the role of benefit transfer in ecosystem service valuation the demand for timely monetary estimates of the economic value of nonmarket ecosystem goods and services has steadily increased over the last few decades this article describes the use of benefit transfer to generate monetary value estimates of ecosystem services specifically the article provides guidance for conducting such benefit transfers and summarizes advancements in benefit transfer methods databases and analysis tools designed to facilitate its application

the drivers of international migration to the uk a panel based bayesian model averaging approach a heterogeneous panel based bayesian model averaging approach is used to identify the robust economic and policy drivers of international migration to the uk from 14 different source regions over 1980 2007 around three quarters of the increase in net immigration over the last decade which is particularly pronounced for selected source regions is associated with structural change which may be attributed to uk and foreign immigration policy the remainder of the rise is largely explained by friends and family effects there are considerable uncertainties associated both with the effects of particular economic drivers of immigration and with forecasts of immigration

statistical efficiency of double bounded dichotomous choice contingent valuation the statistical efficiency of conventional dichotomous choice contingent valuation surveys can be improved by asking each respondent a second dichotomous choice question which depends on the response to the first question if the first response is yes the second bid is some amount greater than the first bid while if the first response is no the second bid is some amount smaller this double bounded approach is shown to be asymptotically more efficient than the conventional singlebounded approach using data from a survey of californians regarding their willingness to pay for wetlands in the san joaquin valley we show that in a finite sample the gain in efficiency can be very substantial

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

is it worthwhile to pay referees there are puzzles in refereeing scholarly articles why are referees willing to review a paper without payment and is it worthwhile to pay referees in order to raise the review rate two interesting results are found in this article first when reviewing services are driven by reciprocity the equilibrium participation of referees may exhibit the so called self fulfilling feature second the optimal payment may not be zero if the referee receives the benefit of reputation gained by refereeing an article in particular this article will show that those journals whose status quo review rate is lower tend to pay reviewers more while journals whose status quo review rate is higher do not find it worthwhile to pay referees enough this result implies that in order to raise its quality a journal with a low review rate is more likely to adopt a strategy to increase pay and attract a critical mass of referees

value at risk estimation with the optimal dynamic biofuel portfolio abstract in the past petroleum companies only paid attention to hedging the variation in the crude oil price and volatility however they have now expanded their analysis to encompass renewable sources such as corn and soybeans under the current low carbon biofuel obligations this paper employs garch 1 1 and arji models to estimate the one day ahead value at risk var of the optimal dynamic biofuel portfolio which consists of crude oil corn and soybeans the optimal blended standard is subject to the dual limitations of minimum production costs and the lowest biofuel using requirements our empirical findings confirm that the arji model is more suitable than the garch 1 1 model and further captures the discontinuous jump behavior from the in the sample data the results of out of sample forecasts also are represented that our models play important roles in var estimation and risk management for biofuel portfolio we therefore suggest that the petroleum companies should simultaneously pay attention to jump risk in hedging material costs in the prices of energy related crops

the performance of composite forecast models of value at risk in the energy market this paper examines a comparative evaluation of the predictive performance of various value at risk var models in the energy market this study extends the conventional research in literature by proposing composite forecast models for applying to brent and wti crude oil prices forecasting techniques considered here include the ewma stable density kernel density hull and white garch gpd plus composite forecasts from linearly combining two or more of the competing models above findings show hull and white to be the most powerful approach for capturing downside risk in the energy market reasonable results are also available from carefully combining var forecasts

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

real time density forecasts from bayesian vector autoregressions with stochastic volatility central banks and other forecasters are increasingly interested in various aspects of density forecasts however recent sharp changes in macroeconomic volatility including the great moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession pose significant challenges to density forecasting accordingly this paper examines with real time data density forecasts of u s gdp growth unemployment inflation and the federal funds rate from bayesian vector autoregression bvar models with stochastic volatility the results indicate that adding stochastic volatility to bvars materially improves the real time accuracy of density forecasts this article has supplementary material online

does paying referees expedite reviews results of a natural experiment a natural experiment in an economics field journal afforded time series observations on payments to referees for on time reviews the natural experiment yielded 15 months worth of data with no payments and about two subsequent years of data with payments using refereeand manuscript specific measures as covariates hazard models were used to gauge the effects of payments on individual referee s review times all models indicate statistically significant reductions in review times owing to referee payments reductions in review times translate into significant reductions in first response time frt median frt was reduced from 90 to 70 days a 22 reduction in the presence of payments with payments only 1 of the frts exceeded six months without payments 16 of the frts exceeded six months

