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Demand Response is a well-known means usually operated by the system operator(SO) or the electricity retailers in order to reduce the peak loads or cut the price in electricity market. KPX(Korea Power eXchange), the SO in Korea has been operating the demand bidding program(or the demand resource market) since it was firstly introduced as the pilot project in 2008. The results has proved to be effective to enhance demand response. This paper describes the basic concepts and the operation results of the program.

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Áö±Ý±îÁö ´Ù¼öÀÇ ¼¾¼­ ³×Æ®¿öÅ©¸¦ À§ÇÑ on-demand ¶ó¿ìÆà ÇÁ·ÎÅäÄݵéÀÌ Á¦¾ÈµÇ¾ú´Ù. ÇÏÁö¸¸ Á¦¾ÈµÈ ¼¾¼­ ³×Æ®¿öÅ©¿ë on-demand ¶ó¿ìÆà ÇÁ·ÎÅäÄݵéÀº ´ëºÎºÐ hop count¸¦ ¶ó¿ìÆà ¸ÞÆ®¸¯À¸·Î »ç¿ëÇϱ⠶§¹®¿¡ »ó´ëÀûÀ¸·Î ¿­¾ÇÇÑ ¹«¼± ȯ°æ°ú ½Å·Ú¼ºÀ» ¿ä±¸ÇÏ´Â ¼¾¼­ ÀÀ¿ë¿¡´Â ÀûÇÕÇÏÁö ¾Ê´Ù. º» ³í¹®¿¡¼­´Â ÀÌ·¯ÇÑ È¯°æ¿¡ ÀûÇÕÇÑ minimum LQI(Link Quality Indicator) ±â¹ÝÀÇ on-demand ¼¾¼­ ³×Æ®¿öÅ© ¶ó¿ìÆà ÇÁ·ÎÅäÄÝÀ» Á¦¾ÈÇÏ¿´´Ù. ¶ÇÇÑ Á¦¾ÈÇÑ ¶ó¿ìÆà ÇÁ·ÎÅäÄÝÀ» TinyOS »ó¿¡¼­ ±¸ÇöÇÏ¿´°í, ¸ÖƼ È© Å×½ºÆ® ȯ°æ¿¡¼­ hop count ±â¹ÝÀÇ ¶ó¿ìÆà ÇÁ·ÎÅäÄÝ°ú ¼º´ÉÀ» ºñ±³, ÃøÁ¤ÇÏ¿´´Ù. ½ÇÇè °á°ú, Á¦¾ÈµÈ ¶ó¿ìÆà ÇÁ·ÎÅäÄÝÀÌ ¿­¾ÇÇÑ ¹«¼± ȯ°æ¿¡¼­ ´õ ³ªÀº µ¥ÀÌÅÍ Àü¼Û ¼º°ø·üÀ» º¸ÀÓÀ» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù.

