particular, to its applications to electricity markets (Hortacsu and Puller  and Wolak [2000b]). More precisely, our approach is structural but rather than estimating structural parameters from market data, we construct and artiﬁcial economy that we simulate and compare to observable data. On the other hand, our model, we believe, is richer and better suited than some of the mentioned studies to capture important aspects of many electricity markets. For example, we explicitly model electricity auctions as discrete bid auctions. This might not be an important limitation in markets where many bids are allowed like in Texas balancing energy market (Hortacsu and Puller ) but it can be important in markets as the British and Wales market where only three half hourly price bids are allowed. Also, as opposed to Hortacsu and Puller  we make no assumption about the functional form of bidding strategies. We share an important distinguishing aspect of this literature which is the attempt to identify agents preferences from observable data in order to built counterfactuals to predict behavior under dierent market conditions (for example a dierent auction format). This is in sharp contrast to a purely econometric tradition in which counterfactuals are based on comparing observable outcomes in dierent market mechanisms but with no predictive power of outcomes in unobserved dierent hypothetical market structures. 1 Finally, we rely on the private values
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straints including price uplifts. Similar to , revenue terms were approx- imated to mixed-integer linear expressions through the use of a binary ex- pansion approach , thereby increasing the number of binary variables. Finally, the performance of the resulting model was only illustrated with a small example that was solved by using commercially available software . It is worth emphasizing that the inclusion of price uplifts in electricity markets raises questions concerning transparency, eﬃciency, and equity [53,72, 98, 143]. Revenue constraints have also been accounted for in the analysis of market equilibria . Garc´ıa-Bertrand et al.  proposed a competitive market near-equilibrium including minimum proﬁt conditions, which comprise bilinear revenue terms. Such revenue constraints were linearized via an approximation based on Schur’s decomposition  requiring additional binary variables.
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On the other hand, the two-stage robust models described in [46, 71, 73, 142, 143] were devoted to energy-only electricity markets. References [46, 73] presented different uncertainty characterizations for wind power generation and demand. In , a new uncertainty set was devised to account for the correlation between both uncertainty sources. In , a multi-band uncertainty set was applied to increase the uncertainty modeling capability and thus reduce the conservativeness of the robust solution. Such an uncertainty characterization was implemented by generating multiple bands within the uncertainty set, which were indexed by discrete variables. Moreover, weighting factors were included to characterize the probability of uncertain parameters falling into each band. Both robust generation scheduling models [46, 73] were solved by the combined use of Benders decomposition and the outer- approximation algorithm. Reference  extended the work in  by incorporating transmission and generator outages as well as the operation of fast-acting generating units. The nonconvexity associated with the operation of such devices was addressed by a heuristic procedure based on Benders decomposition. In order to limit the worst-case redispatch cost, Ye et al. proposed in  the incorporation of a recourse cost requirement, which sets an upper bound on the corrective action cost. Moreover, a heuristic based on the column-and-constraint generation algorithm was developed to effectively solve the resulting robust optimization model. Similar to , a binary expansion approach was used in  to solve the network-constrained unit commitment problem under uncertain nodal net injections. In addition, two acceleration techniques were proposed to improve the computational performance. As a consequence, unlike in , the proposed solution approach was successfully tested on a larger benchmark such as the IEEE 118-bus system.