forecasting portfolio value at risk with nonparametric lower tail dependence estimates abstract we propose to forecast the value at risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence we compare our proposed method to a conventional copula garch model where the parameter of a clayton copula is estimated via canonical maximum likelihood the superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine dimensional financial portfolio a comparison of the out of sample forecasting accuracy of both models confirms that our model yields economically significantly better value at risk forecasts than the competing parametric calibration strategy

valuation of wetlands in a landscape and institutional perspective what is a wise use of nature this perennial issue always controversial due to conflicting human interests has in the last decade tended to be clothed in the context of sustainable development the rapid breakthrough of this concept in political and scientific spheres has brought to our attention the dependence of human survival and well being upon ecosystem supports e g baskin 1997 costanza et al 1997 daily 1997 as well as the susceptibility of ecosystems to human influences how can such a political and scientific attention to ecosystems be translated to good public policy one necessary prerequisite is likely to be the adoption of a landscape perspective such a perspective implies studies of the biological and physical interactions among a mosaic of ecosystems in heterogeneous land areas that together comprise landscapes it is worth emphasising however that human presence and man made social economic and physical structures are equally natural landscape elements continually interacting with ecosystems the fact that humans and nature are inseparable and the apparently ever increasing human influence on her biological and physical environments make an analysis of the linkages between ecosystems and humans an indispensable part of a landscape perspective institutional design in the context of interaction between society and nature has indeed been subject to several recent studies for example ostrom 1990 bromley 1991 hanna et al 1996 and berkes and folke 1998 institutions include social norms codes and other informal constraints for human behaviour as well as formal ones such as constitutions and laws their design is one key to understanding human preferences and behaviour in relation to nature the study of institutions is thus an integral part of a landscape perspective corresponding author tel 46 8 6739540 fax 46 8152464 e mail address tore beijer kva se t soderqvist

does incentive provision increase the quality of peer review an experimental study although peer review is crucial for innovation and experimental discoveries in science it is poorly understood in scientific terms discovering its true dynamics and exploring adjustments which improve the commitment of everyone involved could benefit scientific development for all disciplines and consequently increase innovation in the economy and the society we have reported the results of an innovative experiment developed to model peer review we demonstrate that offering material rewards to referees tends to decrease the quality and efficiency of the reviewing process our findings help to discuss the viability of different options of incentive provision supporting the idea that journal editors and responsible of research funding agencies should be extremely careful in offering material incentives on reviewing since these might undermine moral motives which guide referees behavior

rolling sampled parameters of arch and levy stable models in this paper an asymmetric autoregressive conditional heteroskedasticity arch model and a levy stable distribution are applied to some well known financial indices dax30 ftse20 ftse100 and sp500 using a rolling sample of constant size in order to investigate whether the values of the estimated parameters of the models change over time although there are changes in the estimated parameters reflecting that structural properties and trading behaviour alter over time the arch model adequately forecasts the one day ahead volatility a simulation study is run to investigate whether the time variant attitude holds in the case of a generated arch data process revealing that even in that case the rolling sampled parameters are time varying

liquidity adjusted intraday value at risk modeling and risk management an application to data from deutsche borse abstract this paper develops a high frequency risk measure the liquidity adjusted intraday value at risk livar our objective is to explicitly consider the endogenous liquidity dimension associated with order size by reconstructing the open limit order book of deutsche borse changes in the tick by tick ex ante frictionless return and actual return are modeled jointly the risk related to the ex ante liquidity premium is then quantified our model can be used to identify the impact of ex ante liquidity risk on total risk and to provide an estimation of the var for the actual return at a point in time in our sample liquidity risk can account for up to 32 of total risk depending on order size

asymmetric error correction models for the oil gasoline price relationship abstract the existing literature on price asymmetries does not systematically investigate the sensitivity of the empirical results to the choice of a particular econometric specification this paper fills this gap by providing a detailed comparison of the three most popular models designed to describe asymmetric price behavior namely asymmetric ecm autoregressive threshold ecm and ecm with threshold cointegration each model is estimated on a common monthly data set for the gasoline markets of france germany italy spain and uk over the period 1985 2003 all models are able to capture the temporal delay in the reaction of retail prices to changes in spot gasoline and crude oil prices as well as some evidence of asymmetric behavior however the type of market and the number of countries which are characterized by asymmetric oil gasoline price relations vary across models the asymmetric ecm prescribes that long run price asymmetries are most likely to be found in the second stage of the transmission chain conversely the ecm with threshold cointegration suggests that long run price asymmetries vary across countries and markets short run price asymmetries are captured by the asymmetric ecm specification and the tar ecm the latter model suggests that all european countries are likely to be affected by asymmetries at the distribution stage while the results obtained with the asymmetric ecm are mixed

