the non linear link between electricity consumption and temperature in europe a threshold panel approach this paper investigates the relationship between electricity demand and temperature in the european union we address this issue by means of a panel threshold regression model on 15 european countries over the last two decades our results confirm the non linearity of the link between electricity consumption and temperature found in more limited geographical areas in previous studies by distinguishing between north and south countries we also find that this non linear pattern is more pronounced in the warm countries finally rolling regressions show that the sensitivity of electricity consumption to temperature in summer has increased in the recent period

commodities momentum a behavioral perspective the growth in commodity related investments has sparked interest in the performance of momentum strategies in these markets this paper introduces a behavioral proxy of the 52 week high and low momentum that explains a significant proportion of the variation of conventional momentum returns after controlling for commodity specific risk factors our findings show that the 52 week high strategy generates significant profits after accounting for transaction costs we report that the 52 week high strategy is a better predictor of returns than conventional momentum our findings suggest that term structure and hedging pressure risk factors provide only a partial explanation of the results

on price competition with complementary goods we consider a duopoly industry with two separate firms each selling an indivisible product the joint consumption of these goods has a specific value for the consumers which exceeds the mere addition of utilities when products are consumed in isolation the higher this excess the larger the complementarity between the goods we analyse price equilibria in this market as related to the degree of complementarity existing between the two products

forecasting quantiles of day ahead electricity load accurate load forecasting plays a crucial role in the decision making process of many market participants but probably is most important for the dispatch planning of an electricity market operator despite the competitive forecast accuracy achieved by existing point forecast models point forecasts can only provide limited information relating to the expected level of future load to account for the uncertainty of future load and provide a more complete picture of the future load conditions for dispatch planning purposes quantile forecasts can be useful this paper proposes a computationally efficient approach to forecasting the quantiles of electricity load which is then applied to forecasting in the national electricity market of australia the proposed model performs competitively in comparison with one industry standard and two recently proposed quantile forecasting methods one of the main advantages of the proposed approach is the ease with the number of covariates can be expanded this is a particularly important feature in the context of load forecasting where large numbers of important drivers are usually necessary to provide accurate load forecasts

quality coordination and complementary products this article models the choice of price and quality where products are complementary and components can be provided by either one or two monopolists the firms have to choose price and quality simultaneously but can coordinate in the latter dimension we consider two specifications for the quality of the composite good bottleneck and additive set ups in both cases a single monopolist may produce lower quality as compared to dual ownership if the latter is modelled as a single stage quality and price setting game when separate markets for components of the composite good are added to the model we provide an example where dual ownership leading to higher quality also yields higher consumer surplus but not total welfare than a single monopolist

probabilistic forecasts of the magnitude and timing of peak electricity demand adequate capacity planning requires accurate forecasts of the future magnitude and timing of peak electricity demand electricity demand is affected by the day of the week seasonal variations holiday periods feast days and the weather a model that provides probabilistic forecasts of both magnitude and timing for lead times of one year is presented this model is capable of capturing the main sources of variation in demand and uses simulated weather time series including temperature wind speed and luminosity for producing probabilistic forecasts of future peak demand having access to such probabilistic forecasts provides a means of assessing the uncertainty in the forecasts and can lead to improved decision making and better risk management

dynamic demand for residential electricity in taiwan under seasonality and increasing block pricing abstract this paper studies the dynamic demand for residential electricity in taiwan employing a monthly panel data set composed of 19 counties and spanning the period from 2007 01 to 2013 12 the partial adjustment model used addresses the endogeneity of the electricity price that results from the increasing block pricing the estimated results show that there is a significant seasonal difference in the demand for electricity between the summer and non summer periods both the adjustment speed and own price elasticity during the summer months are found to be lower than those in the non summer months due to the hot weather in summer it is easier for consumers to adjust their electricity consumption in response to the changes in electricity pricing during the non summer time the estimated inelastic short run and long run income effects show that electricity is a necessity for consumers moreover the controversial electricity conservation policies are found to be ineffective measures for reducing electricity consumption in taiwan

