the value of gas fired power plants in markets with high shares of renewable energy a real options application abstract using a real options model this paper quantifies a gas fired power plant s operating value and the value of a new investment against the background of a market transition to renewable electricity the model is run with recent data for germany s power sector and for different types of gas fired power plants the result is twofold first the paper achieves a more realistic value by improving on existing models it models electricity and gas prices as a two dimensional stochastic process each component consisting of the sum of a seasonal pattern and a mean reverting process it uses high granularity by modelling hourly time steps and it incorporates power plant ramping times and costs second it compares two types of power plant models one with daily and one with hourly operating decisions and thereby quantifies the value of a plant s intraday flexibility the hourly model replicates operators and investors decision making accurately this is evidenced by the fact that the results trace current major developments like the recent decline and come back of gas fired generation in germany the paper contributes to a better understanding of the choices operators and investors face in current electricity markets in the absence of large scale storage solutions flexible supply of electricity as provided by gas is important in the transition to renewable energies in germany and across europe

combining day ahead forecasts for british electricity prices abstract this paper considers how well the approach of combining forecasts extends to the context of electricity prices with the increasing popularity of regime switching and time varying parameter models for predicting power prices the multi model and evolutionary considerations that usually support the combining of simpler time series methods may be less applicable when the individual models incorporate these features we address this question with a backtesting analysis on british day ahead prices furthermore given the volatility of power prices and concerns about accurate forecasting under extreme price excursions we evaluate the results using various error metrics including expected shortfall the comparisons are furthermore carefully simulated to consider model selection uncertainty in order to realistically test the value of combining as an ex ante policy overall our results support combining for both accurate operational planning and risk management

a spot forward model for electricity prices with regime shifts 2014 elsevier b v all rights reserved this is the authors manuscript preprint to the article

causal relationship between telecommunications and economic growth in china and its regions shiu a and lam p l causal relationship between telecommunications and economic growth in china and its regions regional studies this paper studies the causal relationship between telecommunications development and economic growth of china its result indicates that there is a unidirectional relationship running from real gross domestic product gdp to telecommunications development at the national level causality running from telecommunications development to real gdp is found only in the provinces in the affluent eastern region but not in the low income central and western provinces the results imply that an improvement in telecommunications infrastructure alone is not sufficient for stimulating growth in the central and western provinces it is equally important for the chinese government to develop and enhance other complementary factors like business environments transportation networks education and manpower training in order to make the best use of the telecommunications systems in the ce

the impact of renewable energy forecast errors on imbalance volumes and electricity spot prices abstract this paper contributes to the general consideration of whether a policy of incentivising system operators to improve the quality and market availability of forecasts for renewable energy outputs would be beneficial using data from the german electricity market we investigate the effect of wind and solar energy forecasts errors on imbalance volumes and subsequent spot electricity prices we use ordinary least squares regression quantile regression and autoregressive moving averages to identify these relationships using variables that have a quarter hourly data granularity the results show that higher wind and solar forecast errors increase the absolute values of imbalance volumes and that these can pass through into higher spot prices we find that wind forecast errors in germany impact spot prices more than solar forecasting errors policy incentives to improve the accuracy and availability of renewable energy forecasts by the system operators should therefore be encouraged

robust estimation and forecasting of the long term seasonal component of electricity spot prices when building stochastic models for electricity spot prices the problem of uttermost importance is the estimation and consequent forecasting of a component to deal with trends and seasonality in the data while the short term seasonal components daily weekly are more regular and less important for valuation of typical power derivatives the l ong term seasonal components ltsc seasonal annual are much more diffi cult to tackle surprisingly in many academic papers dealing with electricity spot price modeling the importance of the seasonal decomposition is neglected and the problem of forecasting it is not considered with this paper we want to fill the gap and present a thorough study on estimation and forecasting of the ltsc of electricity spot prices we consider a battery of models based on fourier or wavelet decomposition combined with linear or exponential decay we find that all considered wavelet base d models are significantly better in terms of forecasting spot prices up to a year ahead than all considered sine based models this result questions the validity and usefulness of stochastic models of spot electricity prices built on sinusoidal long term seasonal components

the hodrick prescott filter the slutzky effect and the distortionary effect of filters abstract i construct a metric based on optimal filtering for measuring the distortionary effect of business cycle filters the distortionary effect of a filter depends both on the power transfer function of the filter and on the spectrum of the filtered time series the metric is used for two purposes first to determine the optimal value of the smoothing parameter in the hodrick prescott filter hp filter secondly to measure the size of distortions of ten different filters the slutzky effect is a special case of a more general pattern of distortions and it is shown that the alleged slutzky effect of the hp filter is due to an insufficient distinction between the effect of filtering with an ideal high pass filter and the distortionary effect of the hp filter

long term swings and seasonality in energy markets abstract this paper introduces a two factor continuous time model for commodity pricing under the assumption that prices revert to a stochastic mean level which shows smooth periodic fluctuations over long periods of time we represent the mean reversion price by a fourier series with a stochastic component we also consider a seasonal component in the price level an essential characteristic of many commodity prices which we represent again by a fourier series we obtain analytical pricing expressions for futures contracts using futures price data on natural gas we provide evidence on the presence of long term fluctuations and show how to estimate the long term component simultaneously with a seasonal component using the kalman filter we analyse the in sample and out of sample empirical performance of our pricing model with and without a seasonal component and compare it with schwartz and smith 2000 model our findings show the in sample and out of sample superiority of our model with seasonal fluctuations thereby providing a simple and powerful tool for portfolio management risk management and derivative pricing