ecological economic analysis of wetlands scientific integration for management and policy abstract wetlands all over the world have been lost or are threatened in spite of various international agreements and national policies this is caused by 1 the public nature of many wetlands products and services 2 user externalities imposed on other stakeholders and 3 policy intervention failures that are due to a lack of consistency among government policies in different areas economics environment nature protection physical planning etc all three causes are related to information failures which in turn can be linked to the complexity and invisibility of spatial relationships among groundwater surface water and wetland vegetation integrated wetland research combining social and natural sciences can help in part to solve the information failure to achieve the required consistency across various government policies an integrated wetland research framework suggests that a combination of economic valuation integrated modelling stakeholder analysis and multi criteria evaluation can provide complementary insights into sustainable and welfare optimising wetland management and policy subsequently each of the various components of such integrated wetland research is reviewed and related to wetland management policy

cowboys cornucopians and long run sustainability abstract in the 1970s there was a lively debate on the relationship between natural resource availability and long run economic growth one side has been characterized as neo malthusian it emphasized the limited global stockpile of critical natural resources from cobalt to petroleum and the need to curb population and economic growth the other side of the debate has been characterized as cornucopian it emphasized the creative powers of technology and free markets to find substitutes for any and all scarce resources this paper argues that the original dichotomy was false it did not adequately represent either the real positions of most conservative business and political leaders today nor did it reflect the currently emerging consensus among environmentalists the former do not concern themselves with long run issues at all nor do they take a global view of the problems of mankind rather they argue from the standpoint of short run national and corporate interest environmentalists on the other hand do not fit the neo malthusian world view which emphasizes the role of natural resources and land as factors of production and points to the limited supply of renewable resources and the inevitable exhaustion of non renewables the most important scarcities in the emergent environmentalist world view are largely outside the market domain soil fertility clean fresh water clean fresh air unspoiled landscapes climatic stability biological diversity biological nutrient recycling and environmental waste assimilative capacity there are no plausible technological substitutes for these the irreversible loss of species and ecosystems and the buildup of greenhouse gases in the atmosphere and of toxic metals and chemicals in the topsoil groundwater and in the silt of lake bottoms and estuaries are not reversible by any plausible technology that could appear in the next few decades finally the great nutrient cycles of the natural world carbon oxygen nitrogen sulfur and phosphorus require that constant stocks in each environmental compartment and balanced inflows and outflows these conditions have already been violated by large scale and unsustainable human intervention

valuation and management of wetland ecosystems we recently completed a study of wetland values in coastal louisiana that employed both willingness to pay and energy analysis based methodologies and were able to bracket a range of values within which we feel fairly confident the true value lies however a large amount of uncertainty remains our current estimates of the total prsent value of an average acre of natural wetlands in louisiana are us 2429 6400 per acre assuming an 8 discount rate to 8977 17000 per acre assuming a 3 discount rate at the lowest value the current annual rate of loss of louisiana wetlands 50 sq miles per year is worth about 77 million at the largest value it is worth about 544 million in this paper we a discuss the fundamental theoretical and practical problems underlying natural resources valuation b summarize our methods and findings for louisiana wetlands and c elaborate on some of the more recalcitrant problems attending applied natural resource valuation including discounting and dealing with uncertainty and imprecision the discount rate makes more difference in the final result than any other one factor and yet there is much disagreement about the appropriate approach to discounting natural resources we discuss the discounting problem as applied to natural resources and argue for lower discount rates for valuing renewable natural resources than apply for other aspects of the economy it now seems clear that no reasonable amount of effort will produce very precise estimates of wetland values and we suspect this is also the case for several other classes of natural resources we elaborate a wetlands asurance bonding system to address these problems

