random yield supply chain with a yield dependent secondary market abstract this paper considers a simple supply chain with one supplier and one retailer where the supplier s production is subject to random yield and the retailer faces uncertain demand there exists a secondary market for acquiring or disposing products by the supplier we study both the centralized and decentralized systems in the decentralized system a no risk sharing contract and a risk sharing minimum commitment contract are analyzed the supply chain with the risk sharing contract is further analyzed with a constant secondary market price and a yield dependent secondary market price we present both the supplier s and the retailer s optimal strategies and provide insights for managers when making decisions under random yield risk and demand uncertainty we find that the secondary market generally has a positive impact on supply chain performance and the actual effect of random yield risk on the supply chain performance depends on cost parameters and supply chain contract settings under certain conditions reducing yield randomness may weaken the double marginalization effect and improve the chain performance from the numerical study we also show that there exists an optimal commitment level for the supply chain

capacity allocation ordering and pricing decisions in a supply chain with demand and supply uncertainties abstract this paper studies coordinated decisions in a decentralized supply chain that consists of one original equipment manufacturer oem one manufacturer and one distributor and possesses uncertainties at both demand and supply sides these uncertainties emerge respectively from random demand the distributor faces and randomness of capacity with which the oem processes the manufacturer s outsourced quantity sharing supply and demand uncertainty information along the supply chain enables us to develop three models with different coordination efforts the oem and manufacturer coordination the manufacturer and distributor coordination and the oem manufacturer and distributor coordination and quantify the coordinated decisions in these three models our analysis of these coordination models suggests that coordinating with the oem improves the manufacturer s probability of meeting downstream demand and his expected profit yet coordinating with the manufacturer is not necessarily beneficial to the oem when downstream coordination is lacking

optimality of myopic ordering policies for inventory model with stochastic supply this paper addresses a discrete time inventory model where the maximum amount of supply from which instantaneous replenishment orders can be made is a random variable optimal ordering policies are characterized as critical number policies with monotone increasing optimal critical values a sufficient condition is then presented for myopic ordering policies to be optimal

a comparative analysis of current credit risk models the new bis 1998 capital requirements for market risks allows banks to use internal models to assess regulatory capital related to both general market risk and credit risk for their trading book this paper reviews the current proposed industry sponsored credit value at risk methodologies first the credit migration approach as proposed by jp morgan with creditmetrics is based on the probability of moving from one credit quality to another including default within a given time horizon second the option pricing or structural approach as initiated by kmv and which is based on the asset value model originally proposed by merton merton r 1974 journal of finance 28 449 470 in this model the default process is endogenous and relates to the capital structure of the firm default occurs when the value of the firm s assets falls below some critical level third the actuarial approach as proposed by credit suisse financial products csfp with creditrisk and which only focuses on default default for individual bonds or loans is assumed to follow an exogenous poisson process finally mckinsey proposes creditportfolioview which is a discrete time multi period model where default probabilities are conditional on the macro variables like unemployment the level of interest rates the growth rate in the economy which to a large extent drive the credit cycle in the economy 2000 elsevier science b v all rights reserved

dynamic replenishment from two sources with different yields costs and leadtimes abstract we study a single item periodic review inventory system with two sources of supply in house production and outsourcing the two sources differ in yields costs and leadtimes demands in consecutive periods are independent random variables and stockout is fully backlogged our problem is to characterize the optimal dynamic policy that simultaneously determines the in house production quantity and the outsourcing quantity for each period to minimize the total discounted cost we show that the optimal policy for in house production can be characterized by a threshold and the production quantity is decreasing in the starting inventory the optimal outsourcing policy however is more complex and a threshold type policy is only optimal under a more restrictive assumption about the yields comparative statics about the effects of yield uncertainty outsourcing on the optimal policy and cost performance are discussed

