industrial pollution abatement the impact on balance of trade this paper uses an ex post partial equilibrium framework to measure the impact of marginal changes in industrial p ollution abatement costs on the u s balance of trade in general and balance of trade with canada in particular the impacts are found to be negative for most industries growing with trade volume and smal l relative to domestic consumption in addition some evidence is fou nd that pollution control programs have changed the u s comparative advantage such that more high abatement cost goods are imported and m ore low abatement cost goods are exported

robust portfolio optimization for electricity planning an application based on the brazilian electricity mix one of the major challenges of today s policy makers and industry strategists is to achieve an electricity mix that presents a high level of energy security within a range of affordable costs and environmental constraints bearing in mind the planning of a more reliable electricity mix the main contribution of this paper is to consider parameter uncertainties on the electricity portfolio optimization problem we assume that the expected and the covariance matrix of the costs for the different energy technologies such as gas coal nuclear oil biomass wind large and small hydropower are not exactly known we consider that these parameters belong to some uncertainty sets box ellipsoidal lower and upper bounds and convex polytopic three problems are analyzed i finding a energy portfolio of minimum worst case volatility with guaranteed fixed maximum expected energy cost ii finding an energy portfolio of minimum worst case expected cost with guaranteed fixed maximum volatility of the energy cost iii finding a combination of the expected and variance of the cost weighted by a risk aversion parameter these problems are written as quadratic second order cone programming socp and semidefinite programming sdp so that robust optimization tools can be applied these results are illustrated by analyzing the efficient brazilian electricity energy mix considered in losekann et al 2013 assuming possible uncertainties in the vector of expected costs and covariance matrix the results suggest that the robust approach being by nature more conservative can be useful in providing a reasonable electricity energy mix conciliating co2 emission risk and costs under uncertainties on the parameters of the model

forecasting model of rss3 price in futures market 3 abstract the agricultural futures market affects the rubber price in thailand rubber processors use the agricultural futures market to avoid risks associated with fluctuations in rubber price investors make profits from the difference between the current price and the future price this paper presents the forecasting models for futures price of the natural rubber ribbed smoked sheets no 3 rss3 the results from the most efficient model can inform the decision of investors on buying and selling at the proper time the study employs the least mean squared error as a criterion for the selection of the best prediction model it includes an analysis of factors affecting the rss3 futures prices in thailand s futures market the results show that the previous monthly futures prices and oil prices significantly affected the futures prices in the same direction the net import of natural rubber by japan was the leading indicator for the trend in rubber futures prices in thailand the analytical model was shown to be applicable and would facilitate related studies in forecasting the futures prices of other commodities time series data was found to be suitable for the forecasting model keywords futures price forecasting agricultural futures market

robust portfolio optimization with derivative insurance guarantees robust portfolio optimization aims to maximize the worst case portfolio return given that the asset returns are allowed to vary within a prescribed uncertainty set if the uncertainty set is not too large the resulting portfolio performs well under normal market conditions however its performance may substantially degrade in the presence of market crashes that is if the asset returns materialize far outside of the uncertainty set we propose a novel robust optimization model for designing portfolios that include european style options this model trades off weak and strong guarantees on the worst case portfolio return the weak guarantee applies as long as the asset returns are realized within the prescribed uncertainty set while the strong guarantee applies for all possible asset returns the resulting model constitutes a convex second order cone program which is amenable to efficient numerical solution procedures we evaluate the model using simulated and empirical backtests and analyze the impact of the insurance guarantees on the portfolio performance

composite forecasting approach application for next day electricity price forecasting abstract accurate forecasting of electricity prices can provide significant benefits to energy suppliers when allocating their assets and to energy consumers for defining an optimal portfolio there are numerous methods that efficiently support the forecasting of time series such as electricity prices which have high volatility however the performance of these approaches varies depending on data sets and operational conditions in this work the concept of composite forecasting is presented and implemented in a retrospective study in real industrial forecasting conditions to show the potential of forecast performance improvement and comparable high consistency of a forecast performance across different day peak and day base electricity price data sets for different seasons as individual methods support vector regression artificial neural networks and ridge regression are implemented the forecast performances of these methods are evaluated and compared with their forecast combination using different error measures the results show that composite forecasting processes with inverse root mean squared error combination approach can generate on average a more accurate and robust forecast than using an individual methods or other combination schemas

integration of discrepant sales forecasts the influence of plausibility inferences based on an evoked range abstract the authors hypothesize that when managers integrate two projections to form a sales estimate they evoke and use a sales range to judge inappropriately the plausibility of each projection this judged plausibility as well as the margin of error based on the market research company s typical accuracy is used to assign weights to each projection five experiments find strong evidence for this process and demonstrate a resulting bias

