Search results for: commodity prices

Authors: Ursachi Andrei

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The Smart Grid Simulator is a computer software based on advanced algorithms which has as the main purpose to lower the energy bill in the most optimized price efficient way as possible for private households, companies or energy providers. It combines the energy provided by a number of solar modules and wind turbines with the consumption of one household or a cluster of nearby households and information regarding weather conditions and energy prices in order to predict the amount of energy that can be produced by renewable energy sources and the amount of energy that will be bought from the distributor for the following day. The user of the system will not only be able to minimize his expenditures on energy fractures, but also he will be informed about his hourly consumption, electricity prices fluctuation and money spent for energy bought as well as how much money he saved each day and since he installed the system. The paper outlines the algorithm that supports the Smart Grid Simulator idea and presents preliminary test results that support the discussion and implementation of the system.

Keywords: smart grid, sustainable energy, applied science, renewable energy sources

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Authors: Iman Atighi, Jalal Soleimannejad, Reza Pourjafarabadi, Saeid Moradpour

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In the past, we could increase profit by increasing product prices. But in the new decade, a competitive market does not let us to increase profit with increased prices. Therefore, the only way to increase profit will be to reduce costs. A significant percentage of production costs are the maintenance costs, and analysis of these costs could achieve more profit. Most maintenance strategies such as RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance), PM (Preventive Maintenance) and etc., are trying to reduce maintenance costs. In this paper, decreasing the maintenance costs of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GeG) was examined by using of MTBF (Mean Time Between Failures) and MTTR (Mean Time To Repair) analyses. These analyses showed that instead of buying new machines and increasing costs in order to promote capacity, the improving of MTBF and MTTR indexes would solve capacity problems in the best way and decrease costs.

Keywords: GeG company, maintainability, maintenance costs, reliability-center-maintenance

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Authors: É. Kónya, E. Szabó, I. Bata-Vidács, T. Deák, M. Ottucsák, N. Adányi, A. Székács

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Spice paprika is a major spice commodity in the European Union (EU), produced locally and imported from non-EU countries, reported not only for chemical and microbiological contamination, but also for fraud. The effective interaction between producers’ quality management practices and government and EU activities is described on the example of spice paprika production and control in Hungary, a country of leading spice paprika producer and per capita consumer in Europe. To demonstrate the importance of various contamination factors in the Hungarian production and EU trade of spice paprika, several aspects concerning food safety of this commodity are presented. Alerts in the Rapid Alert System for Food and Feed (RASFF) of the EU between 2005 and 2013, as well as Hungarian state inspection results on spice paprika in 2004 are discussed, and quality non-compliance claims regarding spice paprika among EU member states are summarized in by means of network analysis. Quality assurance measures established along the spice paprika production technology chain at the leading Hungarian spice paprika manufacturer, Kalocsai Fűszerpaprika Zrt. are surveyed with main critical control points identified. The structure and operation of the Hungarian state food safety inspection system is described. Concerted performance of the latter two quality management systems illustrates the effective interaction between internal (manufacturer) and external (state) quality control measures.

Keywords: spice paprika, quality control, reporting mechanisms, RASFF, vulnerable points, HACCP

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Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu

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Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.

Keywords: earnings call script, random forest, sentiment analysis, stock price prediction

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Authors: Iman Atighi, Jalal Soleimannejad, Ahmad Akbarinasab, Saeid Moradpour

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In the past, we could increase profit by increasing product prices. But in the new decade, a competitive market does not let us to increase profit with increase prices. Therefore, the only way to increase profit will be reduce costs. A significant percentage of production costs are the maintenance costs, and analysis of these costs could achieve more profit. Most maintenance strategies such as RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance), PM (Preventive Maintenance) etc., are trying to reduce maintenance costs. In this paper, decreasing the maintenance costs of Concentration Plant of Golgohar Company (GEG) was examined by using of MTBF (Mean Time between Failures) and MTTR (Mean Time to Repair) analyses. These analyses showed that instead of buying new machines and increasing costs in order to promote capacity, the improving of MTBF and MTTR indexes would solve capacity problems in the best way and decrease costs.