base stock policies for production inventory problems with uncertain capacity levels abstract in this paper we consider a single item stochastic demand production inventory problem where the maximum amount that can be produced or ordered in any given period is assumed to be uncertain inventory levels are reviewed periodically the system operates under a stationary modified base stock policy the intent of our paper is to present a procedure for computing the optimal base stocl level of this policy under expected average cost per period criterion this procedure would provide guidance as to the appropriate amount of capacity to store in the form of inventory in the face of stochastic demand and uncertain capacity in achieving this goal our main contribution is to establish the analogy between the class of base stock production inventory policies that operate under demand capacity uncertainty and the g g 1 queues and their associated random walks we also present example derivations for some important capacity distributions

the risk of second tier supplier failures in serial supply chains implications for order policies and distributor autonomy abstract as organizations decrease inventory the potential impact of a supply disruption increases however due to supply chain structural changes the likelihood of a disruption may be less additionally independent supply chain actors may react to policy changes changing supply chain configurations and perhaps reducing loss magnitudes if risk is a product of likelihood and magnitude does higher inventory reduce an organization s supply related risk this paper examines the supply risk issue within the context of a second tier supply failure and is grounded in inventory and resource dependency theories by evaluating risk assessment in a simulation environment exploratory findings suggest that increased inventory in a tiered supply chain can sometimes increase supply risk rather than decrease it managerial insights into the effects of supply chain stability and coordination are provided by taking a systems perspective of supply risk management organizations will be better able to manage supply risk concerns

continuous review inventory models where random lead time depends on lot size and reserved capacity the processing time of large orders is in many industries longer than that of small orders this renders supply lead times in such settings to be increasing in the order size yet that pattern is not re ected in existing inventory control models especially those allowing for random lead times this work aims at rectifying the situation our setting is an order quantity reorder point model with backordering where the shortage penalty is incurred per unit per unit time the processing time of each unit is random the processing time of a lot is correlated with its size for the case where lead time is proportional to the lot size we obtain a closed form solution that is unlike the classical q r model where lead time is independent of lot size no iterations are required here we also analyze a case where the processing time exhibits economies of scale in the lot size finally we consider a situation where a customer can secure shorter processing times by reserving capacity at the supplier s manufacturing facility 2000 elsevier science b v all rights reserved

economic distribution of budget among producers for fulfilling orders under delivery chance constraints abstract at a common due date k orders with known quantities of the same product should be delivered the product can be manufactured by n producers with stochastic production capabilities random yields the expected capability and its standard deviation increase linearly with the allocated budget according to the pre given plant s capability cost trade off functions our problem is to minimize the total budget and to determine its distribution among the producers in order to ensure the complete fulfillment of all orders in accordance with their pre given confidence levels probabilities necessary and sufficient conditions for the existence of an optimal solution of the considered problem as well as the proof that if the problem has a feasible solution then the optimal solution is unique are provided we propose a method for evaluating the optimal solution and demonstrate it through a numerical example

a periodic review production planning model with uncertain capacity and uncertain demand optimality of extended myopic policies increasing product complexity manufacturing environment complexity and an increased emphasis on product quality are all factors leading to uncertainties in production processes these uncertainties are in the form of unplanned machine maintenance varying production yields and rework among others in planning for production an adequate model must incorporate these uncertainties into the representation of the production process this paper treats the aggregate planning problem for a single product with random demand and random capacity in the single period problem random capacity does not affect the optimal policy but results in a unimodal nonconvex cost function in the multiple period and infinite horizon settings order up to policies that are dependent on the distribution of capacity are shown to be optimal in spite of a nonconvex cost in the infinite horizon setting an intuitive description of the situation leads to the notion of a class of extended myopic policies requiring the consideration o

joint inventory replenishment and pricing control for systems with uncertain yield and demand we study the joint inventory replenishment and pricing problem for production systems with random demand and yield more specifically we analyze the following single item periodic review model demands in consecutive periods are independent random variables and their distributions are price sensitive the production yield is uncertain so that the quantity received from a replenishment is a random variable whose distribution depends on the production quantity stockouts are fully backlogged our problem is to characterize the optimal dynamic policy that simultaneously determines the production quantity and the price for each period to maximize the total discounted profit we show that the optimal replenishment policy is of a threshold type i e it is optimal to produce if and only if the starting inventory in a period is below a threshold value and that both the optimal production quantity and the optimal price in each period are decreasing in the starting inventory we further study the operational e

