Search results for: price forecasting

Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism

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Authors: S. Hamid Mirmohammadi, Shahrazad Tamjidzad

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This paper is concerned with the single-item continuous review inventory system in which demand is stochastic and discrete. The budget consumed for purchasing the ordered items is not restricted but it incurs extra cost when exceeding specific value. The unit purchasing price depends on the quantity ordered under the all-units discounts cost structure. In many actual systems, the budget as a resource which is occupied by the purchased items is limited and the system is able to confront the resource shortage by charging more costs. Thus, considering the resource shortage costs as a part of system costs, especially when the amount of resource occupied by the purchased item is influenced by quantity discounts, is well motivated by practical concerns. In this paper, an optimization problem is formulated for finding the optimal (R, Q) policy, when the system is influenced by the budget limitation and a discount pricing simultaneously. Properties of the cost function are investigated and then an algorithm based on a one-dimensional search procedure is proposed for finding an optimal (R, Q) policy which minimizes the expected system costs .

Keywords: (R, Q) policy, stochastic demand, backorders, limited resource, quantity discounts

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Jerry Gyimah, Ernest Kissi, Safowaa Osei-Tutu, Charles Dela Adobor, Theophilus Adjei-Kumi, Ernest Osei-Tutu

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Price fluctuation contract is imperative and of paramount essence, in the construction industry as it provides adequate relief and cushioning for changes in the prices of input resources during construction. As a result, several methods have been devised to better help in arriving at fair recompense in the event of price changes. However, stakeholders often appear not to be satisfied with the existing methods of fluctuation evaluation, ostensibly because of the challenges associated with them. The aim of this study was to identify the challenges to the usage of building construction cost indices in Ghana. Data was gathered from contractors and quantity surveying firms. The study utilized a survey questionnaire approach to elicit responses from the contractors and the consultants. Data gathered was analyzed scientifically, using the relative importance index (RII) to rank the problems associated with the existing methods. The findings revealed the following, among others, late release of data, inadequate recovery of costs, and work items of interest not included in the published indices as the main challenges of the existing methods. Findings provide useful lessons for policymakers and practitioners in decision making towards the usage and improvement of available indices.

Keywords: building construction cost indices, challenges, usage, Ghana

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Authors: Hui Hsin Huang

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The downstream manufactures will order their materials from different upstream suppliers to maintain a certain level of the demand. This paper proposes a bivariate model to portray this phenomenon of material demand. We use empirical data to estimate the parameters of model and evaluate the RMSD of model calibration. The results show that the model has better fitness.

Keywords: recency, ordering time, materials demand quantity, multi-source ordering

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Authors: Concepcion Gonzalez-Concepcion, Maria Candelaria Gil-Fariña, Celina Pestano-Gabino

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We analyze six relevant economic and financial variables for the period 2000M1-2015M3 in the context of the Spanish economy: a financial index (IBEX35), a commodity (Crude Oil Price in euros), a foreign exchange index (EUR/USD), a bond (Spanish 10-Year Bond), the Spanish National Debt and the Consumer Price Index. The goal of this paper is to analyze the main relations between them by computing the Wavelet Power Spectrum and the Cross Wavelet Coherency associated with Morlet wavelets. By using a special toolbox in MATLAB, we focus our interest on the period variable. We decompose the time-frequency effects and improve the interpretation of the results by non-expert users in the theory of wavelets. The empirical evidence shows certain instability periods and reveals various changes and breaks in the causality relationships for sample data. These variables were individually analyzed with Daubechies Wavelets to visualize high-frequency variance, seasonality, and trend. The results are included in Proceeding 20th International Academic Conference, 2015, International Institute of Social and Economic Sciences (IISES), Madrid.