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±â¾÷ ¼Ò¼Û À§ÇèÀº ±â¾÷Áö¹è±¸Á¶ÀÇ ¿ªÇÒÀ» Çϱ⵵ ÇÏ°í °íÇ°Áú °¨»çÀÎÀ» ±â¾÷ÀÌ °í¿ëÇÏ´Â °ÍÀº ±â¾÷¼Ò¼Û À§ÇèÀ» ³·Ãß±â À§ÇÔÀ̱⵵ ÇÏ´Ù. µû¶ó¼­ ±â¾÷ ¼Ò¼Û À§ÇèÀÇ º¯µ¿Àº ±â¾÷ÀÇ °íÇ°Áú °¨»çÀο¡ ´ëÇÑ ¼ö¿ä¿¡ ¿µÇâÀ» ÁÙ ¼ö ÀÖ´Ù. Á¡ÁøÀûÀ¸·Î Àû¿ëµÈ ±â¾÷ÀÇ ¼Ò¼ÛÀ§ÇèÀ» ÁÙÀÌ´Â Universal Demand (UD)¹ý¾ÈÀ» ÀÌ¿ëÇÏ¿©, ¿ì¸®´Â °¨¼ÒÇÑ ±â¾÷ÀÇ ¼Ò¼Û À§ÇèÀÌ °¨»ç ¼ö¿ä¿¡ ¾î¶°ÇÑ ¿µÇâÀ» ÁÖ´ÂÁö ¿¬±¸ÇÏ¿´´Ù. ¿ì¸®´Â UD¹ý¾È äÅÃÀÌBig (N) °¨»çÀÎ ¹× »ê¾÷ Àü¹® °¨»çÀΠäÅÃÀ» °¨¼Ò½ÃŲ °ÍÀ» ¹ß°ßÇÏ¿´´Ù. ¶ÇÇÑ ¿ì¸®´Â °¨»çÀÎÀÌ ±â¾÷ÀÇ ¼Ò¼Û À§ÇèÀÌ ³·¾ÆÁø ÈÄ¿¡µµ °¨»ç ³ë·ÂÀ» °¨¼Ò½ÃÅ°Áö ¾Ê´Â °ÍÀ» ¹ß°ßÇÏ¿´´Âµ¥ ÀÌ´Â ±â¾÷ÀÇ ¼Ò¼Û À§ÇèÀÌ °¨»çÀÎÀÇ ¼Ò¼Û À§Çè°ú Á÷Á¢ÀûÀÎ ¿¬°üÀÌ ¾øÀ» ¼ö ÀÖÀ½À» ÀǹÌÇÒ ¼ö ÀÖ´Ù. º» ¿¬±¸´Â ±â¾÷ ¼Ò¼Û À§ÇèÀÌ °¨»ç Ç°Áú¿¡ ¿µÇâÀ» ÁÖ´Â ÁÖ¿ä ¿äÀÎÀÎ °¨»çÀÎ ¼ö¿ä¿¡ °üÇÑ ¿µÇâÀ» º¸¿©ÁÖ¾ú´Ù´Â °Í¿¡ ÀÇÀÇ°¡ ÀÖ´Ù°í ÇÏ°Ú´Ù.

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Communication networks in North Korea are inferior as compared to those in South Korea. The demand is limited to special purpose including munitions industry and communication network is not regarded as infrastructure for national economy, yet. Accordingly, people who use communication devices in Korea seem to belong to the upper class and North Korean communication network comes under control of its military and communist party. Therefore, in order to modernize North Korean communication networks, it needs functional and technical approach . In particular, the study aims to make suggestions to prepare for opening up future market by selecting one of main cities in North Korea including Gaesung, Rason, Kumgangsan and Sinuiju, future bases of collaboration and  communication unification as potential demand area and estimating potential demands through evaluation on new demand area. And the study  includes the issue on how to build IT and communication infrastructures in potential demand area, as well.

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AbstractMrázová and Neary (2017) introduce the notion of the Demand Manifold which expresses the relationship between the elasticity and curvature of a demand function. They argue that this determines many important comparative static properties of firm behavior. This paper gives necessary and sufficient conditions for two demand functions to have the same demand manifold and so to have similar comparative static properties.