the structure of periodic review policies in the presence of random yield this work provides a comprehensive analysis of a general periodic review production inventory model with random variable yield existence of an order point whose value does not depend on yield being random is proved in the single period case without specifying the yield model and using a very general cost structure when yield is a random multiple of lot size the nonorder up to optimal policy is characterized for a finite horizon model the finite horizon value functions are shown to converge to the solution of an infinite horizon functional equation and the infinite horizon order point is shown to be no smaller than when yield is certain

agon and ag ec styles of persuasion in agricultural economics it is a tradition that these addresses be given by an outsider i speak as an outsider in praise of agricultural economics an outsider presuming to praise could be accused of condescension but i assure you i come by a favorable opinion of the field honestly i am practically an insider maternal relations own farms in illinois near watseka the same roger gray of the food research institute whom president elect johnston mentions in his paper is my second cousin once removed in england i have worked as an agricultural laborer once in vermont i milked a cow ag econ is in my blood

comparison of two periodic review models for stochastic and price sensitive demand environment abstract in this paper we study two periodic review inventory models which primarily differ in terms of how backordering cost is charged time independent backordering tib model where the backordering cost is charged per unit backordered and is independent of the length of time for which backorders persist and the time dependent backordering tdb model where the backordering cost is charged based on the number of backorders as well as the length of time for which they are on the books i e it is charged per unit per unit time our objective is to investigate the impact of these two different backordering cost structures on the optimal decisions of a firm in a stochastic and price sensitive demand environment in order to do so we first develop a general framework where both such costs exist in a profit maximizing context subsequently we analyze two special cases of this general framework with either one of the costs that is tib and tdb models and derive some analytical results regarding the values and behavior of the optimal decisions for both of them we then concentrate on comparing the two models through extensive numerical experiments our investigation demonstrates that the tib model generally results in longer review periods and lower retail prices as far as the base stock level is concerned we show that it can be higher in either setting however the safety stock is considerably lower for the tib model lastly indeed if a firm s backordering cost is indeed time dependent then use of the tib model for making decisions results in significant profit penalty under most market operating conditions specifically for innovative products except when demand uncertainty and or the backordering cost are quite low i e for mature commodity products

the optimality of myopic stocking policies for systems with decreasing purchasing prices abstract this paper studies the stocking replenishment decisions for inventory systems where the purchasing price of an item decreases overtime in a periodic review setting with stochastic demands we model the purchasing prices of successive periods as a stochastic and decreasing sequence to minimize the expected total discounted costs purchasing inventory holding and shortage penalty for systems with backlogging and lost sales we derive conditions regarding the cost parameters under which myopic stocking policies are optimal

optimal inventory policy with supply uncertainty and demand cancellation we consider a periodic review model where the firm manages its inventory under supply uncertainty and demand cancellation we show that because of supply uncertainty the optimal inventory policy has the structure of re order point type that is we order if the initial inventory falls below this re order point otherwise we do not order this is in contrast to the work of yuan and cheung 2003 who prove the optimality of an order up to policy in the absence of supply uncertainty we also investigate the impact of supply uncertainty and demand cancellation on the performance of the supply chain using our model we are able to quantify the importance of reducing the variance of either the distribution of yield or the distribution of demand cancellation the single multiple periods and the infinite horizon models are studied

ad revenue optimization in live broadcasting in live broadcasting the break lengths available for commercials are not always fixed and known in advance e g strategic and injury time outs are of variable duration in live sports transmissions broadcasters actively manage their advertising revenue by jointly optimizing sales and scheduling policies we characterize the optimal dynamic schedule in a simplified setting that incorporates stochastic break durations and advertisement lengths of 15 and 30 seconds the optimal policy is a greedy look ahead rule that accounts for the remaining number of breaks in this setting there is no value to perfect information at the scheduling stage and hence knowing the duration of all breaks would not change the schedule we present heuristics to help solve scheduling problems of even greater complexity the performance of these heuristics under various scenarios is tested by running simulations calibrated using industry data the simple greedy heuristic is shown to perform well except when revenues are con