the dynamics of electricity demand in pakistan a panel cointegration analysis abstract this paper examines the dynamics of electricity demand in pakistan at the aggregate and sectoral levels over the period 1978 2012 panel cointegration test and fully modified ordinary least squares method is employed to determine the long run relationship between electricity consumption real income real price of electricity and domestic price of non energy products the results reveal that electricity demand is more responsive to changes in income than changes in prices at the aggregate and disaggregate levels short run and long run income elasticities are positive and statistically significant supporting the conservation hypothesis it appears from the results that long run price elasticities are negative and significant at the aggregate level and for the agriculture commercial residential sectors and public utilities the short run price elasticities are significant but low in magnitude which implies that changes in electricity price exert minimal effect on the electricity consumption in pakistan the domestic price of non energy products is positive and significant for aggregate sample in the short run the domestic price of non energy products exert significant negative positive impact on electricity demand in the agriculture industrial sectors the results thus provide important information to the agents operating in the electricity market regarding the income and pricing policies and helps in planning the future strategy of electricity demand management

modelling weather effects for impact analysis of residential time of use electricity pricing abstract analyzing the impact of pricing policies such as time of use tou is challenging in the presence of confounding factors such as weather motivated by a lack of consensus and model selection details in prior work we present a methodology for modelling the effect of weather on residential electricity demand the best model is selected according to explanatory power out of sample prediction accuracy goodness of fit and interpretability we then evaluate the effect of mandatory tou pricing in a local distribution company in southwestern ontario canada we use a smart meter dataset of over 20 000 households which is particularly suited to our analysis it contains data from the summer before and after the implementation of tou pricing in november 2011 and all customers transitioned from tiered rates to tou rates at the same time we find that during the summer rate season tou pricing results in electricity conservation across all price periods the average demand change during on peak and mid peak periods is 2 6 and 2 4 respectively changes during off peak periods are not statistically significant these tou pricing effects are less pronounced compared to previous studies underscoring the need for clear reproducible impact analyses which include full details about the model selection process

effect of stopping hydroelectric power generation on the dynamics of electricity prices an event study approach abstract supply shocks in electricity markets that disrupt energy production cause unexpected spikes in prices which in turn have economic consequences such as higher risk and therefore higher costs and losses for producers and consumers of electricity one relevant shock in this sector is the halting of hydroelectric power generation due to the freezing of water reservoirs after the temperature drops below zero degrees celsius and therefore less efficient technologies such as thermal plants must begin to produce electricity using an event study approach this shock in the nord pool market is explicitly identified and the economic importance of expanding the interconnected market and the inclusion of more renewable sources in the generation mix of the system to smooth out price spikes is quantified when a freezing event occurs it is found that the average electricity prices increase between 1 and 6 and that the negative relationship between temperature and prices also increases for each degree that the temperature decreases prices increase between 1 and 3 however as expected these changes are more pronounced in countries that are most dependent on hydropower generation by identifying this supply shock relevant insights are presented for market players such as policy makers investors and consumers and producers whose decisions are influenced by the effect of temperature particularly when it causes the stopping of hydroelectric plants

forecasting scenarios for uk household expenditure and associated ghg emissions outlook to 2030 using the modelling tool elesa econometric lifestyle environment scenario analysis this paper describes forecast scenarios to 2030 for uk household expenditure and associated direct and indirect greenhouse gas ghg emissions for 16 expenditure categories using assumptions for real household disposable income real prices exogenous non economic factors exnef average uk temperatures and ghg intensities three future scenarios are constructed in each scenario real expenditure for almost all categories of uk expenditure continues to grow up to 2030 the exceptions being alcoholic beverages and tobacco and other fuels and gas and electricity in the low scenario leading to an increase in associated ghg emissions for most of the categories in the reference and high scenarios other than food and non alcoholic beverages alcoholic beverages and tobacco electricity other fuels and recreation and culture of the future ghg emissions about 30 is attributed to direct energy use by households and nearly 70 attributable to indirect energy uk policy makers therefore need to consider a range of policies if they wish to curtail emissions associated with household expenditure including for example economic measures such as taxes alongside measures that reflect the important contribution of exnef to changes in expenditure for most categories of consumption