factor models in the german electricity market stylized facts seasonality and calibration abstract the class of arithmetic factor models is flexible enough to model all stylized facts occurring in electricity markets including negative prices while still yielding tractable derivative prices in this paper we conduct a thorough review of the requirements and possibilities of factor models we compare different seasonality functions and study their power to deseasonalise day ahead spot prices from the epex germany austria market furthermore we introduce an alternative method to estimate mean reversion speed based on arma time series and a method to evaluate the distributional fit of the model to realised market prices which we apply to two non gaussian estimated models

household energy use applying behavioural economics to understand consumer decision making and behaviour household energy conservation has emerged as a major challenge and opportunity for researchers practitioners and policymakers consumers also seem to be gaining greater awareness of the value and need for sustainable energy practices particularly amid growing public concerns over greenhouse gas emissions and climate change yet even with adequate knowledge of how to save energy and a professed desire to do so many consumers still fail to take noticeable steps towards energy efficiency and conservation there is often a sizeable discrepancy between peoples self reported knowledge values attitudes and intentions and their observable behaviour examples include the well known knowledge action gap and value action gap but neither is household energy consumption driven primarily by financial incentives and the rational pursuit of material interests in fact people sometimes respond in unexpected and undesirable ways to rewards and sanctions intended to shift consumers cost benefit calculus in favour of sustainable behaviours why is this so why is household energy consumption and conservation difficult to predict from either core values or material interests by drawing on critical insights from behavioural economics and psychology we illuminate the key cognitive biases and motivational factors that may explain why energy related behaviour so often fails to align with either the personal values or material interests of consumers understanding these psychological phenomena can make household and community responses to public policy interventions less surprising and in parallel can help us design more cost effective and mass scalable behavioural solutions to encourage renewable and sustainable energy use among consumers

hourly electricity prices in day ahead markets this paper focuses on the characteristics of hourly electricity prices in day ahead markets in these markets quotes for day ahead delivery of electricity are submitted simultaneously for all hours in the next day the same information set is used for quoting all hours of the day the dynamics of hourly electricity prices does not behave as a time series process instead these prices should be treated as a panel in which the prices of 24 cross sectional hours vary from day to day this paper introduces a panel model for hourly electricity prices in day ahead markets and examines their characteristics the results show that hourly electricity prices exhibit hourly specific mean reversion and that they oscillate around an hourly specific mean price level furthermore a block structured cross sectional correlation pattern between the hours is apparent

renewable generation and electricity prices taking stock and new evidence for germany and austria abstract economic theory predicts that the increase of renewable electricity production should reduce the price of electricity in the short run which is also known as the merit order effect although the merit order effect is only one of several consequences of renewable production on the electricity system it is crucial to determine its size for the economic evaluation of renewable energies in this paper we present a comprehensive overview of relevant past research results on the price effect of renewables additionally we conduct a new empirical analysis of the price effect of renewable production for the austrian german region a market that clearly qualifies for a merit order effect analysis given its characteristics based on the review and our own analysis we show that the merit order effect varies depending on the region and the assessment method chosen we also find that the size of this effect is less dispersed throughout different markets than previously suggested by the literature

telecommunications and economic growth an empirical analysis of sub saharan africa we examine the effect of mobile cellular phones on economic growth in sub saharan africa where a marked asymmetry is present between land line penetration and mobile telecommunications expansion this study extends previous research along two important dimensions first we allow for the potential endogeneity between economic growth and telecommunications expansion by employing a special linear generalized method of moments gmm estimator second we explicitly model for varying degrees of substitutability between mobile cellular and land line telephony so that greater expansion of mobile telecommunications can have a different impact whenever the level of land line penetration differs we find that mobile cellular phone expansion is an important determinant of the rate of economic growth in sub saharan africa moreover we find that the contribution of mobile cellular phones to economic growth has been growing in importance in the region and that the marginal impact of mobile telecommunication service

analysis on the growth of telecommunication services a global comparison of diffusion patterns with the development of the internet the telecommunication market has seen a rapid shift from voice based services to data based services relationships of substitutability and complementarity have emerged among communications technology services such as internet service mobile phone service and fixed telephone service the article analyses the diffusion patterns of communication services in different continents a modified logistic growth model is estimated using panel data for the years 1975 2004 the research forms a valuable framework for forecasting demand for new services based on the diffusion of incumbent services and can inform strategies for entering the communications network industry

electricity futures prices indirect storability expectations and risk premiums the goal of this paper is to examine to what extent electricity futures prices contain expected risk premiums or have power to forecast spot prices and whether this might be dependent on the type of electricity supply we analyse futures prices from the dutch market a market in which power is produced with storable fossil fuels and futures prices from the nordpool market where electricity is mostly produced by hydropower we show that futures prices from markets in which electricity is predominantly produced by imperfectly storable fuels such as hydro wind and solar contain information about expected changes in the spot price of electricity whereas futures prices from markets in which electricity is predominantly produced with perfectly storable fuels contain information about both expected price changes and time varying risk premiums these findings provide insight in the applicability of forward price models one cannot apply the same model to all electricity markets forward models for markets with imperfect indirect storability should depend heavily on price expectations and models should include time varying risk premiums for markets with perfect indirect storability