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The problem of determining the possible equilibria reached in a competitive electricity market, with strategic generators influencing the market’s clearance price, can be represented as a combinatorial problem or a constraint satisfaction problem (CSP). In this case, concurrent constraint programming (CCP) can be used to solve a CSP. Hence, as shown in(Londoño, 2012), it is possible to use constraint programming to analyze electricity markets, particularly with SFE models using step functions (block form). The SFE model has been widely used (Green & Newbery, 1992), (Von der Fehr & Harbord, 1993), (Berry, et al., 1999), (Anderson & Philpott, 2002), (Rudkevich, 2003), (Correia, et al., 2003), (Li & Shahidehpour, 2005), (Liu, et al., 2006), (Bompard, et al., 2006), (Yuan, et al., 2007), (Holmberg, 2008), (Hasan, et al., 2008), (Hasan & Galiana, 2008), (Gao & Sheblé, 2010), (Bompard, et al., 2010), (Sahraei- Ardakani & Blumsack, 2012) but seldom in block form (Von der Fehr & Harbord, 1993) which is closer to real market condition; besides, it is limited to a few participants. On the other hand, to consider bigger systems and with asymmetric generation companies (Gencos), many approaches have used linear SFE (Baldick, et al., 2004). Recently, a method that allows many asymmetric Gencos with multiple blocks (Hasan, et al., 2008) has been proposed, expressing the problem as a mixed integer linear program (MILP). However, computations times are still high in large systems and it is necessary the linearization of system equations for this kind of market. CCP, which is the proposed solution method in this paper for this kind of market, is a programming paradigm that reduces the search space of a problem using its constraints and makes a controlled search using distribution strategies; then, it is possible to find the market outcomes at low computation times. CCP allows also a much more natural modeling and the linearization of system equations for this kind of market is not necessary. In this way, the proposed solution method makes a contribution to the electricity market modeling problem with several Gencos and multiple blocks each. This
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2) A pool-based electricity market is considered in this chapter where a market operator clears the pool once a day, one day ahead, and on an hourly basis. The market operator seeks to maximize the social welfare considering the stepwise supply function offers submitted by producers and the demand function bids submitted by consumers. The market clearing results are hourly productions, consumptions and locational marginal prices (LMPs). 3) The clearing prices corresponding to the pool, i.e., the pool LMPs, are ob- tained as the dual variables associated with the balance constraints. Thus, the marginalist price theory is adopted .
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volume series in their specification and they find a significant impact of volume on volatility only in few markets, while in most of them they find no impact. Moreover, Kanamura and Ohashi (2007) try to link transition probabilities to current level of demand. Finally Karakatsani and Bunn (2004) include demand in the variance equation, specified by a GARCH(1,1), and they conclude that, when it was not impossible to get convergence, the impact of demand is not significant because the specified volatility model does not take into account extreme values. The problem of modelling extreme values is pervasive in electricity markets. To solve for this problem we suggest the following econometric approach. It is well known that electricity prices display pronounced spikes which are mostly due to power shortages. Modelling these spikes as random variables is difficult, since upward jumps are usually but not generally followed by downward jumps which bring back the price to the original level, see Cartea and Figueroa (2005) and Geman and Roncoroni (2006). It is economically sounder to consider prices at different levels following different regimes, see e.g. Kanamura and Ohashi (2004) and Escribano et al. (2002). Thus, following Huisman and Mahieu (2003); Guir-
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Abstract: In the context of the liberalization of electricity markets, forecasting prices is essential. With this aim, research has evolved to model the particularities of electricity prices. In particular, dynamic factor models have been quite successful in the task, both in the short and long run. However, specifying a single model for the unobserved factors is difficult, and it cannot be guaranteed that such a model exists. In this paper, model averaging is employed to overcome this difficulty, with the expectation that electricity prices would be better forecast by a combination of models for the factors than by a single model. Although our procedure is applicable in other markets, it is illustrated with an application to forecasting spot prices of the Iberian Market, MIBEL (The Iberian Electricity Market). Three combinations of forecasts are successful in providing improved results for alternative forecasting horizons.
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in generation and transmission assets. For instance, if the price at a location is consis- tently high, there may be several factors interacting such as lack of supply, congestion that prevents bringing power from other locations, and power losses. This may drive the at- tention of investors and after investing in increasing capacity, these conditions would be improved and electricity consumers may benefit from lower electricity prices. Deregulated electricity markets that use locational marginal pricing systems differ in their mechanisms. For instance, the Nord Pool presents 6 different regions that differ in price only when congestion occurs, but when congestion is not present the 6 regions have identic prices. Another example is the New York system, where 11 zones exist with prices that are cor- related but different. More information about locational marginal pricing can be found in Shahidehpour et al. (2002), and the web sites of the New York Independent System Opera- tor (http://www.nyiso.com/public/index.jsp, last visit 10 July 2010) and of the New England Independent System Operator (http://www.iso-ne.com, last visit 10 July 2010).