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À§Ä¡ ±â¹Ý ¶ó¿ìÆà ÇÁ·ÎÅäÄݵ鿡 ±âº» °¡Á¤ÀÎ ÀÌ¿ô ³ëµåµé°£ÀÇ ÁÖ±âÀûÀÎ À§Ä¡ Á¤º¸ ±³È¯Àº ´ÙÀ½ µÎ °¡Áö ¹®Á¦¸¦ °®´Â´Ù: (1) µ¥ÀÌÅÍ Àü´ÞÀÌ ¾ø´Â Áö¿ª¿¡ ³ëµåµéÀÇ ºÒÇÊ¿äÇÑ ¿¡³ÊÁö ¼Òºñ¿Í (2) µ¥ÀÌÅÍ Àü´Þ ½ÃÁ¡¿¡ ÀÌ¿ô ³ëµå À§Ä¡ Á¤º¸ÀÇ ºÎÁ¤È®¼º. µû¶ó¼­, º» ³í¹®Àº À̵¿ ¹«¼± ¼¾¼­ ³×Æ®¿öÅ©¿¡¼­ on-demand À§Ä¡ ±â¹Ý ¶ó¿ìÆà ÇÁ·ÎÅäÄÝÀ» Á¦¾ÈÇÑ´Ù. Á¦¾È ¹æ¾È¿¡¼­ ¼Û½Å ³ëµå´Â µ¥ÀÌÅÍ Àü´Þ ½ÃÁ¡¿¡ ÇÊ¿äÇÑ ÀÌ¿ô ³ëµåµé¸¸ÀÇ À§Ä¡ Á¤º¸¸¦ ȹµæÇÏ°í ±× ³ëµåµéÀÇ À̵¿¼ºÀ» °í·ÁÇÏ¿© ±× ÀÌ¿ô ³ëµåµé Áß¿¡ °¡Àå ÀûÇÕÇÑ ³ëµå¸¦ ¸ñÀûÁö ³ëµå±îÁö µ¥ÀÌÅÍ Àü´ÞÀ» À§ÇÑ ¼ö½Å ³ëµå¸¦ °áÁ¤ÇÑ´Ù. ½Ã¹Ä·¹ÀÌ¼Ç °á°ú´Â Á¦¾È ¹æ¾ÈÀÌ ±âÁ¸ÀÇ À§Ä¡ ±â¹Ý ¶ó¿ìÆà ÇÁ·ÎÅäÄݺ¸´Ù ´õ È¿À²ÀûÀÓÀ» º¸ÀδÙ.

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In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.

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AbstractComputable General Equilibrium (CGE) models are increasingly being used to project world food markets in order to support forward-looking policy analysis. Such projections hinge critically on the underlying functional form for representing consumer demand. Simple functional forms can lead to unrealistic projections by failing to capture changes in income elasticities of demand. We adopt as our benchmark the recently introduced An Implicitly Direct Additive Demand System (AIDADS) demand system and compare it with several alternative demand systems currently in widespread use in CGE models. This comparison is conducted in the context of projections for disaggregated global food demand using a global CGE model. We find that AIDADS represents a substantial improvement, particularly for the rapidly growing developing countries. For these economies, the most widely used demand systems tend to over-predict future food demands, and hence overestimate future production and import requirements for agricultural products.

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Purpose This study presents an empirical examination of Japan¡¯s short-run and long-run aggregate demand for imports, compared with the study on Korea¡¯s import, using quarterly economic data for the period 2000-2020 including aggregate imports, final consumption expenditure components, investment and relative price of imports.Design/Methodology/Approach - This paper has employed multivariate co-integration procedure and the short-run error correction model to find the existence of a cointegration and the relationship among variables in import demand function.Findings - This paper shows that the variables are all cointegrated and there exist significant differences with reference to different factors of final expenditure. Partial elasticities with respect to government expenditure, investment, exports and import prices are reported to be positive while imports seem to move negatively to changes in private consumption, in contrast to the case of Korea which shows that imports only move negatively with respect to investment. Export appears to indicate a relatively insignificant impact on Japan¡¯s aggregate imports in the long run. However, an vector error correction model demonstrates that only exports have an influence on the imports in the short run while, in Korea, the current period changes in the demand for imports are related only to the previous period changes in relative price of imports.Research Implications - This paper provides significant implications for policy makers in a nation seeking to improve the country¡¯s trade balances. Exchange rate policies in Japan appear to have significant long-term impact on Japan¡¯s import demand, but no significant effect in the short term. Policies to increase the private sector consumption could be of a crucial importance in decreasing aggregate imports in the long term, resulting in further improvement in Japan¡¯s balance of trade. In contrast to Japan, the exchange rate scheme has a short-term effect on Korea¡¯s demand for imports but not a long-term impact on the country¡¯s imports while investment component plays a key role in reducing imports in the long run, leading to enhancement in the Korea¡¯s balance of trade.