do banks overstate their value at risk abstract this paper is the first empirical study of banks risk management systems based on non anonymous daily value at risk var and profit and loss data using actual data from the six largest canadian commercial banks we uncover evidence that banks exhibit a systematic excess of conservatism in their var estimates the data used in this paper have been extracted from the banks annual reports using an innovative matlab based data extraction method out of the 7354 trading days analyzed in this study there are only two exceptions i e days when the actual loss exceeds the disclosed var whereas the expected number of exceptions with a 99 var is 74 for each sample bank we extract from historical vars a risk overstatement coefficient ranging between 19 and 79 we attribute var overstatement to several factors including extreme cautiousness and underestimation of diversification effects when aggregating vars across business lines and or risk categories we also discuss the economic and social cost of reporting inflated vars

comparison of historically simulated var evidence from oil prices abstract cabedo and moya cabedo j d moya i 2003 estimating oil price value at risk using the historical simulation approach energy economics 25 239 253 find that arma with historical simulation delivers var forecasts that are superior to those from garch we compare the arma with historical simulation to the semi parametric garch model proposed by barone adesi et al barone adesi g giannopoulos k vosper l 1999 var without correlations for portfolios of derivative securities journal of futures markets 19 5 583 602 the results suggest that the semi parametric garch model generates var forecasts that are superior to the var forecasts from the arma with historical simulation this is due to the fact that garch captures volatility clustering our findings suggest that cabedo and moya s conclusion is mainly driven by the normal distributional assumption imposed on the future risk structure in the garch model

a new pearson type qmle for conditionally heteroscedastic models this article proposes a novel pearson type quasi maximum likelihood estimator qmle of garch p q models unlike the existing gaussian qmle laplacian qmle generalized non gaussian qmle or lad estimator our pearsonian qmle pqmle captures not just the heavy tailed but also the skewed innovations under strict stationarity and some weak moment conditions the strong consistency and asymptotic normality of the pqmle are obtained with no further efforts the pqmle can be applied to other conditionally heteroscedastic models a simulation study is carried out to assess the performance of the pqmle two applications to four major stock indexes and two exchange rates further highlight the importance of our new method heavy tailed and skewed innovations are often observed together in practice and the pqmle now gives us a systematic way to capture these two coexisting features

roughing it up including jump components in the measurement modeling and forecasting of return volatility a rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high frequency returns coupled with simple modeling procedures building on recent theoretical results in barndorff nielsen and shephard 2004a 2005 for related bi power variation measures the present paper provides a practical and robust framework for non parametrically measuring the jump component in asset return volatility in an application to the dm exchange rate the s p500 market index and the 30 year u s treasury bond yield we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process moreover many jumps appear directly associated with specific macroeconomic news announcements separating jump from non jump movements in a simple but sophisticated volatility forecasting model we find that almost all of the predictability in daily weekly and monthly return volatilities comes from the non jump component our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling forecasting and pricing the continuous and jump components of the total return variation process

ecosystem service value assessment for constructed wetlands a case study in hangzhou china abstract based on a comprehensive analysis of various classifications of natural resource values we summarized an ecological economic value system of constructed wetland cw ecosystems for treating eutrophic water using the cw located at the hangzhou botanical garden as an example the contingent valuation method cvm and shadow project approach spa were applied to estimate the economic values of cw system ecosystem services the cvm estimated a value of 800 000 yuan yuan chinese currency 7 6 yuan 1 usd as of august 2007 as the total economic value of the cw in a twenty year period meanwhile the spa calculated a value of 23 04 million yuan as the total economic value of the cw in a twenty year period it is determined that compared to the cvm the spa provides a more approximate value of the true monetary value of the hangzhou botanical garden cw this study could fill the gap of knowledge and provide a benchmark when evaluating constructed ecosystem services and help policy makers to promote the development of constructed wetlands in china

implementing a stochastic model for oil futures prices this paper develops a parsimonious three factor model of the term structure of oil futures prices that can be easily estimated from available futures price data in addition it proposes a new simple spreadsheet implementation procedure the procedure is flexible may be used with market prices of any oil contingent claim with closed form pricing solution and easily deals with missing data problems the approach is implemented using daily prices of all futures contracts traded at the new york mercantile exchange between 1991 and 2001 in sample and out of sample tests indicate that the model fits the data extremely well though the paper concentrates on oil the approach can be used for any other commodity with well developed futures markets

