a generalized schwartz model for energy spot prices estimation using a particle mcmc method we propose an energy spot price model featuring a two factor price process and a two component stochastic volatility process the first factor in the price process captures the normal variations the second accounts for spikes the two component volatility allows for a flexible autocorrelation structure instead of using various filtering techniques for splitting the two factors as often found in the literature we estimate the model in one step using an adaptive mcmc method with a rao blackwellized particle filter we fit the model to uk natural gas spot prices and investigate the importance of spikes and stochastic volatility we find that the inclusion of stochastic volatility is crucial and that it strongly impacts the jump intensity in the spike process furthermore our estimation method enables us to consider both continuous and purely jump driven volatility processes and thereby assess if the volatility specification also influences the spike process and the overall model fit

modelling short and long term risks in power markets empirical evidence from nord pool in this paper we propose a three factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the scandinavian power market in this model both short and long run factors are unobservable and are hence estimated as latent variables using the kalman filter the proposed model has several advantages first it seems to capture in a parsimonious way the most important risks that practitioners face in the market such as spike risk short term risk and long term risk second it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices particularly for long dated forward contracts finally closed form solutions for forward contracts derived from the model are consistent with the fact that the correlation between contracts of different maturities is imperfect the resulting model is very promising providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long dated contracts

forecasting day ahead electricity load using a multiple equation time series approach the quality of short term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market in this paper it is shown that a multiple equation time series model which is estimated by repeated application of ordinary least squares has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models the key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra day dependencies although the model is built using data for the queensland region of australia the method is completely generic and applicable to any load forecasting problem the model s forecasting ability is assessed by means of the mean absolute percentage error mape for day ahead forecast the mape returned by the model over a period of 11 years is an impressive 1 36 the forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the australia energy market operator aemo the performance of the model developed in this paper is superior to all benchmarks and outperforms the aemo forecasts by about a third in terms of the mape criterion

time varying convergence in european electricity spot markets and their association with carbon and fuel prices abstract long run dynamics of electricity prices are expected to reflect fuel price developments since fuels generally account for a large share in the cost of generation as an integrated european market for electricity develops wholesale electricity prices should be converging as a result of market coupling and increased interconnectivity electricity mixes are also changing spurred by a drive to significantly increase the share of renewables consequently the electricity wholesale price dynamics are evolving and the fuel electricity price nexus that has been described in the literature is likely to reflect this evolution this study investigates associations between spot prices from the british french and nordpool markets with those in connected electricity markets and fuel input prices from december 2005 to october 2013 in order to assess the time varying dynamics of electricity spot price series localized autocorrelation functions are used electricity spot prices in the three markets are found to have stationary and non stationary periods when a trend in spot prices is observed it is likely to reflect the trend in fuel prices cointegration analysis is then used to assess co movement between electricity spot prices and fuel inputs to generation the results show that british electricity spot prices are associated with fuel prices and not with price developments in connected markets while the opposite is observed in the french and nordpool day ahead markets

the crucial relationship among energy commodity prices evidence from the spanish electricity market the main purpose of this article is twofold to analyze a the long term relation among the commodities prices and between spot electricity market price and commodity prices and b the short term dynamics among commodity prices and between electricity prices and commodity prices data between 2002 and 2005 from the spanish electricity market was used econometric methods were used in the analysis of the commodity spot price namely the vector autoregression model the vector error correction model and the granger causality test the co integration approach was used to analyze the long term relationship between the common stochastic trends of four fossil fuel prices one of the findings in the long term relation is that the prices of fuel and the prices of brent are intertwined though the prices of brent ten to move to reestablish the price equilibrium another finding is that the price of electricity is explained by the evolution of the natural gas series

when supply meets demand the case of hourly spot electricity prices we use a supply demand framework to model the hourly day ahead price of electricity the spot price based on publicly available information with the model we can forecast the level and probability of a spike in the spot price defined as the spot price above a certain threshold several european countries have recently started publishing day ahead forecasts of the available supply this paper shows this forecasted capacity is quite successful in predicting spot price movements 24 h ahead

the impact of wind power generation on the electricity price in germany abstract this paper investigates the relationship between intermittent wind power generation and electricity price behaviour in germany using a garch model i evaluate the effect of wind electricity generation on the level and the volatility of the electricity price in an integrated approach the results show that variable wind power reduces the price level but increases its volatility this paper s results also indicate that regulatory change has stabilised the wholesale price the electricity price volatility has decreased in germany after a modification of the marketing mechanism of renewable electricity this gives confidence that further adjustments to regulation and policy may foster a better integration of renewables into the power system