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ABSTRACTIn today's competitive market, demand volume and even the underlying demand distribution can change quickly for a newsvendor seller. We refer to sudden changes in demand distribution as demand shocks. When a newsvendor seller has limited demand distribution information and also experiences underlying demand shocks, the majority of existing methods for newsvendor problems may not work well since they either require demand distribution information or assume stationary demand distribution. We present a new, robust, and effective machine learning algorithm for newsvendor problems with demand shocks but without any demand distribution information. The algorithm needs only an approximate estimate of the lower and upper bounds of demand range; no other knowledge such as demand mean, variance, or distribution type is necessary. We establish the theoretical bounds that determine this machine learning algorithm's performance in handling demand shocks. Computational experiments show that this algorithm outperforms the traditional approaches in a variety of situations including large and frequent shocks of the demand mean. The method can also be used as a meta‐algorithm by incorporating other traditional approaches as experts. Working together, the original algorithm and the extended meta‐algorithm can help manufacturers and retailers better adapt their production and inventory control decisions in dynamic environments where demand information is limited and demand shocks are frequent

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This research is motivated by the capacity allocation problem at a major provider of customized products to the oil and gas drilling industry. We formulate a finite-horizon, discrete-time, dynamic programming model in which a firm decides how to reserve capacity for emergency demand and how to prioritize two classes of regular demand. While regular demand can be backlogged, emergency demand will be lost if not fulfilled within the period of its arrival. Since backlogging cost accumulates over time, we find it optimal for the firm to adopt a dynamic prioritization policy that evaluates the priorities of different classes of regular demand every period. The optimal prioritization involves metrics that measure backlogging losses from various perspectives. We fully characterize the firm's optimal prioritization and reservation policy. Those characterizations shed light on managerial insights.

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Abstract Saltwater recreational fishing in the North and Mid-Atlantic has steadily increased over the last two decades. A generalized demand model is applied in this study to examine the demand structure for recreational fishing in the Northeastern United States across three fishing modes: for-hire, private, and shore. Welfare variations are measured as changes in price scenarios. The overall demand for angler trips is found to be inelastic. Angler trips with private mode and for-hire mode fishing are sensitive to price changes, especially in New York and New Jersey; while, angler trips in Connecticut and Rhode Island are only responsive to the changes in private mode fishing. The model provides local policymakers with useful information on fishing regulations design. Highlights One of the first studies to apply a Generalized Demand Approach to analyze regional recreational fishing demand. The method provides a means to estimate angler demand elasticities. .Provides a means to estimate variations in welfare resulting from regulatory and policy changes.

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Implementation of new energy efficiency measures for the heating and building sectors is of utmost importance. Demand side management offers means to involve individual buildings in the optimization of the heat demand at city level to improve energy efficiency. In this work, two models were applied to forecast the heat demand from individual buildings up to a city-wide area. District heating data at the city level from more than 4000 different buildings was utilized in the validation of the forecast models. Forecast simulations with the applied models and measured data showed that, during the heating season, the relative error of the city level heat demand forecast for 48 h was 4% on average. In individual buildings, the accuracy of the models varied based on the building type and heat demand pattern. The forecasting accuracy, the limited amount of measurement information and the short time required for model calibration enable the models to be applied to the whole building stock. This should enable demand side management and lead to the predictive optimization of heat demand at city level, leading to increased energy efficiency.