comparison of extended mean reversion and time series models for electricity spot price simulation considering negative prices abstract this paper evaluates different financial price and time series models such as mean reversion autoregressive moving average arma integrated arma arima and general autoregressive conditional heteroscedasticity garch process usually applied for electricity price simulations however as these models are developed to describe the stochastic behaviour of electricity prices they are extended by a separate data treatment for the deterministic components trend daily weekly and annual cycles of electricity spot prices furthermore price jumps are considered and implemented within a regime switching model since 2008 market design allows for negative prices at the european energy exchange which also occurred for several hours in the last years up to now only a few financial and time series approaches exist which are able to capture negative prices this paper presents a new approach incorporating negative prices the evaluation of the different approaches presented points out that the mean reversion and the arma models deliver the lowest mean root square error between simulated and historical electricity spot prices gained from the european energy exchange these models posses also lower mean average errors than garch models hence they are more suitable to simulate well fitting price paths furthermore it is shown that the daily structure of historical price curves is better captured applying arma or arima processes instead of mean reversion or garch models another important outcome of the paper is that the regime switching approach and the consideration of negative prices via the new proposed approach lead to a significant improvement of the electricity price simulation

forecasting nord pool day ahead prices with an autoregressive model abstract this paper presents a model to forecast nord pool hourly day ahead prices the model is based on weron and misiorek 2008 but reduced in terms of estimation parameters from 24 sets to 1 and modified to include nordic demand and danish wind power as exogenous variables we model prices across all hours in the analysis period rather than across each single hour of 24 hours by applying three model variants on nord pool data we achieve a weekly mean absolute percentage error wmae of around 6 7 and an hourly mean absolute percentage error mape ranging from 8 to 11 out of sample results yields a wmae and an hourly mape of around 5 the models enable analysts and traders to forecast hourly day ahead prices accurately moreover the models are relatively straightforward and user friendly to implement they can be set up in any trading organization

divestiture and its implications for innovation and productivity growth in u s telecommunications this study has sought to determine the impact of policy changes that led to the breakup of the monopoly structure of u s telecommunications on productivity and research activities of at t a simultaneous equations model is used to examine the relationship between research intensity market share firm size and total factor productivity tfp before and after divestiture the results show that the effect of divestiture on productivity is negative but that competition has a significantly positive effect contrary to popular argument competition led to significant increases in r d investment by at t the study also finds a strong and positive relationship between r d and productivity in the postdivestiture period marked by its absence in the predivestiture years scale economies remain important indicating the industry continues to favor large firms

on the economics of renewable energy sources abstract with the global expansion of renewable energy re technologies the provision of optimal re policy packages becomes an important task we review pivotal aspects regarding the economics of renewables that are relevant to the design of an optimal re policy many of which are to date unresolved we do so from three interrelated perspectives that a meaningful public policy framework for inquiry must take into account first we explore different social objectives justifying the deployment of re technologies and review model based estimates of the economic potential of re technologies i e their socially optimal deployment level second we address pivotal market failures that arise in the course of implementing the economic potential of re sources in decentralized markets third we discuss multiple policy instruments curing these market failures our framework reveals the requirements for an assessment of the relevant options for real world decision makers in the field of re policies this review makes it clear that there are remaining white areas on the knowledge map concerning consistent and socially optimal re policies

efficient modeling and forecasting of electricity spot prices abstract the increasing importance of renewable energy especially solar and wind power has led to new forces in the formation of electricity prices hence this paper introduces an econometric model for the hourly time series of electricity prices of the european power exchange epex which incorporates specific features like renewable energy the model consists of several sophisticated and established approaches and can be regarded as a periodic var tarch with wind power solar power and load as influences on the time series it is able to map the distinct and well known features of electricity prices in germany an efficient iteratively reweighted lasso approach is used for the estimation moreover it is shown that several existing models are outperformed by the procedure developed in this paper

asymmetric volatility in european day ahead power markets a comparative microeconomic analysis this paper uses high frequency spot price data from fourteen wholesale electricity markets in europe to analyze asymmetric volatility in european day ahead power markets with exponential garch e garch and tarch models our data set ranges from 1992 to 2015 and consists of approximately 926 000 observations as such this paper constitutes the most extensive and comprehensive work conducted so far on european power markets to the best of our knowledge unlike most of the literature that treats price as a continuous variable and attempts to model its trajectory this paper adopts a unique approach and regards each hour in a day a separate market the results show in post 2008 period the most expensive electricity is consumed in turkey ireland and uk while the cheapest power is in russia nordic countries and czech republic russia poland and czech republic have the least volatile markets while france ireland and portugal have the most volatile ones volatility has decreased in many european countries in post 2008 period besides we find magnitude effect is usually larger than the leverage effect meaning that the absolute value of price change is relatively more important than the sign of the change whether it is an increase or a decrease to explain volatility in european day ahead power markets moreover the results imply there is not a uniform inverse leverage effect in electricity prices that is price increases are more destabilizing in some european markets e g poland slovenia ireland netherlands than comparable price decreases but vice versa also holds true in some other countries e g portugal and france leverage or inverse leverage effect in post 2008 period is relatively stronger in portugal france and ireland but its impact is quite limited in turkey and germany furthermore although the impact of seasonality on prices is obvious a specific pattern cannot be identified finally large changes in the volatility will affect future volatilities for a relatively longer period of time in nordic countries ireland and the uk while changes in current volatility will have less effect on future volatilities in czech republic russia and turkey

electricity demand in multi family renter occupied residences this paper focuses on multi family renter occupied housing where the landlord provides major appliances a large residential sector that has not received widespread attention in the literature experimental data are used from a test where one group of households was billed directly for the electricity they consumed while a control group had unlimited electric service included as part of the monthly rent the empirical analysis yields short run demand estimates that satisfy to a remarkable extent the ceteris paribus assumptions of demand analysis this is the case for two reasons 1 the households did not individually execute the appliance choice decision at various unknown times in the past and 2 the stock of appliances upon which the derived short run demand is conditional is identical for all households in the sample a second important feature is emphasis on functional form examined in some detail is the question of the appropriate functional form for residential electricity demand finally empirical results of the analysis are used to investigate the cost effectiveness and welfare effects of installing submeters in existing multi family residences