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

asymmetric forecast densities for u s macroeconomic variables from a gaussian copula model of cross sectional and serial dependence most existing reduced form macroeconomic multivariate time series models employ elliptical disturbances so that the forecast densities produced are symmetric in this article we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry empirical and skew t distributions are employed for the margins and a high dimensional gaussian copula is used to jointly capture cross sectional and multivariate serial dependence the copula parameter matrix is given by the correlation matrix of a latent stationary and markov vector autoregression var we show that the likelihood can be evaluated efficiently using the unique partial correlations and estimate the copula using bayesian methods we examine the forecasting performance of the model for four u s macroeconomic variables between 1975 q1 and 2011 q2 using quarterly real time data we find that the point and density forecasts from the copula model are competitive with those from a bayesian

causal modeling and inference for electricity markets abstract how does dynamic price information flow among northern european electricity spot prices and prices of major electricity generation fuel sources we use time series models combined with new advances in causal inference to answer these questions applying our methods to weekly nordic and german electricity prices and oil gas and coal prices with german wind power and nordic water reservoir levels as exogenous variables we estimate a causal model for the price dynamics both for contemporaneous and lagged relationships in contemporaneous time nordic and german electricity prices are interlinked through gas prices in the long run electricity prices and british gas prices adjust themselves to establish the equilibrium price level since oil coal continental gas and eur usd are found to be weakly exogenous

incorporating option values into the economic evaluation of health care technologies abstract despite uncertainty being intrinsic to economic evaluation of health care existing techniques for handling uncertainty remain underdeveloped compared to the formal techniques commonly applied in the business sector this paper develops an alternative approach to handling uncertainty in economic evaluation based on option pricing techniques the presence of uncertainty and the degree of irreversibility of a decision make it clear that some flexibility in the timing of a decision is often a desirable characteristic with an economic value we demonstrate how option pricing techniques can be applied to the decision rules for economic evaluation in health care the key determinants of an option value are the presence and type of uncertainty the ability to defer a decision and the irreversibility of the decision the relative significance of each of these for a particular economic evaluation will depend on the particular characteristics of the technology under consideration

oil and gas markets in the uk evidence from a cointegrating approach the paper examines the relationship between uk wholesale gas prices and the brent oil price over the period 1996 2003 in order to investigate whether oil and gas prices decoupled during this period as orthodox gas market liberalisation theory suggests tests for unit roots and cointegration are carried out and it is discovered that a long run equilibrium relationship between uk gas and oil prices exists moreover this relationship pre dates the opening of the uk mainland europe interconnector following a recursive methodology hansen h and johansen s 1999 some tests for parameter constancy in cointegrated var models econometrics journal 2 306 333 it was found that the cointegrating relationship is present throughout the sample period however the long run solutions seem to be more volatile evidence is provided that the short run relationship is linear and impulse response functions are used to examine the effects that a shock in oil would have on gas these findings do not support the assumption that gas prices and oil prices decouple

fitting semiparametric markov regime switching models to electricity spot prices abstract recently regime switching models have become the standard tool for modeling electricity prices these models capture the main properties of electricity spot prices well but estimation of the model parameters requires computer intensive methods moreover the distribution of the price spikes must be fully specified although the high volatility of the spikes makes it difficult to check such distributional assumptions consequently there are a number of competing proposals for the distribution in the spike regime as an alternative we propose a semiparametric markov regime switching model that leaves the distribution under the spike regime unspecified we show that the model parameters can be estimated by employing robust statistical techniques this presents an alternative to the existing estimation methods that are based on computer intensive numerical maximization of the likelihood function the model in combination with the estimation framework is easier to estimate needs less computation time and distributional assumptions to show its advantages we compare the proposed model with a well established markov regime switching model in a simulation study furthermore we apply the model to log prices for the australian electricity market the results are in accordance with the results from the simulation study indicating that the proposed model might be advantageous whenever the distribution of the spike process is not sufficiently known the results are thus encouraging and suggest the use of our approach when modeling electricity prices and pricing derivatives

the influence of temperature on spike probability in day ahead power prices it is well known that day ahead prices in power markets exhibit spikes and time varying volatility spikes and extremely high volatility are the results of short term frictions in demand and or supply conditions it is known that information on load or the reserve margin help to forecast spikes however these variables are not timely available for every market participant and this paper suggests to use temperature as a proxy interpreting the results from several switching regimes models the paper shows that the probability of spike occurrence increases when temperature deviates substantially from mean temperature levels

jump processes in natural gas markets abstract many analysts believe that natural gas will have an increasingly important role in the next few decades accordingly understanding the underpinnings of natural gas prices is likely to be critical both to policy analysts and to market participants at present it is common to assume that these prices follow a geometric brownian motion i e that log returns the inter temporal differences in the natural log of prices are normally distributed possibly allowing for some form of mean reversion increasingly however it has been recognized that the arrival of new information can lead to unexpectedly rapid changes or jumps in spot prices the implication is that the presumption of normally distributed log returns may be suspect in particular the prospect for abnormally fat tails becomes important this article investigates the potential presence of jumps in two key natural gas prices the spot price at the henry hub in the u s and the spot price for natural gas at the national balancing point in the u k we found compelling empirical evidence for the importance of jumps in both markets though jumps appear to be more important in the u k

analyzing the impact of futures trading on spot price volatility evidence from the spot electricity market in france and germany abstract this paper examines the impact of the introduction of electricity futures on the spot price volatility of the french powernext and german eex electricity markets as well as the degree of their price correlation over the period 2002 2011 our working hypotheses were tested based on a bivariate vecm garch model the results indicate that the introduction of futures contracts in the french electricity market as well as the launch of the joint futures market in these countries in 2009 has decreased spot price volatility however this effect was not as explicit for the german market due to data specificities other interesting results are the german market dominates and leads the long run price relationship the impact of cooling needs on demand is greater than the impact of heating needs there is a substantial systematic pattern of electricity prices and their respective volatilities during weekdays and holidays overall results are supportive of policy making at the european commission regarding electricity market integration