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Abstract This study applies stated-preference choice experiments and accompanying surveys to examine how Subscription Video on Demand (SVoD) has disrupted film and television consumption. We examine demand for a large set of traditional consumption alternatives, such as cinema and free-to-air TV, as well as newer internet-based subscription services, such as Netflix. We consider a range of alternative-specific product attributes —including price, viewing quality, and release delay— that allow us to quantify substitution effects and willingness-to-pay estimates. In addition, we also consider illegal viewing alternatives, with associated attributes related to (potential) punishment that inform on the efficacy of policy against digital piracy. Our primary results reveal that while some traditional alternatives remain important, consumers derive significant utility from SVoD, which provides a large surplus at current pricing. We also observe that marginal effects and willingness-to-pay estimates are sensitive to ex-ante interest in a film or TV series. Moreover, we provide evidence that consumers can be segmented in relation to (survey-reported) piracy experience, as well as perceptions of punishment risk and (industry) damage associated with piracy. We also find some evidence that increasing punishment probability and fines may discourage illegal consumption. Finally, we provide some validation of our results with a follow-up survey conducted six months after the experiment. Highlights We use stated-preference experiments to examine how SVoD has disrupted film and TV consumption. We find consumers derive significant surplus from SVoD at current prices. We observe marginal effects and willingness-to-pay is sensitive to ex-ante interest in film and TV. We segment consumers by piracy experience and perceptions of punishment and (industry) damage.

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In this paper, we show that a group of Demand Response (DR) providing customers will benefit by transferring into a cooperative. While the benefit of aggregation is definite when unconstrained, this paper is devoted to studying benefits of a DR cooperative with a nonlinear piecewise objective function of minimizing net cost comprising energy charges and demand charges while being constrained by power system constraints and other physical constraints. We propose a two-level stochastic optimization formulation that provides a model for DR cooperatives to aggregate and schedule participating resources with the objective of minimizing the total electricity bill comprising energy and demand charges. It also provides a settlement tool for the cooperative to share costs and benefits among its members. In the first level, a stochastic mixed integer linear optimization formulation to minimize the total resource cost for the electricity market is solved considering various probabilistic scenarios to find locational marginal prices (LMPs) for 24-hours and the corresponding amount of DR scheduled for DR participants including the cooperative. In the second level, a linear optimization formulation is solved to schedule DR of cooperative members with the objective of minimizing the total electricity bill of the cooperative comprising energy and demand charges. Finally, we present a settlement tool to share the costs and benefits amongst the cooperative members, whereby all members benefit from reduced electricity bills. The proposed model was tested on modified IEEE 6-bus and 118-bus systems. The results conclusively demonstrate the benefit of the proposed cooperative model for DR where scheduling DR in concert by members has a pronounced effect in reducing demand charges for all more than that achieved by individual members minimizing their own electricity bills.

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Abstract The active participation of demand-side flexible resources in the wholesale market price formation and load dispatch process is crucial to encouraging demand-side participation. This calls for a joint supply-demand coordination mechanism to fully take advantage of the flexible resources in distribution systems, including distributed energy resources (DERs) and responsive loads (RLs). This paper aims at comparing and evaluating the centralized and transactive distribution-level market coordination mechanisms. We introduce the centralized and transactive demand-supply coordination mechanisms for the distribution-level market and elaborate on the structural difference between the two frameworks. Relevant metrics and test scenarios are proposed for a meaningful comparison. The key observations of the comparative study are generalized from the perspective of different entities in the market: fixed loads, flexible loads, DERs, and conventional generators. It is observed that while the centralized approach leads to socially optimum solutions, the transactive approach by allowing for competitive bidding at the distribution-level, results in clearing higher flexible demand, and thus higher electricity cost at the transmission-level. As a result, DERs and fixed loads receive a higher surplus in the centralized approach, while conventional generators and flexible loads are more profitable in the transactive approach. Highlights Describe centralized and transactive coordination for retail electricity market. Compare the economic performance of the different market coordination methods. Assess the economic impacts of the retail electricity markets on the participants.

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AbstractIntercepts of share equations generally include demand shift variables. In the Almost Ideal demand system and related models, this results in estimates that depend on units of measurement. Solutions to this problem are identified and discussed.