a note on using the hodrick prescott filter in electricity markets abstract recently nowotarski et al 2013 have found that wavelet based models for the long term seasonal component ltsc are not only better in extracting the ltsc from a series of spot electricity prices but also significantly more accurate in terms of forecasting these prices up to a year ahead than the commonly used monthly dummies and sine based models however a clear disadvantage of the wavelet based approach is the increased complexity of the technique as compared to the other two classes of ltsc models and the resulting need for dedicated numerical software which may not be readily available to practitioners in their work environments to facilitate this problem we propose here a much simpler yet equally powerful method for identifying the ltsc in electricity spot price series it makes use of the hodrick prescott hp filter a widely recognized tool in macroeconomics

analysis of commodity prices with the particle filter the behavior of commodities prices is fundamental to real asset investment decisions hedging and pricing financial derivatives schwartz and smith schwartz e s smith j e 2000 short term variations and long term dynamics in commodity prices management science 46 893 911 proposed a two factor model for describing the stochastic processes of commodity prices in which the two factors are short term variations and equilibrium prices these are both unobserved state variables that are estimated using the kalman filter the estimation is based on the observation of future prices for different maturities the authors have carried out this process without incorporating jumps in the short term variation of prices here we aim to demonstrate that the inclusion of jumps better explains the behavior of oil prices and in fact creates difficulties in the estimation of state variables this is because the variables become non gaussian so the kalman filter is not recommended another methodology called the particle filter is more suitable in this case and we describe its application in this article

pricing reliability options under different electricity price regimes abstract reliability options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems they can be framed as call options on electricity sold by power producers to system operators this paper provides a comprehensive mathematical treatment of reliability options their value is first derived by means of closed form pricing formulae which are obtained under several assumptions about the dynamics of electricity prices and strike prices then the value of the reliability option is simulated under a real market calibration using data of the italian power market we perform sensitivity analyses to highlight the role of the level and volatility of both power and strike price of the mean reversion speeds and of the correlation coefficient on the reliability options value finally we calculate the parameter model risk to quantify the impact that a model misspecification has on the equilibrium value of the ro

transaction costs telecommunications and the microeconomics of macroeconomic growth the sources of differences in growth rates across nations are unclear this observation constitutes one of the central intellectual challenges of our time why is the whole world not developed consequently a host of scholars offer various explanations for growth or nongrowth including cultural factors politics and economics 2 the objective of this article is to determine whether a link exists between transaction costs telecommunications and economic growth the article builds on recent research on the macroeconomic determinants of growth as well as on research regarding the significant economic effects of telecommunications on transaction costs it is organized as follows section i reviews the theory of transaction costs section ii the link between transaction costs and telecommunications section iii contains the empirical analysis and section iv some conclusions

motivating non ratepaying households with feedback and social nudges a cautionary tale abstract behavioral interventions have been shown to be valuable instruments in reducing energy use among ratepaying customers but their effect on non ratepayers has received less attention this study uses a randomized controlled trial research design to examine the effect of feedback and a social nudge in the form of peer comparison on energy consumption of non ratepaying households the study setting is a university family housing complex and findings are based on hourly observations of energy use by 62 households over thirteen weeks our results suggest that neither feedback or peer comparison is an effective instrument to reduce energy use of non ratepaying households and may even increase energy consumption in some contexts we find heterogeneous effects among households that are low and high users of energy in the pre treatment period with high users increasing energy consumption in response to feedback thus caution is needed in applying behavioral interventions when financial incentives to reinforce intended effects are absent

weekly self scheduling forward contracting and pool involvement for an electricity producer an adaptive robust optimization approach abstract this paper addresses the optimization under uncertainty of the self scheduling forward contracting and pool involvement of an electricity producer operating a mixed power generation station which combines thermal hydro and wind sources and uses a two stage adaptive robust optimization approach in this problem the wind power production and the electricity pool price are considered to be uncertain and are described by uncertainty convex sets to solve this problem two variants of a constraint generation algorithm are proposed and their application and characteristics discussed both algorithms are used to solve two case studies based on two producers each operating equivalent generation units differing only in the thermal units characteristics their market strategies are investigated for three different scenarios corresponding to as many instances of electricity price forecasts the effect of the producers approach whether conservative or more risk prone is also investigated by solving each instance for multiple values of the so called budget parameter it was possible to conclude that this parameter influences markedly the producers strategy in terms of scheduling profit forward contracting and pool involvement these findings are presented and analyzed in detail and an attempted rationale is proposed to explain the less intuitive outcomes regarding the computational results these show that for some instances the two variants of the algorithms have a similar performance while for a particular subset of them one variant has a clear superiority

a new measure of cross sectional risk and its empirical implications for portfolio risk management abstract litterman et al litterman r scheinkman j weiss l 1991 volatility and the yield curve journal of fixed income 1 june 49 53 and engle and ng engle r f ng v k 1993 time varying volatility and the dynamic behavior of the term structure journal of money credit and banking 25 3 336 349 provide empirical evidence of a relation between yield curve shape and volatility this study offers theoretical support for that finding in the general context of cross sectional time series we introduce a new risk measure quantifying the link between cross sectional shape and market risk a simple econometric procedure allows us to represent the risk experienced by cross sections over a time period in terms of independent factors reproducing possible cross sectional deformations we compare our risk measure to the traditional cross yield covariance according to their relative performance empirical investigation in the us interest rate market shows that 1 cross shape risk factors outperform cross yield risk factors i e yield curve level slope and convexity in explaining the market risk of yield curve dynamics 2 hedging multiple liabilities against cross shape risk delivers superior trading strategies compared to those stemming from cross yield risk management