the new approach to wilderness preservation through benefit cost analysis over the last 15 years economists of resources for the future led by john krutilla have been developing a new approach to wilderness preservation this paper offers a concise exposition of their approach and adds a few new steps the basic ingredient of the new approach is a perception of declining net benefits of wilderness development and rising net benefits of wilderness preservation over time these alter the entire shape of the benefit cost analysis of potential development the new steps involve reversibility postponability and recognition of multiple interest rates

the ecosystem services framework and natural capital conservation work at the interface of ecology and economics has inspired a major transformation in the way people think about the environment increasingly ecosystems are seen as capital assets with the potential to generate a stream of vital life support services meriting careful evaluation and investment we first present the concepts underpinning the ecosystem services framework esf laying out the scope and limitations of the approach we then describe the major challenges in making the esf operational i detailed information at scales relevant to decision making ii practical know how in the process of institutional design implementation and iii compelling models of success in which economic incentives are aligned with conservation we close with a brief review of pioneering experiments now underway worldwide which illustrate how these challenges can be overcome

time series copulas for heteroskedastic data we propose parametric copulas that capture serial dependence in stationary heteroskedastic time series we suggest copulas for first order markov series and then extend them to higher orders and multivariate series we derive the copula of a volatility proxy based on which we propose new measures of volatility dependence including co movement and spillover in multivariate series in general these depend upon the marginal distributions of the series using exchange rate returns we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models and produce more accurate value at risk forecasts

wilderness development decisions and the krutilla fisher model the case of scotland s flow country this paper reports some results from an empirical study of wilderness management in the flow country of northern scotland the flow country is an area of extensive blanket bog characterized by extensive populations of internationally rare breeding birds and by a very distinctive landscape the principle threat to the area at present comes from large scale afforestation this activity is subsidized by the state through the forestry commission and yet seems likely to create irreversible external cost flows the economic efficiency of continued planting in the area is tested for using the krutilla fisher model preservation benefits accruing to both users and non users are estimated using contingent valuation

modeling and forecasting extreme commodity prices a markov switching based extreme value model abstract we propose a markov switching multifractal peaks over threshold msm pot model to capture the dynamic behavior of the random occurrences of extreme events exceeding a high threshold in time series of returns this approach allows introducing changes of regimes in the conditional mean function of the inter exceedance times i e the time between two consecutive extreme events in order to admit the presence of short and long term memory patterns further through its multifractal structure the msm pot approach is able to capture the typical stylized facts of extreme events observed in financial time series such as temporal clustering of the size of exceedances and temporal behavior of tail thickness we compare the performance of the msm pot model with competing self exciting models and a garch evt approach in an in and out of sample var forecasting exercise based on the extreme returns of six daily commodity futures prices i e brent and wti crude oil cocoa cotton copper and gold empirical results suggest that the var estimates generated by the msm pot model for the returns analyzed produce the most accurate forecasts

multivariate density forecast evaluation and calibration in financial risk management high frequency returns on foreign exchange we provide a framework for evaluating and improving multivariate density forecasts among other things the multivariate framework lets us evaluate the adequacy of density forecasts involving cross variable interactions such as time varying conditional correlations we also provide conditions under which a technique of density forecast calibration can be used to improve deficient density forecasts and we show how the calibration method can be used to generate good density forecasts from econometric models even when the conditional density is unknown finally motivated by recent advances in financial risk management we provide a detailed application to multivariate high frequency exchange rate density forecasts

modeling global and local dependence in a pair of commodity forward curves with an application to the us natural gas and heating oil markets abstract the goal of this paper is to present a model for the joint evolution of correlated commodity forward curves each forward curve is directed by two state variables namely slope and level and the model is meant to capture both the local and global dependence structures between slopes and levels our framework can be interpreted as an extension of the concept of cointegration to forward curves the model is applied to a us database of heating oil and natural gas futures prices over the period february 2000 february 2009 we find the long run slope and level relationships between natural gas and heating oil markets analyze the lead and lag properties between the two energy commodities the volatilities and correlations between their daily co movements and evaluate the robustness of these observations to the turmoil experienced by energy markets since 2003