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In India, Rajasthan is endowed with the largest resources of high grade lead ore contributing 89% of the total resources of lead. Lead metal is used in various applications especially in the manufacture of lead acid battery which consumes about 74% of lead in the country. The balance 26% demand is in cable sheathing, alloys, pigments & compounds and other products such as sheets etc. More than 50% domestic demand of lead is met through imports and recycles lead. Limited reserve base of lead coupled with constrained domestic production and ever increasing demand, compounded on account of diverse industrial applications have aggrandized the strategic value of lead metal. The endeavour of this paper has been to relook in to the future domestic scenario of lead in respect of demand forecasting with coverage on both short-term and long-term perspective.

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Long‐term projections of global food demand are heavily dependent on which functional form of the food demand equation is used. Given that real incomes can change substantially over the long‐term, key elements are the dependence of the income elasticity on income, which ensures that the food budget share always lies within the [0, 1] range, and the role of income inequality. This article analyzes these issues, proposes a new functional form that deals with them, and presents estimates of income and price elasticities for food in 138 countries.

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Abstract Given a rational agent, demand for a habit-forming good is sensitive to uncertainty in future prices. In particular, price uncertainty reduces both the level and the price responsiveness of demand. These two effects, which may bear heavily on the efficacy of policies to discourage consumption of harmful addictive goods, can be tested by augmenting a simple demand model with a measure of price uncertainty. Modeling gasoline as a habit-forming good offers a succinct way to capture the investment and behavioral decisions that determine gasoline usage. An uncertainty-augmented model is therefore applied to gasoline demand across a panel of 29 countries, 1990–2011. Price uncertainty as proxied by a measure of forecast error does in fact depress the level and the price responsiveness of demand. This suggests that consumers care about the time-series process of gasoline prices, and that traditional demand models will systematically mis-predict the consumer reaction to any policy that tinkers with this process. Highlights Gasoline is an addictive or ‘habit-forming’ good. Rational consumers of a habit-forming good care about price uncertainty. Ignoring uncertainty may lead us to mispredict consumers' reaction to new policies. International data confirm that uncertainty dampens price responsiveness.

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AbstractIn many markets, demand adjusts slowly to changes in prices, i.e., demand is “viscous”. This viscosity gives each firm some monopoly power, since it can raise its price above that of its competitors without immediately losing all of its customers. The resulting equilibrium pricing behavior and market outcomes can differ significantly from what one would predict in the absence of demand viscosity. In particular, the model explains the importance of market share as an investment, as well as “kinked demand curves”. It also explains how apparently “competitive” pricing behavior can lead to outcomes that mimic those of collusion.

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This paper investigates the long-run relationship between electricity demand and real GDP (gross domestic product). In particular, this study explores the possibility of the lock-in effect by using the TAR (threshold autoregressive regression) and the regime switching regression models. When electricity demand dramatically increased between 2000 and 2010, lower relative price of electricity to the other energy sources was often considered as the main cause of an increase in electricity demand. However, electricity demand remains relatively high even after relative price of electricity has significantly risen since then. This study explains the observed asymmetric response of electricity demand using lock-in effect of real GDP. This study reports two important findings. First, this study confirms that electricity demand maintains a long-run relation with real GDP. Second, this study provides empirical evidence to support the presence of the lock-in effect of real GDP on electricity demand. The empirical result shows that electricity demand asymmetrically responses to the changes of GDP growth in the long-run. The empirical result of this study suggests that the possibility of asymmetric adjustment of variables must be taken into consideration when the future electricity demand is estimated.

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Disaggregated food demand projections for developing countries although essential for improved development planning and effective policy making, are rare. Moreover food demand projection models are usually based on aggregated, national-level data. In this article, under conditions of weak separability and multistage budgeting decisions, a structural model capable of generating regional-level food demand projections for a disaggregated set of commodities is developed and estimated using data from an Indonesian expenditure survey. Regional food demand projections in Indonesia obtained under a scenario assuming constant real prices are then combined into national-level estimates.