growth effects of currency mismatches evidence from emerging economies this article investigates empirically the effects of currency mismatches on economic growth and volatility of growth in emerging market economies using the arellano bond dynamic panel data approach the analyses provide evidence on the presence of adverse growth effects of currency mismatches this illustrates the crucial role played by foreign currency denominated debts in the propagation mechanism of contractionary depreciations in emerging economies in the last decade further evidence from estimations implies that the adverse effects of mismatches on growth and growth volatility are more pronounced with higher exchange rate fluctuations

a garch forecasting model to predict day ahead electricity prices price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets both for spot markets and long term contracts price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize profits this paper provides an approach to predict next day electricity prices based on the generalized autoregressive conditional heteroskedastic garch methodology that is already being used to analyze time series data in general a detailed explanation of garch models is presented and empirical results from the mainland spain and california deregulated electricity markets are discussed

arima models to predict next day electricity prices price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets both for spot markets and long term contracts price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize benefit this paper provides a method to predict next day electricity prices based on the arima methodology arima techniques are used to analyze time series and in the past have been mainly used for load forecasting due to their accuracy and mathematical soundness a detailed explanation of the aforementioned arima models and results from mainland spain and californian markets are presented

effects of feedback on residential electricity demand findings from a field trial in austria abstract this paper analyzes the effects of providing feedback on electricity consumption in a field trial involving more than 1500 households in linz austria about half of these households received feedback together with information about electricity saving measures pilot group while the remaining households served as a control group participation in the pilot group was random but households were able to choose between two types of feedback access to a web portal or written feedback by post results from cross section ols regression suggest that feedback provided to the pilot group corresponds with electricity savings of around 4 5 for the average household our results from quantile regressions imply that for households in the 30th to the 70th percentile of electricity consumption feedback on electricity consumption is statistically significant and effects are highest in absolute terms and as a share of electricity consumption for percentiles below or above this range feedback appears to have no effect finally controlling for a potential endogeneity bias induced by non random participation in the feedback type groups we find no difference in the effects of feedback provided via the web portal and by post

public sector capital and the productivity puzzle a number of studies have suggested a quantitatively important relationship between public sector capital accumulation and private sector productivity with the most compelling evidence derived from analyses of state level data estimates herein of production functions that use standard techniques to control for unobserved state specific characteristics however reveal essentially no role for public sector capital in affecting private sector productivity only estimates of state production functions that do not include such controls find substantial productivity impacts this result reconciles existing econometric estimates with the findings of hulten and schwab based on growth accounting techniques as such techniques effectively control for state specific effects region level estimates are essentially identical to those from state data suggesting no quantitatively important spillover effects across states copyright 1994 by mit press

telecommunications infrastructure and economic development a simultaneous approach in diesem beitrag wird untersucht welchen einflus die telekommunikations infrastruktur auf die wirtschaftliche entwicklung ausubt diese wichtige frage hat im zusammenhang mit der diskussion um informationsautobahnen aktualitat erlangt in der vorliegenden studie wird der einflus der telekommunikations infrastruktur fur 21 oecdlander fur die vergangenen 20 jahre analysiert es wird ein strukturgleichungsmodell geschatzt in dem investitionen in die telekommunikations infrastruktur als endogene variable erfast werden und in einem mikromodell angebot und nachfrage nach telekommunikations investitionen spezifiziert werden das mikromodell wird dann zusammen mit der makro wachstumsgleichung geschatzt als ergebnis stellen die autoren dann eine positive kausalbeziehung zwischen telekommunikations investitionen und wirtschaftlicher entwicklung fest wenn eine kritische masse an telekommunikations infrastruktur existiert

the merit order effect a detailed analysis of the price effect of renewable electricity generation on spot market prices in germany the german feed in support of electricity generation from renewable energy sources has led to high growth rates of the supported technologies critics state that the costs for consumers are too high an important aspect to be considered in the discussion is the price effect created by renewable electricity generation this paper seeks to analyse the impact of privileged renewable electricity generation on the electricity market in germany the central aspect to be analysed is the impact of renewable electricity generation on spot market prices the results generated by an agent based simulation platform indicate that the financial volume of the price reduction is considerable in the short run this gives rise to a distributional effect which creates savings for the demand side by reducing generator profits in the case of the year 2006 the volume of the merit order effect exceeds the volume of the net support payments for renewable electricity generation which have to be paid by consumers

pricing german energiewende products intraday cap floor futures abstract in this paper we introduce a model for the pricing of german intraday cap floor futures introduced by the eex in 2015 we give a thorough overview of the german intraday market and in particular introduce the id3 price index which is the underlying for intraday cap floor futures to price these derivatives we propose a hull white model from interest rate theory with seasonality from futures prices we apply our theoretical results to market data and conduct an empirical analysis involving the initial fit and empirical distribution of intraday cap futures prices

short term forecasting of electricity prices for miso hubs evidence from arima egarch models this study estimates three time series models arima arima egarch and arima egarch m for hourly real time electricity prices for each of the five hubs of the midwest independent system operator miso and examines the in and out of sample forecasting performance of the respective models the results from the arima models reveal the presence of autoregressive conditional heteroskedasticity recognizing the possibility of asymmetric time varying volatility the egarch specification for the variance equation demonstrates the presence of an inverse leverage effect in electricity prices for each hub with respect to forecasts no one model clearly dominates the others in terms of in sample forecasting performance based on four forecast evaluation statistics however the arima egarch m model outperforms the other models michigan hub is the exception in terms of the out of sample forecasting performance