cyclical correlations credit contagion and portfolio losses abstract we model aggregate credit losses on large portfolios of financial positions contracted with firms subject to both cyclical default correlation and direct default contagion processes cyclical correlation is due to the dependence of firms on common economic factors contagion is associated with the local interaction of firms with their business partners we provide an explicit normal approximation of the distribution of portfolio losses we quantify the relation between the variability of global economic fundamentals strength of local firm interaction and the fluctuation of losses we find that cyclical oscillations in fundamentals dominate average losses while local interaction causes additional fluctuations of losses around their average the strength of the contagion induced loss variability depends on the complexity of the business partner network

a periodic review lot sizing problem with random yields disruptions and inventory capacity this paper examines a periodic reviewed lot sizing problem with random yields disruptions and limited inventory capacity to characterise the continuous production an additive random yield model is considered rather than a multiplicative one disruptions cause breakdowns to production inventory capacity is included since the production has to be shut down when the inventory buffer is full both disruptions and shutdowns lead to a start up cost and a stochastic lead time to recover the production these compound factors of uncertainty are encountered in practical planning decisions in process industries we review the existing random yield models which are then compared with the additive model with a linear production cost the additive model has an order up to policy to be optimal disruptions deteriorate the expected actual production quantity and the fill rate dramatically even though the optimal order up to level increases compared with the cases of no disruption considering inventory capacity makes the problem to be a non convex dynamic programming problem numerical analysis shows that the performance is dramatically deteriorated when the inventory capacity is rather tight which indicates the importance of selecting a proper inventory capacity to reduce the negative impacts and avoid redundant investment on capacity moreover the start up cost plays an important role in determining the level of inventory capacity

inventory control with markovian capacity and the option of order rejection we consider a stochastic inventory control problem with markovian capacity and the option of order rejection we show its optimal policy to be the combination of a capacity dependent modified base stock production policy and a capacity dependent critical point order acceptance policy when capacity is stochastically monotone we show that the policy parameters change over the current capacity level in an intuitive way all these results can be extended to the infinite horizon case with or without cost discounting our computational study substantiates the benefits from both exploiting the markovian behavior of the capacity and rejecting orders when necessary

a non stationary periodic review production inventory model with uncertain production capacity and uncertain demand abstract in this paper we consider a nonstationary periodic review dynamic production inventory model with uncertain production capacity and uncertain demand the maximum production capacity varies stochastically it is known that order up to or base stock critical number policies are optimal for both finite horizon problems and infinite horizon problems we obtain upper and lower bounds of the optimal order up to levels and show that for an infinite horizon problem the upper and the lower bounds of the optimal order up to levels for the finite horizon counterparts converge as the planning horizons considered get longer furthermore under mild conditions the differences between the upper and the lower bounds converge exponentially to zero

the risk averse newsvendor problem with random capacity abstract we study the effect of capacity uncertainty on the inventory decisions of a risk averse newsvendor we consider two well known risk criteria namely value at risk var included as a constraint and conditional value at risk cvar for the risk neutral newsvendor we find that the optimal order quantity is not affected by the capacity uncertainty however this result does not hold for the risk averse newsvendor problem specifically we find that capacity uncertainty decreases the order quantity under the cvar criterion under the var constraint capacity uncertainty leads to an order decrease for low confidence levels but to an order increase for high confidence levels this implies that the risk criterion should be carefully selected as it has an important effect on inventory decisions this is shown for the newsvendor problem but is also likely to hold for other inventory control problems that future research can address

how much intraregional exchange rate variability could a currency union remove the case of asean 3 abstract a multilateral currency union removes intraregional exchange rates but not the union rate the pre union intraregional exchange rate variability is thus latent a two step procedure is developed to measure this the measured variables are used to model inflation and intraregional trade growth of individual union members counterfactual simulations of the union impact are carried out using the resulting models application to asean 3 shows that the intraregional variability mainly consists of short run exchange rate shocks that the variability significantly affects inflation and intraregional trade of major asean 3 members and that a union would reduce inflation and promote trade regionwide