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The literature on the characterization of aggregate excess and market demand has generated three types of results: global, local, or 'at a point'. In this note, we study the relationship between the last two approaches. We prove that within the class of functions satisfying standard conditions and whose Jacobian matrix is negative semi-definite, only n/2+1 agents are needed for the 'at' decomposition. We ask whether, within the same class, the 'around' decomposition also requires only n/2+1 agents.

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Quasimonotone individual demand correspondences are characterized as those which can be rationalized (in a weak sense) by a complete, upper continuous, monotone, and convex preference relation. Moreover, it is shown that an arbitrary set of demand ob-servations can be rationalized by a reflexive, upper continuous, monotone and convex preference if and only if it is properly quasimonotone

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A retailer assortment is defined as a mix of products stocked in a retail store. The identification of proper assortment has become difficult in the current consumer-centric environment. Assortment planning (AP) in a retail chain largely depends on the estimation of demand of various products under consideration. The knowledge of the true demand rates and substitution rates is important for a retailer for a variety of management decisions, such as the ideal assortment to carry, the quantum of each item to be stocked and how often to replenish the stock (Anupindi, Dada & Gupta, 1998).Space elastic demand model is one of the models which have been widely used for demand estimation in retail AP literature. However, there is paucity of empirical studies in this field of research. In this article, the demand has been estimated using space elastic demand model for two product categories comprising 11 products within the category. The study illustrates the methodology for estimation of demand using space elastic demand model. The results obtained are consistent with the results obtained in few of the empirical studies done in other contexts.

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The type of shift in a kinked demand curve is shown to influence marginal revenue and hence the profit-maximizing price.

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This article tests the Fourier flexible form on quarterly U.S. monetary data. The data have been prescreened for consistency with the general axiom of revealed preference, and subindexes are formed using the Divisia approach. In this article, the global Fourier model fits well, although there is a potential problem of overfitting and certain data points exhibit behavior inconsistent with the model. The elasticities are variable over time, particularly around business-cycle troughs. It appears that financial asset demand surfaces are highly nonlinear and the many unsuccessful existing attempts to estimate money demand may not have worked well for this reason.

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AbstractThis paper analyzes consumer demand using a Quadratic Almost Ideal Demand System (QUAIDS), which is an extension of an Almost Ideal Demand System (a complete demand system). Complete demand system models can be used to find the relationships that are impossible to discover using single-equation models. Additionally, the QUAIDS model can be used to model a nonlinear Engel curve. The research was based on household microeconomic data collected by GUS (the Polish Central Statistical Office) in the period 1999-2015. The complete demand model has been extended by demographic variable. The results show that the QUAIDS model does not reduce to the AIDS model and is an adequate tool to analyze consumer demand.

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Abstract Effective management of demand information is a critical factor in the successful operation of autonomous mobility-on-demand (AMoD) systems. This paper classifies, measures and evaluates the demand information for an AMoD system. First, the paper studies demand information at both individual and aggregate levels and measures two critical attributes: dynamism and granularity. We identify the trade-offs between both attributes during the data collection and information inference processes and discuss the compatibility of the AMoD dispatching algorithms with different types of information. Second, the paper assesses the value of demand information through agent-based simulation experiments with the actual road network and travel demand in a major European city, where we assume a single operator monopolizes the AMoD service in the case study area but competes with other transportation modes. The performance of the AMoD system is evaluated from the perspectives of travelers, AMoD operators, and transportation authority in terms of the overall system performance. The paper tests multiple scenarios, combining different information levels, information dynamism, and information granularity, as well as various fleet sizes. Results show that aggregate demand information leads to more served requests, shorter wait time and higher profit through effective rebalancing, especially when supply is high and demand information is spatially granular. Individual demand information from in-advance requests also improves the system performance, the degree of which depends on the spatial disparity of requests and their coupled service priority. By designing hailing policies accordingly, the operator is able to maximize the potential benefits. The paper concludes that the strategic trade-offs of demand information need to be made regarding the information level, information dynamism, and information granularity. It also offers a broader discussion on the benefits and costs of demand information for key stakeholders including the users, the operator, and the society.

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