Keywords: Golgohar Iron Ore Mining and Industrial Company, maintainability, maintenance costs, reliability-center-maintenance

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Authors: Aydin Sipahioglu, Gokhan Celik

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Helicopter routing problem (HRP) is finding good tours for helicopter so as to pick up and deliver personnel or material among specified nodes, mutually. It can be encountered in case of being lots of supply and demand points for different commodities and requiring delivering commodities with helicopter. For instance, to deliver personnel or material from shore to oil rig is a good example. In fact, HRP is a branch of vehicle routing problem with pickup and delivery (VRPPD). However, it has additional constraints such that fuel capacity, performance of helicopter in different altitude and temperature, and the number of maximum takeoff and landing allowed. This kind of pickup and delivery problems can be classified into 3 groups, basically. 1-1 (one to one), M-M (many to many) and 1-M-1 (one to many to one). 1-1 means each commodity has only one supply and one demand point. M-M means there can be more than one supply and demand points for each kind of commodity. 1-M-1 means commodities at depot are delivered to demand points and commodities at customers are delivered to depot. In this case helicopter takes off from its own base, complete its tour and return to its own base. In this study, we define 1-M-M-1 type HRP. That means helicopter takes off from its home base, deliver commodities among the nodes as well as between depot and customers and return to its home base. These problems have NP-hard nature. Therefore, obtaining a good solution in a reasonable time is not easy. In this study, a model is offered for 1-M-M-1 type HRP. It is shown on small scale test instances that the model can find the optimal solution.

Keywords: helicopter routing problem, vehicle routing with pickup and delivery, integer programming

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Authors: Kara Gianina D. Rosas, Jade Emily L. Tong

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This study assesses the vulnerability of households to food price shocks. Using the Philippines as a case study, the researchers aim to understand how such shocks can cause food insecurity in different types of households. This paper measures the impact of actual food price changes during the food crisis of 2006-2009 on poverty in relation to their spatial location. Households are classified as rural or urban and agricultural or non-agricultural. By treating food prices and consumption patterns as heterogeneous, this study differs from conventional poverty analysis as actual prices are used. Merging the Family, Income and Expenditure Survey (FIES) with the Consumer Price Index dataset (CPI), the researchers were able to determine the effects on poverty measures, specifically, headcount index, poverty gap, and poverty severity. The study finds that, without other interventions, food inflation would lead to a significant increase in the number of households that fall below the poverty threshold, except for households whose income is derived from agricultural activities. It also finds that much of the inflation during these years was fueled by the rise in staple food prices. Essentially, this paper aims to broaden the economic perspective of policymakers with regard to the heterogeneity of impacts of inflation through analyzing the deeper microeconomic levels of different subgroups. In hopes of finding a solution to lessen the inequality gap of poverty between the rural and urban poor, this paper aims to aid policymakers in creating projects targeted towards food insecurity.

Keywords: poverty, food inflation, agricultural households, non-agricultural households, net consumption ratio, urban poor, rural poor, head count index, poverty gap, poverty severity

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Authors: Vaishali Sharma, Anirbid Sircar

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Energy is one of the most eminent and fundamental strategic commodity, scarcity of which may poses great impact on the functioning of the entire commodity. According to the present study, the estimated reserves of gas in India as on 31.03.2015 stood at 1427.15 BCM. It is expected that the gas demand is set to grow significantly at a CAGR of 7% from 226.7 MMSCMD in 2012-13 to 713.5 MMSCMD in 2009-30. To bridge the gap between the demand and supply of energy, the interest towards the exploration and exploitation of unconventional resources like – Shale gas, Coal bed methane, Gas hydrates, tight gas etc has immensed. Nowadays, Shale gas prospects are emerging rapidly as a promising energy source globally. The United States of America (USA) has 240 TCF of proved reserves of shale gas and presently contributed more than 17% of total gas production. As compared to USA, shale gas production in India is at nascent stage. A resource potential of around 2000 TCF is estimated and according to preliminary data analysis, basins like Gondwana, Cambay, Krishna – Godavari, Cauvery, Assam-Arakan, Rajasthan, Vindhyan, and Bengal are the most promising shale gas basins. In the present study, the careful evaluation of Cambay Shale (Indian Shale) properties like geological age, lithology, depth, organically rich thickness, TOC, thermal maturity, porosity, permeability, clay content, quartz content, Kerogen type, Hydrocarbon window etc. has been done. And then the detailed comparison of Indian shale with USA shale will be discussed. This study investigates qualitative and quantitative nature of potential shale basins which will be helpful from exploration and exploitation point of view.