Keywords: economic and financial variables, Spain, time-frequency domain, wavelet coherency

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Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

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Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

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Authors: Wei Yao, Constantinos Alexiou

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In the existing literature, many studies have focused on the implementation and effectiveness of quantitative easing (QE) since 2008, but only a few have evaluated QE’s effect on commodity prices. In this context, by following Frankel’s (1986) commodity price overshooting model, we study the dynamic covariation between the expected real interest rates and six agricultural commodities’ real returns over the period from 2000:1 to 2018 for the US economy. We use wavelet analysis to investigate the causal relationship and co-movement of time series data by calculating the coefficient of determination in different frequencies. We find that a) US unconventional monetary policy may cause more positive and significant covariation between the expected real interest rates and agricultural commodities’ real returns over the short horizons; b) a lead-lag relationship that runs from agricultural commodities’ real returns to the expected real short-term interest rates over the long horizons; and c) a lead-lag relationship from agricultural commodities’ real returns to the expected real long-term interest rates over short horizons. In the realm of monetary policy, we argue that QE may shift the negative relationship between most commodities’ real returns and the expected real interest rates to a positive one over a short horizon.

Keywords: QE, commodity price, interest rate, wavelet coherence

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Arjun Paul, Adrijit Goswami

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In our present work, an economic order quantity inventory model with shortages is developed where holding cost is expressed as linearly increasing function of time and demand rate is a ramp type function of time. The items considered in the model are deteriorating in nature so that a small fraction of the items is depleted with the passage of time. In order to consider a more realistic situation, the deterioration rate is assumed to follow a continuous uniform distribution with the parameters involved being triangular fuzzy numbers. The inventory manager offers his customer a discount in case he is willing to backorder his demand when there is a stock-out. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval. For better illustration of our proposed model in both the crisp and fuzzy sense and for providing richer insights, a numerical example is cited to exemplify the policy and to analyze the sensitivity of the model parameters.

Keywords: fuzzy deterioration rate, price discount on backorder, ramp type demand, shortage, time varying holding cost

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Authors: W. A. Nalaka Wijesooriya

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The increasing paddy production, stabilization of domestic rice consumption and the increasing dynamism of rice processing and domestic markets call for a rethinking of the general direction of the rice milling industry in Sri Lanka. The main purpose of the study was to explore levels of concentration in rice milling industry in Polonnaruwa and Hambanthota which are the major hubs of the country for rice milling. Concentration indices reveal that the rice milling industry in Polonnaruwa operates weak oligopsony and is highly competitive in Hambanthota. According to the actual quantity of paddy milling per day, 47 % is less than 8Mt/Day, while 34 % is 8-20 Mt/day, and the rest (19%) is greater than 20 Mt/day. In Hambanthota, nearly 50% of the mills belong to the range of 8-20 Mt/day. Lack of experience of the milling industry, poor knowledge on milling technology, lack of capital and finding an output market are the major entry barriers to the industry. Major problems faced by all the rice millers are the lack of a uniform electricity supply and low quality paddy. Many of the millers emphasized that the rice ceiling price is a constraint to produce quality rice. More than 80% of the millers in Polonnaruwa which is the major parboiling rice producing area have mechanical dryers. Nearly 22% millers have modern machineries like color sorters, water jet polishers. Major paddy purchasing method of large scale millers in Polonnaruwa is through brokers. In Hambanthota major channel is miller purchasing from paddy farmers. Millers in both districts have major rice selling markets in Colombo and suburbs. Huge variation can be observed in the amount of pledge (for paddy storage) loans. There is a strong relationship among the storage ability, credit affordability and the scale of operation of rice millers. The inter annual price fluctuation ranged 30%-35%. Analysis of market margins by using series of secondary data shows that farmers’ share on rice consumer price is stable or slightly increases in both districts. In Hambanthota a greater share goes to the farmer. Only four mills which have obtained the Good Manufacturing Practices (GMP) certification from Sri Lanka Standards Institution can be found. All those millers are small quantity rice exporters. Priority should be given for the Small and medium scale millers in distribution of storage paddy of PMB during the off season. The industry needs a proper rice grading system, and it is recommended to introduce a ceiling price based on graded rice according to the standards. Both husk and rice bran were underutilized. Encouraging investment for establishing rice oil manufacturing plant in Polonnaruwa area is highly recommended. The current taxation procedure needs to be restructured in order to ensure the sustainability of the industry.