a markov decision process model for equitable distribution of supplies under uncertainty abstract many individuals suffering from food insecurity obtain assistance from governmental programs and nonprofit agencies such as food banks much of the food distributed by food banks come from donations which are received from various sources in uncertain quantities at random points in time this paper presents a model that can assist food banks in distributing these uncertain supplies equitably and measure the performance of their distribution efforts we formulate this decision problem as a discrete time discrete state markov decision process that considers stochastic supply deterministic demand and an equity based objective we investigate three different allocation rules and describe the optimal policy as a function of available inventory we also provide county level estimates of unmet need and determine the probability distribution associated with the number of underserved counties a numerical study is performed to show how the allocation policy and unmet need are impacted by uncertain supply and deterministic time varying demand we also compare different allocation rules in terms of equity and effectiveness

benefits of leadtime information and of its combination with demand forecast information abstract this paper studies both the benefits of leadtime information and the interrelationships among demand forecast information leadtime uncertainty and leadtime information for improving inventory control performance to this end it explicitly incorporates both leadtime information and demand forecast information into an inventory model although they have conventionally been dealt with individually in the literature specifically it considers a periodic review inventory model with uncertain leadtimes in which both leadtime information and demand forecast information are available the leadtime information is modeled as the information of the arrival of outstanding orders and the demand forecast information as the martingale model of forecast evolution mmfe the paper analyzes the way to use both leadtime information and demand forecast information for inventory control operations specifically under certain conditions the optimality of the state dependent base stock policy is shown and an effective heuristic policy is developed it also derives some managerial insights for exploiting both leadtime information and demand forecast information in the case where leadtimes are uncertain for instance while leadtime information itself significantly improves inventory control performance it also enhances the benefits of demand forecast information specifically the benefits of demand forecast information may significantly decrease as leadtime uncertainty increases however the decrease of the benefits of demand forecast information may be alleviated with leadtime information

robust portfolio choice with learning in the framework of regret single period case in this paper we formulate a single period portfolio choice problem with parameter uncertainty in the framework of relative regret relative regret evaluates a portfolio by comparing its return to a family of benchmarks where the benchmarks are the wealths of fictitious investors who invest optimally given knowledge of the model parameters and is a natural objective when there is concern about parameter uncertainty or model ambiguity the optimal relative regret portfolio is the one that performs well in relation to all the benchmarks over the family of possible parameter values we analyze this problem using convex duality and show that it is equivalent to a bayesian problem where the lagrange multipliers play the role of the prior distribution and the learning model involves bayesian updating of these lagrange multipliers prior this bayesian problem is unusual in that the prior distribution is endogenously chosen by solving the dual optimization problem for the lagrange multipliers and the objective function involves the family of benchmarks from the relative regret problem these results show that regret is a natural means by which robust decision making and learning can be combined this paper was accepted by dimitris bertsimas optimization

analysis of an inventory system under supply uncertainty in this paper we analyze a periodic review single item inventory model under supply uncertainty the objective is to minimize expected holding and backorder costs over a finite planning horizon under the supply constraints the uncertainty in supply is modeled using a three point probability mass function the supply is either completely available partially available or the supply is unavailable machine breakdowns shortages in the capacity of the supplier strikes etc are possible causes of uncertainty in supply we demonstrate various properties of the expected cost function and show the optimality of order up to type policies using a stochastic dynamic programming formulation under the assumption of a bernoulli type supply process in which the supply is either completely available or unavailable and when the demand is deterministic and dynamic we provide a newsboy like formula which explicitly characterizes the optimal order up to levels an algorithm is given that computes the optimal inventory levels over the planning horizon extensions and computational analysis are presented for the case where the partial supply availability has positive probability of occurrence