residential energy demand for space heating in the nordic countries accounting for interfuel substitution abstract reliable estimation of fuel consumption in residential sector is crucial for the future development of fuel supply system three approaches are compared in this study to capture climate impact as well as and interfuel substitution between fuels on residential fuel consumption for space heating in the nordic countries the first approach aims at directly estimating the demand for each energy carrier as a function of explanatory variables including heating degree days fuels price and gdp per capita the second approach is a two stage model combing an econometric model for total energy use for space heating and the market share for energy carriers based on cross price elasticities while in the third approach a set of simultaneous equations models were estimated based on the results of the mean average error and root mean square error criteria for three approaches across the nordic countries it was found that the second and third approaches were able to capture the complementary and substitution effects between fuels this finding confirms our hypothesis that the interfuel substitution is a key factor for estimating changes in fuel demand and should be accounted for when residential energy demand is projected the results additionally have important implications for climate change policy by exploring the impact of fuel price on residential energy demand for space heating

modeling energy demand some emerging issues abstract the proliferation of papers on energy demand modeling has offered different dimensions both in terms of methodology and estimation while this development has strengthened our understanding of the subject it may render the identification of gaps in the literature arduous for future research thus this study sets out to document some emerging issues that seem to have engendered new directions on energy demand modeling ranging from asymmetric price responses time varying demand parameters triangulation analyses to seasonal and climate change effects it is hoped that access to this review complemented with the previous ones will facilitate the comprehension of the extant literature as well as areas of future research in energy demand modeling

competition and integration among complements and network market structure this article analyzes the competition and integration among complementary products that can be combined to create composite goods or systems the model generalizes the cournot duopoly complements model to the case in which there are multiple brands of compatible components it analyzes equilibrium prices for a variety of organizational and market structures that differ in their degree of competition and integration the model applies to a variety of product networks including automatic teller machines real estate multiple listing services and airlines crs as well as to nonnetwork markets of compatible components such as computer cpus and peripherals hardware and software and long distance and local telephone services copyright 1992 by blackwell publishing ltd

residential electricity demand in spain new empirical evidence using aggregate data this paper presents an empirical analysis on residential demand for electricity this analysis has been performed using aggregate panel data at the province level for 47 spanish provinces for the period from 2000 to 2008 for this purpose we estimated a log log demand equation for electricity consumption using a dynamic partial adjustment approach this dynamic demand function has been estimated using a two step system gmm estimator proposed by blundell and bond 1998 the purpose of this empirical analysis is to highlight some of the characteristics of spanish residential electricity demand particular attention has been paid to the influence of price income and weather conditions on electricity demand the estimated short and long run own price elasticities are negative as expected but lower than 1 furthermore weather variables have a significant impact on electricity demand

modeling special day effects for forecasting intraday electricity demand abstract we propose and apply a novel approach for modeling special day effects to predict electricity demand in korea notably we model special day effects on an hourly rather than a daily basis hourly specified predictor variables are implemented in the regression model with a seasonal autoregressive moving average sarma type error structure in order to efficiently reflect the special day effects the interaction terms between the hour of day effects and the hourly based special day effects are also included to capture the unique intraday patterns of special days more accurately the multiplicative sarma mechanism is employed in order to identify the double seasonal cycles namely the intraday effect and the intraweek effect the forecast results of the suggested model are evaluated by comparing them with those of various benchmark models for the following year the empirical results indicate that the suggested model outperforms the benchmark models for both special and non special day predictions

cheap talk games may have unique informative equilibrium outcomes abstract we demonstrate that cheap talk games can have unique informative equilibrium outcomes by providing an example of an infinite action bayesian game which absent cheap talk does not possess an equilibrium