Keywords: conduct, performance, structure (SCP), rice millers

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Authors: Seyran Naghdi

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Background: Orphan drug development is limited by very high costs attributed to the research and development and small size market. How health policymakers address this challenge to consider both supply and demand sides need to be explored for directing the policies and plans in the right way. The price is an important signal for pharmaceutical companies’ profitability and the patients’ accessibility as well. Objective: This study aims to find out the orphan drugs' price-setting patterns and approaches in health systems through a systematic review of the available evidence. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach was used. MedLine, Embase, and Web of Sciences were searched via appropriate search strategies. Through Medical Subject Headings (MeSH), the appropriate terms for pricing were 'cost and cost analysis', and it was 'orphan drug production', and 'orphan drug', for orphan drugs. The critical appraisal was performed by the Joanna-Briggs tool. A Cochrane data extraction form was used to obtain the data about the studies' characteristics, results, and conclusions. Results: Totally, 1,197 records were found. It included 640 hits from Embase, 327 from Web of Sciences, and 230 MedLine. After removing the duplicates, 1,056 studies remained. Of them, 924 studies were removed in the primary screening phase. Of them, 26 studies were included for data extraction. The majority of the studies (>75%) are from developed countries, among them, approximately 80% of the studies are from European countries. Approximately 85% of evidence has been produced in the recent decade. Conclusions: There is a huge variation of price-setting among countries, and this is related to the specific pharmacological market structure and the thresholds that governments want to intervene in the process of pricing. On the other hand, there is some evidence on the availability of spaces to reduce the very high costs of orphan drugs development through an early agreement between pharmacological firms and governments. Further studies need to focus on how the governments could incentivize the companies to agree on providing the drugs at lower prices.

Keywords: orphan drugs, orphan drug production, pricing, costs, cost analysis

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Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

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Authors: Tetsuji Tanaka, Jin Guo

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The extant literature has not succeeded in uncovering the common determinants of price volatility transmissions of agricultural commodities from international to local markets, and further, has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed various factors to determine the degree of price volatility transmissions of wheat, rice, and maize between world and domestic markets using GARCH models with dynamic conditional correlation (DCC) specifications and panel-feasible generalized least square models. We found that the grain autarky system has the potential to diminish volatility pass-throughs for three grain commodities. Furthermore, it was discovered that the substitutive commodity consumption behavior between maize and wheat buffers the volatility transmissions of both, but rice does not function as a transmission-relieving element, either for the volatilities of wheat or maize. The effectiveness of grain consumption substitution to insulate the pass-throughs from global markets is greater than that of cereal self-sufficiency. These implications are extremely beneficial for developing governments to protect their domestic food markets from uncertainty in foreign countries and as such, improves food security.

Keywords: food security, GARCH, grain self-sufficiency, volatility transmission

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Authors: Cristian Păuna

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In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: algorithmic trading, automated trading systems, high-frequency trading, DAX Deutscher Aktienindex

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Authors: Yanping He-Ulbricht, Marc Oliver Rieger

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Based on survey data collected from people with Chinese roots living in Germany, this paper examines the impact of assimilation degree and language priming (Chinese or German) on individuals’ perceived fairness of economic and social differences and their attitude towards these. The results show that both the language used and the length of time spent in a foreign culture have a significant impact. Subjects who had spent less than 10 years in Germany demonstrated a higher readiness to accept government intervention in markets with price limits than those who had lived there longer. Subjects who were asked and answered in German perceived the current economic situation as less fair and were also less inclined to accept inequality, even when it leads to a Pareto improvement. While the difference in fairness perception of inequality was a cultural effect, the difference in attitudes towards government intervention was rather a result of learning process. The findings imply that both learning processes of individuals and culture play an important role in perception and preferences regarding social and economic differences.