Keywords: shale, shale gas, energy source, lithology

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Authors: Benbya Hind, Belbaly Nassim

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Markets and communities are often cast as alternative forms of knowledge sharing, but an open question is how and why people dynamically transition between them. To study these transitions, we design a technology that allows geographically distributed participants to either buy knowledge (using virtual points) or request it for free. We use a data-driven, inductive approach, studying 550 members in over 5000 interactions, during nine months. Because the technology offered participants choices between market or community forms, we can document both individual and collective transitions that emerge as people cycle between these forms. Our inductive analysis revealed that uncertainties endemic to knowledge sharing were the impetus for these transitions. Communities evoke uncertainties about knowledge sharing’s costs and benefits, which markets resolve by quantifying explicit prices. However, if people manipulate markets, they create uncertainties about the validity of those prices, allowing communities to reemerge to establish certainty via identity-based validation.

Keywords: knowledge sharing, communities, information technology design, transitions, markets

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Authors: Monica Dantas

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At what socio-economic costs can the food industry offer products at low prices? This research seeks to understand and to explore how we attribute competence and meaning, what enables the outcomes of agriculture and what institutions provides validation regarding food production. This study objective is to explain and interpret conditions of the present state of agriculture in Brazil centring on two distinct segments, agribusiness and family farming, as the Brazilian, rapidly changing political environment unfolds. The approach is grounded in multidisciplinary literature drawing from the politics of development, the sociology of food, the sustainability framework and the conceptual differences between agribusiness and family farming regarding the innate purpose of the two segments. In addition, a quantitative portion of the research includes secondary data analysis from statistical measurements, economic indicators, federal budget information, and census data to compare the two segments, conveying a general snapshot of the conditions investigated. The results raised questions about the perceived image of the success of agribusiness, against some contradicting economic checks and balances. Analyzing how public funds are invested in agriculture shed light on what can enable or undermine the development of food systems in Brazil. It also revealed how politics, ideology, and corporations might influence the Brazilian Federal. In the 2000-2018 observed timeline of annual federal spending on agriculture in Brazil, there is variation in the amount invested in family farming that seems to 'coincide' with the ideological direction of the federal government in power. It was also observed that significant changes in the institutional framework and financial support either promoted or purposely undermined family farming importance using public institutions to validate support for agribusiness.

Keywords: food politics, sustainability, family farming, food system, public budget

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Authors: Yusuf Seedat

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The necessity to understand global financial markets has increased following the unfortunate spread of the recent financial crisis around the world. Financial markets are considered to be complex systems consisting of highly volatile move-ments whose indexes fluctuate without any clear pattern. Analytic methods of stock prices have been proposed in which financial markets are modeled using common network analysis tools and methods. It has been found that two key components of social network analysis are relevant to modeling financial markets, allowing us to forecast accurate predictions of stock prices within the financial market. Financial markets have a number of interacting components, leading to complex behavioral patterns. This paper describes a social network approach to analyzing financial markets as a viable approach to studying the way complex stock markets function. We also look at how social network analysis techniques and metrics are used to gauge an understanding of the evolution of financial markets as well as how community detection can be used to qualify and quantify in-fluence within a network.

