evaluation of forecasting error measurements and techniques for intermittent demand abstract this paper is a part and contribution to develop flexible and robust supply chain forecasting systems under changing market demands it suggests new tools and models to evaluate forecasting error measurements the paper especially studies slow moving or intermittent demand when for items the forecasting time periods often have zero demand for the difficult to forecast intermittent demand the croston forecasting technique is mostly regarded as a better choice than single exponential smoothing these two methods croston and single exponential smoothing together with two modifications of the croston method are discussed and evaluated with real intermittent data the apprehended performance of a forecasting technique is dependent of the chosen measurement of forecast errors the main purpose is to examine and evaluate different forecasting error measurements traditional measurements of forecast errors are studied mean absolute deviation mad mean square error mse etc together with new suggested error and bias measurements periods in stock pis and number of shortages nos pis considers the time aspect of the forecast error nos considers the development of cumulated forecast error cfe a complementary measure for descriptive statistics of time series is also suggested mean average change the conclusion through principal components analysis pca is that a single measure of forecast errors does not present the total different dimensions of the errors complementary error measures must be used

an inventory model for slow moving items subject to obsolescence in this paper we consider a continuous review inventory system of a slow moving item for which the demand rate drops to a lower level at a known future time instance the inventory system is controlled according to a one for one replenishment policy with a fixed lead time adapting to lower demand is achieved by changing the control policy in advance and letting the demand take away the excess stocks we show that the timing of the control policy change primarily determines the tradeoff between backordering penalties and obsolescence costs we propose an approximate solution for the optimal time to shift to the new control policy minimizing the expected total cost during the transient period we find that the advance policy change results in significant cost savings and the approximation yields near optimal expected total costs

energy consumption financial development and economic growth in india new evidence from a nonlinear and asymmetric analysis this paper investigates the asymmetric relationship between energy consumption and economic growth by incorporating financial development capital and labour into a production function covering the indian economy from 1960q1 2015q4 the nonlinear autoregressive distributed lag bounds testing approach is applied to examine the asymmetric cointegration between the variables an asymmetric causality test is also employed to examine the causal association between the considered variables the results indicate cointegration between the variables in the presence of asymmetries the asymmetric causality results show that only negative shocks in energy consumption have impacts on economic growth in the same vein only negative shocks in financial development have impacts on economic growth by contrast symmetrically capital formation causes economic growth finally over the study period a neutral effect exists between the labour force and economic growth in india the implications of these results for growth policies in india are also discussed

on the stock control performance of intermittent demand estimators the purpose of this paper is to assess the empirical stock control performance of intermittent demand estimation procedures the forecasting methods considered are the simple moving average single exponential smoothing croston s method and a new method recently developed by the authors of this paper we first discuss the nature of the empirical demand data set 3000 stock keeping units and we specify the stock control model to be used for experimentation purposes performance measures are then selected to report customer service level and stock volume differences the out of sample empirical comparison results demonstrate the superior stock control performance of the new intermittent demand forecasting method and enable insights to be gained into the empirical utility of the other estimators

the relationship amongst energy consumption renewable and non renewable and gdp in algeria abstract this study aims to explore economic growth energy consumption nexus in algeria between 1980 and 2012 with cointegration tests we demonstrate the existence of long run link between real gross domestic product real capital and the two categories of energy consumption i e renewable energy per capita and non renewable energy the long run and the short run autoregressive distributed lag ardl estimates indicate that only the non renewable energy sort and capital can contribute to enhancing economic growth whereas renewable energy does not show any significant effect the outcome of causality tests proves a feedback link among non renewable energy consumption and gross domestic product among capital and gross domestic product and among non renewable energy and capital in both short run and long run terms moreover the results reveal a unidirectional link going from renewable energy to economic growth capital and non renewable energy respectively in the long run furthermore the results illustrate the presence of a unidirectional link going from non renewable energy to renewable energy in the short term our outcome suggests that policy makers in algeria should enhance the renewable energy share together with controlling the non renewable one

is income inequality a driver for renewable energy consumption abstract although many initiatives have been made to research the effect of income inequality on environmental issues the question of whether income inequality affects renewable energy consumption hasn t been answered this gap in the literature raises an important question that needs to be answered by researchers can the income inequality affect renewable energy consumption as far as is known the study is the first attempt to discover this relationship therefore the impact of income inequality on renewable energy consumption is examined theoretically and empirically in 43 developed and developing countries for 2000 2015 in order to avoid the omitted variable problem economic environmental and institutional variables such as gdp per capita corruption co2 emissions and trade openness are included in the model the results demonstrate that the decline in income inequality will enhance renewable energy consumption in other words policymakers have the opportunity to reduce income inequality and environmental degradation at the same time similarly corruption control and raise co2 emissions will increase also renewable energy consumption otherwise economic determinants such as economic growth and trade openness have no meaningful effect on renewable energy consumption