Keywords: assimilation, bilingualism, cross-cultural comparison, income inequality, language priming, price fairness

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Authors: Nini Johana Marin Rodriguez

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This paper applies DCC, EWMA and OGARCH models to compare the dynamic correlations between exchange rates, oil prices, exchange rates and stock markets to examine the time-varying conditional correlations to the daily oil prices and index returns in relation to the US dollar/local currency for developed (Canada and Mexico) and emerging Latin American markets (Brazil, Chile, Colombia and Peru). Changes in correlation interactions are indicative of structural changes in market linkages with implications to contagion and interdependence. For each pair of stock price-exchange rate and oil price-US dollar/local currency, empirical evidence confirms of a strengthening negative correlation in the last decade. Methodologies suggest only two events have significatively impact in the countries analyzed: global financial crisis and Europe crisis, both events are associated with shifts of correlations to stronger negative level for most of the pairs analyzed. While, the first event has a shifting effect on mainly emerging members, the latter affects developed members. The identification of these relationships provides benefits in risk diversification and inflation targeting.

Keywords: crude oil, dynamic conditional correlation, exchange rates, interdependence, stock prices

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Authors: Maria Amaia Iza Padilla, Ibai Ostolozaga

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The objective of this paper is to analyze how transportation costs between regions within a country can affect not only domestic trade but also the allocation of resources in a given region, aggregate productivity, and relative domestic prices (tradable versus non-tradable). On the one hand, there is a vast literature that analyzes the transportation costs faced by countries when trading with the rest of the world. However, this paper focuses on the effect of transportation costs on domestic trade. Countries differ in their domestic road infrastructure and transport quality. There is also some literature that focuses on the effect of road infrastructure on the price difference between regions but not on relative prices at the aggregate level. On the other hand, this work is also related to the literature on resource misallocation. Finally, the paper is also related to the literature analyzing the effect of trade on the development of the manufacturing sector. Using the World Bank Enterprise Survey database, it is observed cross-country differences in the proportion of firms that consider transportation as an obstacle. From the International Comparison Program, we obtain a significant negative correlation between GDP per worker and relative prices (manufacturing sector prices relative to the service sector). Furthermore, there is a significant negative correlation between a country’s transportation quality and the relative price of manufactured goods with respect to the price of services in that country. This is consistent with the empirical evidence of a negative correlation between transportation quality and GDP per worker, on the one hand, and the negative correlation between GDP per worker and domestic relative prices, on the other. It is also shown that in a country, the share of manufacturing firms whose main market is at the local (regional) level is negatively related to the quality of the transportation infrastructure within the country. Similarly, this index is positively related to the share of manufacturing firms whose main market is national or international. The data also shows that those countries with a higher proportion of manufacturing firms operating locally have higher relative prices. With this information in hand, the paper attempts to quantify the effects of the allocation of resources between and within sectors. The higher the trade barriers caused by transportation costs, the less efficient allocation, which causes lower aggregate productivity. Second, it is built a two-sector model where regions within a country trade with each other. On the one hand, it is found that with respect to the manufacturing sector, those countries with less trade between their regions will be characterized by a smaller variety of goods, less productive manufacturing firms on average, and higher relative prices for manufactured goods relative to service sector prices. Thus, the decline in the relative price of manufactured goods in more advanced countries could also be explained by the degree of trade between regions. This trade allows for efficient intra-industry allocation (traders are more productive, and resources are allocated more efficiently)).

Keywords: misallocation, relative prices, TFP, transportation cost

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Authors: Medani Prasad Rijal