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

a robust hedging algorithm abstract hedging the risk of writing options is a major concern in finance considering the potentially huge losses in derivatives trading we present two hedging strategies which determine the optimum number of shares that minimizes the worst case potential hedging error under transaction costs given some predefined sources of uncertainty we present a minimax algorithm as a computational tool for these strategies and discuss its performance from the point of view of optimization it is shown that depending on the hedging strategy the performance of the algorithm is determined by the hessian of the objective function which in turn is determined by the option pricing model embedded within the objective function

an empirical demand and supply model of multilateral trade t his study develops an empirical model for the joint determination of the demand and supply for bilateral trade in which both bilateral quantities and bilateral prices are endogenous in theory each bilateral demand supply equation would contain income output variables together with all relevant bilateral prices given differences in the commodity composition of trade and given price discrimination export prices of any country will differ over destination countries in addition transport costs and tariffs will drive a wedge between bilateral export and import prices thus a bilateral demand and supply system for aggregate trade among n countries would require consideration of 2n2 price variables an overwhelming task for empirical research as a compromise between pure theory and practice we use a two tier construction in which total import demand and export supply are determined by aggregate real income output and relative aggregate prices and then bilateral trade flows are determined by theory based allocations featuring relative bilateral prices this approach is more general than either specifying only bilateral demand behavior assuming infinitely elastic supply at given prices or including the supply side through stringent assumptions such as constant market shares for empirical application the model is extended to include proxies for nonprice competition and structural factors a flowadjustment specification of dynamics and a trend cycle decomposition of income output the model is estimated from a panel of bilateral trade flows covering the united states japan france germany and united kingdom for the years 1958 1974 the theoretical model is developed in section ii the empirical specification is presented in section iii and the empirical results are discussed in section iv

which dreams come true endogeneity industry structure and forecasting accuracy forecasts are plentiful accurate long range forecasts are rare but some forecasts are more accurate than others are and a few are very accurate in this paper we first explore the case of moore s law a forecast that has proven quite accurate for almost 40 years we illustrate how expectations that moore s law will continue to be accurate actually make it accurate based on the insights of this case we hypothesize that two factors facilitate such self fulfilling forecasts and so make accuracy more possible we test these hypotheses on a set of 3142 forecasts about us manufacturing industries during the 1970s we find that high industry concentration and high control over the predicted variable tend to increase the accuracy of forecasts copyright 2003 oxford university press

confidence based optimisation for the newsvendor problem under binomial poisson and exponential demand abstract we introduce a novel strategy to address the issue of demand estimation in single item single period stochastic inventory optimisation problems our strategy analytically combines confidence interval analysis and inventory optimisation we assume that the decision maker is given a set of past demand samples and we employ confidence interval analysis in order to identify a range of candidate order quantities that with prescribed confidence probability includes the real optimal order quantity for the underlying stochastic demand process with unknown stationary parameter s in addition for each candidate order quantity that is identified our approach produces an upper and a lower bound for the associated cost we apply this approach to three demand distributions in the exponential family binomial poisson and exponential for two of these distributions we also discuss the extension to the case of unobserved lost sales numerical examples are presented in which we show how our approach complements existing frequentist e g based on maximum likelihood estimators or bayesian strategies

the effectiveness of alternative preference elicitation procedures in predicting choice in a large scale national study the authors evaluated the effectiveness of several preference elicitation techniques for predicting choices the criteria for accuracy included both individual hit

combining economic forecasts a method for combining forecasts may or may not account for dependence and differing precision among forecasts in this article we test a variety of such methods in the context of combining forecasts of gnp from four major econometric models the methods include one in which forecasting errors are jointly normally distributed and several variants of this model as well as some simpler procedures and a bayesian approach with a prior distribution based on exchangeability of forecasters the results indicate that a simple average the normal model with an independence assumption and the bayesian model perform better than the other approaches that are studied here

the enlargement of the european union effects on trade and emissions of greenhouse gases abstract with the gradual accession of various central and eastern european countries ceecs to the european union eu international trade between the eu and the ceecs will change as a result of trade liberalisation and the mobility of production factors within the eu the eu and most of the ceecs have already committed themselves to reduce by 2008 2012 their emissions of greenhouse gases ghgs by 8 compared to the 1990 level this paper reports on an investigation of the potential consequences of the enlargement of the eu and of the emission reduction target set by the kyoto protocol on the sectoral production patterns and international trade a comparative static general equilibrium model was developed to examine the impacts under different scenarios for illustrative purposes two regions the eu and the ceecs and three categories of goods and services agricultural goods industrial goods and services were included the model was calibrated by the 1998 data the model was subsequently applied to study the effects of free trade the mobility of factors and the environmental constraints on production and international trade in light of the enlargement of the eu we show that in this specific context free trade is beneficial to economic welfare and does not necessarily increase emissions of greenhouse gases the mobility of factors also increases economic welfare but in the case of fixed production technology it may harm the environment through more emissions of ghgs

forecaster diversity and the benefits of combining forecasts the expected error variance of a combined forecast is necessarily lower than that of an individual forecast but in practice there may be considerable variation around these expected values this paper introduces a measure of the benefit from combining the probability of a reduction in error variance which recognizes this problem the measure is applied to data on the forecasts and forecasting methods of a panel of u s economists to determine how the benefits of combining vary with the number of forecasts combined and with the diversity in theories and techniques among the component forecasts

the impacts of exchange rate volatility on vegetable trade flows trade flows of commodities are generally affected by the principles of comparative advantage in a free trade however trade flows might be enhanced or distorted not only by various government interventions but also by exchange rate fluctuations among others this study applies a commodity specific gravity model to selected vegetable trade flows among organization for economic co operation and development oecd countries to determine the effects of exchange rate uncertainty on the trade flows using the data from 1996 to 2002 the results show that while the exchange rate uncertainty significantly reduces trade in the majority of commodity flows there is evidence that both short and long term volatility have positive effect on trade flows of specific commodities this study also tests the regional preferential trade agreements such as the north american free trade agreement nafta the asia pacific economic cooperation apec and the eu and their different effects on commodities