the impact of renewable energies on eex day ahead electricity prices in this paper we analyze the impact of renewable energies wind and photovoltaic on the formation of day ahead electricity prices at eex we give an overview of the policy decisions concerning the promotion of renewable energy sources in germany and discuss their consequences on day ahead prices an analysis of electricity spot prices reveals that the introduction of renewable energies enhances extreme price changes in the frame of a dynamic fundamental model we show that there has been a continuous electricity price adaption process to market fundamentals furthermore the fundamental drivers of prices differ among hours with different load profiles our results imply that renewable energies decrease market spot prices and have implications on the traditional fuel mix for electricity production however the prices for the final consumers increased overall because they must pay in addition the feed in tariffs for the promotion of renewable energy

telecommunications and economic growth a panel data approach telecommunication investment is increasingly identified as one with a strong potential to improve economic productivity and growth the objective of this study is to investigate the long run relationship between telecommunications infrastructure and economic growth using data from 22 oecd countries a dynamic panel data method is used for estimation which corrects for omitted variables bias of single equation cross section regression the fixed effects specification accounts for country specific differences in aggregate production functions the results show a significant and positive correlation between telecommunications infrastructure and growth after controlling for a number of other factors

electricity futures price models calibration and forecasting a new one factor model with a random volatility parameter is presented in this paper for pricing of electricity futures contracts it is shown that the model is more tractable than multi factor jump diffusion models and yields an approximate closed form pricing formula for the electricity futures prices on real market data it is shown that the performance of the new model compares favourably with two existing models in the literature viz a two factor jump diffusion model and its jump free version i e a two factor linear gaussian model in terms of ability to predict one day ahead futures prices further a multi stage procedure is suggested and implemented for calibration of the two factor jump diffusion model which alleviates the difficulty in calibration due to a large number of parameters and pricing formulae which involve numerical evaluation of integrals we demonstrate the utility of our new model as well as the utility of the calibration procedure for the existing two factor jump diffusion model by model calibration and price forecasting experiments on three different futures price data sets from nord pool electricity data for the jump diffusion model we also investigate empirically whether it performs better in terms of futures price prediction than a corresponding jump free linear gaussian model finally we investigate whether an explicit calibration of jump risk premium in the jump diffusion model adds value to the quality of futures price prediction our experiments do not yield any evidence that modelling jumps leads to a better price prediction in electricity markets

externalities information costs and social benefit cost analysis for economic development an example from telecommunications the analytics of achieving a socially optimal allocation of investment resources has been a continuing problem in the field of economic development early work on this subject focused on externalities and on the need to include in the analysis a project s indirect promotional effects later research in what came to be called social benefit cost analysis sbca has added an emphasis on shadow prices on uncertainty and increasingly on income distribution effects 2 in principle these diverse concerns of social benefit cost analysis are complementary rather than competitive in the conditions of a less developed country ldc an investment project s side effects on income creation can be very significant 3 similarly an investment project s indirect impact on income distribution may also be substantial consequently an analysis incorporating externalities is necessary to take indirect social benefits and costs into account in practice however the more recent concerns of sbca have sometimes been accompanied by diminished interest in externalities 4 this paper presents an example that illustrates the importance of including externalities in considering both the efficiency and the equity consequences of investment choice our example analyzes the welfare effects of investment in telecommunications primarily telephone facilities in developing countries 5 investments that make available additional telephones in ldcs are often viewed as having welfare effects similar to increased availability of consumer durables like color television or air conditioning those goods are primarily an added convenience for the upper classes and their availability enlarges further the

is public expenditure productive abstract this paper considers the relationship between aggregate productivity and stock and flow government spending variables the empirical results indicate that i the nonmilitary public capital stock is dramatically more important in determining productivity than is either the flow of nonmilitary or military spending ii military capital bears little relation to productivity and iii a core infrastructure of streets highways airports mass transit sewers water systems etc has most explanatory power for productivity the paper also suggests an important role for the net public capital stock in the productivity slowdown of the last fifteen years

returns to residential energy efficiency and conservation measures a field experiment abstract residential energy conservation is a key component of contemporary energy and climate change policy in the us and elsewhere comparisons of the relative effectiveness of measures aimed at reducing residential energy consumption are made challenging however by the endogeneity of technology and energy use decisions in this paper we describe a novel small scale field experiment that uses randomized treatments to estimate the returns to three types of energy conservation measures in institutionally owned homes the results from the experiment indicate considerable reductions in natural gas consumption associated with the installation of attic insulation and the provision of incentives for conservation the results are supported by observations of ambient indoor temperature data which show that households receiving incentives significantly reduce their temperature settings especially when coupled with access to a programmable thermostat the study will ideally provide guidance for institutions and communities considering energy efficiency measures and for future researchers designing randomized experiments to study residential energy use

a combined modeling approach for wind power feed in and electricity spot prices abstract wind power generation and its impacts on electricity prices has strongly increased in the eu therefore appropriate mark to market evaluation of new investments in wind power and energy storage plants should consider the fluctuant generation of wind power and uncertain electricity prices which are affected by wind power feed in wpf to gain the input data for wpf and electricity prices simulation models such as econometric models can serve as a data basis this paper describes a combined modeling approach for the simulation of wpf series and electricity prices considering the impacts of wpf on prices based on an autoregressive approach thereby wpf series are firstly simulated for each hour of the year and integrated in the electricity price model to generate an hourly resolved price series for a year the model results demonstrate that the wpf model delivers satisfying wpf series and that the extended electricity price model considering wpf leads to a significant improvement of the electricity price simulation compared to a model version without wpf effects as the simulated series of wpf and electricity prices also contain the correlation between both series market evaluation of wind power technologies can be accurately done based on these series