abatement and allocation in the pilot phase of the eu ets we use historical industrial emissions data to assess the level of abatement and over allocation that took place across european countries during the pilot phase 2005 2007 of the european union emission trading scheme using a dynamic panel data model we estimate the counter factual business as usual emissions scenario for eu member states comparing this baseline to allocated and verified emissions we find that both over allocation and abatement occurred along with under allocation and emissions inflation over the three trading years of the pilot phase we find over allocation of approximately 280 million euas and total abatement of 247 mt co2 however we calculate that emissions inflation of approximately 73 mt co2 also occurred possibly due to uncertainty about future policy design features

stochastic factor model for electricity spot price the case of the nordic market this paper presents a stochastic factor based approach to mid term modeling of spot prices in deregulated electricity markets the fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail paper shows realistic numerical examples on the forerunner scandinavian electricity market the model is used to price an exotic electricity derivative

forecasting risks of natural gas consumption in slovenia abstract efficient operation of modern energy distribution systems often requires forecasting future energy demand this paper proposes a strategy to estimate forecasting risk the objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance based on the risk model the strategy combines an energy demand forecasting model an economic incentive model and a risk model basic guidelines are given for the construction of a forecasting model that combines past energy consumption data weather data and weather forecast the forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation the risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems cash flow the economic model defines the critical forecasting error levels that most strongly influence cash flow based on the forecasting model and the economic model the development of a risk model is proposed the risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data month day of the week and temperature the risk model is applicable to estimating the daily forecasting risk based on the influential parameters the proposed approach is illustrated by a case study of a slovenian natural gas distribution company

temperature and seasonality influences on spanish electricity load abstract deregulation of the spanish electricity market in 1998 and the possible listing of electricity or weather derivative contracts have encouraged the study of the relationship between electricity demand and weather in spain in this paper a transfer function intervention model is developed for forecasting daily electricity load from cooling and heating degree days the influence of weather and seasonality is proved and is significant even when the autoregressive effects and the dynamic specification of the temperature are taken into account the estimated general model shows a high predictive power the results and information presented in this paper could be of interest for current users and potential traders in the deregulated spanish electricity market

indications for a changing electricity demand pattern the temperature dependence of electricity demand in the netherlands abstract this study assesses the electricity demand pattern in the relatively temperate climate of the netherlands latitude 52 30 n daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of electricity demand we hypothesize that the increased use of cooling applications has shifted the temperature dependence of electricity demand upwards in summer months our results show significant increases in temperature dependence of electricity demand in may june september october and during the summer holidays during the period studied temperature dependence in these months has shifted from negative to positive meaning that a higher temperature now leads to an increased electricity demand in these months rather than a decreased demand as observed historically although electricity demand in countries with moderate summer temperatures such as the netherlands generally peaks in winter months and shows a minimum in summer months this trend may signal the development of an additional peak in summer especially given the expected climatic change as power generating capacity may be negatively influenced by higher temperatures due to decreasing process cooling possibilities an increasing electricity demand at higher temperatures may have important consequences for power generation capacity planning and maintenance scheduling

communication in bargaining over decision rights abstract this paper develops a model of bargaining over decision rights between an uninformed principal and an informed but self interested agent we introduce two different bargaining mechanisms tacit and explicit bargaining in tacit bargaining an uninformed principal makes a take it or leave it price offer to the agent who then decides whether to accept or reject the offer in the equilibrium of the game the principal inefficiently screens out some agent types so that the agent s private information cannot be fully utilized when the decision is made in explicit bargaining in which parties can communicate explicitly via cheap talk before tacit bargaining however an equilibrium with no such inefficient screening exists even when the conflict of interest is arbitrarily large we also follow a mechanism design approach showing that under certain conditions explicit bargaining is an optimal bargaining mechanism that maximizes the joint surplus of the parties

estimation of tourism induced electricity consumption the case study of balearics islands spain tourism has started to be acknowledged as a significant contributor to the increase in environmental externalities especially to climate change various studies have started to estimate and compute the role of the different tourism sectors contributions to greenhouse gas ghg emissions these estimations have been made from a sectoral perspective assessing the contribution of air transport the accommodation sector or other tourism related economic sectors however in order to evaluate the impact of this sector on energy use the approaches used in the literature consider tourism in its disaggregated way this paper assesses the electricity demand pattern and investigates the aggregated contribution of tourism to electricity consumption using the case study of the balearic islands spain using a conventional daily electricity demand model including data for daily stocks of tourists the impact of the different population growth rate scenarios on electricity loads is also investigated the results show that in terms of electricity consumption tourism cannot be considered a very energy intensive sector