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In this paper we focus on a way to obtain the information requirements needed for water to be allocated efficiently. On the whole, information requirements for efficient water marketing are no greater than those needed for an effective administrative allocation of water (Easter, 1994). Besides it is shown herein that intra-sectoral water markets for irrigation can improve substantially the efficiency gained by other allocative mechanisms and approach the most profitable water allocation among the users within an irrigation district. This aproximation will be bigger the lower the transaction costs are, hence a comparisson is made. The optimal water allocation can also be attained through an institutional setting of water rights, as long as there is no informational constraints, making that the marginal benefit gained from every single plot of land within a district is the same. In this paper we study annalytically the way to do this when an irrigation water shortage is concerned.
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in specification (7) of table 2, and, therefore, is also significant at the one percent level. The confidence interval implies that the true demand elasticity is below 0.091 or above 0.481 with a 10 percent probability only. The demand elasticity in W2 is 0.151, with a much sharper confidence interval. The demand elasticity decreases to -0.2 for W3, but uncertainty about the estimate increases, so we cannot conclude that an additional bank with insufficient funds would actu- ally lower attainment. Note that this is not implausible given that congestion can occur in search markets. The supply elasticity is 0.479, 0.653, and -0.127 for W1, W2, and W3, respectively. The negative estimate arises when the Fed pumped liquidity into the system under the policy of quantitative easing. In plain English,
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Now consider implications for policy and practice in Malaysia and possibly in other countries. This research found that experience is an important part of building an investment decision making process. This importance of experience provides three implications for potential and current investment practitioners. Firstly, those wishing to become investment practitioners should accumulate their own experience of making investment decisions with real money in real markets in real time, or possibly with realistic simulations. The second aspect of experience that should interest practitioners is leveraging the experience of other practitioners by triangulating one’s own experience and knowledge, perhaps with research like this. A third implication for investment practitioners is the creation of knowledge through personal experience that could be done by reflective practice and other action reflection methodologies like action research or grounded theory (Sankaran, 2001; Dick, 1999; Sankaran et al., 2007). Note that the interpretation of data in this research is different from the standard reflection or evaluation that occurs in funds management firms. This qualitative method contained
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The first two findings are consistent with the existence of default punishments in the form of trade sanctions and exclusion from trade credit markets. Reduced im- ports should boost the performance of domestic producers which faced strong foreign competition before the default. Conversely, exporters are hurt by a loss of access to foreign markets and unavailability of export-linked credits. The links between asset tangibility and post-default performance do not have a clear counterpart in the lit- erature discussing the costs of default. I hypothesize that sovereign defaults result in a deterioration of private credit relationships. Those who are able to offer more collateral can partially offset the adverse effect, preserve access to credit, and thus grow faster than average.
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Islamic traditions and other confessions. This distinction of dominant denominational traditions becomes relevant; indeed, countries with a Catholic or Islamic majority reveal a greater level of participation (models 2 and 3). Nevertheless, these results do not allow for any discrimination between the respective explanatory capacities of both paradigms the secularization and the religious markets hypotheses.
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Since the 1960’s economic literature has produced broad discussion on health goods and services specific issues and markets. How the sector works and the effectiveness with which health services meet social needs are different from traditional competitive markets. Kenneth Arrow (1963) pointed out that health markets’ difference from competitive markets arises from: 1) the nature of its demand, which is marked by irregularity and unpredictability, thus restraining consumers ability to foresee or estimate demand for goods and services; 2) the expected behavior of physicians, as once product consumption and production takes place simultaneously, consumers cannot try products before using it; 3) the uncertainty in relation to the product’s quality, a reflex of huge information asymmetry in between those who buy and those who sell healthcare products; 4) supply conditions, since health activities require high levels of skills and regulation associated with licensing the activity and professionals involved. This poses strong barriers to new suppliers’ access to the market; 4) prices are not established according to market conditions, but to individuals’ level of income, and health institutions’ contracting mechanisms. These range from payment for medical care to pre-payment of assumed risk, associated with a set of prospective goods and services.