renewable energy consumption economic growth nexus in turkey abstract this paper examines the renewable energy consumption economic growth causality nexus in turkey studies in the literature can be grouped as country specific and multi country studies the results of these studies are inconsistent and there is no agreement on the existence or the direction of causality between renewable energy consumption and economic growth the results of this country specific study support conservation hypothesis the results of empirical tests from ardl approach show that renewable energy consumption has a negative impact on economic growth and the ones of toda yamamoto causality tests show that there is a unidirectional causality running from economic growth to renewable energy consumption

investigation of the causal relationships between combustible renewables and waste consumption and co2 emissions in the case of tunisian maritime and rail transport abstract this study investigates the dynamic causal links between carbon dioxide co 2 emissions real gross domestic product gdp combustible renewables and waste consumption and maritime and rail transport in tunisia spanning the period 1980 2011 the autoregressive distributed lag ardl approach and granger causality tests are employed to examine the short and long run relationships between variables the empirical results suggest a bidirectional short run causality between co 2 emissions and maritime transport and a unidirectional causality running from real gdp combustible renewables and waste consumption rail transport to co 2 emissions the long run estimates reveal that real gdp contributes to the decrease of co 2 emissions while combustible renewables and waste consumption and maritime and rail transport have a positive impact on emissions our policy recommendation is that tunisia should use more combustible renewables and waste energy and increase the number of passenger s rail and maritime transport in order to motivate economic activities however the level of renewables energy required to reduce co 2 emissions caused by transport sector is still very weak

renewable energy oil prices and economic activity a granger causality in quantiles analysis this paper analyzes the causal relationship between renewable energy consumption oil prices and economic activity in the united states from july 1989 to july 2016 considering all quantiles of the distribution although the concept of granger causality is defined for the conditional distribution the majority of papers have tested granger causality using conditional mean regression models in which the causal relations are linear we apply a granger causality in quantiles analysis that evaluates causal relations in each quantile of the distribution under this approach we can discriminate between causality affecting the median and the tails of the conditional distribution we find evidence of bi directional causality between changes in renewable energy consumption and economic growth at the lowest tail of the distribution besides changes in renewable energy consumption lead economic growth at the highest tail of the distribution our results also support the unidirectional causality from fluctuations in oil prices to economic growth at the extreme quantiles of the distribution finally we find evidence of lower tail dependence from changes in oil prices to changes in renewable energy consumption our findings call for government policies aimed at developing renewable energy markets to increase energy efficiency in the u s

overlapping efforts in the eu emissions trading system abstract according to the phase iv 2021 2030 rules of the eu ets the total amount of emission permits allocated to firms is not fixed but endogenous this implies that a national climate policy that overlaps with the ets can have an impact on total aggregate emissions roughly speaking if firms increase their holdings of emission permits the total amount of permits allocated is reduced this paper analytically investigates how an overlapping national policy affects the aggregate bank of emission permits if marginal abatement costs are not too convex national climate policies increase banking and thus tend to reduce overall emissions

modeling the causal linkages between nuclear energy renewable energy and economic growth in developed and developing countries abstract this article investigates the causal relationship between two types of energy variables and economic growth using dynamic simultaneous equation panel data models for 17 developed and developing countries our results indicate that there is a unidirectional causality running from nuclear consumption to economic growth in belgium and spain while a unidirectional causality running from economic growth to nuclear consumption is supported in bulgaria canada netherlands and sweden a bidirectional relationship appears in argentina brazil france pakistan and the usa while no causality exists in finland hungary india japan switzerland and the u k second the results for the second nexus among renewable energy and economic growth show that there is a unidirectional causality running from renewable consumption to economic growth in hungary india japan netherlands and sweden while there exist a unidirectional running from economic growth to renewable consumption in argentina spain and switzerland a bidirectional relationship is supported in belgium bulgaria canada france pakistan and the usa while no causality exists in brazil finland and switzerland third we find the existence of a bidirectional causality between nuclear consumption and economic and a unidirectional causality running from economic growth to renewable energy consumption for the global panel

cause and effect of renewable energy consumption on urbanization and economic growth in china s provinces and regions abstract renewable energy development is one of the cleaner production paths for china s transformation of urbanization and economic development recognizing the nexus among them may help china to formulate a targeted policy for efficient and clean energy utilization as well as for carbon reduction based on the panel data of 30 provinces and seven geographical regions over the period of 1997 2015 we apply a bootstrap panel causality test to explore the cause and effect of renewable energy consumption on urbanization and economic growth in china after a cross sectional dependence test and a slope homogeneity test we find that china s renewable energy consumption urbanization and economic growth in one region might be influenced by the others however no causality is found in 80 of provinces and 71 of geographical regions for the nexus of renewable energy consumption and urbanization and no causality is found in 53 of provinces and 43 of geographical regions for the nexus of renewable energy consumption and economic growth besides significant geographical differences are found for the nexus therefore the chinese government should not only strengthen a unified renewable energy management system to advocate regional cooperation but also give full play to the weak joint linkages and adopt differentiated renewable energy policies according to local conditions the interactive mechanism and a virtuous cycle among the three indicators should be established in the medium and long term to help china s energy use towards a cleaner transition