residential energy demand in the united states analysis using static and dynamic approaches abstract the residential sector is the main consumer of energy in the united states and reducing energy consumption is an important goal for policymakers in each state to know how reducing residential energy demand could be achieved this study develops a set of static and dynamic models to investigate and identify the impact of socio economic and demographic characteristics building age energy prices and weather conditions on residential energy demand at the state level from 2005 to 2013 next this study proposes two alternative scenarios to reduce residential energy demand based on the most precise model for every 10 000 dollars of per capita income in each state 1 increasing residential electricity price by 1 cent per kw h and 2 decreasing average building age by 1 in the first scenario the findings indicate that annual residential electricity demand would decrease by 7 3 on average with the highest reductions in washington 11 9 north dakota 10 9 and idaho 9 7 in the second scenario residential gas demand would decrease by an average of 15 8 annually with the highest reduction in connecticut 33 2 followed by new york 33 0 and massachusetts 30 7 these proposed scenarios assist policymakers in optimizing decisions and investments to reduce residential energy consumption

congestion management rules and trading strategies in the spanish electricity market abstract this paper analyses the economic incentives embodied in the rules governing the resolution of transmission constraints in the spanish wholesale electricity market and the way these incentives may have influenced on the trading behaviour of both the generators and the demand side the evidence obtained is consistent with them responding to these incentives in particular buyers would respond to the way congestion costs are billed to them by abandoning the daily market in favour of the intraday market as far as possible additionally some strategic generators may have been prompted the system operator to require them to inject electricity into the system to solve network congestions finally these results may contribute to shed light on what should be expected of the reform in the aforementioned rules

pricing decisions for complementary products with firms different market powers abstract this article reports the results of a study that explores the pricing problems with regard to two complementary products in a supply chain with two manufacturers and one common retailer the authors establish five pricing models under decentralized decision cases including the ms bertrand ms stackelberg rs bertrand rs stackelberg and ng models with consideration of different market power structures among channel members by applying a game theoretical approach corresponding analytic solutions are obtained then by comparing the maximum profits and optimal pricing decisions obtained in different decision cases interesting and valuable managerial insights are established

an empirical analysis of electricity consumption in cyprus abstract the paper presents the first empirical analysis of electricity consumption in cyprus using annual data from 1960 to 2004 we have examined electricity use in the residential and the services sectors which are the fastest growing electricity consumers in the island and its interaction with income prices and the weather the analysis was performed with the aid of time series analysis techniques such as unit root tests with and without a structural break in levels cointegration tests vector error correction models granger causality tests and impulse response functions results show long term elasticities of electricity use above unity for income and of the order of 0 3 to 0 4 for prices in the short term electricity consumption is rather inelastic mostly affected by weather fluctuations granger causality tests confirm exogeneity of electricity prices and bidirectional causality between residential electricity consumption and private income the commercial sector is less elastic and reverts faster to equilibrium than the residential sector despite the relatively small sample size results reported here are quite robust and can be used for forecasts and policy analyses

impact of temperature on electricity demand evidence from delhi and indian states abstract electricity for cooling improves health and quality of life and is an important mode of adapting to extreme weather conditions and to climate change this study measures the change in electricity demand in response to weather shocks at the household level in delhi and at various aggregate levels in india our econometric analysis uses a semi parametric model to capture the nonlinearity of short run temperature response on average aggregate electricity demand in india increases by 11 or more at temperatures above 30 c from demand at temperatures of 21 24 c with substantial heterogeneity across states aggregate demand in delhi increases by 30 or more at temperatures above 30 c using rich micro data on electricity demand in delhi we do a first of its kind estimation of household level temperature response we find evidence that low income consumers especially those living in slums show limited incremental response to high temperatures likely due to an absence of cooling options these findings underscore the need to improve our understanding of the constraints posed by poverty on climate change adaptation and for interventions to mitigate risks of heat stress among the poor this also suggests rising affluence will lead to sharp increases in electricity demand for cooling

