banking sector. Design/methodology/approach - This study employs the standard event study methodology with the market model for estimating the normal returns. Findings - The statistical results indicate that while the private sector banks experienced positive average abnormal returns on the event day, the cumulative effect of the announcement is negatively significant for both private and public sector banks. The statistical results also provide evidence of information leakage, with significant results before the announcement date. The shorter event windows analysis exhibits significant positive returns in the 5-days [−2, +2] window for the private sector banks and the entire sample, signifying a positive short-term impact on the private sector banks. Originality/value - The event study literature captures the impacts of many events. However, to the best of our knowledge, the impacts of the privatization of the Indian public sector banks have never been examined using the event study methodology. Hence, this study anticipates being the first-ever study to fill this gap and extend the available literature in finance. In addition, although we provide Indian evidence, future studies may be oriented to capture cross-country impacts.

This paper aims to determine the reaction of the Algerian Stock Exchange (SGBV) to dividend announcements by a sample of companies listed on the Algiers Stock Exchange, and for a fixed period 2018-2019. To reach the goal, the event's methodology was relied upon to study the effect of the dividend announcement on the share price surrounding forty days of the announcement. Additionally, the stock price reaction is determined for the dividend announcement. The results of the research indicate that stock prices are moving up significantly after dividend announcements, and downward after the date of loss of the right to claim dividends. It was statistically disclosed using abnormal return (AR) from the market model. The results emphasize the theory of dividend distribution, because dividend announcements have a significant impact on stock prices. [ABSTRACT FROM AUTHOR]

The novel Covid-19 virus has changed the dynamics of 'flight to safety' investment for various economies. Thus, the hedging ability of the stocks must be revisited in the scenario of this pandemic. For this purpose, specifically understanding the importance of a semi-strong form of an efficient market hypothesis is important. This was to observe the speed at which the markets react to the news announcement, and how rapidly they absorb new information to regain thier position in the market. Hence, this study conducts an event study analysis on Pakistan's emerging market to detect the financial and non-financial stock price reactions towards the lockdown announcement, following the spread of Covid-19 in Pakistan. The daily data on the KSE-100 index for thirty different industries, comprising of ninety firms, spanning from December 12, 2019, till June 7, 2020, was collected and analyzed. The abnormal returns were recorded to be at around 21 [−10. +10] and 41 days [−20, +20] event window, around the day of the lockdown announcement. These abnormal returns were obtained through the market model regression. The data collected implied that most of the industries were stable and behaved well before the event day, while the affected sectors recovered fairly quickly. Therefore, it has been affirmed that Pakistan's equity portfolios are informationally efficient, and can benefit the investors during a pandemic. [ABSTRACT FROM AUTHOR]

In wireless communication networks, the stock of spectrum, computing, storage and other resources at the edge was limited. The traditional decentralized and exclusive resource allocation resulted in weak resource reuse capability and low utilization rate. At the same time, it was difficult to ensure the fairness of resource sharing in the traditional resource scheduling process due to the lack of trust between the owners. First, a double auction model of computing and wireless communication resource joint management based on blockchain was proposed. In the model, a resource market was established, in which resource buyers and sellers allocated resources through double auctions. Secondly, blockchain was used to store the resource information of buyers and sellers to solve the mutual trust problem of all parties in the network. Finally, the experimental simulation was carried out to verify that the proposed model effectively improved the system performance and resource utilization efficiency. [ABSTRACT FROM AUTHOR]