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The study outlines the impacts of decentralized forest policy on natural Sal (shorea robusta) forests in the Terai region of Nepal. The government has implemented community forestry program to manage the forest resources and improve the livelihood of local people collectively. The forest management authorities such as conserve, manage, develop and use of forest resources were shifted to the local communities, however, the ownership right of the forestland retained by the government. Local communities took the decision on harvesting, distribution, and sell of forest products by fixing the prices independently. The local communities were putting the low value of forest products and distributed among the user households on the name of collective decision. The decision of low valuation is devaluating the worth of forest products. Therefore, the study hypothesized that decision-making capacities are equally prominent next to the decentralized policy and program formulation. To accomplish the study, individual to group level discussions and questionnaire survey methods were applied with executive committee members and user households. The study revealed that the local intuition called Community Forest User Group (CFUG) committee normally took the decisions on consensus basis. Considering to the access and affording capacity of user households having poor economic backgrounds, low pricing mechanism of forest products has been practiced, even though the Sal timber is far expensive in the local market. The local communities thought that low pricing mechanism is accessible to all user households from poor to better off households. However, the analysis of forest products distribution opposed the assumption as most of the Sal timber, which is the most valuable forest product of community forest only purchased by the limited households of better economic conditions. Since the Terai region is heterogeneous by socio-economic conditions, better off households always have higher affording capacity and possibility of taking higher timber benefits because of low price mechanism. On the other hand, the minimum price rate of forest products has poor contribution in community fund collection. Consequently, it has poor support to carry out poverty alleviation activities to poor people. The local communities have been fixed Sal timber price rate around three times cheaper than normal market price, which is a strong evidence of forest product devaluation itself. Finally, the study concluded that the capacity building of local executives as the decision-makers of natural Sal forests is equally indispensable next to the policy and program formulation for effective decentralized forest management. Unilateral decentralized forest policy may devaluate the forest products rather than devolve of power to the local communities and empower to them.

Keywords: community forestry program, decentralized forest policy, Nepal, Sal forests, Terai

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Authors: Rania Sherif Abd El-Azim

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The role of corporate social responsibility (CSR) in business has evolved and led to an era where industry leaders can no longer overlook the importance of being participative corporate citizens. This is not only because of the media’s skeptical attitude toward whether or not companies’ CSR efforts are sincere but also due to key stakeholders’ ability to hold companies to a higher standard than ever before as companies can gain competitive advantage through CSR. These programs result in addressing global challenges, such as climate, and poverty, or simply improving employee retention, so it has become increasingly clear that CSR is not just the new trend for companies but a necessary tool that organizations must integrate into their overall business strategies to build a stronger reputation as well as to also increase credibility among their key audience and enhance customers’ willingness to repurchase, pay premium price and enhancing positive word of mouth. According to the literature review, the link between CSR and competitive advantage at the firm level has long been an important topic for both CSR researchers and practitioners. Thus CSR can play an important role in enhancing the firm's competitive advantage, which seems an attractive area to investigate specially in Egypt. So, this paper will investigate the role of corporate social responsibility in enhancing the firm competitive advantage.

Keywords: corporate social responsibility, competitive advantage, corporate reputation, customers' willingness to repurchase, willingness to pay premium price, positive word of mouth

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Authors: Matteo Bonaventura, Giancarlo Giudici

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This paper analyses the valuation process of companies listed on the Italian Exchange in the period 2000-2009 at their Initial Public Offering (IPO). One the most common valuation techniques declared in the IPO prospectus to determine the offer price is the Discounted Cash Flow (DCF) method. We develop a ‘reverse engineering’ model to discover the short term profitability implied in the offer prices. We show that there is a significant optimistic bias in the estimation of future profitability compared to ex-post actual realization and the mean forecast error is substantially large. Yet we show that such error characterizes also the estimations carried out by analysts evaluating non-IPO companies. The forecast error is larger the faster has been the recent growth of the company, the higher is the leverage of the IPO firm, the more companies issued equity on the market. IPO companies generally exhibit better operating performance before the listing, with respect to comparable listed companies, while after the flotation they do not perform significantly different in term of return on invested capital. Pre-IPO book building activity plays a significant role in partially reducing the forecast error and revising expectations, while the market price of the first day of trading does not contain information for further reducing forecast errors.