robust portfolio selection using linear matrix inequalities abstract in this paper we consider the problem of robust optimal portfolio selection for tracking error when the expected returns of the risky and risk free assets as well as the covariance matrix of the risky assets are not exactly known we assume that these parameters belong to a convex polytope defined by some known elements which form the vertices of this polytope we consider two problems the first one is to find a portfolio of minimum worst case volatility of the tracking error with guaranteed fixed minimum target expected performance the second one is to find a portfolio of maximum worst case target expected performance with guaranteed fixed maximum volatility of the tracking error we show that these two problems are equivalent to solving linear matrix inequalities lmi optimization problems so that the powerful numerical packages nowadays available for this class of problems can be used a numerical example in the sao paulo stock exchange bovespa is presented

empirical generalizations about market evolution and stationarity we present empirical generalizations about conditions under which marketing variables evolve or remain stationary we first define evolution statistically and make the case why it is an important concept for increasing our understanding of long run marketing effectiveness we then briefly review ways in which evolution can be tested empirically from readily available data we present a database of over 400 prior analyses and catalog the relative incidence of stationarity versus evolution in market performance and marketing spending we find that evolution is the dominant characteristic for sales and marketing mix spending but that stationarity is the dominant characteristic for market share thus we find strong support for the conjecture that many markets are in a long run equilibrium where the relative position of the players is only temporarily disturbed by their respective marketing activities we assess the impact of a number of covariates on the likelihood of finding stationarity evolution in sales

impacts of regulating greenhouse gas emissions on livestock trade flows policies regulating greenhouse gas ghg emissions are expected to create a significant burden on emitting industries as well as final consumers which can lead to a strong influence on international trade flows of commodities this study examines whether the regulation of ghg emissions affects livestock trade flows a commodity specific gravity model approach is employed to estimate and test the impact of regulating ghg emissions on livestock trade flows the results show that regulation of ghg emissions has a negative effect on livestock trade flows from countries restricting ghg emissions to countries without ghg restriction from restricting countries to restricting countries and unrestricting countries to restricting countries

marketing information a competitive analysis selling information that is later used in decision making constitutes an increasingly important business in modern economies jensen jensen fred o 1991 information services congram friedman eds the ama handbook of marketing for the service industries chapter 22 ama com new york 423 443 information is sold under a large variety of forms industry reports consulting services database access and or professional opinions given by medical engineering accounting financial and legal professionals among others this paper is the first attempt in marketing to study competition in the rapidly emerging information sector specifically we are interested in answering the following questions 1 is competition fundamentally different when competing firms sell information rather than traditional goods and services and if yes why 2 what are the implications of such differences for decision makers marketers and regulators 3 can we explain some of the observed marketing strategies in the information industry as such the audience of the paper includes academics as well as professionals who are interested in understanding what is specific about competition in information markets familiarity with the practical implications of such differences and understanding of the mechanisms that drive them is essential for those who are faced with the problem of marketing information to answer the above research questions we build a simple game theoretic model that consists of two firms selling information to a population of consumers who are heterogeneous in their willingness to pay for the quality of information the most important features of the model are the following information products sold by the two firms are modeled as random draws from two normal distributions having equal mean the variances of these distributions and their correlatedness constitute the product attribute space which is assumed to be common knowledge consumers are interested in assessing the mean of the distributions and to do so they can buy the sample from any of the firms or they can buy both samples and combine them to obtain a more accurate estimate quality of information is linked to the accuracy of consumers estimate of the mean which in turn is influenced by the accuracy of each sample as well as by their correlatedness consumers utility depends on the quality of information they purchased on their inherent utility for quality taste and on the total price they paid to acquire information knowing consumer preferences firms simultaneously price their information products the main finding of the paper is that information markets face unique competitive structures in particular the qualitative nature of competition changes depending on basic product characteristics while traditional products and services compete either as substitutes or as complements in the relevant product attribute space information may be one or the other depending on its position within the same product attribute space said differently the nature of competition changes qualitatively with a continuous change in basic product attribute levels the intuition behind this finding is the following when purchasing information consumers facing important decisions may find it beneficial to purchase from several information sellers this is more likely to happen when the reliability of information is low and the sources of information are independent under such conditions information products tend to be complements and as a result competition between sellers is relatively mild in the opposite case when information is reliable and or sellers sources are highly correlated consumers are satisfied after consulting a single source in this case information products are substitutes and sellers tend to undercut one another s prices to induce consumers to choose their brand understanding this discontinuity in competitive structures has important implications for decision makers as very different strategies are optimal under different product characteristics under substitution traditional strategies to avoid competition e g differentiation are recommended when the competing products reliability is generally low they are complements firms are better off accommodating competition in fact we find that a firm may benefit from inviting a competitor finally our findings are also important for regulators of information markets as the literature on complementarity suggests price fixing agreements between firms offering complementary products may benefit firms as well as consumers

multi period minimax hedging strategies abstract option pricing and hedging under transaction costs are of major importance to marketmakers and investors in this paper we present the basic minimax strategy which determines the optimum number of shares that minimizes the worst case potential hedging error under transaction costs for the next period we present two extensions of this strategy the first extension is the two period minimax where the worst case is defined over a two period setting the objective function of the basic minimax strategy is augmented to include the hedging error for the second period the second extension is the variable minimax strategy where early rebalancing is triggered by the minimax hedging error simulation results suggest that the basic minimax strategy and its two extensions are superior in performance to delta hedging and that the variable minimax strategy is superior to both the basic and the two period strategies this result is due to the opportunity provided by the variable minimax strategy to rebalance early the greatest amount of business for traded options is done for at the money options in this paper we have concluded that the minimax strategies are particularly suitable for managing the risk of such options in the appendix we present the minimax algorithm used for the implementation of these strategies