price dynamics among u s electricity spot markets combining recent advances in causal flows with time series analysis relationships among 11 u s spot market electricity prices are examined results suggest that the relationships among the markets vary by time frame in contemporaneous time the western markets are separated from the eastern markets and the electricity reliability council of texas at longer time frames these separations disappear even though electricity transmission between the regions is limited it appears the relationships among markets are not only a function of physical assets such as transmissions lines among markets but by similar and dissimilar institutional arrangements among the markets

volatility transmission and volatility impulse response functions in european electricity forward markets using daily data from march 2001 to june 2005 we estimate a var bekk model and find evidence of return and volatility spillovers between the german the dutch and the british forward electricity markets we apply hafner and herwartz 2006 journal of international money and finance 25 719 740 volatility impulse response function virf to quantify the impact of shock on expected conditional volatility we observe that a shock has a high positive impact only if its size is large compared to the current level of volatility the impact of shocks are usually not persistent which may be an indication of market efficiency finally we estimate the density of the virf at different forecast horizon these fitted distributions are asymmetric and show that extreme events are possible even if their probability is low these results have interesting implications for market participants whose risk management policy is based on option prices which themselves depend on the volatility level

electricity portfolio management optimal peak off peak allocations electricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients this paper proposes a mean variance framework to address the concept of structuring the portfolio and focuses on how to optimally allocate positions in peak and off peak forward contracts it is shown that the optimal allocations are based on the difference in risk premiums per unit of day ahead risk as a measure of relative costs of hedging risk in the day ahead markets the outcomes of the model are then applied to show i that it is typically not optimal to hedge a baseload consumption profile with a baseload forward contract and ii that under reasonable assumptions risk taking by the purchaser is rewarded by lower expected costs

electricity price forecasting using sale and purchase curves the x model abstract our paper aims to model and forecast the electricity price by taking a completely new perspective on the data it will be the first approach which is able to combine the insights of market structure models with extensive and modern econometric analysis instead of directly modeling the electricity price as it is usually done in time series or data mining approaches we model and utilize its true source the sale and purchase curves of the electricity exchange we will refer to this new model as x model as almost every deregulated electricity price is simply the result of the intersection of the electricity supply and demand curve at a certain auction therefore we show an approach to deal with a tremendous amount of auction data using a subtle data processing technique as well as dimension reduction and lasso based estimation methods we incorporate not only several known features such as seasonal behavior or the impact of other processes like renewable energy but also completely new elaborated stylized facts of the bidding structure our model is able to capture the non linear behavior of the electricity price which is especially useful for predicting huge price spikes using simulation methods we show how to derive prediction intervals for probabilistic forecasting we describe and show the proposed methods for the day ahead epex spot price of germany and austria

cointegration analysis of spot electricity prices insights on transmission efficiency in the western us abstract the us energy policy act of 1992 promoted the development of spot markets for electric power by requiring utilities to open their transmission systems to wholesale power sales in this paper we specify and estimate a vector error correction model using peak and off peak electricity spot prices during 1994 1996 covering 11 regional markets in the western united states and test these prices for evidence of market integration the results show evidence of an efficient and stable wholesale power market

electricity prices large scale renewable integration and policy implications abstract this paper investigates the effects of intermittent solar and wind power generation on electricity price formation in germany we use daily data from 2010 to 2015 a period with profound modifications in the german electricity market the most notable being the rapid integration of photovoltaic and wind power sources as well as the phasing out of nuclear energy in the context of a garch in mean model we show that both solar and wind power granger cause electricity prices that solar power generation reduces the volatility of electricity prices by scaling down the use of peak load power plants and that wind power generation increases the volatility of electricity prices by challenging electricity market flexibility

land reforms poverty reduction and economic growth evidence from india recognition of the importance of institutions that provide security of property rights and relatively equal access to economic resources to a broad cross section of society has renewed interest in the potential of asset redistribution including land reforms empirical analysis of the impact of such policies is however scant and often contradictory this paper uses panel household data from india together with state level variation in the implementation of land reform to address some of the deficiencies of earlier studies the results suggest that land reform had a significant and positive impact on income growth and accumulation of human and physical capital the paper draws policy implications especially from the fact that the observed impact of land reform seems to have declined over time

an analysis of the decline of electricity spot prices in europe who is to blame abstract the european electricity markets are going through a phase of agitating transition which is shaped by different key factors such as the expansion of renewable energies the changes in the eu carbon trading scheme and the european market integration in addition markets are affected by the volatile prices of primary energy carriers e g gas and coal the development of these different factors led to a decline of german wholesale electricity prices of almost 40 from about 51 mwh in 2011 to 31 mwh in 2015 the goal of this study is to analyze the contribution of different price drivers to this decline thus an agent based modeling and a regression approach are applied to investigate the effect of price drivers and to verify model results by comparing both approaches our results show that against the public perception the impact of carbon and coal prices on german electricity prices has been twice as high as the renewable expansion between 2011 and 2015 furthermore if carbon and coal prices do not recover to at least the level of 2011 electricity prices will remain on the current low level complicating the economic operation of gas power plants