economic valuation of biodiversity sense or nonsense this paper critically evaluates the notion and application of economic monetary valuation of biological diversity or biodiversity for this purpose four levels of diversity are considered genes species ecosystems and functions different perspectives on biodiversity value can be characterized through a number of factors instrumental vs intrinsic values local vs global diversity life diversity vs biological resources etc a classification of biodiversity values is offered based on a system of logical relationships among biodiversity ecosystems species and human welfare suggestions are made about which economic valuation methods can address which type of biodiversity value the resulting framework is the starting point for a survey and evaluation of empirical studies at each of the four levels of diversity the contingent valuation method is by far the most used method an important reason is that the other valuation methods are unable to identify and measure passive or nonuse values of biodiversity at first sight the resulting monetary value estimates seem to give unequivocal support to the belief that biodiversity has a significant positive social value nevertheless most studies lack a uniform clear perspective on biodiversity as a distinct concept from biological resources in fact the empirical literature fails to apply economic valuation to the entire range of biodiversity benefits therefore available economic valuation estimates should generally be regarded as providing a very incomplete perspective on and at best lower bounds to the unknown value of biodiversity changes 2001 elsevier science b v all rights reserved

evolution of social norms with heterogeneous preferences a general model and an application to the academic review process abstract the article presents a model of social norm evolution that suggests how the increase in optimal and actual first response times frt of economics journals can be related when the optimal frt and the norm about how much time refereeing should take increase it seems that the existence of a norm increases the average refereeing time the model suggests the surprising result that this is not necessarily true i also discuss applications of the model in other contexts differences in the optimal frt between disciplines the effects of the frt on the tenure process and strategic behavior of referees

the slowdown in first response times of economics journals can it be beneficial the first response time henceforth frt of economics journals has increased over the last four decades from 1 2 months to 3 6 months the optimal frt however is not zero because the frt deters submission of mediocre papers to good journals and consequently saves valuable time of referees and editors the change in the actual frt is in the same direction as the change in the optimal frt which has increased because of the availability of research on the internet prior to publication and because the costs of refereeing a paper have increased

continuous cascade models for asset returns abstract in this paper we make a short overview of continuous cascade models recently introduced to model asset return fluctuations we show that these models account in a very parcimonious manner for most of stylized facts of financial time series we review in more details the simplest continuous cascade namely the log normal multifractal random walk mrw it can simply be considered as a stochastic volatility model where the log volatility memory has a peculiar logarithmic shape this model possesses some appealing stability properties with respect to time aggregation we describe how one can estimate it using a gmm method and we present some applications to volatility and var value at risk forecasting

forecasting daily supermarket sales using exponentially weighted quantile regression inventory control systems typically require the frequent updating of forecasts for many different products in addition to point predictions interval forecasts are needed to set appropriate levels of safety stock the series considered in this paper are characterised by high volatility and skewness which are both time varying these features motivate the consideration of forecasting methods that are robust with regard to distributional assumptions the widespread use of exponential smoothing for point forecasting in inventory control motivates the development of the approach for interval forecasting in this paper we construct interval forecasts from quantile predictions generated using exponentially weighted quantile regression the approach amounts to exponential smoothing of the cumulative distribution function and can be viewed as an extension of generalised exponential smoothing to quantile forecasting empirical results are encouraging with improvements over traditional methods being particularly apparent when the approach is used as the basis for robust point forecasting

value at risk estimations of energy commodities via long memory asymmetry and fat tailed garch models abstract in this paper we evaluate the value at risk var and the expected shortfalls for some major crude oil and gas commodities for both short and long trading positions classical var estimations as well as riskmetrics and other extensions to cases considering for long range memory asymmetry and fat tail in energy markets volatility were conducted we computed the var for three arch garch type models including figarch fiaparch and hygarch these models were estimated in the presence of three alternative innovation s distributions normal student and skewed student our results show that considering for long range memory fat tails and asymmetry performs better in predicting a one day ahead var for both short and long trading positions moreover the fiaparch model outperforms the other models in the var s prediction these results present several potential implications for energy markets risk quantifications and hedging strategies

forecasting the joint distribution of australian electricity prices using dynamic vine copulae abstract we consider the problem of modelling and forecasting the distribution of a vector of prices from interconnected electricity markets using a flexible class of drawable vine copula models where we allow the dependence parameters of the constituting bivariate copulae to be time varying we undertake in sample and out of sample tests using daily electricity prices and evidence that our model provides accurate forecasts of the underlying distribution and outperforms a set of competing models in their abilities to forecast one day ahead conditional quantiles of a portfolio of electricity prices our study is conducted in the australian national electricity market nem which is the most efficient power auction in the world electricity prices exhibit highly stylised features such as extreme price spikes price dependency between regional markets correlation asymmetry and non linear dependency the developed approach can be used as a risk management tool in the electricity retail industry which plays an integral role in the apparatus of modern energy markets electricity retailers are responsible for the efficient distribution of electricity while being exposed to market risk with extreme magnitudes