forecasting with temporal hierarchies this paper introduces the concept of temporal hierarchies for time series forecasting a temporal hierarchy can be constructed for any time series by means of non overlapping temporal aggregation predictions constructed at all aggregation levels are combined with the proposed framework to result in temporally reconciled accurate and robust forecasts the implied combination mitigates modelling uncertainty while the reconciled nature of the forecasts results in a unified prediction that supports aligned decisions at different planning horizons from short term operational up to long term strategic planning the proposed methodology is independent of forecasting models it can embed high level managerial forecasts that incorporate complex and unstructured information with lower level statistical forecasts our results show that forecasting with temporal hierarchies increases accuracy over conventional forecasting particularly under increased modelling uncertainty we discuss organisational implications of the temporally reconciled forecasts using a case study of accident emergency departments

does environmental dumping lead to delocation environmental dumping is often viewed as an instrument used by some countries in the attempt to attract foreign investments stated otherwise the delocation of firms would be a major outcome of a stiff environmental policy in this paper we study the impact of a strict anti pollution policy pursued by a government on domestic firms locational decisions and determine the main variables that interact with such a policy some preliminary welfare implications are also provided

tightening environmental standards the benefit cost or the no cost paradigm ms ff ichael porter and claas van der linde have written a paper that is interesting and to us at least somewhat astonishing it is a defense of environmental regulation indeed an invitation to more stringent regulation that makes essentially no reference to the social benefits of such regulation this approach contrasts starkly with the methods that economists and other policy analysts have traditionally used when assessing environmental or other regulatory programs the traditional approach consists of comparing the beneficial effects of regulation with the costs that must be borne to secure these benefits for environmental regulation the social benefits include the reductions in morbidity or premature mortality that can accompany cleaner air the enhanced recreational opportunities that can result from water quality improvements the increased land values that might attend the cleanup of a hazardous waste site the enhanced vitality of aquatic ecosystems that might follow reductions in agricultural pesticide use or any of the other potentially significant benefits associated with tighter standards from this benefit cost approach emerges the standard tradeoff discussed in virtually every economics textbook porter and van der linde deny the validity of this approach to the analysis of environmental regulation claiming it to be an artifact of what they see as a static mindset in their view economists have failed to appreciate the capacity of

unilateral climate policy and competitiveness economic implications of differential emission pricing unilateral emission reduction commitments raise concerns on international competitiveness and emission leakage that result in preferential regulatory treatment of domestic energy intensive and trade exposed industries our analysis illustrates the potential pitfalls of climate policy design which narrowly focuses on competitiveness concerns about energy intensive and trade exposed eite branches the sector specific gains of preferential regulation in favour of these branches must be traded off against the additional burden imposed on other industries beyond burden shifting between industries differential emission pricing bears the risk for substantial excess cost in emission reduction as policy concedes too low carbon prices to eite industries and thereby foregoes relatively cheap abatement options in these sectors from the perspective of global cost effectiveness we find that differential emission pricing of eite industries hardly reduces emission leakage since the latter is driven through robust international energy market responses to emission constraints as a consequence the scope for efficiency compared to uniform pricing is very limited only towards stringent emission reduction targets will a moderate price differentiation achieve sufficient gains from leakage reduction to offset the losses of diverging marginal abatement cost

toward a new conception of the environment competitiveness relationship accepting a fixed trade off between environmental regulation and competitiveness unnecessarily raises costs and slows down environmental progress studies finding high environmental compliance costs have traditionally focused on static cost impacts ignoring any offsetting productivity benefits from innovation they typically overestimated compliance costs neglected innovation offsets and disregarded the affected industry s initial competitiveness rather than simply adding to cost properly crafted environmental standards can trigger innovation offsets allowing companies to improve their resource productivity shifting the debate from pollution control to pollution prevention was a step forward it is now necessary to make the next step and focus on resource productivity

the simultaneous use of rival models in policy optimisation an important problem in macroeconomic policy design that has hitherto received little attention is the uncertainty of model structure by that we mean that more than one model fits the data reasonably well however each model is based on a different school of economic thought and thus has a different structure hence our analysis is based on non nested models when statistical inference cannot reject one model in favour of the other in this paper we discuss a way in which policy optimisation can be used to derive policies that are compatible with more than one model structure this is accomplished by extending an optimisation algorithm for a single nonlinear model of the economy to handle simultaneously more than one model and objective function the algorithm is designed to be efficient and relatively modest in its storage requirements a minimax extension is also considered for optimal policies robust to model choice when any one of the models turns out to represent the real economy two large scale nonlinear models of the uk economy are used simultaneously to obtain policies which are optimal with respect to a combined cost function this cost function is a combination of the cost functions associated with the individual models the models used are the h m treasury model and the model of the national institute of economic and social research

automated earnings forecasts beat analysts or combine and conquer prior studies attribute analysts forecast superiority over time series forecasting models to their access to a large set of firm industry and macroeconomic information an information advantage which they use to update their forecasts on a daily weekly or monthly basis a timing advantage this study leverages recently developed mixed data sampling midas regression methods to synthesize a broad spectrum of high frequency data to construct forecasts of firm level earnings we compare the accuracy of these forecasts to those of analysts at short horizons of one quarter or less we find that our midas forecasts are more accurate and have forecast errors that are smaller than analysts when forecast dispersion is high and when the firm size is smaller in addition we find that combining our midas forecasts with analysts forecasts systematically outperforms analysts alone which indicates that our midas models provide information orthogonal to analysts our results provide preliminary support for th