a space time random field model for electricity forward prices abstract stochastic models for forward electricity prices are of great relevance nowadays given the major structural changes in the market due to the increase of renewable energy in the production mix in this study we derive a spatio temporal dynamical model based on the heath jarrow morton hjm approach under the musiela parametrization which ensures an arbitrage free model for electricity forward prices the model is fitted to a unique data set of historical price forward curves as a particular feature of the model we disentangle the temporal from spatial maturity effects on the dynamics of forward prices and shed light on the statistical properties of risk premia of the noise volatility term structure and of the spatio temporal noise correlation structures we find that the short term risk premia oscillates around zero but becomes negative in the long run we identify the samuelson effect in the volatility term structure and volatility bumps explained by market fundamentals furthermore we find evidence for coloured noise and correlated residuals which we model by a hilbert space valued normal inverse gaussian levy process with a suitable covariance functional

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

econometric analysis of 15 minute intraday electricity prices abstract the trading activity in the german intraday electricity market has increased significantly over the last years this is partially due to an increasing share of renewable energy wind and photovoltaic which requires power generators to balance out the forecasting errors in their production we investigate the bidding behaviour in the intraday market by looking at both last prices and continuous bidding in the context of a reduced form econometric analysis a unique data set of 15 minute intraday prices and intraday updated forecasts of wind and photovoltaic has been employed price bids are explained by prior information on renewables forecasts and demand supply market specific exogenous variables we show that intraday prices adjust asymmetrically to both forecasting errors in renewables and to the volume of trades dependent on the threshold variable demand quote which reflects the expected demand covered by the planned traditional capacity in the day ahead market the location of the threshold can be used by market participants to adjust their bids accordingly given the latest updates in the wind and photovoltaic forecasting errors and the forecasts of the control area balances

the relationship between spot and futures prices in the nord pool electricity market abstract we analyze 11 years of historical spot and futures prices from the hydro dominated nord pool electricity market we find that futures prices tend to be higher than spot prices the average convenience yield is therefore negative but varies by season and depends on the storage levels in hydro reservoirs the average realized return on holding a long position in the futures market is also negative the negative convenience yield and risk premium contrast empirical findings in most other commodity markets we argue that differences between the supply and demand sides in terms of risk preferences and the ability to take advantage of short term price variations can contribute to explain the observed relationship between spot and futures prices in addition our analysis shows that the relationship between spot and futures prices is clearly linked to the physical state of the system such as hydro inflow reservoir levels and demand

forecasting next day electricity prices by time series models in the framework of competitive electricity markets power producers and consumers need accurate price forecasting tools price forecasts embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities respectively this paper provides two highly accurate yet efficient price forecasting tools based on time series analysis dynamic regression and transfer function models these techniques are explained and checked against each other results and discussions from real world case studies based on the electricity markets of mainland spain and california are presented

regime jumps in electricity prices many countries are liberalizing their energy markets participants in these markets are exposed to market risk due to the characteristics of electricity price dynamics electricity prices are known to be mean reverting very volatile and subject to frequent spikes models that describe the dynamics of electricity prices should incorporate these characteristics in order to capture the price spikes many researchers have introduced stochastic jump processes but we argue and show that this specification might lead to potential problems with specifying the true amount of mean reversion within the process in this paper we propose a regime switching model that models price spikes separated from normal mean reverting prices

electricity forward curves with thin granularity theory and empirical evidence in the hourly epexspot market we propose a constructive definition of electricity forward price curve with cross sectional timescales featuring hourly frequency on the curve is jointly consistent with both risk neutral market information represented by baseload and peakload futures quotes and historical market information as mirrored by periodical patterns exhibited by the time series of day ahead prices from a methodological standpoint we combine nonparametric filtering with monotone convex interpolation such that the resulting forward curve is pathwise smooth and monotonic cross sectionally stable and time local from an empirical standpoint we exhibit these features in the context of epex spot and eex derivative markets we perform a backtesting analysis to assess the relative quality of our forward curve estimate compared to the benchmark market model of benth koekebakker and ollmar 2007

saving power to conserve your reputation the effectiveness of private versus public information environmental damage is often an unseen byproduct of other activities disclosing environmental impact privately to consumers can reduce the costs and or increase the moral benefits of conservation behaviors while publicly disclosing such information can provide an additional motivation for conservation cultivating a green reputation in a unique field experiment in the residence halls at the university of california los angeles we test the efficacy of detailed private and public information on electricity conservation private information was given through real time appliance level feedback and social norms over usage and public information was given through a publicly visible conservation rating our analysis is based on 7 120 daily observations about energy use from heating and cooling lights and plug load for 66 rooms collected over an academic year our results suggest that while private information alone was ineffective public information combined with private information motivated a 20 percent reduction in electricity consumption achieved through lower use of heating and cooling public information was particularly effective for above median energy users

constructing forward price curves in electricity markets we present and analyze a method for constructing approximated high resolution forward price curves in electricity markets because a limited number of forward or futures contracts are traded in the market only a limited picture of the theoretical continuous forward price curve is available to the analyst our method combines the information contained in observed bid and ask prices with information from the forecasts generated by bottom up models as an example we use information concerning the shape of the seasonal variation from a bottom up model to improve the forward price curve quoted on the nordic power exchange