intermittent demand forecasts with neural networks intermittent demand appears when demand events occur only sporadically typically such time series have few observations making intermittent demand forecasting challenging forecast errors can be costly in terms of unmet demand or obsolescent stock intermittent demand forecasting has been addressed using established forecasting methods including simple moving averages exponential smoothing and croston s method with its variants this study proposes a neural network nn methodology to forecast intermittent time series these nns are used to provide dynamic demand rate forecasts which do not assume constant demand rate in the future and can capture interactions between the non zero demand and the inter arrival rate of demand events overcoming the limitations of croston s method in order to mitigate the issue of limited fitting sample which is common in intermittent demand the proposed models use regularised training and median ensembles over multiple training initialisations to produce robust forecasts the nns are evaluated against established benchmarks using both forecasting accuracy and inventory metrics the findings of forecasting and inventory metrics are conflicting while nns achieved poor forecasting accuracy and bias all nn variants achieved higher service levels than the best performing croston s method variant without requiring analogous increases in stock holding volume therefore nns are found to be effective for intermittent demand applications this study provides further arguments and evidence against the use of conventional forecasting accuracy metrics to evaluate forecasting methods for intermittent demand concluding that attention to inventory metrics is desirable

forecasting and stock control a study in a wholesaling context wholesalers add value to the products they deal with by essentially bringing them closer to the end consumers in that respect the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels in this paper we address issues pertinent to forecasting and inventory management in a wholesaling environment and discuss the recommendations proposed in such a context in a case study organization our findings demonstrate the considerable scope that exists for improving current practices and offers insights into possible managerial issues

renewable energy consumption economic growth and human development index in pakistan evidence form simultaneous equation model abstract the major consumption of energy around the globe is related to human activities however it may be essential to quantify how renewable energy consumption influence process of human development this particular area of research still needs to be explored thus this paper explores the relationship between renewable energy consumption economic growth and human development index for 1990 2014 in pakistan by using two stage least square 2sls method empirical results reveal that renewable energy consumption does not improve the situation of the human development process in pakistan more interestingly higher the income of the country the lower is level of human development in addition the co2 emission is helpful to improve human development index furthermore trade openness discourages human development process in pakistan furthermore causality analysis confirms feedback hypothesis between environmental factor and human development process in the long run path these novel findings would help policymaker and government officials to better understand the role of renewable energy and economic growth in the human development process in pakistan

impacts of renewable energy consumption on the german economic growth evidence from combined cointegration test abstract germany is the largest economy in europe and the leading renewable energy user comparable to none in the entire of the european continents it is in reference to these developments that this study investigates whether the impacts of renewable energy have consolidated the economic growth prospects of the country to ensure this quarterly time series data from 1971q1 to 2013qiv was used the study employed the clemente montanes reyes detrended structural break test the bayer hanck combined cointegration test and the ardl bounds testing approach to cointegration in addition the causality analysis was observed using vecm granger causality framework the results confirmed the existence of cointegration among the variables the results show that renewable energy consumption in germany consolidates the country s economic growth prospects to the extend that a 1 increase in renewable energy consumption boosts german economic growth by 0 2194 in addition to that a 1 increase in capital lead to the rise in economic growth by 1 1320 while a 0 5125 increase in economic growth is due to 1 increase in labor productivity the causality analysis on the other hand revealed the existence of feedback effect between renewable energy consumption and economic growth while the relationship between renewable energy consumption and capital is found to be bidirectional and same inference was found to exist between capital and economic growth the study proposes solid mechanisms that will help in averting renewable energy market failure locally and internationally among others

tests for unit root versus threshold specification with an application to the purchasing power parity relationship we consider modeling the real exchange rate by a stationary three regime self exciting threshold autoregressive setar model with possibly a unit root in the middle regime this representation is consistent with purchasing power parity in the presence of trading costs our main contribution is to provide statistical tools for testing unit root versus a setar first we show that a setar with a unit root in the middle regime is stationary and mixing under reasonable assumptions second we derive analytically the asymptotic distribution of our unit root test under the null using monthly real exchange rate data our test rejects the null of unit root against a threshold process for five european series

reduction of the value of information sharing as demand becomes strongly auto correlated information sharing has been identified in the academic literature as one of the most important levers to mitigate the bullwhip effect in supply chains a highly cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain when the downstream demand is autoregressive of order one is an increasing function of the autoregressive parameter of the demand in this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero we also show that this maximum value of the autoregressive parameter can be as high as 0 7 which represents a common value that may be encountered in many practical contexts this means that large benefits of information sharing cannot be assumed for those stock keeping units skus with highly positively auto correlated demand instead equally careful analysis is needed for these items as for those skus with less strongly auto correlated demand