aggregating subjective forecasts some empirical results the impact on forecast accuracy of aggregating the subjective forecasts of up to 13 individuals was examined for five forecast weighting methods equal weighting two ex post methods that took advantage of prior information about the individuals relative accuracy and two ex ante methods based on objective and subjective assessments of relative accuracy the individuals were executives managers and sales personnel employed by time inc and the variable forecasted was the number of advertising pages sold annually by time magazine over a 14 year period the results show that both the average forecast error and the variance of the error decrease as additional individuals forecasts are included in the aggregate only two to five individuals forecasts must be included to achieve much of the total improvement available from combining all 13 forecasts three of the differential weighting methods produced more accurate forecasts than equal weighting but the magnitude of the improvement was small implications for realistic forecasting situations are discussed as are conditions under which the use of aggregates seems attractive

averages of forecasts some empirical results an alternative to using a single forecasting method is to average the forecasts obtained from several methods in this paper we investigate empirically the impact of the number and choice of forecasting methods on the accuracy of simple averages it is concluded that the forecasting accuracy improves and that the variability of accuracy among different combinations decreases as the number of methods in the average increases thus combining forecasts seems to be a reasonable practical alternative when as is often the case a true model of the data generating process or a single best forecasting method cannot be or is not for whatever reasons identified

probabilistic decision model of wind power investment and influence of green power market this paper presents results from a model of a representative wind power investor s decision making process using a monte carlo simulation of a project financial analysis data in the form of probability distribution functions pdfs for key input variables were collected from interviews with investors and other professionals active in the u s wind power industry using a formal expert elicitation protocol this study presents the first quantitative estimates of the effect of the u s voluntary renewable energy certificate rec market on renewable energy generation the results indicate that the investment decisions of wind power project developers in the united states are unlikely to have been altered by the voluntary rec market the problem with the current voluntary rec market is that it does not offer developers a reliable risk adjusted revenue stream consequently the claims by u s green power retailers and promoters that voluntary market recs result in additional wind power projects lack credibility even dramatic increases in voluntary market rec prices in the absence of long term contracts were found to have only a small effect on investor behavior

robust min max portfolio strategies for rival forecast and risk scenarios we consider an extension of the markowitz mean variance optimization framework to multiple return and risk scenarios it is well known that asset return forecasts and risk estimates are inherently inaccurate the method proposed provides a means for considering rival representations of the future the optimal portfolio is computed simultaneously with the worst case to take account of all rival scenarios this is a min max strategy which is essentially equivalent to a robust pooling of the scenarios robustness is ensured by the noninferiority of min max for example a basic worst case optimal return is guaranteed in view of multiple return scenarios if robustness happens to have too high a cost guided by the min max pooling it is also possible to explore other pooling alternatives a min max algorithm is used to solve the problem and illustrate the robust character of min max with return and risk scenarios we study the properties of the min max risk return frontier and compare with the potentially suboptimal worst case where the investment strategy and the worst case are computed separately 2000 elsevier science b v all rights reserved jel classixcation c44 c61 c63 g11

the impact of environmental policy on international competitiveness in manufacturing the aim of this study is to test the hypothesis that environmental stringency adversely affects the international competitiveness net exports in manufacturing sectors the model follows the standard factor endowment approach to explain the effects of environmental regulatory policy on net exports in different product based industries an econometric model is constructed which includes factor endowments and environmental regulations to examine how strict environmental policies impact export competitiveness a panel dataset of 10 organisation for economic co operation and development oecd countries over 17 years 1987 2003 was constructed for the modelling effort the study finds that environmental regulations can be a way to combat the flight of manufacturing out of developed countries if the output from these industries can be identified as environmentally friendly a positive relationship between net exports and environmental regulations was found for paper products wood products and textile prod

a structural bayesian var for model based fan charts inflation forecast uncertainty is of importance for a wide range of agents in the economy central banks in particular ways to describe and account for this uncertainty in a consistent manner have received increasing attention of late in part due to the growing number of inflation targeting central banks this article develops a large structural var for the swedish economy and estimates it in a bayesian framework the methodology permits not only structural interpretation and analysis but offers a natural way to formalize forecast uncertainty as the posterior predictive density from the model has the interpretation of a fan chart

estimating the demand distributions of single period items having frequent stockouts abstract very often the service level of a single period newsboy type product is set at such a low level that i stockouts occur in the majority of the periods and ii a large right hand side of the empirical demand distribution is never observable this paper reports a practical approach for estimating the periodic demand distribution of such a product the approach has three components i using the non parametric product limit method to estimate the fractiles of the observable left hand side of the empirical distribution ii using a subjective approach and an extrapolation of hourly sales approach to fill in the missing right hand side of the empirical distribution iii fitting the estimates obtained in the preceding two components to a tocher curve which can handle the diversity of shapes of a realistic demand distribution and is also computationally very convenient for subsequent calculations for production inventory decisions the entire approach is shown to be simpler but more powerful than existing alternatives for the problem

gstp tariff reduction and its effects on south south trade in manufactures using a gravity model with import tariffs on manufactures as an explanatory variable both at the import and at the export side the impact of tariffs on trade in manufactures is analyzed for a sample of 39 less developed country ldc importers the consequences of an agreement on a global system of trade preferences gstp for manufactures are estimated by lowering these tariffs for intra ldc trade by 20 and 50 alternatively the short term effects are found to be relatively modest and the long term effects considerably larger trade diversion from developed country dc to ldc suppliers has only limited impact