residential electricity pricing in china the context of price based demand response abstract as a secondary energy electricity is an important channel between original energy and energy consumers electricity price is a critical factor for the interests of all involvers in the electric power market it also plays an important role for the sustainable development of energy and environment smart grid is a new conception proposed in recent years to improve the intelligent level and increase the efficiency of electric power system operation smart grid combines and integrates information technology communication technology and intelligent control technology with tradition power system to achieve the many objectives of smart grid demand response dr as an effective technique of demand side management dsm refers to the changes in electricity consumption behavior of users in response to the dynamic price or incentive rewards price based demand response pbdr is one of the two major dr programs in this paper we first introduce the pricing theories in economics the pricing of electricity and the development of electricity pricing in china then we present a detailed discussion on the pbdr strategies in the dsm of smart grid also the research status of pbdr is reviewed finally it gives a summary of the whole paper in the last section

energy conservation nudges and environmentalist ideology evidence from a randomized residential electricity field experiment nudges are being widely promoted to encourage energy conservation we show that while the electricity conservation nudge of providing feedback to households on own and peers home electricity usage works with liberals it can backfire with conservatives our regression estimates predict that a democratic household that pays for electricity from renewable sources that donates to environmental groups and that lives in a liberal neighborhood reduces its consumption by 3 percent in response to this nudge a republican household that does not pay for electricity from renewable sources and that does not donate to environmental groups increases its consumption by 1 percent

filtering and forecasting commodity futures prices under an hmm framework abstract we propose a model for the evolution of arbitrage free futures prices under a regime switching framework the estimation of model parameters is carried out using the hidden markov filtering algorithms comprehensive numerical experiments on real financial market data are provided to illustrate the effectiveness of our algorithm in particular the model is calibrated with data from heating oil futures and its forecasting performance as well as statistical validity is investigated the proposed model is parsimonious self calibrating and can be very useful in predicting futures prices

one for all the impact of different types of energy feedback and goal setting on individuals motivation to conserve electricity abstract we investigate how different types of energy feedback combined with goal setting impact on consumers motivation to conserve electricity using an online survey we test the influence of energy feedback in physical units kwh monetary values eur and environmental values avoided co2 emissions we asked participants to set themselves either a high low or no energy conservation goal in addition we assess the respondents value types hedonic egoistic altruistic and biospheric to test predictions derived from goal framing theory in general individuals scoring high on biospheric values were more motivated to conserve electricity and their motivation did not increase in response to setting an energy conservation goal individuals with egoistic values seem less willing to reduce their electricity consumption unless in the monetary feedback or high goal conditions a high conservation goal was only found to be effective in combination with monetary feedback it increased the motivation to save electricity by 6 7 percentage points in comparison to the low goal condition and 6 6 percentage points in comparison to the control condition

linear complementarity models of nash cournot competition in bilateral and poolco power markets two cournot models of imperfect competition among electricity producers are formulated as mixed linear complementarity problems lcps and a simple example is presented to illustrate their application the two models simulate bilateral markets the models include a congestion pricing scheme for transmission but other transmission pricing approaches can also be represented in this framework the two models differ from each other in that one has no arbitrage between nodes of the network while in the other model arbitragers erase any noncost based differences in price the latter bilateral model turns out to be equivalent to a cournot model of a poolco the models differ from other cournot market models in that they include both of kirchhoff s laws via a dc approximation can include arbitragers possess unique solutions and are readily solved by efficient lcp algorithms the key assumption that permits their formulation as lcps is that each producer naively assumes that its output will not affect transmission prices

forecasting electricity spot prices using lasso on capturing the autoregressive intraday structure in this paper we present a regression based model for day ahead electricity spot prices we estimate the considered linear regression model by the lasso estimation method the lasso approach allows for many possible parameters in the model but also shrinks and sparsifies the parameters automatically to avoid overfitting thus it is able to capture the autoregressive intraday dependency structure of the electricity price well we discuss in detail the estimation results which provide insights to the intraday behavior of electricity prices we perform an out of sample forecasting study for several european electricity markets the results illustrate well that the efficient lasso based estimation technique can exhibit advantages from two popular model approaches

applying arma garch approaches to forecasting short term electricity prices abstract accurately modeling and predicting the mean and volatility of electricity prices can be of great importance to value electricity bid or hedge against the volatility of electricity prices and manage risk the paper applies various autoregressive moving average arma models with generalized autoregressive conditional heteroskedasticity garch processes namely arma garch models along with their modified forms arma garch in mean arma garch m to model and forecast hourly ahead electricity prices in total 10 different model structures are adopted and this paper thus conducts a comprehensive investigation on the arma garch based time series forecasting of electricity prices multiple statistical measures are employed to evaluate the modeling sufficiency and predication accuracy of the arma garch m methods the results show that the arma garch m models are in general an effective tool for modeling and forecasting the mean and volatility of electricity prices while arma sgarch m models are simple and robust and the arma gjrgarch m model is very competitive in addition we observe that hourly electricity prices exhibit apparent daily weekly and monthly periodicities and have the nonlinear and asymmetric time varying volatility together with an inverse leverage effect

day ahead electricity price forecasting using the wavelet transform and arima models this paper proposes a novel technique to forecast day ahead electricity prices based on the wavelet transform and arima models the historical and usually ill behaved price series is decomposed using the wavelet transform in a set of better behaved constitutive series then the future values of these constitutive series are forecast using properly fitted arima models in turn the arima forecasts allow through the inverse wavelet transform reconstructing the future behavior of the price series and therefore to forecast prices results from the electricity market of mainland spain in year 2002 are reported