emissions trading systems with cap adjustments abstract emissions trading systems etss with fixed caps lack provisions to address systematic imbalances in the supply and demand of permits due to changes in the state of the regulated economy we propose a mechanism which adjusts the allocation of permits based on the current bank of permits the mechanism spans the spectrum between a pure quantity instrument and a pure price instrument we solve the firms emissions control problem and obtain an explicit dependency between the key policy stringency parameter the adjustment rate and the firms abatement and trading strategies we present an analytical tool for selecting the optimal adjustment rate under both risk neutrality and risk aversion which provides an analytical basis for the regulator s choice of a responsive ets policy

endogenizing the cap in a cap and trade system assessing the agreement on eu ets phase 4 in early 2018 a reform of the world s largest functioning greenhouse gas emissions cap and trade system the eu emissions trading system ets was formally approved the reform changed the main principles of the system by endogenizing the emissions cap we show that the emissions cap is now affected by the allowance demand and is therefore no longer set directly by eu policymakers as a consequence national policies that reduce allowance demand can now reduce long run cumulative emissions which is not possible in a standard cap and trade system using a newly developed dynamic model of the eu ets we show that policies that reduce allowance demand can have substantial effects on cumulative emissions after the reform model simulations also suggest that the reform reduces long run cumulative emissions and to a lesser extent reduces emissions in the short run even so the reform has a small short run impact on the currently large allowance surplus

another look at estimators for intermittent demand abstract in this paper we focus on forecasting for intermittent demand data we propose a new aggregation framework for intermittent demand forecasting that performs aggregation over the demand volumes in contrast to the standard framework that employs temporal over time aggregation to achieve this we construct a transformed time series the inverse intermittent demand series the new algorithm is expected to work best on erratic and lumpy demand as a result of the variance reduction of the non zero demands the improvement in forecasting performance is empirically demonstrated through an extensive evaluation in more than 8000 time series of two well researched spare parts data sets from the automotive and defence sectors furthermore a simulation is performed so as to provide a stock control evaluation the proposed framework could find popularity among practitioners given its suitability when dealing with clump sizes as such it could be used in conjunction with existing popular forecasting methods for intermittent demand as an exception handling mechanism when certain types of demand are observed

intermittent demand linking forecasting to inventory obsolescence the standard method to forecast intermittent demand is that by croston this method is available in erp type solutions such as sap and specialised forecasting software packages e g forecast pro and often applied in practice it uses exponential smoothing to separately update the estimated demand size and demand interval whenever a positive demand occurs and their ratio provides the forecast of demand per period the croston method has two important disadvantages first and foremost not updating after many periods with zero demand renders the method unsuitable for dealing with obsolescence issues second the method is positively biased and this is true for all points in time i e considering the forecasts made at an arbitrary time period and issue points only i e considering the forecasts following a positive demand occurrence only the second issue has been addressed in the literature by the proposal of an estimator syntetos boylan approximation sba that is approximately unbiased in this paper we propose a new method that overcomes both these shortcomings while not adding complexity different from the croston method the new method is unbiased for all points in time and it updates the demand probability instead of the demand interval doing so in every period the comparative merits of the new estimator are assessed by means of an extensive simulation experiment the results indicate its superior performance and enable insights to be gained into the linkage between demand forecasting and obsolescence

on energy consumption and gdp studies a meta analysis of the last two decades abstract the relationship between energy consumption and gdp growth has been intensely examined in multiple frameworks set by various methods and countries this paper is a meta analysis of 51 studies published in the last two decades with worldwide data since 1949 on the relationship between energy consumption and gdp growth the aim is to systemize some of the factors that cause the variation of results in these studies our results yield evidence that the long run elasticity of gdp growth with respect to energy consumption is not independent of the method employed for cointegration the data type and the inclusion of variables such as the price level or capital in the cointegration equation also 1 increase in capital increases the elasticity of gdp with respect to energy consumption by 0 85

causes of the eu ets price drop recession cdm renewable policies or a bit of everything new evidence the price of eu allowances euas in the eu emissions trading scheme eu ets fell from almost 30 tco2 in mid 2008 to less than 5 tco2 in mid 2013 the sharp and persistent price decline has sparked intense debates both in academia and among policy makers about the decisive allowance price drivers in this paper we examine whether and to what extent the eua price drop can be justified by three commonly identified explanatory factors the economic recession renewable policies and the use of international credits capitalizing on marginal abatement cost theory and a broadly extended data set we find that only variations in economic activity and the growth of wind and solar electricity production are robustly explaining eua price dynamics contrary to simulation based analyses our results point to moderate interaction effects between the overlapping eu ets and renewable policies the bottom line however is that 90 of the variations of eua price changes remains unexplained by the abatement related fundamentals together our findings do not support the widely held view that negative demand shocks are the main cause of the weak carbon price signal in view of the new evidence we evaluate the eu ets reform options which are currently discussed