Keywords: initial public offerings, DCF, book building, post-IPO profitability drop

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Authors: Catherine Heyjung Sonu

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This paper examines the effect of accounting quality on the process in which stock price is determined by focusing on contribution-in-kind valuations using Korean setting. In Korea, a number of chaebol firms have transformed into holding company system starting in 2003. With an attempt to gain as much voting right, management sold shares of subsidiaries to purchase shares of the holding company. In so doing, management of these firms received share issues for the contribution in kind that has been made to obtain additional shares of the holding company. The price of these share issues against contribution in kind is allowed to be discounted up to 30%. Using this interesting setting in Korea, this paper examines whether accounting quality affects the extent of the discount applied to the share issues. If the accounting quality of the firm for which the management is receiving share issues is poor, the extent of discount is likely to be high. The extent of discount is likely lower for firms with superior accounting quality. Using 24 cases, we find that, on average, the extent of discount is larger for share issues in which the accounting quality, proxied by the absolute value of discretionary accruals, is poor. This paper provides insight by examining the effect of accounting quality on the stock market. It sheds light on the intersection between finance and accounting research and should be of interest to researchers and practitioners.

Keywords: Accounting quality, Contribution-in-kind, discount, holding company

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Clarinda V. Nhangumbe, Ercília Sousa

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Weather Derivatives are financial instruments used to cover non-catastrophic weather events and can be expressed in the form of standard or plain vanilla products, structured or exotics products. The underlying asset, in this case, is the weather index, such as temperature, rainfall, humidity, wind, and snowfall. The complexity of the Weather Derivatives structure shows the weakness of the Black Scholes framework. Therefore, under the risk-neutral probability measure, the option price of a weather contract can be given as a unique solution of a two-dimensional partial differential equation (parabolic in one direction and hyperbolic in other directions), with an initial condition and subjected to adequate boundary conditions. To calculate the price of the option, one can use numerical methods such as the Monte Carlo simulations and implicit finite difference schemes conjugated with Semi-Lagrangian methods. This paper is proposed two explicit methods, namely, first-order upwind in the hyperbolic direction combined with Lax-Wendroff in the parabolic direction and first-order upwind in the hyperbolic direction combined with second-order upwind in the parabolic direction. One of the advantages of these methods is the fact that they take into consideration the boundary conditions obtained from the financial interpretation and deal efficiently with the different choices of the convection coefficients.

Keywords: incomplete markets, numerical methods, partial differential equations, stochastic process, weather derivatives

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

Procedia PDF Downloads 561

Authors: Savita Tangwongkit, Chittur S Srinivasan, Philip J. Jones

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Thailand has become the world’s fourth largest sugarcane producer and second largest sugar exporter. While there have been a number of drivers of this growth, the primary driver has been wide-ranging government support measures. Recently, the Thai government has emphasized the need for policy reform as part of a broader industry restructuring to bring the sector up-to-date with the current and future developments in the international sugar market. Because of the sectors historical dependence on government support, any such reform is likely to have a very significant impact on the fortunes of Thai cane farmers. This study explores the impact of three policy scenarios, representing a spectrum of policy approaches, on Thai cane producers. These reform scenarios were designed in consultation with policy makers and academics working in the cane sector. Scenario 1 captures the current ‘government proposal’ for policy reform. This scenario removes certain domestic production subsidies but seeks to maintain as much support as is permissible under current WTO rules. The second scenario, ‘protectionism’, maintains the current internal market producer supports, but otherwise complies with international (WTO) commitments. Third, the ‘libertarian scenario’ removes all production support and market interventions, trade and domestic consumption distortions. Most important driver of producer behaviour in all of the scenarios is the producer price of cane. Cane price is obviously highest under the protectionism scenario, followed by government proposal and libertarian scenarios, respectively. Likely producer responses to these three policy scenarios was determined by means of a large-scale survey of cane farmers. The sample was stratified by size group and quotas filled by size group and region. One scenario was presented to each of three sub-samples, consisting of approx.150 farmers. Total sample size was 462 farms. Data was collected by face-to-face interview between June and August 2019. There was a marked difference in farmer response to the three scenarios. Farmers in the ‘Protectionism’ scenario, which maintains the highest cane price and those who farm larger cane areas are more likely to continue cane farming. The libertarian scenario is likely to result in the greatest losses in terms of cane production volume broadly double that of the ‘protectionism’ scenario, primarily due to farmers quitting cane production altogether. Over half of loss cane production volume comes from medium-size farm, i.e. the largest and smallest producers are the most resilient. This result is likely due to the fact that the medium size group are large enough to require hired labour but lack the economies of scale of the largest farms. Over all size groups the farms most heavily specialized in cane production, i.e. those devoting 26-50% of arable land to cane, are also the most vulnerable, with 70% of all farmers quitting cane production coming from this group. This investigation suggests that cane price is the most significant determinant of farmer behaviour. Also, that where scenarios drive significantly lower cane price, policy makers should target support towards mid-sized producers, with policies that encourage efficiency gains and diversification into alternative agricultural crops.