Keywords: network analysis, social networks, financial markets, stocks, nodes, edges, complex networks

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Authors: Chomba Kalunga

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Many developing countries have a rich endowment of natural resources. Yet, amidst that wealth, living standards remain poor. At the same time, international markets have been surged with an increase in copper prices in the last twenty years. This is a presentation of the findings on the causal economic impact of Zambia’s copper mines, a country located in sub-Saharan Africa endowed with vast copper deposits on living standards using household data from 1996 to 2010, exploiting an episode where the copper prices on the international market were rising. Using an Instrumental Variable approach and controlling for constituency-level and microeconomic factors, the results show a significant impact of copper production on living standards. After splitting the constituencies close to and far away from the nearest mine, the results document that constituencies close to the mines benefited significantly from the increase in copper production, compared to their counterparts through increased levels of employment. Finally, the results are not consistent with the natural resource curse hypothesis; findings show a positive causal relationship between the presence of natural resources and socioeconomic outcomes in less developed countries, particularly for constituencies close to the mines in Zambia. Some key policy implications follow from the findings. The finding that increased copper production led to an increase in employment suggests that, in Zambias’ context, policies that promote local employment may be more beneficial to residents. Meaning that it is government policies that can help improve the living standards were government needs to work towards making this impact more substantial.

Keywords: copper prices, local development, mining, natural resources

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Authors: R. T. Aggangan

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Woodfuels continue to be a major component of the energy supply mix of the Philippines due to increasing demand for energy that are not adequately met by decreasing supply and increasing prices of fuel oil such as liquefied petroleum gas (LPG) and kerosene. The Development Academy of the Philippines projects the demand of woodfuels in 2016 as 28.3 million metric tons in the household sector and about 105.4 million metric tons combined supply potentials of both forest and non-forest lands. However, the Revised Master Plan for Forestry Development projects a demand of about 50 million cu meters of fuelwood in 2016 but the capability to supply from local sources is only about 28 million cu meters indicating a 44 % deficiency. Household demand constitutes 82% while industries demand is 18%. Domestic household demand for energy is for cooking needs while the industrial demand is for steam power generation, curing barns of tobacco: brick, ceramics and pot making; bakery; lime production; and small scale food processing. Factors that favour increased use of wood-based energy include the relatively low prices (increasing oil-based fuel prices), availability of efficient wood-based energy utilization technology, increasing supply, and increasing population that cannot afford conventional fuels. Moreover, innovations in combustion technology and cogeneration of heat and power from biomass for modern applications favour biomass energy development. This paper recommends policies and strategic directions for the development of the woodfuel industry with the twin goals of sustainably supplying the energy requirements of households and industry.

Keywords: biomass energy development, fuelwood, households and industry, innovations in combustion technology, supply and demand

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Authors: András Medve, Katalin Szabad, István Patkó

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According to the International Energy Association the previous principles of the energy sector should be reassessed, in which renewable energy sources have a significant role. We might witness the exchange of roles of countries from importer to exporter, which look for the main resources of market needs. According to the World Energy Outlook 2013, the duration of high oil prices is exceptionally long in the history of the energy market. Forecasts also point at the expected great differences between the regional prices of gas and electric energy. The energy need of the world will grow by its third. two thirds of which will appear in China, India, and South-East Asia, while only 4 per cent of which will be related to OECD countries. Current trends also forecast the growth of the price of energy sources and the emission of glasshouse gases. As a reflection of these forecasts alternative energy sources will gain value, of which geothermic energy is one of the cheapest and most economical. Hungary possesses outstanding resources of geothermic energy. The aim of the study is to research the environmental effects of geothermic energy and the opportunities of its exploitation in Hungary, related to „Horizon 2020” project.

Keywords: sustainable energy, renewable energy, development of geothermic energy in Hungary

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Authors: A. Hol

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Even in the well developed countries like Australia, Small to Medium Farmers do not often have the power over the market prices as they are more often than not set by the farming agents. This in turn creates problems as farmers only get to know for how much their produce has been sold for by the agents three to four weeks after the sale has taken the place. To see and identify if and how peri-urban Sydney farmers could be assisted, carefully selected group of peri-urban Sydney farmers of the stone fruit has been interviewed. Following the case based interviews collected data was analyzed in detail using the Scenario Based Transformation principles. Analyzed data was then used to create a most common transformation case. The case identified that a mobile web based system could be develop so that framers can monitor agent earnings and in turn gain more power over the markets. It is expected that after the system has been in action for six months to a year, farmers will become empowered and they will gain means to monitor the market and negotiate agent prices.