a new statistic and practical guidelines for nonparametric granger causality testing abstract in this paper we introduce a new nonparametric test for granger non causality which avoids the over rejection observed in the frequently used test proposed by hiemstra and jones 1994 testing for linear and nonlinear granger causality in the stock price volume relation journal of finance 49 1639 1664 after illustrating the problem by showing that rejection probabilities under the null hypothesis may tend to one as the sample size increases we study the reason behind this phenomenon analytically it turns out that the hiemstra jones test for the null of granger non causality which can be rephrased in terms of conditional independence of two vectors x and z given a third vector y is sensitive to variations in the conditional distributions of x and z that may be present under the null to overcome this problem we replace the global test statistic by an average of local conditional dependence measures by letting the bandwidth tend to zero at appropriate rates the variations in the conditional distributions are accounted for automatically based on asymptotic theory we formulate practical guidelines for choosing the bandwidth depending on the sample size we conclude with an application to historical returns and trading volumes of the standard and poor s index which indicates that the evidence for volume granger causing returns is weaker than suggested by the hiemstra jones test

non fossil fuel energy usage and economic growth in india a study on non linear cointegration asymmetry and causality abstract this study evaluates the potential impact of promoting non fossil fuel energy on india s economic growth in a regime based non linear asymmetric framework the empirical outcomes affirm regime shift and asymmetric cointegrating links of the non fossil fuel energy usage represented by combustible renewables waste crew and alternative nuclear energy anen with the gross domestic product gdp the study establishes the existence of threshold cointegration between crew and gdp the causal links between crew and gdp are regime variant and asymmetric whereas the dynamics between anen and gdp are proven to be asymmetric and regime invariant crew and gdp supports a feedback hypothesis in a normal regime and a conservation hypothesis in a rare regime the asymmetric causality between crew and gdp validates an inverse feedback hypothesis and a negative growth hypothesis a negative growth hypothesis is also ascertained between anen and gdp the empirical findings convey meaningful insights for government and policymakers

adapting wright s modification of holt s method to forecasting intermittent demand abstract the challenge of accurately forecasting demand for spare parts is due to the intermittent nature of their demand this study compares a recent modification of croston s method and a method based on holt s double exponential smoothing taking the firm s competitive priorities into consideration wright s modification of holt s method is presented as a viable alternative when forecasting demand for spares especially when trend is present results indicate that firms focusing on minimizing inventory levels as a priority should consider forecasting using the modified croston s method if their priority is high customer service then the modified holt s method is superior

on the bias of intermittent demand estimates forecasting and inventory control for intermittent demand items has been a major problem in the manufacturing and supply environment croston operational research quarterly 23 1972 289 proposed a method according to which intermittent demand estimates can be built from constituent events croston s method has been reported to be a robust method but has shown more modest benefits in forecasting accuracy than expected in this research one of the causes of this unexpected performance has been identified as a first step towards improving croston s method certain limitations are identified in croston s approach and a correction in his derivation of the expected estimate of demand per time period is presented in addition a modification to his method that gives approximately unbiased demand per period estimates is introduced all the conclusions are confirmed by means of an extended simulation experiment where croston s and revised croston s methods are compared the forecasting accuracy comparison corresponds to a situation of an inventory control system employing a re order interval or product group review

an improved method for forecasting spare parts demand using extreme value theory inventory control for spare parts is essential for many organizations due to the trade off between preventing high holding cost and stockouts the lead time demand distribution plays a central role in inventory control the estimation of this distribution is problematic as the spare part demand is often intermittent and as a consequence often only a limited number of non zero data points are available in practice the well known empirical method uses historical demand data to construct the lead time demand distribution although it performs reasonably well when service requirements are relatively low it has difficulties in achieving high target service levels in this paper we improve the empirical method by applying extreme value theory to model the tail of the lead time demand distribution to make the most out of a limited number of demand observations we establish that extreme value theory can be applied to lead time demand periods computed over overlapping intervals we consider two service levels the expected waiting time and cycle service level our experiments show that our method improves the inventory performance compared to the empirical method and is competitive with the wss method croston s method and sba for a range of demand distributions

the asymmetric effects of foreign direct investment on clean energy consumption in brics countries a recently introduced hidden cointegration test abstract this study investigates the effects of foreign direct investment and the trade openness on clean energy consumption for brics countries brazil russia india china and south africa during the period 1985 2017 for that purpose the study employs fourier adl autoregressive distributed lag and hidden fourier adl cointegration tests and fourier toda yamamoto approach to granger causality considering both raw data and the asymmetric components of the series empirical results reveal that these variables are cointegrated in russia china and south africa regarding hidden fourier adl cointegration test while they are cointegrated only in south africa considering the fourier adl test it is found that trade positively affects clean energy use in south africa in the context of negative components foreign direct investment has a positive impact on clean energy use in russia while its effect is insignificant in china and south africa moreover trade openness influences clean energy consumption negatively in russia china and south africa according to the fourier toda yamamoto and asymmetric fourier toda yamamoto causality tests results regarding negative components there is unidirectional causality from foreign direct investment inflows to clean energy consumption in china findings of this study may provide beneficial information to the policymakers to design proper environmental policies such as the imposition of the carbon tax and subsidy on cleaner energy consumption