the limits to land reform the land acts in ireland 1870 1909 ireland experienced two great waves of land reform during the late nineteenth and early twentieth centuries land reform was a central demand of irish political factions of the time and by acceding to this demand successive british governments hoped to pacify ireland this article reconsiders the economic significance of the several irish land reform measures by examining them in the context of economic theory and by comparing them to other land reform episodes in currently developing countries and in european history the irish reforms contained little that could better the allocation of resources and so had little impact on economic efficiency even though the end result was the creation of a class of peasant proprietors operating in a free market the analysis focuses on the structure of the laws and their relation to irish institutions although we also discuss the aggregate evidence on the evolution of agricultural efficiency following the reforms moreover the irish legislation missed an important opportunity to improve smallholders access to credit some facets of the land legislation interacting with some unusual institutional features of land tenure in ireland made credit conditions worse land reform in ireland was much more a wealth redistribution program financed by britain than a serious effort to improve the efficiency of agriculture land tenure and land reform occupy central roles in both the history and historiography of the political struggles that culminated in the partition of ireland in the 1920s successive waves of irish politicians sought to harness essentially nationalist ambitions to the more mundane dissatisfactions of the irish farmer convincing the latter that economic prosperity required alterations to or complete abolition of an agrarian system

heterogeneous price dynamics in u s regional electricity markets abstract the u s electricity wholesale market is organized in several deregulated regional markets this paper compares price dynamics of electricity in the u s wholesale markets and shows that electricity prices from the west and east coasts have different regime dynamics our methodology suggests that electricity prices are better parameterized by four regimes with different levels of volatility additionally west and east coast markets differ in the time spent in each regime the extremely high volatility regime describes west coast prices during the california electricity crisis but east coast prices are also frequent in that regime we find evidence of synchronization of price dynamics in the mean reverting and highest volatility regimes i e prices from the east and west coasts tend to be in the same regimes at the same time

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

predicting price spikes in electricity markets using a regime switching model with time varying parameters this paper shows that a stochastic regime switching model can represent the volatile behavior of wholesale electricity prices associated with price spikes effectively the structure of the model is very flexible because the mean prices in the two regimes and the two transition probabilities are functions of the load and or the implicit reserve margin using price data from the single settlement market in pjm may 1999 to may 2000 the results show that the estimated switching probability from the low to the high regime predicts price spikes well if the reserve margin is measured accurately

the diversity of land markets and regulations in europe and some of its causes abstractthe creation of optimal land institutions attracted renewed attention in the 1990s because of its central role in the transition process in former communist countries in the former soviet union and eastern europe and more recently because of large scale land investments in developing countries this article documents the existence of large variations in land institutions markets and regulation using current and historical data from western and eastern europe it then offers explanations for these differences and draws implications for the role and optimality of land institutions in development with special reference to the current debate on large scale land acquisitions

acquisition of project specific assets with bayesian updating we study the impact of learning on the optimal policy and the time to decision in an infinite horizon bayesian sequential decision model with two irreversible alternatives exit and expansion in our model a firm undertakes a small scale pilot project to learn via bayesian updating about the project s profitability which is known to be in one of two possible states the firm continuously observes the project s cumulative profit but the true state of the profitability is not immediately revealed because of the inherent noise in the profit stream the firm bases its exit or expansion decision on the posterior probability distribution of the profitability the optimal policy is characterized by a pair of thresholds for the posterior probability we find that the time to decision does not necessarily have a monotonic relation with the arrival rate of new information

why ireland starved a quantitative and analytical history of the irish economy 1800 1850 acknowledgements page ix ensp 1 introduction 1 ensp 2 a poverty stricken economy 6 ensp 3 the problem of population was maithus right 30 ensp 4 land leases and length of tenure 81 ensp 5 the economics of rural conflict and unrest 112 ensp 6 the problem of wealth 151 ensp 7 the human factor entrepreneurship and labor 197 ensp 8 emigration and the prefamine economy 230 ensp 9 the great famine the economics of vulnerability 261 10 explaining irish poverty 278 bibliography 295 index 317

spot and derivative pricing in the eex power market using spot and futures price data from the german eex power market we test the adequacy of various one factor and two factor models for electricity spot prices the models are compared along two different dimensions 1 we assess their ability to explain the major data characteristics and 2 the forecasting accuracy for expected future spot prices is analyzed we find that the regime switching models clearly outperform its competitors in almost all respects the best results are obtained using a two regime model with a gaussian distribution in the spike regime furthermore for short and medium term periods our results underpin the frequently stated hypothesis that electricity futures quotes are consistently greater than the expected future spot a situation which is denoted as contango

dependence structure in the australian electricity markets new evidence from regular vine copulae abstract in this study regular vine copula was used to investigate the dependence structure of electricity prices at the state level in the australian national electricity market nem during three periods related to the adoption and abolition of the carbon tax in the pre carbon period we found evidence of tail dependence separately in the northern and southern nem but not across them during the carbon period the joint spike in the northern nem disappeared and the tail dependence in the southern nem decreased in the post carbon period the best dependence structure turned out to be a flexible structure of the regular vine which exactly matches the geographical infrastructure connectedness of transmission wires besides both upper and lower tail dependences were found in all adjacent states after the abolition of the carbon tax suggesting a more integrated market regarding tail dependence our findings have substantial implications for risk management in the nem especially for those participants exposed to multiple states