consensus forests of corporate earnings analysts forecasts and time series methods an alternative to using a single forecasting method is to average the forecasts made by various methods in this paper we examine empirically combinations of financial analysts forecasts and forecasts from time series methods in order to predict corporate earnings per share we conclude that on average the primary forecasting advantages of analysts over time series methods based on annual data appear to occur over short forecast horizons less than a year neither analysts nor other time series methods substantially outperform a random walk prediction of no change when forecasts are made near the beginning of the fiscal year for predictions in the first half of the fiscal year there is evidence of forecasting benefits from combining time series and analysts forecasts especially if there are few analysts forecasts

average of forecasts an improvement stein rules are used in forming combination forecasts such forecasts have smaller prediction risk under certain conditions than the preferred method of average of forecasts the new composite forecasts will be theoretically biased but are likely to have smaller mean squared error of forecasts as shown in the empirical exercises examined when the forecasts appear to be unbiased and have a common mean lindley type combination is most useful

steel safeguards and the welfare of u s steel firms and downstream consumers of steel a shareholder wealth perspective this paper analyses the steel safeguards applied during 2001 3 results reveal that for shareholders of u s steel companies safeguards generated positive abnormal returns of approximately 6 the cancellation of the safeguards resulted in wealth gains of about 5 steel shareholders experienced negative abnormal returns of 5 in response to the wto ruling that the u s had violated wto law our results are consistent with the neoclassical view that producers gain at the expense of consumers also findings indicate that downstream consuming firms that diversify production in nafta countries avert some trade policy risk associated with higher steel costs caused by safeguard protection ce texte analyse l effet de la protection des acieries americaines au cours de la periode 2001 03 les resultats montrent que pour les actionnaires des societes americaines cette protection a engendre des profits anormaux de l ordre de 6 l annulation de cette protection a resulte en des gains de richesse d environ 5 les actionnaires des acieries ont subi des rendements anormaux negatifs de l ordre de 5 a la suite de la decision de l omc a savoir que les etats unis avaient enfreint la loi ces resultats sont consistants avec le point de vue neo classique qui suggere que les producteurs gagnent au detriment des consommateurs de plus les resultats indiquent que les entreprises consommatrices d acier en aval qui ont diversifie leur production dans les pays de l alena se sont premunies contre certains risques associes a la politique commerciale et aux hauts couts de l acier engendres par la protection

a two factor stochastic programming model of danish mortgage backed securities abstract danish mortgage loans have several features that make them interesting short term revolving adjustable rate mortgages are available as well as fixed rate 10 20 or 30 year annuities that contain embedded options call and delivery options the decisions faced by a mortgagor are therefore non trivial both in terms of deciding on an initial mortgage and in terms of managing rebalancing it optimally we propose a two factor arbitrage free interest rate model calibrated to observable security prices and implement on top of it a multi stage stochastic optimization program with the purpose of optimally composing and managing a typical mortgage loan we model accurately both fixed and proportional transaction costs as well as tax effects risk attitudes are addressed through utility functions and through worst case min max optimization the model is solved in up to 9 stages having 19 683 scenarios numerical results which were obtained using standard soft and hardware indicate that the primary determinant in choosing between adjustable rate and fixed rate loans is the short long interest rate differential i e term structure steepness but volatility also matters refinancing activity is influenced by volatility and of course transaction costs

wto ministerial conference in singapore environmental diversity versus harmonization 1 introductionin december 1996 a newera of the international trade regime started with the rstwto ministerial conferencein singapore substantialprogress hasbeenachievedin freeing trade in information technology products and a north south collision oninternational labour standards has been averted however these successes over shadow the apparant stagnation in the area of trade and environment at last aftermanyyearsofintensivediscussions manyhadhopedthatthe rstwtoministerialconferencewouldaddressthissensitivepolicy eld outofthewiderangeofissuesthat can be dealt with under this heading two gure prominently trade measurespursuantto multilateral environmentalagreementsandeco labellingschemes thisnote rstly tries to explain why exactly these two issues draw most of the atten tion of policymakers and secondly discusses how these issues can be resolvedagainst the background of established welfare theory it also tries to make clearwhy the ministers in singapore pussyfooted around these issues and only decidedthat the wto committee on trade and environment has to continue its explora tory work to come to grisp with these issues insights from the literature on thetrade environment interface are rst summarized in eight propositions 2 propositions on trade and environmentbefore setting forth the propositions it is good to knowthat in analyticalstudies ontrade and environment the following distinctions are usually made first there areon the one hand local and national environmental problems and on the other handtransboundary i e international and global environmental problems the formerrefer to externalities caused by domestic environmental distortions that do notexpell beyond national borders the latter refer to environmental problems thataffect welfare both in the home country and in one or more foreign countries

is india specialising in polluting industries evidence from us india bilateral trade recently the apex environmental agency of india observed that domestic industrial pollution has been increasing at an alarming rate over the last two decades and the need to rein in traditional polluting industries this raises the pertinent question of whether the poor domestic pollution regime has affected the pattern of india s trade in dirty manufactured products in the post liberalisation era since 1991 we find that on the whole india has remained a net importer of pollution intensive manufactured goods however there is a distinct trend of increasing specialisation in specific dirty industries especially in the bilateral trade with high income countries and to a lesser degree with low income countries the usa being india s single largest country trading partner in the post liberalisation era we test for pollution offshoring at the finer industry level in us india bilateral trade while we find that the pollution haven effect is not significant india s specialisation in certain dirty manufacturing industries through the last decade remains a disturbing trend india needs to integrate environmental sustainability within industrial growth urgently and it is pertinent to implement policies which would reflect the true pollution costs in an industry that is increasingly competing in the international market