Keywords: mobile applications, farming, scenario-based analysis, scenario-based transformation, user empowerment

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Muhammad Ghaffar Doggar, Farah

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The primary objective of this feasibility study is to conduct a techno-financial assessment for installation of biomass based power plant in Faisalabad division. The study involves identification of best site for power plant followed by an assessment of biomass resource potential in the area and propose power plant of suitable size. The study also entailed comprehensive supply chain analysis to determine biomass fuel pricing, transportation and storage. Further technical and financial analyses have been done for selection of appropriate technology for the power plant and its financial viability, respectively. The assessment of biomass resources and the subsequent technical analysis revealed that 20 MW biomass power plant could be implemented at one of the locations near Faisalabad city i.e. AARI Site, Near Chak Jhumra district Faisalabad, Punjab province. Three options for steam pressure; namely, 70 bar, 90 bar and 100 bar boilers have been considered. Using international experience and prices on power plant technology and local prices on locally available equipment, the study concludes biomass fuel price of around 50 US dollars (USD) per ton when delivered to power plant site. The electricity prices used for feasibility calculations were 0.13 USD per KWh for electricity from a locally financed project and 0.11 USD per KWh for internationally financed power plant. For local financing the most viable choice is the 70 bar solution and with international financing, the most feasible solution is using a 90 bar boiler. Between the two options, the internationally financed 90 bar boiler setup gives better financial results than the locally financed 70 bar boiler project. It has been concluded that 20 MW with 90 bar power plant and internationally financed would have an equity IRR of 23% and a payback period of 7 years. This will be a cheap option for installation of power plants.

Keywords: AARI, Ayub agriculture research institute, biomass - crops residue, KWh - electricity Units, MG - Muhammad Ghaffar

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Authors: Liuyao Chai, Colin Clark

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Analysis of 574 participants in a simulated two-person distributive negotiation revealed that the first price 245 (42.7%) of these participants actually asked/offered for the item under negotiation (a used car) differed from the first price they previously stated they intended to ask/offer during their negotiation. This discrepancy between a negotiator’s intended first asking/offer price and his/her actual first asking/offer price had a significant and economically consequential impact on both the course and the outcomes of the negotiations studied. Participants whose actual first price remained the same as their intended first price tended to secure better negotiation outcomes. Moreover, participants who changed their intended first price tended to obtain relatively lower outcomes regardless of whether their modified first announced price had created a negotiating position that was ‘stronger’ or ‘weaker’ than if they had opened with their intended first price. Subsequent investigation of over twenty negotiation behaviours and pre-negotiation perceptual variables within this dataset indicated that the three types of first price announcers—i.e. intended first asking/offer price ‘weakeners’, ‘maintainers’ and ‘strengtheners’— comprised persons who tended to have significantly different pre-negotiation perceptions and behaved in systematically different ways during their negotiation. Typically, the most negative, outcome-compromising consequences of changing, weakening or strengthening an intended first price occurred at the very beginning of a negotiation when participants exchanged their actual first asking/offer prices.

Keywords: business communication, negotiation, persuasion, intended first asking/offer prices, bargaining

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Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

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Authors: Wahyu Riawanti

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Food safety is the one of a prominent issue for globalization era. The more concern is paid in international food and agriculture trade; the more consumers will consider raising the standard of food safety. For this reason, the role of the issue is not only in term of added value but since then also the main requirement in import export activity, including agriculture products. Unfortunately, Indonesia and other developing countries found it difficult to fulfill some of the technical issues and end it up with the lower export activity. In this case, the technical requirements of food safety become an obstacle rather than challenging. Furthermore for local farmers’ activity, food safety is more or less a threat. The study is aimed to reveal on how Indonesian government had dealt with the certification regulation to face problem on competitiveness of Indonesian products. Local government has conducted the regulation of food certification. The study used the case of Salak Pondoh fruit (Salacca zalacca) certification process on Sleman District- Yogyakarta. Triangulation method was used to analyze the effectiveness of the certification program. The quantitative data series taken from 7 farmer groups during the certification processes were used for the research main data. The supporting qualitative data was obtained from in-depth interview with the members of farmers group. The pre-research result has shown that the impact varied from different groups. Conclusively the certification regulation has partly failed to make a significant change in local farmers’ competitiveness. Even the profit was increased, the highly amount budget of the program did not significantly increase the economic incentives for local farmers.