modeling extreme dependence between european electricity markets electricity spot prices are characterized by sudden large movements followed a few days later by an equally large movement in the opposite direction these phenomena are called spikes upward movements and drops downward movements recent research has suggested that the dynamics of the electricity spot prices can be accurately described by hidden markov regime switching mrs models regime switch models separate the ordinary dependence and the extreme spike or drop dependence this is a crucial point since it is the extreme dependence that is of interest when computing risks we fit a large number of mrs models to six european electricity markets eex powernext apx power uk nl nord pool system sweden in order to analyze the nature of the prices the estimated regimes are then used to analyze the probability of an extreme event and the conditional probability for one market to experience an extreme event conditional that another market is experiencing the same event we find that the frequency of extreme events is positively related to the amount of renewable energy sources in the power system it can be argued that the dependence results in this paper give an indication of what future dependence for even more integrated markets with more renewable energy will be the integration of markets will lead to efficient sharing of reserves while the additional renewable energy will increase the need for reserves the results are of interest when computing financial risks e g var or expected shortfall when designing reserves but also as an indication of the degree of integration between markets

a stochastic fuel switching model for electricity prices abstract this paper develops and applies a novel electricity price model we reproduce the merit order of a thermal dominated electricity system by establishing a non linear dependency of wholesale electricity prices on the prices of fuels coal and natural gas and of co 2 emission allowances the coefficients are estimated using a markov switching regression this approach might prove valuable for cross hedging positions in the fuel electricity and emission spot markets it is also of use for studying the degree to which electricity prices in different countries reflect fuel and emission cost applying the model to the electricity markets of the uk and germany we find that british electricity prices are quite well explained by short run cost factors while the german ones are less well explained

the case of negative day ahead electricity prices in recent years germany has significantly increased its share of electricity produced from renewable sources which is mainly due to the renewable energy act eeg the eeg substantially impacts the dynamics of intra day electricity prices by increasing the likelihood of negative prices in this paper we present a non gaussian process to model german intra day electricity prices and propose an estimation procedure for this model most importantly our model is able to generate extreme positive and negative spikes a simulation study demonstrates the ability of our model to capture the characteristics of the data

an empirical comparison of alternate regime switching models for electricity spot prices one of the most profound features of electricity spot prices are the price spikes markov regime switching mrs models seem to be a natural candidate for modeling this spiky behavior however in the studies published so far the goodness of fit of the proposed models has not been a major focus while most of the models were elegant their fit to empirical data has either been not examined thoroughly or the signs of a bad fit ignored with this paper we want to fill the gap we calibrate and test a range of mrs models in an attempt to find parsimonious specifications that not only address the main characteristics of electricity prices but are statistically sound as well we find that the most universal and robust structure is that of an independent spike 3 regime model with heteroscedastic diffusion type base regime dynamics and shifted spike regime distributions

long run relations in european electricity prices this paper analyses the interdependencies existing in wholesale electricity prices in six major european countries the results of a robust multivariate long run dynamic analysis reveal the presence of four highly integrated central european markets france germany the netherlands and austria the trend shared by these four electricity markets appears to be common also to gas prices but not to oil prices the existence of a common long term dynamics among electricity prices and between electricity prices and gas prices can be explained by the similarity of the market design across europe and by the same marginal generation technology since standard unit root and cointegration tests are not robust to the peculiar characteristics of electricity prices time series we also develop a battery of robust inference procedures that should assure the reliability of our results copyright 2009 john wiley sons ltd

combining forecast densities from vars with uncertain instabilities recursive weight forecast combination is often found to an ineffective method of improving point forecast accuracy in the presence of uncertain instabilities we examine the effectiveness of this strategy for forecast densities using many vector autoregressive var and autoregressive ar models of output growth inflation and interest rates our proposed recursive weight density combination strategy based on the recursive logarithmic score of the forecast densities produces well calibrated predictive densities for us real time data by giving substantial weight to models that allow for structural breaks in contrast equal weight combinations produce poorly calibrated forecast densities for great moderation data copyright 2010 john wiley sons ltd

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

stochastic price modeling of high volatility mean reverting spike prone commodities the australian wholesale spot electricity market it is commonly known that wholesale spot electricity markets exhibit high price volatility strong mean reversion and frequent extreme price spikes this paper employs a basic stochastic model a mean reverting model and a regime switching model to capture these features in the australian national electricity market nem comprising the interconnected markets of new south wales queensland south australia and victoria daily spot prices from 1 january 1999 to 31 december 2004 are employed the results show that the regime switching model outperforms the basic stochastic and mean reverting models electricity prices are also found to exhibit stronger mean reversion after a price spike than in the normal period and price volatility is more than fourteen times higher in spike periods than in normal periods the probability of a spike on any given day ranges between 5 16 in nsw and 9 44 in victoria

modelling interregional links in electricity price spikes abnormally high price spikes in spot electricity markets represent a significant risk to market participants as such a literature has developed that focuses on forecasting the probability of such spike events moving beyond simply forecasting the level of price many univariate time series models have been proposed to dealwith spikes within an individual market region this paper is the first to develop a multivariate self exciting point process model for dealing with price spikes across connected regions in the australian national electricity market the importance of the physical infrastructure connecting the regions on the transmission of spikes is examined it is found that spikes are transmitted between the regions and the size of spikes is influenced by the available transmission capacity it is also found that improved risk estimates are obtained when inter regional linkages are taken into account