To characterize any standard market, generally, we need a model consisting of at least two equations, one of which describes the pattern of demand for the relevant goods or resources, and the other the pattern of supply. In the simplest case, when all the factors, except price, affecting demand and supply are fixed, and the market is standard, we have the following version of the model:, where and functions of demand and supply depend on price. When the specific type of these functions is known, it is easy to determine the equilibrium point of the market (if it exists) using the following equation:. As a rule, in most cases, specific types of and functions are unknown, and we have to resort to econometric modeling to estimate them. To accomplish this, we must 1) transform the above-mentioned system into a model comprising of regression equations and 2) obtain, data for the variables, and included in the model. The first requirement, transformation into a regression system, is easy to accomplish by including the random error terms, and, with the expected value equal to zero, into the corresponding equations:. The second requirement--obtaining the observation data for, and variables--is much harder to fulfill. The difficulty is that in market model analysis, the separate and values of supply and demand are rarely available, except when research is specifically done to examine market subjects. As a rule, the existing statistical system gives information on price values together with the variable--the volume of actual sales, but not what the demand, and the supply were under different price conditions. In such cases, if no additional information is available, the demand and supply functions of the market model are considered unidentifiable. The widely used standard approach to solving this problem involves changing the specification of the model by including additional explanatory variables in the equations and making an assumption that observed values, together with their respective prices, correspond to the point of market equilibrium, i.e., we have the following equations:. This article proposes a different method to estimate the market model consisting of regression equations. It takes into account the specifics of the market mechanism and makes it possible to fully or partially identify the functions of supply and demand, even when the only data available is on the price and the volume of sales. Unlike the traditional approach, the proposed method is based on the assumption that not every pair of price and sales volume included in the data sample, corresponds to the point of market equilibrium. The estimation of equations of this model involves a two-step process. First, using the sample of data on price and sales volume, the sales line is estimated, and the point of its maximum, which corresponds to the point of market equilibrium, is defined. Then, given the location of the equilibrium point, using a particular technique, subsamples that define demand and supply are identified from the total sample, and their respective equations are constructed. The article demonstrates how to apply this method, using the Georgian labor market as an example. The employment line equation estimated using quarterly data on real wages and employment in 2010-2021 showed that the labor market in Georgia was in equilibrium in the third quarter of 2013. On the basis of this information, we used data from the first quarter of 2010 through the third quarter of 2013 to estimate the labor supply function, and the rest of the data was applied to estimate the labor demand function. Based on these estimates, a 100 GEL increase in real wages in Georgia during the analyzed period caused a 5.2% increase in labor supply and a 5.6% decrease in demand for labor. [ABSTRACT FROM AUTHOR]

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The avenue to find a balanced assessment of systemic financial institutions needs the integration of macro and micro granular datasets. This paper investigates how macroeconomic shocks affect systemic risk through several transmission channels. Employing Indonesia datasets over 2008–2019, we regressed three market models: CoVaR, MES, and SRISK using fixed effect, random effect, GARCH(1,1), and finite mixture models. The findings show that stock beta, market index, and exchange rate volatility amplify the systemic risk while the liquidity spread outcome varies due to different of model variables and the deepness of the country's financial market. We propose a practical systemic risk assessment framework and samples of technical integration to capture the overall risk endogenously and externally expose the systemically important financial institutions. [ABSTRACT FROM AUTHOR]

Research aims: COVID-19 Pandemic happens all over the world. Pandemic impact hits almost all elements of life, one of the affected real sectors is finance especially the stock market. This research is aimed to present the reaction of the equity market in Indonesia towards the COVID-19 pandemic Design/Methodology/Approach: The research method that is used is the study to examine market reaction towards the pandemic and abnormal return around the occurrence by using two methods; mean-adjusted abnormal return and market model. Research findings: From the research conducted over the 10 indicators of the stock market index in Indonesia, it is concluded that 8 industrial sectors that have tenacious reaction toward the COVID-19 pandemic hit in Indonesia, where it is also found that the agriculture sector; basic and chemical industry; miscellaneous, consumer goods; property and real estate; transport and infrastructure; finance; trade, service, and investment, give stronger reactions compared with mining and manufacture. Theoretical contribution/Originality: Researches about the stock market reaction to the non-economy phenomenon have already been carried out, but the research that is specifically done to study sectoral index reaction towards the non-economy occurrences is still wide open to doing for deeper research. Practitioner/Policy implication: This research can be important information for investors to understand the behavior of stock market efficiency in Indonesia in making decisions of investment Research limitation/Implication: Non-economy event that becomes the subject of research is the COVID-19 pandemic that appeared and escalated fast all over the world. The researcher conducted the research and presented it as quickly as possible since the time is limited. It is meant to show a systematic and scientific thinking framework in addressing the non-economy events, but still in the context of reliability on the result of research to the same topic about the COVID-19 effect in other countries.

This paper is concerned with the multivariate extended skew-normal [MESN] and multivariate extended skew-Student [MEST] distributions, that is, distributions in which the location parameters of the underlying truncated distributions are not zero. The extra parameter leads to greater variability in the moments and critical values, thus providing greater flexibility for empirical work. It is reported in this paper that various theoretical properties of the extended distributions, notably the limiting forms as the magnitude of the extension parameter, denoted τ in this paper, increases without limit. In particular, it is shown that as τ → − ∞ , the limiting forms of the MESN and MEST distributions are different. The effect of the difference is exemplified by a study of stockmarket crashes. A second example is a short study of the extent to which the extended skew-normal distribution can be approximated by the skew-Student. [ABSTRACT FROM AUTHOR]