optimality of myopic policies for dynamic lot sizing problems in serial production lines with random yields and autoregressive demand we study lot size policies in a serial multistage manufacturing inventory system with two key generalizations namely 1 random yields at each production stage and 2 an autoregressive demand process previous research shows that the optimal policies in models with random yields even in models with a single installation lack the familiar order up to structure and are not myopic thus dynamic programming algorithms are needed to compute optimal policies and one encounters the curse of dimensionality this is exacerbated here by the need to expand the size and dimension of the state space to accommodate the autoregressive demand feature nevertheless although our model is more complex we prove that there is an optimal policy with the order up to feature and more importantly that the optimal policy is myopic this avoids the computational burden of dynamic programming our results depend on two assumptions concerning the stochastic yield namely that the expected yield at a work station is proportional to the lot size and the distribution of the deviation of the yield from its mean does not depend on the lot size we introduce the concept of echelon like variables a generalization of clark and scarf s classical concept of echelon variables to derive the structure of optimal policies furthermore we show that the same kind of policy is optimal for several criteria infinite horizon discounted cost infinite horizon long run average cost and finite horizon discounted cost with the appropriate choice of the salvage value function

effects of constrained supply and price contracts on agricultural cooperatives planning strategies depend in part on the supply flow structure of a supply chain in food supply chains many firms are constrained by raw material supply e g vegetables and milk this paper first examines the economic consequences of constrained supply in agricultural cooperatives secondly it deals with the effects of adding price contracts to the current cooperative contract this model combines an inventory policy approach and a monte carlo simulation to take into account price uncertainty we illustrate our results using the case of a dairy cooperative c 2008 elsevier b v all rights reserved

optimal inventory decisions in a multiperiod newsvendor problem with partially observed markovian supply capacities abstract this paper considers a multi period news vendor problem with partially observed supply capacity information which evolves as a markovian process the supply capacity is fully observed by the buyer when the capacity is smaller than the buyer s ordering quantity otherwise the buyer knows that the current period supply capacity is greater than its ordering quantity based on these two observations the buyer updates the future supply capacity forecasting accordingly with a dynamic programming formulation we prove the existence of an optimal ordering policy we also prove that the optimal order quantity is greater than the myopic order quantity

environmental safety stock the impacts of regulatory and voluntary control policies on production planning inventory control and environmental performance abstract this paper analyzes the impacts of different pollution control policies on a firm s decisions of production planning and inventory control based on a stochastic model with both demand and environmental uncertainties we derive the optimal policies of production planning and inventory control under both regulatory and voluntary pollution control approaches and investigate their operational and environmental effects we establish that the conventional wisdom which suggests that reduction of environmental waste at the end of a production process also decreases the stock and throughput levels of a production system is not necessarily true rather a regulatory environmental standard that limits the total amount of waste may induce the firm to raise its planned stock level which would lead to a higher expected amount of environmental wastes before the standard is enforced as well as environmental risks at other stages of the production process the additional planned stock level which is termed environmental safety stock can be reversed by using the voluntary control approach that provides the firm with the flexibility to occasionally exceed the environmental standard we also conduct numerical experiments to analyze the effects of different values of model parameters under different control approaches the analytical results provide new insights to the impacts of a firm s production and inventory decisions on the natural environment as well as to the choices of pollution control approaches by decision makers in both the private and public sectors

the rate of return to public sector agricultural r d in the uk 1965 80 1989 the rate of return to public sector agricultural r d in the uk 1965 80 applied economics vol 21 no 8 pp 1063 1086

a production inventory system with markovian capacity and outsourcing option we study the optimal production inventory outsourcing policy for a firm with markovian in house production capacity that faces independent stochastic demand and has the option to outsource we find very simple optimal policy forms under fairly reasonable assumptions in addition when the capacity markov process is stochastically monotone the policy parameters decrease in the firm s current capacity level under additional assumptions all these results extend to the infinite horizon and undiscounted cost cases we analyze comparative statics and the necessity of some technical conditions and discuss when the outsourcing option is more valuable