portfolio applications in electricity markets review private investor and manager perspective trends abstract the private sector plays a major role in the expansion and operation of power systems in most countries especially those running liberalized electricity markets policymakers have the task of inducing private agents through their regulatory designs to make decisions that point toward social welfare maximization conversely it is a task of private agents to protect themselves against the risks of the sector including regulatory risks international fuel price uncertainty climate change policies natural resource availability electricity demand uncertainty co2 clearance prices etc instead of hiding all of these risks within the total project costs and losing competitiveness private agents can use diversification as a strategy to deal with them this paper presents a review of the main applications voids and challenges of portfolio optimization for two key agents of the private sector investors and managers the problem of the investor is to design a technology portfolio to invest in that maximizes its expected returns and limits risks while the manager has to design a portfolio of financial physical instruments long term contracts futures etc to sell buy electricity and hedge against price risks we have found two fundamental issues in the literature the first and most important is excessive confidence in historical data and statistical analysis for predicting future price behavior for a changing future in detriment of more structural analysis structural analysis can include particularities of modern power systems such as future transmission changes congestion operational constraints ramps new entrants new technologies and new demand grow patterns that cannot be taken into account by simply analyzing price historical values the second is the omission of renewable complementarities which is a proven characteristic of dispersed renewable plants that may have important risk mitigation effects although it has largely been ignored in portfolio analysis due to insufficient data modeling limitations and computational complexity

why do electricity prices jump empirical evidence from the nordic electricity market the paper empirically explores the possible causes behind electricity price jumps in the nordic electricity market nord pool a time series model a mixed garch earji jump model capturing the com

hmm filtering and parameter estimation of an electricity spot price model abstract in this paper we develop a model for electricity spot price dynamics the spot price is assumed to follow an exponential ornstein uhlenbeck ou process with an added compound poisson process in this way the model allows for mean reversion and possible jumps all parameters are modulated by a hidden markov chain in discrete time they are able to switch between different economic regimes representing the interaction of various factors through the application of reference probability technique adaptive filters are derived which in turn provide optimal estimates for the state of the markov chain and related quantities of the observation process the em algorithm is applied to find optimal estimates of the model parameters in terms of the recursive filters we implement this self calibrating model on a deseasonalised series of daily spot electricity prices from the nordic exchange nord pool on the basis of one step ahead forecasts we found that the model is able to capture the empirical characteristics of nord pool spot prices

inequality as a determinant of malnutrition and unemployment policy this paper explores the policy implications that are obtained once it is recognized that at low nutrition intakes a person s productivity is an increasing function of intake in the context of a fully general equilibrium model it is shown that if aggregate assets in an economy are neither large nor small certain patterns of lorenz improving asset redistributions or nutrition transfers increase aggregate output and reduce the volume of involuntary unemployment and the incidence of undernourishment copyright 1987 by royal economic society

switching outputs in a bioenergy cogeneration project a real options approach abstract environmental concerns have stimulated the search for economically feasible renewable energy projects one such alternative is the use of biomass for energy generation which has increasingly been the focus of interest traditional valuation methods on the other hand fail to capture the value of the embedded options that exist in many of these projects which may lead to non optimal investment decisions in this article we analyze the feasibility of installing a cogeneration unit in an industrial plant in brazil in order to extract value from biomass residue currently discarded which can be used for thermal and electric energy generation the cogeneration unit also allows the firm the flexibility to optimally choose between an increase in production or the generation of surplus energy for sale in the short term market once additional investment in interconnection to the grid is made we model the uncertainty over future energy prices as a mean reverting process with jumps and seasonality and the embedded flexibility as a bundle of european options under the real options approach the results indicate that the investment in the cogeneration plant is warranted and that the option to switch outputs adds significant value to the project which suggests that biomass residue may be a sustainable energy alternative in this case

costly sequential experimentation and project valuation with an application to health technology assessment we study the optimal investment abandonment decision for a project where costly sequential experimentation provides information about its true profitability we derive the optimal decision rule by appropriately extending the bayesian framework of sequential hypothesis testing the optimal decision time takes the form of the first exit time of a particular inaction region we find that increased noise in the observations lowers the value of the project and that the effect on the expected time at which a decision is taken is ambiguous delays in observations affect both project value and the inaction region the model is illustrated with a health technology assessment application using data on standard versus robot assisted laporascopic prostatectomy

valuation anomalies for interconnector transmission rights whilst the acquisition of physical transmission interconnector rights between two or more electricity markets can be structured as spread options on the spot prices of electricity between connected markets empirical evidence suggests that actual prices may be quite different this raises issues for the valuation of transmission rights particularly in the european context of market harmonisation and the use of transmission rights with increasing levels of wind penetration we examine the price differentials between the irish and british electricity markets where explicit transmission capacity auctions have been persistently undersubscribed and transmission rights acquired but not fully utilised we find significant empirical indications that auction prices for transmission rights are undervalued against both arbitrage and spread option valuations we also find significant power flows against the efficient price spread direction a survey of a group of experts with an interest in trading power between ireland and britain inform a number of possible explanations for the apparent inefficiencies these include ex post pricing in the irish market intermittent wind and strategic behaviour by dominant firms

on transition probabilities of regime switching in electricity prices we analyze the transition probabilities of regime switching in electricity prices by explicitly incorporating the underlying demand supply structure we show that the transition probabilities of electricity prices cannot be constant and depend on both the current demand level relative to the supply capacity and the trends of demand fluctuation these results not only contrast with the assumption of constant transition probabilities on which many regime switching models are built but also provide new insights on the determinants of the state dependent transition probabilities of regime switching