estimating oil price value at risk using the historical simulation approach abstract in this paper we propose using value at risk var for oil price risk quantification var provides an estimation for the maximum oil price change associated with a likelihood level and can be used for designing risk management strategies we analyse three var calculation methods the historical simulation standard approach the historical simulation with arma forecasts hsaf approach developed in this paper and the variance covariance method based on autoregressive conditional heteroskedasticity models forecasts the results obtained indicate that hsaf methodology provides a flexible var quantification which fits the continuous oil price movements well and provides an efficient risk quantification

the welfare economic theory of green national accounts this paper takes a critical look at the literature on green national accounts the problem studied is to find a linear index of economic variables that responds to perturbations in the same direction as social well being the thesis of a large literature that net national product which is a flow is that index in closed economies is shown in some interpretations to be simply false and in others to suffer from deep estimation problems it is argued that capital depreciation using shadow prices should certainly be included in national accounts but that the right welfare index is a comprehensive measure of wealth defined as the shadow value of an economy s stock of all capital assets it is shown that comprehensive wealth is usable as a criterion for policy evaluation as well as for determining sustainable economic development

valuing environmental functions tropical wetlands recent studies have suggested that tropical wetland systems may have a crucial economic role to play in development the following paper provides an overview of these benefits using the general framework of cost benefit analysis as the methodological approach to assessing wetland values an analysis of trade offs between conserving or converting tropical wetlands demonstrates that taking into account the opportunity cost of wetland loss leads to a lower level of conversion than would otherwise be the case finally the paper discusses the extensions and limitations of the production function approach as applied to valuing nonmarketed wetland benefits

submission fees and response times in academic publishing both submission fees and response times enable editors to maintain an acceptable refereeing burden by discouraging the submission of articles with low probability of acceptance when authors differ in their ability or willingness to pay submission fees and deal with delays journal quality is maximized under a combination of moderate fees and moderate delays

capturing deep tail risk via sequential learning of quantile dynamics abstract this paper develops a conditional quantile model that can learn long term and short term memories of sequential data it builds on sequential neural networks and yet outputs interpretable dynamics we apply the model to asset return time series across eleven asset classes using historical data from the 1960s to 2018 our results reveal that it extracts not only the serial dependence structure in conditional volatility but also the memories buried deep in the tails of historical prices we further evaluate its value at risk forecasts against a wide range of prevailing models our model outperforms the garch family as well as models using filtered historical simulation conditional extreme value theory and dynamic quantile regression these studies indicate that conditional quantiles of asset return have persistent sources of risk that are not coming from those responsible for volatility clustering these findings could have important implications for risk management in general and tail risk forecasts in particular

no arbitrage conditions for storable commodities and the modeling of futures term structures abstract one distinguishable feature of storable commodities is that they relate to two markets cash market and storage market this paper proves that if no arbitrage exists in the storage cash dual markets the commodity convenience yield has to be non negative however classical reduced form models for futures term structures could allow serious arbitrages due to the high volatility of the convenience yield to avoid negative convenience yield this paper proposes a semi affine arbitrage free model which prices futures analytically and fits futures term structures reasonably well importantly our model prices commodity related contingent claims such as calendar spread options quite differently with classical models

estimation of value at risk for energy commodities via fat tailed garch models the choice of an appropriate distribution for return innovations is important in var applications owing to its ability to directly affect the estimation quality of the required quantiles this study investigates the influence of fat tailed innovation process on the performance of one day ahead var estimates using three garch models garch n garch t and garch ht daily spot prices of five energy commodities wti crude oil brent crude oil heating oil 2 propane and new york harbor conventional gasoline regular are used to compare the accuracy and efficiency of the var models empirical results suggest that for asset returns that exhibit leptokurtic and fat tailed features the var estimates generated by the garch ht models have good accuracy at both low and high confidence levels additionally mrsb indicates that the garch ht model is more efficient than alternatives for most cases at high confidence levels these findings suggest that the heavy tailed distribution is more suitable for energy commodities particularly var calculation