the accuracy of a modified croston procedure a modified croston procedure to forecast intermittent demand is reviewed the modified procedure published in this journal in 2004 consists of a new method for estimating the mean demand and a smoothing method for estimating the variance of the forecasted demand rate it is found that the smoothed variance estimate is based on an invalid measure of forecast accuracy moreover it is shown that the method of forecasting mean demand produces biased forecasts the accuracy of this method is assessed using simulated data and the mean square error measure and compared with croston s method and single exponential smoothing it is found that croston s method is generally more accurate than its modification particularly for strongly intermittent series

on the variance of intermittent demand estimates intermittent demand occurs at random with many time periods showing no demand at all forecasting such demand patterns constitutes a challenging exercise because of the associated dual source of variation demand intervals and demand sizes research in this area has developed rapidly in recent years with new results implemented into supply chain software solutions because of its practical implications in an inventory context both the accuracy of the forecasts and their variability sampling error of the mean have equal importance in terms of service level achievement and or inventory cost minimisation although the former issue has been studied extensively mainly building upon croston s model 1972 the latter has been largely ignored the purpose of this paper is to analyse the most well cited intermittent demand estimation procedures in terms of the variance of their estimates detailed derivations are offered along with a discussion of the underlying assumptions as such we hope that our contribution may constitute a point of reference for further analytical work in this area as well as facilitate a better understanding of issues related to modelling intermittent demands

exploiting elapsed time for managing intermittent demand for spare parts we present an intermittent demand forecasting method that conditions on the elapsed time since the last demand occurrence to anticipate incoming demand and show using empirical data that this can substantially reduce both stock investment and lost revenue for spare parts management we extensively benchmark our method against existing forecasting and bootstrapping methods on forecast accuracy and inventory performance and demonstrate that its performance is robust under general conditions our method is the first to incorporate that activities at the demand side such as aggregation of demand preventive and corrective maintenance can lead to a positive relation between demand size and inter arrival time of demand occurrences by anticipating incoming demand our method offers substantial financial gains

a meta analysis investigation of the direction of the energy gdp causal relationship implications for the growth degrowth dialogue abstract the complex relation between energy use and the economic process has long attracted attention issues such as the scarcity of energy resources energy theory of value degrowth and a growth approaches are closely related to the relationship between energy and development the present study traces the implications of the energy gdp causality dialogue for the context of the growth degrowth debate where the energy development link plays a decisive role in that context the present research investigates the possible existence of a fundamental macro direction of causality between energy use and economic growth that is not influenced by study specific characteristics and events towards this objective we perform a meta analysis that takes into account 158 studies on causality between energy and gdp covering the period 1978 2011 this is the first time to our knowledge that meta analysis has been applied to investigate the direction of the energy and gdp causal relationship the meta analysis results neither support the existence of a fundamental macro direction nor the so called neutrality hypothesis e gdp in the causal relationship between energy consumption and economic growth

from nonrenewable to renewable energy and its impact on economic growth the role of research development expenditures in asia pacific economic cooperation countries abstract this study disaggregates energy i e non renewable and renewable energy consumption and investigates its effect on economic growth the period of 1990 2015 is used to examine asia pacific economic cooperation apec countries this paper determines the cross sectional dependence and employs a second generation panel unit root test for precise estimation westerlund cointegration test is used to examine the long run equilibrium relationship between the variables and confirm the presence of cointegration in the long run the continuously updated fully modified ordinary least square cup fm approaches are applied to investigate long term output elasticities between the variables the results show the stimulating role of energy renewable and nonrenewable consumption in economic growth research and development expenditures and trade openness have a positive effect on economic growth moreover the time series individual country analysis also confirms that renewable energy has a positive impact on economic growth the heterogenous causality analysis reveals the feedback effect i e bidirectional causal associations among economic growth renewable energy consumption and nonrenewable energy consumption this empirical evidence suggests that countries should increase investment in renewable energy sectors and plan for development in renewable energy for sustainable energy growth