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

market price of risk implied by asian style electricity options and futures in this paper we propose a jump diffusion type model which recovers the main characteristics of electricity spot price dynamics in the nordic market including seasonality mean reversion and spiky behavior we show how the calibration of the market price of risk to actively traded futures contracts allows for efficient valuation of nord pool s asian style options written on the spot electricity price furthermore we study the evolution of the market price of risk and the risk premium over a three year time period and compare the obtained results with those reported in the literature

regime switching based vehicle to building operation against electricity price spikes abstract electricity price may present very large spikes due to imbalance between generation and demand especially during heavily loaded periods such peak price may incur significant cost to building operation with the vehicle to building v2b technology electric vehicle battery can be used as temporal energy source for the building load for a short period which leads to a possible solution for reducing the energy cost during peak price periods in this paper the problem of reducing the energy cost due to the peak price is approached from the prospective of risk management a regime switching based risk management scheme is proposed for the v2b operation based on the availability of electric vehicles ev plugged in the parking lots attached to the building in the low risk regime the objective is to minimize the ev charging cost while in the high risk regime the objective is to reduce the potentially high energy cost due the peak price via the power stored in ev batteries based on markov regime switching model the operation minimizes the conditional value at risk involved simulation results show that the proposed framework can greatly reduce the energy cost against the electricity peak prices

forecasting power prices using a hybrid fundamental econometric model we investigate the performance of two hybrid forecasting models to predict the next day base load electricity prices on the apx power exchange for great britain hybrid models have often been advocated as a synthetic method for forecasting but it is an open question how well they perform at the day ahead stage a conventional hybrid approach combines a fundamental model formulated with supply stack modeling with an econometric model using data on price drivers we extend this model to one based upon logistic smooth transition regression which represents a regime switching for periods of structural change empirical results for out of sample forecasting using both hybrid approaches are discussed and compared to non hybrid time series forecasting methods

econometric modeling of regional electricity spot prices in the australian market abstract wholesale electricity markets are increasingly integrated via high voltage interconnectors and inter regional trade in electricity is growing to model this we consider a spatial equilibrium model of price formation where constraints on inter regional flows result in three distinct equilibria in prices we use this to motivate an econometric model for the distribution of observed electricity spot prices that captures many of their unique empirical characteristics the econometric model features supply and inter regional trade cost functions which are estimated using bayesian monotonic regression smoothing methodology a copula multivariate time series model is employed to capture additional dependence both cross sectional and serial in regional prices the marginal distributions are nonparametric with means given by the regression means the model has the advantage of preserving the heavy right hand tail in the predictive densities of price we fit the model to half hourly spot price data in the five interconnected regions of the australian national electricity market the fitted model is then used to measure how both supply and price shocks in one region are transmitted to the distribution of prices in all regions in subsequent periods finally to validate our econometric model we show that prices forecast using the proposed model compares favorably with those from some benchmark alternatives

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

counterfactual comparisons of investment options for wind power and agricultural production in the united states lessons from northern ohio abstract we analyze potential efficiency gains in wind power projects by comparing counterfactual investment decisions in two different scenarios under a real options framework the first scenario is a standard wind power investment where the investor rents the land from local farms in the second scenario the wind power investor buys the land and commercializes both electricity and crop production thus reducing the revenue risk through the diversification both scenarios have a waiting option with the wholesale prices leading the installation decision we model the electricity price as a mean reverting process with jumps and with different jumping probabilities for the different seasons of the year corn prices follow a mean reverting process the waiting flexibility was modeled as a bundle of european options the results indicate that the waiting option is exercised in 100 of our simulations in both scenarios suggesting the still important role of government policies to stimulate wind power more importantly in more than 90 of the simulations the second scenario brought value to the investment furthermore net present values are more sensitive to reductions in capital costs than electricity prices these results can form the basis for more effective policies for the wind power sector

the effects of renewables in space and time a regime switching model of the italian power price abstract renewable energy production can exercise a downward pressure on electricity prices by partly crowding out conventional units characterized by higher marginal costs merit order effect yet congestion induced by renewables would partly offset the merit order effect in the congested zone unless renewables reduce the need for imports and allow the emergence of prosumers these congestion effects of renewables are hereby jointly tested with the merit order effect by means of an endogenous regime switching model wherein a regime corresponds to the observable status congested non congested of the grid the model is taken to data from the italian power exchange observed in 2012 and 2013 with a focus on the line connecting sicily with the south zone a frequent bottleneck in the italian transmission grid the results confirm the merit order effect previously detected in the literature and highlight a negative congestion effect i e renewables relieve congestion from sicily a systematic importer but not from the italian peninsula the exporting region this effect is mainly driven by the wind power in feed

how renewable production depresses electricity prices evidence from the german market abstract the urgency of climate change has led several countries to develop renewable energy in order to reduce co2 emissions through the means of various subsidies in the electricity sector one drawback of such policies is the negative impact on electricity prices known as the merit order effect this paper aims at assessing how intermittent renewable production depresses electricity prices in germany which has experienced a significant increase of its renewable capacity over the last two decades to do so we use a two regime markov switching model that enables to disentangle the impact of wind and solar generation depending on the price being high or low we find as expected that renewable production induces a negative marginal effect which is stronger in regimes of relatively high prices in addition we show that both wind and solar productions have a significant impact on the distribution of prices and in particular on the frequency and expected duration of each regime this has implications in terms of market design security of supply and support mechanisms for renewables