Keywords: economic incentive, food security, government regulation, international trade, local commodity, Salacca zalacca

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Authors: Anna Ching-Yu Wong

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Introduction: Textbooks play a sizable portion of the overall cost of higher education students. It is a board consent that open education resources (OER) reduce the te4xtbook costs and provide students a way to receive high-quality learning materials at little or no cost to them. However, there is less agreement over exactly how much. This study presents an approach for calculating OER savings by using SUNY Canton NON-OER courses (N=233) to estimate the potentially textbook savings for one semester – Fall 2022. The purpose in collecting data is to understand how much potentially saved from using OER materials and to have a record for future further studies. Literature Reviews: In the past years, researchers identified the rising cost of textbooks disproportionately harm students in higher education institutions and how much an average cost of a textbook. For example, Nyamweya (2018) found that on average students save $116.94 per course when OER adopted in place of traditional commercial textbooks by using a simple formula. Student PIRGs (2015) used reports of per-course savings when transforming a course from using a commercial textbook to OER to reach an estimate of $100 average cost savings per course. Allen and Wiley (2016) presented at the 2016 Open Education Conference on multiple cost-savings studies and concluded $100 was reasonable per-course savings estimates. Ruth (2018) calculated an average cost of a textbook was $79.37 per-course. Hilton, et al (2014) conducted a study with seven community colleges across the nation and found the average textbook cost to be $90.61. There is less agreement over exactly how much would be saved by adopting an OER course. This study used SUNY Canton as a case study to create an approach for estimating OER savings. Methodology: Step one: Identify NON-OER courses from UcanWeb Class Schedule. Step two: View textbook lists for the classes (Campus bookstore prices). Step three: Calculate the average textbook prices by averaging the new book and used book prices. Step four: Multiply the average textbook prices with the number of students in the course. Findings: The result of this calculation was straightforward. The average of a traditional textbooks is $132.45. Students potentially saved $1,091,879.94. Conclusion: (1) The result confirms what we have known: Adopting OER in place of traditional textbooks and materials achieves significant savings for students, as well as the parents and taxpayers who support them through grants and loans. (2) The average textbook savings for adopting an OER course is variable depending on the size of the college and as well as the number of enrollment students.

Keywords: textbook savings, open textbooks, textbook costs assessment, open access

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Authors: Tianyu Chen

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China's school district education policy has encouraged parents to purchase properties in school districts with high-quality education resources. Shanghai has implemented "Simultaneous Admission to Public and Private Schools" (SAPPS) since 2018, which has covered all nine-year compulsory education by 2020. This study examines the impact of SAPPS on the housing market, specifically the premium effect of houses located in dual-school districts. Based on the Hedonic Pricing Model and the Signaling Theory, data is collected from 585 second-hand house transactions in Pudong New Area, Shanghai, and it is analyzed with the Difference-in-Differences (DID) model. The results indicate that the implementation of SAPPS has exacerbated the premium of dual school district housing and weakened the effect of the policy to a certain degree. To ensure equal access to education for all students, the government should work both on the supply and demand sides of the education resource equation.

Keywords: simultaneous admission to public and private schools, housing prices, education policy, education equity

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Authors: Mounir Azzam, Valerie Graw, Andreas Rienow