international trade and environmental regulation time series evidence and cross section test this paper examines empiricallywhether more stringent domestic environmental policiesreduce the international competitiveness ofenvironmentally sensitive goods esgs our timeseries evidence indicates that there are no systematicchanges in trade patterns of esgs in the last threedecades despite the introduction of more stringentenvironmental regulations in most of the developedcountries in the 1970s and 1980s this observedphenomenon is then subjected to a multi countryeconometric test using an extended gravity equationframework the test suggests that overall morestringent environmental regulations do not reducetotal exports exports of esgs and exports ofnon resource based esgs neither was there anyevidence to support the hypothesis that new tradebarriers emerge to offset the effects of morestringent environmental regulations

is environmental efficiency trade inducing or trade hindering abstract global efforts to identify strategies for sustainable economic growth and development underline the need for understanding important links between environmental policies and international trade in this paper by constructing an environmental efficiency index for 111 countries from 1980 to 2009 we are able to empirically test for one such link an improvement in the environmental efficiency index in terms of carbon dioxide emissions reflects a decrease in the cost of efforts to mitigate the environmental costs associated with growth countries that improve their environmental efficiency are found to experience strong international trade effects both through increased exports and increased imports while the positive link between efficiency improvements and exports is supportive of the porter hypothesis the positive link between efficiency improvements and imports is supportive of strong positive income effects on account of environmental efforts these results which are robust to alternative estimation strategies lend strong support to global efforts to improve countries environmental efficiencies

the excess supply pure demand approach to international commodity trade the case of japanese steel exports to the united states the purpose of this paper is twofold 1 to develop a theoretical framework for the analysis of export supply which is empirically more fruitful than existing approaches and 2 to present an empirical application of the theory to the market for japanese steel thereby quantifying important export supply elasticities not dealt with in the past evidence is presented which indicates that the supply of japanese steel exports to the u s is price elastic and sensitive to japanese and rest of world demand conditions

the data driven newsvendor with censored demand observations motivated by data from a large european retail chain we tackle the newsvendor problem with censored demand observations by a distribution free approach based on a data driven approach for this purpose we extend the model introduced in chap 3 to improve the forecast accuracy we simultaneously estimate unobservable lost sales determine the coefficients of the exogenous variables which drive demand and calculate the optimal order quantity since demand exceeding supply cannot be recorded we use the timing of hourly sales occurrences to establish daily sales patterns these sales patterns allow conclusions on the amount of unsatisfied demand and thus the true customer demand to determine the coefficients of the inventory function we formulate a linear programming model that balances inventory holding and penalty costs based on the censored demand observations in a numerical study with data generated from the normal and the negative binomial distribution we compare our model with other parametric and non parametric estimation approaches we evaluate the performance in terms of inventory and service level for non price dependent demands and different censoring levels we find that the data driven newsvendor model copes especially well with highly censored data and price dependent demand in most settings with price dependent demand it achieves similar or higher service levels by holding lower inventories than other benchmark approaches from the literature finally we show that the non parametric approaches are better than the parametric ones based on real data with several exogenous variables where the true demand distribution is unknown

the value of combining forecasts in inventory management a case study in banking managing inventories in the face of uncertain stochastic demand requires an investment in safety stocks these are related to the accuracy in forecasting future demands and the noise in the demand generation process reducing the demand forecasting error can free up capital and space and reduce the operating costs of managing the inventories a leading bank in hong kong consumes more than three hundred kinds of printed forms for its daily operations a major problem of its inventory control system for the forms management is to forecast the monthly demand of these forms in this study the idea of combining forecasts is introduced and its practical application is addressed the individual forecasts come from well established time series models and the weights for combination are estimated with quadratic programming the combined forecast is found to perform better than any of the individual forecasts

the effects of integrating management judgement into out levels in or out of context physical inventories constitute a significant proportion of companies investments in today s competitive environment the trade off between customer service levels and inventory reserves is addressed in practice by statistical inventory software solutions given the tremendous number of stock keeping units skus that contemporary organizations deal with such solutions are fully automated however empirical evidence suggests that managers habitually judgementally adjust the output of such solutions such as replenishment orders or re order levels this research is concerned with the value being added or not when statistically derived inventory related decisions order up to out levels in particular are judgementally adjusted we aim at developing our current understanding on the effects of incorporating human judgement into inventory decisions to our knowledge such effects do not appear to have been studied empirically before and this is the first endeavour to do so a number of research questions are examined and a simulation experiment is performed using an extended database of approximately 1 800 skus from the electronics industry in order to evaluate human judgement effects the linkage between adjustments and their justification is also evaluated given the apparent lack of comprehensive empirical evidence in this area including the field of demand forecasting this is a contribution in its own right insights are offered to academics to facilitate further research in this area practitioners to enable more constructive intervention into statistical inventory solutions and software developers to consider the interface with human decision makers