In England, care to support people living at home is largely commissioned by local authorities (statutory organisations with responsibility for social care in specific localities) from non‐statutory home‐care providers (for‐profit, not‐for‐profit, voluntary). This paper explores how managers of these services perceive commissioning arrangements and their impact on home‐care providers, the care workforce and service users. Little formal research of providers' experiences of working with local authorities in a commissioning model is available. A qualitative study employed semi‐structured telephone interviews with 20 managers of for‐profit home‐care providers from 10 selected local authority areas in England. Data were analysed using thematic analysis to identify main and subsidiary themes. Home‐care providers reported operating in a complex and changeable partnership with commissioners, characterised by: (a) relationships ranging from transactional to collaborative, (b) providers expressing a strong sense of public service motivation, (c) commissioning practices that were complex to negotiate, time‐consuming and overly prescriptive, (d) frequent changes in commissioning practices and a perceived lack of strategic planning, which were reported as contributing to uncertainty and tension for providers and confusion for service users. Attempting to operate a market model with tightly prescribed contracts is likely to be unsustainable. An alternative approach based on a collaborative model of joint responsibility for providing home care is recommended drawing on a conceptual framework of principal–steward relationships in contracting. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomika is the property of Society of Economists 'Ekonomika' and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under current conditions the alternative energy development and bioenergy fuels use issues are actual for an energy-dependent country. The main strategic goals of the state in the national bioenergy fuels production which make it possible to determine the main advantages and priorities of the industry or market are presented in the research paper. Econometric models of Ukraine bioethanol market development and functioning have been studied and presented. Correlations between bioethanol market variables have been established, regression equations of five models of this market have been obtained and their adequacy analysis was carried out. Graphic representation of the bioethanol market was presented, and the main indicators that affect the development of this market were identified in the process of bioethanol market variables study. Economic and mathematical justification and correlation matrix using software statistical environment - "R", while least squares method and the stepwise regression method were used in the process of bioethanol market models design and researching. The purpose of the study is to analyze bioethanol market models in Ukraine, biofuel exchange development and implementation. Ukrainian bioenergy fuels market is quite problematic and has a number of obstacles and shortcomings, which negatively affect this market infrastructure. The state regulation should be performed in order to regulate relations at the biofuel market. Electronic trading platforms in the form of bioenergy fuels exchange implementation is one of the fundamental bioenergy fuels market state regulation directions. Bioenergy fuels exchange functioning advantages are revealed during the research. Biofuel exchange structure as one of the main tools for between producers and consumers of biofuels relationship settling has been presented. The development of the biofuel market in Ukraine is extremely relevant and needs further research, especially in the process of state regulation and state support in this area.

The scope of this paper is to make an empirical analysis regarding the market model introduced by the American economist Wiliam Sharpe (1963), a research developed based on the idea of portfolio simplification. In this paper, we tested the ability to predict a market model for shares issued by Petrom S.A. company. The result shows that the market model can be used to predict the profitability of a security, the forecast errors being insignificant. The results of this paper can help the investors to decide when to invest. [ABSTRACT FROM AUTHOR]

Proton exchange membrane water electrolysis (PEMWE) is a key technology for future sustainable energy systems. Proton exchange membrane (PEM) electrolysis cells use iridium, one of the scarcest elements on earth, as catalyst for the oxygen evolution reaction. In the present study, the expected iridium demand and potential bottlenecks in the realization of PEMWE for hydrogen production in the targeted GW a−1 scale are assessed in a model built on three pillars: (i) an in-depth analysis of iridium reserves and mine production, (ii) technical prospects for the optimization of PEM water electrolyzers, and (iii) PEMWE installation rates for a market ramp-up and maturation model covering 50 years. As a main result, two necessary preconditions have been identified to meet the immense future iridium demand: first, the dramatic reduction of iridium catalyst loading in PEM electrolysis cells and second, the development of a recycling infrastructure for iridium catalysts with technical end-of-life recycling rates of at least 90%. [Display omitted] • First feasibility-study on iridium supply and demand for hydrogen economy. • Linking iridium production and recycling with technical prospects for catalyst loading. • Providing a technology specific iridium demand model for PEM water electrolysis. • Scenario analysis of large-scale PEM water electrolysis future market development. [ABSTRACT FROM AUTHOR]

In order to analyze simple and complex models of market, market equilibrium and market efficiency, this article considers a more complex and realistic market model with the existence of public goods. This topic is the subject of attention of many scientists, but only recently has it been possible to apply these models on real life situations and verify their correctness and justifiably. To understand the problems of the existence of public goods on the competitive market better, first one should first understand the nature and characteristics of public goods. Having derived Pareto efficiency criterion with the presence of public goods, the article attempts to answer the question whether there is an economy where competitive behavior may result in an efficient solution.