combining momentum with reversal in commodity futures this paper examines profitable trading strategies that jointly exploit momentum and reversal signals in commodity futures while the single sort momentum strategies returns 11 14 per annum on average a consistent reversal pattern of momentum profits is pronounced from 12 to 30 months after portfolio formation combining the observed reversal pattern with the momentum signal our double sort strategy returns 20 24 per annum which significantly outperforms single sort strategies the proposed strategy is robust to seasonality effects and sample adjustments in commodity futures the profitability of the double sort strategy cannot be explained by standard risk factors term structure market volatility investor sentiment data mining or transaction costs but appears to be related to global funding liquidity as a consequence the double sort strategy in commodity futures may be employed as a portfolio diversification tool

spot price modeling and the valuation of electricity forward contracts the role of demand and capacity we propose a model where wholesale electricity prices are explained by two state variables demand and capacity we derive analytical expressions to price forward contracts and to calculate the forward premium we apply our model to the pjm england and wales and nord pool markets our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive both of which exert an upward seasonal pressure on the price of forward contracts we assume that both volatility of capacity and the market price of capacity risk are constant and find that depending on the market and period under study it could either exert an upward or downward pressure on forward prices in all markets we find that the forward premium exhibits a seasonal pattern during the months of high volatility of demand forward contracts trade at a premium during months of low volatility of demand forwards can either trade at a relatively small premium or even in some cases at a discount i e they exhibit a negative forward premium

electricity demand elasticities and temperature evidence from panel smooth transition regression with instrumental variable approach abstract this study applies a non linear model i e the recently developed panel smooth transition regression pstr model and takes into account the potential endogeneity biases to investigate the demand function of electricity for 24 oecd countries from the period 1978 2004 our empirical results demonstrate that there is a strongly non linear link among electricity consumption real income electricity price and temperature a result that is new to the literature as real income rises electricity consumption rapidly increases first and after the level of real income exceeds approximately us 2500 its increasing rate turns slow down an increase in electricity price has a negative or no influence on electricity consumption evidence of a u shaped relationship between electricity consumption and temperature is supported and the threshold value of temperature is approximately 53 f which is endogenously determined furthermore the estimated elasticities of time dynamic indicate that electricity demand is income inelastic price inelastic and temperature inelastic as time goes on the absolute elasticities of electricity demand gradually decrease with respect to real gdp and electricity price whereas they gradually increase with respect to temperature suggesting that the impact of temperature on electricity demand is becoming more important in recent years

prediction of daily peak electricity demand in south africa using volatility forecasting models abstract daily peak electricity demand forecasting in south africa using a seasonal autoregressive integrated moving average sarima model a sarima model with generalized autoregressive conditional heteroskedastic sarima garch errors and a regression sarima garch reg sarima garch model is presented in this paper the garch modeling methodology is introduced to accommodate the possibility of serial correlation in volatility since the daily peak demand data exhibits non constant mean and variance and multiple seasonality corresponding to weekly and monthly periodicity the proposed reg sarima garch model is designed in such a way that the predictor variables are initially selected using a multivariate adaptive regression splines algorithm the developed models are used for out of sample prediction of daily peak demand a comparative analysis is done with a piecewise linear regression model results from the study show that the reg sarima garch model produces better forecast accuracy with a mean absolute percent error mape of 1 42

the demand for electricity in israel quarterly data for israel are used to compare and contrast three dynamic econometric methodologies for estimating the demand for electricity by households and industrial companies these are the dynamic regression model and two approaches to cointegration ols and maximum likelihood since we find evidence of seasonal unit roots in the data we also test for seasonal cointegration we find that the scale elasticities are similar in all three approaches but the ols price elasticities are considerably lower moreover ols suggests non cointegration the paper concludes by stochastically simulating the drms to calculate upside risk in electricity demand