a theory of commodity price fluctuations this paper studies the price fluctuations of storable commodities that are traded in open markets and are subject to random shocks to demand or more particularly to supply it relaxes the common assumption that the shocks are identically and independently distributed in favor of temporally dependent and periodic disturbances the existence of a unique stationary rational expectations equilibrium is demonstrated for each of the models analyzed and testable implications of the models are derived an illustrative empirical investigation is then undertaken for the model with periodic disturbances using monthly time series observations for seven commodities over the period 1960 93

oil price shocks stock market economic activity and employment in greece abstract using a multivariate vector autoregression var approach this paper attempts to shed light into the dynamic relationship among oil prices real stock prices interest rates real economic activity and employment for greece the empirical evidence suggests that oil price changes affect real economic activity and employment oil prices are important in explaining stock price movements stock returns do not lead to changes in real activity and employment

is there value added from the review process in economics preliminary evidence from authors do referees employed by journals merely screen acceptable from unacceptable manuscripts or are they charged with an additional value adding responsibility vis a vis the papers they review drawing from editorial correspondence provided by survey respondents i address this question by examining the relationship between citations of published papers and comments provided by reviewers and editors referees comments demonstrate a positive impact on subsequent citation of papers while comments made by editors show no such impact value adding by editors appears to derive principally from efficient matching of papers with reviewers

on publication refereeing and working hard we present a model for academia with heterogeneous author types and endogenous effort to evaluate recent changes in the publication process in economics we analyze the implications of these developments on research output lowering the precision of refereeing signals lowers the effort choices of intermediate ability authors but invites more submissions from less able authors increasing the number of journals stimulates less able authors to submit their papers the editor can improve the journal s quality pool of submitted manuscripts by improving the precision of refereeing but not by lowering acceptance standards the submission strategy of an author is informative of his ability

market risk in commodity markets a var approach we put forward value at risk models relevant for commodity traders who have long and short trading positions in commodity markets in a 5 year out of sample study on aluminium copper nickel brent crude oil and wti crude oil daily cash prices and cocoa nearby futures contracts we assess the performance of the riskmetrics skewed student aparch and skewed student arch models while the skewed student aparch model performs best in all cases the skewed student arch model delivers good results and its estimation does not require non linear optimization procedures as such this new model could be relatively easily integrated in a spreadsheet like environment and used by market practitioners

modelling general dependence between commodity forward curves abstract this study proposes a novel framework for the joint modelling of commodity forward curves its key contribution is twofold first we introduce a family of dynamic conditional correlation models based on hierarchical archimedean copulae hac dcc which are flexible but parsimonious instruments that capture a wide range of dynamic dependencies second we apply these models in the context of commodity forward curves as part of the framework an extensive value at risk analysis shows that certain hac dcc models consistently outperform other introduced benchmarks in terms of the preciseness of their out of sample distribution forecasts of the returns of various commodity futures portfolios this shows that the proposed modelling framework as one of its possible applications can be a useful and convenient risk management tool

point process models for extreme returns harnessing implied volatility forecasting the risk of extreme losses is an important issue in the management of financial risk there has been a great deal of research examining how option implied volatilities iv can be used to forecast asset return volatility however the role of iv in the context of predicting extreme risk has received relatively little attention the potential benefit of iv in forecasting extreme risk is considered within a range of models beginning with the traditional garch based approach along with a number of novel point process models univariate models where iv is included as an exogenous variable are considered along with a novel bivariate approach where extreme movements in iv are treated as another point process it is found that in the context of forecasting value at risk the bivariate models produce the most accurate forecasts across a wide range of scenarios

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

multinomial var backtests a simple implicit approach to backtesting expected shortfall under the fundamental review of the trading book frtb capital charges for the trading book are based on the coherent expected shortfall es risk measure which show greater sensitivity to tail risk in this paper it is argued that backtesting of expected shortfall or the trading book model from which it is calculated can be based on a simultaneous multinomial test of value at risk var exceptions at different levels an idea supported by an approximation of es in terms of multiple quantiles of a distribution proposed in emmer et al 2015 by comparing pearson nass and likelihood ratio tests lrts for different numbers of var levels n it is shown in a series of simulation experiments that multinomial tests with n 4 are much more powerful at detecting misspecifications of trading book loss models than standard bi nomial exception tests corresponding to the case n 1 each test has its merits pearson offers simplicity nass is robust in its size properties to the choice of n the lrt is very powerful though slightly over sized in small samples and more computationally burdensome a traffic light system for trading book models based on the multinomial test is proposed and the recommended procedure is applied to a real data example spanning the 2008 financial crisis