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The Syrian war, which commenced in 2011, has resulted in significant changes in the real estate market in the Damascus metropolitan area, with rising levels of insecurity and disputes over tenure rights. The quest for spatial justice is, therefore, imperative, and this study performs a spatiotemporal analysis to investigate the impact of the war on real estate differentiation. Using the hedonic price models including 2,411 housing transactions over the period 2010-2022, this study aims to understand the spatial dynamics of the real estate market in wartime. Our findings indicate that war variables have had a significant impact on the differentiation and depreciation of property prices. Notably, property attributes have a more substantial impact on real estate values than district location, with severely damaged buildings in Damascus city resulting in an 89% decline in prices, while prices in Rural Damascus districts have decreased by 50%. Additionally, this study examines the urban texture of Damascus using correlation and homogeneity statistics derived from the gray-level co-occurrence matrix obtained from Google Earth Engine. We monitored 250 samples from hedonic datasets within three different years of the Syrian war (2015, 2019, and 2022). Our findings show that correlation values were highly differentiated, particularly among Rural Damascus districts, with a total decline of 87.2%. While homogeneity values decreased overall between 2015 and 2019, they improved slightly after 2019. The findings have valuable implications, not only for investment prospects in setting up a successful reconstruction strategy but also for spatial justice of property rights in strongly encouraging sustainable real estate development.

Keywords: hedonic price, real estate differentiation, reconstruction strategy, spatial justice, urban texture analysis

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Authors: Saadia Izzeldin Malik

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Lack of ethics is the crisis of the 21-century. Today’s global world is filled with economic, political, environmental, media/communication, and social crises that all generated by the eroding fabric of ethics and moral values that guide human’s decisions in all aspects of live. Our global world is guided by liberal western democratic principles and liberal capitalist economic principles that define and reinforce each other. In economic terms, capitalism has turned world economic systems into one market place of ideas and products controlled by big multinational corporations that not only determine the conditions and terms of commodity production and commodity exchange between countries, but also transform the political economy of media systems around the globe. The citizen (read the consumer) today is the target of persuasion by all types of media at a time when her/his interests should be, ethically and in principle, the basic significant factor in the selection of media content. It is very important in this juncture of clashing media values –professional and commercial- and wide spread ethical lapses of media organizations and media professionals to think of a perspective to theorize these conflicting values within a broader framework of media ethics. Thus, the aim of this paper is to, epistemologically, bring to the center a perspective on media ethics as a basis for reconciliation of clashing values of the media. The paper focuses on conflicting ethical values in current media debate; namely ownership of media vs. press freedom, individual right for privacy vs. public right to know, and global western consumerism values vs. media values. The paper concludes that a framework to reconcile conflicting values of media ethics should focus on the “individual” journalist and his/her moral development as well as focus on maintaining ethical principles of the media as an institution with a primary social responsibility for the “public” it serves.

Keywords: ethics, media, journalism, social responsibility, conflicting values, global

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

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Authors: S. L. Tulasi Devi, Shivam Azad

Abstract:

The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Mei-Yi Wu, Shang-Ming Huang

Abstract:

The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Peng Yew Wong

Abstract:

House prices in the Australian capital cities were at record levels subsequent to Global Financial Crisis (GFC) 2008 and many believed that foreign investors, especially the Chinese investors, were the main reason for the Australian capital cities’ house prices escalation. This research conducted an Australian cross border semi-structured interviews in Shanghai, China to uncover historical evidence and emerging trend supporting the existence of a significant relationship between overseas investors and residential housing markets performance in Australia subsequent to the GFC 2008. Some unique investment strategies of private investors from China which emphasised on non-capitalist factors such as early education were identified, alongside with some insights on the significant China government policies that have incentivised the cross border investments from China. It is believed that this understanding will assist policy makers to effectively manage the overheated Australian residential property market without compromising the steady flow of FREI.

Keywords: Australian housing market, residential property, foreign real estate investment, education, China investor

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Authors: Asmita A. Vaidya, Shahista S. Inamdar

Abstract:

Society is dynamic, in this changing and development processes, Indian Muslim women where no exception to this social change. Islam has elevated her status from being chattels/commodity to individual human being having separate legal personality and equal to that of men but in India, even two women are not equal in availing their matrimonial rights and remedies, separate personal laws are applicable to them and thus gender justice is a fragile myth.

Keywords: Muslim women, gender justice, polygamy, Islamic jurisprudence, equality

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Authors: Vikrant Gupta, Amrit Goswami

Abstract:

The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

Procedia PDF Downloads 105