unstable weights in the combination of forecasts the weights used in the combination of forecasts are shown to be very unstable they are generally so unstable that the combined forecasts often do not perform better than some of the individual forecasts or a simple average of the forecasts in practice the instability is found from a series of monte carlo experiments as well as from the nominal gnp forecasts from four well known macro forecasters the monte carlo experiments also show that when the underlying models are known a composite forecast from a composite model is generally more accurate than the combination of the individual forecasts a simple average is shown to be the best technique to use in practice because the weights in the combination are so unstable

tourism forecasting to combine or not to combine abstract existing non tourism related literature shows that forecast combination can improve forecasting accuracy this study tests this proposition in the tourism context by examining the efficiency of combining forecasts based on three different combination methods the data used for this study relate to tourist arrivals in hong kong from the top ten tourism generating countries regions the forecasts are derived from four different forecasting models autoregressive integrated moving average arima model autoregressive distributed lag model adlm error correction model ecm and vector autoregressive var model all forecasts are ex post and the empirical results show that the relative performance of combination versus single model forecasts varies according to the origin destination tourist flow under consideration which parallels previous findings regarding the relative performance of individual forecasting methods the results also vary with the combination techniques used furthermore although the combined forecasts do not always outperform the best single model forecasts almost all the combined forecasts are not outperformed by the worst single model forecasts this suggests that forecast combination can considerably reduce the risk of forecasting failure this conclusion also implies that combined forecasts are likely to be preferred to single model forecasts in many practical situations

parameter estimation and performance measurement in lost sales inventory systems abstract in most retail environments the only information available on customer demand comes from sales data when a product is out of stock there is generally no knowledge of what potential sales have been lost this creates problems when it comes to estimating forecasting the demand distribution and its parameters this paper looks at this problem and considers ways of overcoming it in particular making use of data captured by modern point of sale systems

the accuracy of combining judgemental and statistical forecasts judgement based forecasts are widely used in practice either alone or in conjunction with computer prepared forecasts this study empirically examines the improvement in accuracy which can be gained from combining judgemental forecasts either with other judgemental or with quantitatively derived forecasts two judgemental forecasting approaches are used by each of two different groups in a laboratory setting to give four sets of judgemental forecasts for the 68 monthly time series of the m competition these are combined either with each other or with forecasts from deseasonalised single exponential smoothing combined forecasts are found to be more accurate than single forecasts with the greatest benefit realised at short forecast horizons and for easier as opposed to harder forecast series averaging was observed to be a far better way of combining judgemental forecasts than a judgemental nonsystematic combination

robust portfolio optimization with copulas abstract conditional value at risk cvar is widely used in portfolio optimization as a measure of risk cvar is clearly dependent on the underlying probability distribution of the portfolio we show how copulas can be introduced to any problem that involves distributions and how they can provide solutions for the modeling of the portfolio we use this to provide the copula formulation of the cvar of a portfolio given the critical dependence of cvar on the underlying distribution we use a robust framework to extend our approach to worst case cvar wcvar wcvar is achieved through the use of rival copulas these rival copulas have the advantage of exploiting a variety of dependence structures symmetric and not we compare our model against two other models gaussian cvar and worst case markowitz our empirical analysis shows that wcvar can asses the risk more adequately than the two competitive models during periods of crisis

robust one period option hedging we consider robust optimization to cope with uncertainty about the stock return process in one period option hedging problems the robust approach relates portfolio choice to uncertainty making more cautious hedges when uncertainty is high we represent uncertainty by a set of plausible expected returns of the underlying stocks and show that for this set the robust problem is a second order cone program that can be solved efficiently we apply the approach to find an optimal portfolio to hedge an index option

forecasting aggregate retail sales the case of south africa abstract forecasting aggregate retail sales may improve portfolio investors ability to predict movements in the stock prices of retail chains this paper uses 26 23 single and 3 combination forecasting models to forecast south africa s aggregate seasonal retail sales we use data from 1970 01 2012 05 with 1987 01 2012 05 as the out of sample period unlike the previous literature on retail sales forecasting we not only look at a wide array of linear and nonlinear models but also generate multi step ahead forecasts using a real time recursive estimation scheme over the out of sample period to better mimic the practical scenario faced by economic agents making retailing decisions in addition we deviate from the uniform symmetric quadratic loss function typically used in forecast evaluation exercises by considering loss functions that overweight the forecast error in booms and recessions focusing on the results of single models alone shows that their performances differ greatly across forecast horizons and for different weighting schemes with no unique model performing the best across various scenarios however combination forecast models especially the discounted mean square forecast error method which weighs current information more than past not only produced better forecasts but were also largely unaffected by business cycles and time horizons this result along with individual nonlinear models performing better than linear models led us to conclude that theoretical research on retail sales should look at developing dynamic stochastic general equilibrium models that not only incorporate learning behavior but also allow the behavioral parameters of the model to be state dependent to account for regime switching behavior across alternative states of the economy

cleaning up while cleaning up pollution abatement interest groups and contingent trade policies this paper analyzes the political economy of environmental policy formation in a trading economy with established rules for administered protection we argue that the social costs associated with the adoption of an inefficient environmental regime are likely to be compounded by induced restrictions on trade when the effected industries are import competing the preferences of interest groups for alternative environmental regimes tend to be linked to the legal institutional setting in which trade policy is conducted under existing rules and practices in the area of administered protection there is reason to believe that interest group preferences for an inefficient approach to pollution control will be strengthened because the adoption of such a regime is more likely to lead to a concomitant increase in trade barriers

modeling and forecasting sales data by time series analysis time series modeling technique is used to model a series of sales data in which seasonality causes distinct spike peaks the analysis of actual sales data shows that the seasonality in the data can