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country in the periphery wants to access the core of the network, it has to implement strategies for growth at the expense of other countries of similar status and rank position in the market, provided that the overall bipartite features do not significantly change over the years. This may also be the case because the rational thinking process would tell the country not to risk a strategy that implies a direct competition with a much larger exporter or importer, but rather competition against another player of a similar size, where the chances for a positive outcome are higher. If we also take in account that, the closer to the core a country is, the lower the probability for temporal variances to appear, we may conclude that it is this range of the occurrence distance where a larger number of dynamical phenomema take place as a consequence of the periphery countries trying to reach the core. The emerging phenomenon is that this competition force may be a systemic protection to keep the core robust and stable, but without denying the access, or at least the possibility of access, to the periphery exporters and importers. If this is the case, trade markets would not be a case of perfect competition, but they would be an approximation to it, as described in the economics literatureSamu48,Smith76.
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Es por ello que el presente artículo pretende mostrar la conceptualización del posicionamiento además indicar la importancia del nivel del posicionamiento en los clientes que frecuentan en los markets de Lima Este. El propósito es aportar como antecedente para las futuras investigaciones y contribuir a las cadenas de Markets para que identifiquen que aspectos valoran los consumidores, de tal modo que mejoren el desarrollo de productos y rediseñar las estrategias de marketing, así como de servicio.
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Risk calculation, in the form of beta estimation, is a key aspect of asset valuation. When assets do not trade as frequently as the market portfolio, the standard OLS beta exhibits thin trading bias. Several beta adjustment techniques exist to correct for this bias; however, no consensus exists as to which adjustment is best. This paper compares the behavior of the most widely used beta adjustments proposed in the literature in a comprehensive group of emerging markets. Using a linear programing model, we form portfolios with equal risk characteristics, but different levels of censoring. Since beta is a measure of systematic risk, if most risk factors are kept constant across portfolios, the resulting betas should be approximately the same. Our results show that beta adjustments based on trade-to-trade returns perform best. Specifically, the best overall adjustment is the sample selectivity adjustment, which provides up to a 41% improvement over OLS betas.
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All three essays are motivated by real life importance of these issues. The …rst essay was motivated by the concerns about the stock market performance during the oil prices increases 2003 – 2007 and the repeatedly appearing comments in the …nancial press about the negative impact of these oil price peaks on the daily stock market results. The second essay discusses the changes in correlations between Central and Eastern European stock markets and Western Eu- ropean stock markets when these Central and Eastern European countries joined the European Union in 2004 and the possible changes in the prospects of these countries as the investment op- portunity. The third essay analyzes the volatility of the Spanish stock index (IBEX 35) and the Dow Jones Industrial Average over the last 20 years concentrating heavily on the last …nancial crisis and high levels of volatility not seen before.
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Participants in these markets are on one hand the actors involved in these markets are known as market units, and basically distinguishes between producers and qualified consumers. It can also be a qualified consumer who goes to a wholesale market to purchase energy is typically a marketer or a large direct consumer. The traders then formalize contracts with small consumers, households and businesses, to resell the electricity purchased, thus obtaining a profit for the role of intermediaries. In this way is generated a retail market where final consumers have the choice that marketer that offers more advantageous contracts.
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electricity sector in Mexico. In doing the latter, it also provides evidence to explain public opinion’s reaction to privatization. Surveys like the one mentioned above have an urban bias and, as it shall be hereby shown, privatization tends to affect urban middle classes who use to benefit from generalized subsidies that state-owned enterprises (SOEs) typically provide (see López-Calva, 2001). Consumption of certain commodities like electricity is highly unequal and generalized subsidies are in turn regressive. In the case of Mexico, the latter situation will be aggravated by the fact that the logic behind electricity subsidies does not have any distributional basis. Quite on the contrary, subsidies are based on average temperature in the location, while relatively poorer people tend to be less protected against harsh weather than people who are relatively better-off. Even though this paper only discusses in detail the case of subsidies for domestic consumption, subsidized rates for agricultural use, for example, also have a seriously regressive logic by supplying electricity for irrigation systems at considerably lower prices –around 15% of its cost—than those for other use, while it is clear than the poorer regions in agriculture only possess rain-fed lands.
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