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

forecasting sales of slow and fast moving inventories abstract traditional computerised inventory control systems usually rely on exponential smoothing to forecast the demand for fast moving inventories practices in relation to slow moving inventories are more varied but the croston method is often used it is an adaptation of exponential smoothing that 1 incorporates a bernoulli process to capture the sporadic nature of demand and 2 allows the average variability to change over time the croston approach is critically appraised in this paper corrections are made to underlying theory and modifications are proposed to overcome certain implementation difficulties a parametric bootstrap approach is outlined that integrates demand forecasting with inventory control the approach is illustrated on real demand data for car parts

renewable energy carbon emission and economic growth a revised environmental kuznets curve perspective abstract renewable energy plays an important role in reducing global carbon co2 emission this paper builds a rer renewable energy consumption rate index to represent the energy structure of a country and proposes a u shaped rkc renewable energy kuznets curve hypothesis between rer and economic growth we also examine the dynamic relationship between rer and the environmental kuznets curve ekc hypothesis using two panel data sets of 17 major developing and developed countries as well as six geo economic regions of the world during 1990 2014 panel co integration tests indicate that a long run relationship exists among economic growth rer and carbon emission we employ the fully modified ordinary least squares fmols and the dynamic ordinary least squares dols techniques to estimate the co integration coefficients of the panels and individual countries regions respectively the results verify both the ekc and rkc hypotheses indicating that a 10 rise in rer would to a 1 6 carbon emission reduction it is also found that the rkc turning points of individual countries and the entire samples in general take place before the turning points of the respective ekcs it suggests that promoting renewable energy consumption to make rkc cross its turning point earlier can accelerate ekc to reach its turning point more quickly this finding has important policy implications with respect to the development and utilization of renewable energy and environmental protection

lumpy demand forecasting using neural networks abstract the current study applies neural network nn modeling in forecasting lumpy demand it is to the best of our knowledge the first such study our study compares the performance of nn forecasts to those using three traditional time series methods single exponential smoothing croston s method and the syntetos boylan approximation we find nn models to generally perform better than the traditional methods using three different performance measures we also independently validate earlier findings that the syntetos boylan approximation performs better than the croston s and single exponential smoothing methods in lumpy demand forecasting

economic welfare impacts from renewable energy consumption the china experience over the last years renewable energy sources have increased their share on electricity generation of china due to environmental and security of supply concerns in this work author assesses the role of both the amount and share of renewable energy consumption in economic welfare using cobb douglas type production functions this assessment is carried out by multivariate ols and spss software for china from 1978 to 2008 results indicate that a 1 increase in renewable energy consumption rec increases real gdp by 0 120 gdp per capita by 0 162 per capita annual income of rural households by 0 444 and per capita annual income of urban households by 0 368 respectively the impact of renewable energy consumption share srec on economic welfare is insignificant and an increasing share of rec negatively affects economic welfare growth to a certain extent in this paper the cost structural demand accounting mechanism and policy reasons of renewable energy development are interpreted marginal effects analysis show that the shape of sound and robust renewable energy institutions and policies would matter for increasing the standards of economic welfare in the context of speeding up renewable energy development and increasing share of renewable energy consumption especially the goal oriented policy refinement should be addressed efficiently in improvement households income while increasing share of renewable energy consumption c 2011 elsevier ltd all rights reserved

a simulation framework for forecasting uncertain lumpy demand abstract managing uncertainty when the demand is irregular and sporadic i e lumpy is a complex issue as well as an unexplored one this study analyses the behaviour of forecasting techniques when dealing with lumpy demand at the master production scheduling level in particular three forecasting techniques exponentially weighted moving average early sales and order overplanning are considered it is argued that demand lumpiness is a multidimensional phenomenon generated by different market characteristics namely numerousness of customers heterogeneity of customers frequency of order placing variety of each customer s request and correlation between customers behaviour hence the performances of the three forecasting methods are compared through simulation experiments with different values of the sources of lumpiness a framework is then proposed that indicates the domain of applicability of each forecasting technique according to the prevailing source of lumpiness in the market

the effects of integrating management judgement into intermittent demand forecasts empirical research suggests that quantitatively derived forecasts are very frequently judgementally adjusted nevertheless little work has been conducted to evaluate the performance of these judgemental adjustments in a practical demand sales context in addition the relevant analysis does not distinguish between slow and fast moving items currently there are neither conceptual developments nor empirical evidence on the issue of integrating judgements and statistical forecasts for slow intermittent demand items moreover no results have ever been reported on the stock control implications of these human judgements our work analyses monthly intermittent demand forecasts for the uk branch of a major international pharmaceutical company the company relies upon a commercially available statistical forecasting system to produce forecasts that are subsequently judgementally adjusted based on marketing intelligence gathered by the company forecasters the benefits of the intervention are evaluated by comparing the actual sales to system and final forecasts using both forecast accuracy and inventory control accuracy implication metrics our study allows insights to be gained on potential improvements to intermittent demand forecasting processes and subsequently the design effectiveness of forecasting support systems