Keywords: farmer intentions, farm survey, policy reform, Thai cane production

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Dhruba Khatri

Abstract:

Despite the short history of community based forest management, the community forestry program of Nepal has produced substantial positive effects to organize the local people at a local level institution called Community Forest User Group and manage the local forest resources in the line of poverty reduction since its inception in 1970s. Moreover, each CFUG has collected a community fund from the sale of forest products and non-forestry sources as well and the fund has played a vital role to improve the livelihood of user households living in and around the forests. The specific study sites were selected based on the criteria of i) community forests having dominancy of Sal forests, and ii) forests having 3-5 years experience of community forest management. The price rates of forest products fixed by the CFUGs and the distribution records were collected from the respective community forests. Nonetheless, the relation between pricing strategy and community fund collection revealed that the small change in price of forest products could greatly affect in community fund collection and carry out of forest management, community development, and income generation activities in the line of poverty reduction at local level.

Keywords: benefit sharing, community forest, equitable, Nepal

Procedia PDF Downloads 384

Authors: Lars Rödel, Jonas Krebs, Gregor Müller

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The growing price pressure due to the increasing number of global suppliers, the growing individualization of products and ever-shorter delivery times are upcoming challenges in the industry. In this context, Mass Personalization stands for the individualized production of customer products in batch size 1 at the price of standardized products. The possibilities of digitalization and automation of technical order processing open up the opportunity for companies to significantly reduce their cost of complexity and lead times and thus enhance their competitiveness. Many companies already use a range of CAx tools and configuration solutions today. Often, the expert knowledge of employees is hidden in "knowledge silos" and is rarely networked across processes. DesignChain describes the automated digital process from the recording of individual customer requirements, through design and technical preparation, to production. Configurators offer the possibility of mapping variant-rich products within the Design Chain. This transformation of customer requirements into product features makes it possible to generate even complex CAD models, such as those for large-scale plants, on a rule-based basis. With the aid of an automated CAx chain, production-relevant documents are thus transferred digitally to production. This process, which can be fully automated, allows variants to always be generated on the basis of current version statuses.

Keywords: automation, design, CAD, CAx

Procedia PDF Downloads 76

Authors: N. M. Tawil, A. R. Musa, A. I Che-Ani, H. Basri

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It is known that rising of house prices recently has affected the home ownership, especially for the future. Hence to overcome the rose of housing prices, the self-build home or DIY concept is perceived as one of the solution. This concept is proposed to be implemented for the future housing design as a strategy in helping the government to provide affordable housing, especially for middle income group to own a landed housing property. This concept is expected to offer a lower housing price for middle-income buyers and provide an opportunity for buyers to design their dream’s home with the self-build home or 'Do It Yourself' (DIY) concept. In order to implement this concept as affordable housing for MIG, the public perceptions and acceptances on the self-build home/ DIY concept itself should be identified. To achieve this aim this study was conducted by using 2 method namely literature review and questionnaire survey. The questionnaire survey was distributed to 200 respondents randomly in Lembah Klang and were analysed through the SPSS program. The results show that respondents are very interested in buying a home that they can have with the appropriate size of the home. Average of them known about Do It Yourself (DIY) concept but none of respondent have implement this concept. Most of respondents were agreed that this DIY method suitable to be implemented in the housing industry in Malaysia and they were agreed that this concept can offer a cheaper housing price because the construction costs were reduced. Moreover by providing a basic home the owner can renovate their home according to their need and financial capability.

Keywords: affordable housing, Do It Yourself, self-Built home, perception, middle income group

Procedia PDF Downloads 416