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

an hour ahead prediction model for heavy tailed spot prices abstract we propose an hour ahead prediction model for electricity prices that capture the heavy tailed behavior that we observe in the hourly spot market in the ercot texas and the pjm west hub grids we present a model according to which we separate the price process into a thin tailed trailing median process and a heavy tailed residual process whose probability distribution can be approximated by a cauchy distribution we show empirical evidence that supports our model

integration and shock transmissions across european electricity forward markets abstract new results are presented relating to the integration of the french german british dutch and spanish power markets at day ahead week ahead one month ahead and two month ahead lead times overall there is evidence of market integration increasing over time despite an underlying inefficiency in each market with respect to the forward and spot price convergence the spatial analysis on a financial dimension is undertaken using causality tests cointegration and impulse response techniques for both price levels and volatilities in general we find less influence of the size and proximity of neighbouring markets than other studies more integration at baseload than peak and surprisingly less integration in forwards than spot prices

modeling and short term forecasting of new south wales electricity system load this article employs bayesian semiparametric regression methodology to model intraday electricity load data and obtain short term load forecasts the role of such forecasts in the new south wales wholesale electricity market is discussed and the method applied to new south wales system load data the semiparametric regression model used identifies daily periodic weekly periodic and temperature sensitive components of load each component is decomposed as a linear combination of basis functions with a nonzero probability mass that the corresponding coefficients are exactly zero three possible models for the errors are also considered including independent autoregressive and first differenced autoregressive models a moving window of data is used to overcome the slow time varying nature of the temperature and periodic effects the entire model is estimated using a bayesian markov chain monte carlo approach and forecasts are obtained using a monte carlo sample from the joint predictive distribution o

modeling and forecasting multivariate electricity price spikes abstract we consider the problem of forecasting the occurrence of extreme prices in the australian electricity markets from high frequency spot prices in particular we are interested in the simultaneous occurrence of such so called spikes in two or more markets our approach is based on a novel dynamic model for multivariate binary outcomes which allows the latent variables driving these observed outcomes to follow a vector autoregressive process furthermore the model is constructed using a copula representation for the joint distribution of the resulting innovations this has several advantages over the standard multivariate probit model first it allows for nonlinear dependence between the error terms second the distribution of the latent errors can be chosen freely third the computational burden can be greatly reduced making estimation feasible in higher dimensions and for large samples the model is applied to spikes in half hourly electricity prices in four interconnected australian markets the multivariate model provides a superior fit compared to single equation models and generates better forecasts for spike probabilities furthermore evidence of spillover dynamics between the markets is revealed

making negotiated land reform work initial experience from colombia brazil and south africa abstract the paper describes background initial experience and future challenges associated with a new negotiated approach to land reform this approach has emerged as following the end of the cold war and broad macroeconomic adjustment many countries face a second generation of reforms to address deep rooted structural problems and provide the basis for sustainable poverty reduction and economic growth it reviews possible theoretical links through credit market or political channels between asset ownership and economic performance program characteristics in each country as well as lessons for implementation and implications for monitoring and impact assessment are discussed

a history of european electricity day ahead prices in this article we examine the development of day ahead prices in five european markets which became more connected over recent years where previous studies examined the convergence of price levels over time we focus on patterns in estimates for the parameters in a switching regimes model this makes it possible to distinguish between prices under normal market conditions and under non normal market conditions those market conditions that can cause extreme price spikes we expect that increased connectivity yields additional supply in the short term and therefore will reduce the impact of price spikes our results indicate that the impact of price spikes and volatility decreased over time that prices behave more random and that the parameter estimates between various connected markets seem to have converged between the belgian dutch french german and nordic day ahead markets over the years 2003 through 2010 these results can be explained by increased connectivity and improved liquidity

effects of renewables on the stylized facts of electricity prices abstract many countries around the world have increased their renewable installed capacity due to a greater awareness of climate concerns under this new framework with renewables being among the main generation sources the literature warns of a dramatic change in price behaviour some of the most commonly claimed effects of having a significant proportion of renewable generating sources in the total electricity production mix include i a systematic decrease in overall wholesale market prices ii a higher occurrence of price jumps and iii a significant increase in price volatility the goal of the present study is to test whether these changes in price behaviour have actually come about to do so we focus on the spanish day ahead electricity market as a paradigmatic example in line with the literature it is found a statistically negative relationship between the renewable generation share and the day ahead market marginal prices as well we have obtained statistical confirmation of the fact that renewables generation share volatility is transferred to price volatility though similarly to other generation technologies finally in contrast to the general belief that the introduction of renewable generation would give rise to extreme positive prices according to our results increases in renewables generation share reduce the probability of upward jumps in prices the results obtained are of interest for portfolio managers practitioners and regulators