joint optimisation of demand forecasting and stock control parameters abstract exponential smoothing methods are very commonly used for forecasting demand in a supply chain context when estimating the parameters used in these methods a common practice is to optimise only the smoothing constants and not the initial parameter values in this paper we show that if we treat initial values as well as smoothing constants as decision variables a considerable reduction in forecast error can be achieved additionally the optimisation of the forecasting method should not be treated separately from the production or inventory model in which forecasts are used the case of a centralised supply chain with an order up to inventory policy shows that calculated forecasts of demand determined by minimising mean absolute error mae or mean squared error mse are not optimal finally a method for simultaneous optimisation of demand forecasting and a stock control policy is described initial and smoothing parameters in the forecasting methods can be determined to minimise the total costs

forecasting method for noisy demand abstract exponential smoothing methods are very commonly used for forecasting demand regarding the process of forecasting demand the main approach towards the selection and optimisation of alternative methods relates to the minimisation of forecast error measures such as the mean square error mse with regard to pegels classification of usage of proper forecasting methods hw methods additive and multiplicative are appropriate for demand with trend and seasonality which corresponds to b 2 and b 3 but hw methods are not accurate enough for demand with large noise that is often a property of real data in this paper we present improved an hw method for demand with noise and we demonstrate that a reduction in forecast error mse can be reached from the results we prove that the proposed method is more accurate than the existing ones and that it is the proper choice for forecasting noisy demand furthermore we show that essential reduction of supply chain costs can be achieved if we use improved the hw method for joined optimisation

renewable non renewable energy consumption economic growth trade openness and ecological footprint evidence from organisation for economic co operation and development countries the purpose of this study is to examine the validity of environmental kuznets curve hypothesis for ecological footprint with the role of renewable energy use non renewable energy use and trade openness in 24 organisation for economic co operation and development countries for this purpose we investigate the period from 1980 to 2014 using with second generation panel data methodologies which allow to cross sectional dependence among countries the group mean results show that the inverted u shaped environmental kuznets curve hypothesis does not hold in organisation for economic co operation and development countries because we found the u shaped relationship between economic growth and ecological footprint in addition it is concluded that increasing renewable energy consumption reduces ecological footprint and increasing non renewable energy consumption increases environmental degradation

procrastinating reform the impact of the market stability reserve on the eu ets abstract we study the impact of the market stability reserve msr on price and emission paths of the eu ets from 2019 onwards the msr will adjust the number of allowances auctioned as a function of the size of the surplus i e in times of a large surplus it shifts the issue date of allowances into the future in a perfectly competitive allowance market the msr only affects price and emission paths if the baseline equilibrium becomes unfeasible if the msr is binding prices increase in the short run but drop in the medium run relative to the baseline the msr increases price variability if uncertainty over future allowance demand is resolved while there is a surplus the long run cap is unaffected by both the msr and overlapping climate policies this contrasts the eu s objectives of improving the resilience of the eu ets and increasing synergies with overlapping climate policies

renewable energy consumption economic growth nexus in emerging countries a bootstrap panel causality test abstract in this study we analyzed the relationship between renewable energy consumption and economic growth in 17 emerging countries spanning the period of 1990 2016 the bootstrap panel causality test allowing for dependence across countries and heterogeneity in slope parameters developed by konya 2006 1 was employed the results indicated that the neutrality hypothesis does hold for all of the markets studied except for poland which confirmed the growth hypothesis as such because of the nonexistence of causality running from renewable energy demand to economic growth energy saving mitigation policies do not have any detrimental influence on the growth rates of these 16 emerging economies for poland however energy conservation policies may have detrimental effects on the country s economic performance level

intermittent demand forecasting an empirical study on accuracy and the risk of obsolescence intermittent demand items account collectively for considerable proportions of the total stock value of any organization forecasting the relevant inventory requirements constitutes a very difficult task and most work in this area is based on croston s estimator that relies upon exponentially smoothed demand sizes and inter demand intervals this method has been shown to be biased and a number of variants have been introduced in the literature including the recently proposed tsb method that updates the demand probability instead of the demand interval and in doing so reacts faster to decreasing demand the tsb has been shown theoretically to be unbiased for all points in time but its empirical performance has not been investigated yet and this constitutes one of the objectives of our work more generally we explore the empirical performance of forecasting methods used in an intermittent demand context paying particular attention to the effects and implications of the smoothing constant values employed for updating purposes we do so by means of experimentation on large empirical datasets from the military sector and automotive industry the results enable insights to be gained into the sensitivity of the various methods forecasting and stock control performance to the smoothing constant values used the paper concludes with an agenda for further research

eu ets emissions under the cancellation mechanism effects of national measures abstract beginning in 2023 allowances held in the market stability reserve of the eu ets above the number of allowances auctioned the previous year will be cancelled in this paper we analyse the consequences of this new cancellation mechanism using numerical analysis we show that additional national abatement measures now have the potential to reduce total eu ets emissions a key insight is that for this to happen domestic emission reductions must occur early how early depends crucially on how the future demand for allowances evolve to facilitate an understanding of the rather complex system the reformed eu ets constitutes we present a series of extensions to the analysis to show how the results are affected by for example future emission levels technological development optimising agents and speculative trading in allowances