tactical inventory and backorder decisions for systems with predictable production yield abstract we consider a manufacturing system with stochastic demand and predictable production yield the manufacturer has predetermined prices and limited production capacity in each period the manufacturer also has the option to save some inventory for future periods even if there is demand in the current period the demand that is not met is lost or may be backordered for only one period our objective is to maximize the expected profit by choosing optimal produce up to level y t save s t and backorder quantities b t in each period t we formulate this problem as a markov decision process where the state of the system is represented by the net inventory and the yield rate we show that a modified order up to policy y t s t b t is optimal in each period t we also perform computational analysis to examine the effects of production yield on the optimal decisions

inventory models with random yield in a random environment abstract we consider a single item inventory model which is observed periodically in a randomly changing environment all model parameters are specified by the state of the environment which is assumed to be a time homogeneous markov chain yield is random due to the random capacity of the vendor i e a given order is fully received if the order quantity is less than this capacity otherwise the quantity received is equal to the available capacity the problem is analyzed in single multiple and infinite periods and it is shown that in all cases the optimal policy is the well known base stock policy where the optimal order up to level depends on the state of the environment the results are compared with the solutions of the certain yield model when there is infinite capacity we show that the order up to levels are equal in the single period case however in multiple and infinite periods we order the same or more if the yield is random

does food safety information impact u s meat demand a theoretical model of consumer response to publicized food safety information on meat demand is developed with an empirical application to u s meat consumption evidence is found for the existence of pre committed levels of consumption seasonal factors time trends and contemporaneous own and cross commodity food safety concerns the average demand response to food safety concerns is small especially in comparison to price effects and to previous estimates of health related issues this small average effect masks periods of significantly larger responses corresponding with prominent food safety events but these larger impacts are short lived with no apparent food safety lagged effects on food safety concerns in the united states have dramatically increased in the past decade with regard to incidences of contaminated meat products concerns have arisen because contaminated meat products can result in serious risk to the well being and health of consumers contamination comes from a myriad of sources including but not limited to outbreaks of listeria monocytogenes escherichia coli e coli and salmonella centers for disease control and prevention food safety problems are not isolated to the united states as other unsafe contaminates in meats have emerged across the world including highly publicized outbreaks of bovine spongiform encephalopathy bse in europe the potential impacts of publicized food safety events on consumer s demand for meat products in the united states include own effects on the demand for the contaminated meat involved as well as cross effects impacting the demand for other meats the objective of this article is to investigate whether publicized food safety concerns surrounding beef pork and poultry chicken and turkey have impacted meat consumption food safety indices are constructed separately for beef pork and poultry

do prices respond asymmetrically to cost changes this article investigates price asymmetry by using an almost complete sample of taiwanese industries to see whether output prices respond faster to cost increases than they do to decreases in contrast with the earlier literature the evidence shows that positive price asymmetry cannot be applied to all industries especially those industries with rapid productivity growth the evidence also indicates that firms exhibiting fast slow productivity growth see their prices react less more to cost increases than to cost decreases

the power of bias in economics research we investigate two critical dimensions of the credibility of empirical economics research statistical power and bias we survey 159 empirical economics literatures that draw upon 64 076 estimates of economic parameters reported in more than 6 700 empirical studies half of the research areas have nearly 90 of their results under powered the median statistical power is 18 or less a simple weighted average of those reported results that are adequately powered power 80 reveals that nearly 80 of the reported effects in these empirical economics literatures are exaggerated typically by a factor of two and with one third inflated by a factor of four or more

common failings how corporate defaults are correlated we test the doubly stochastic assumption under which firms default times are correlated only as implied by the correlation of factors determining their default intensities using data on u s corporations from 1979 to 2004 this assumption is violated in the presence of contagion or frailty unobservable explanatory variables that are correlated across firms our tests do not depend on the time series properties of default intensities the data do not support the joint hypothesis of well specified default intensities and the doubly stochastic assumption we find some evidence of default clustering exceeding that implied by the doubly stochastic model with the given intensities why do corporate defaults cluster in time several explanations have been explored first firms may be exposed to common or correlated risk factors whose co movements cause correlated changes in conditional default probabilities second the event of default by one firm may be contagious in that one such event may directly induce other corporate failures as with the collapse of penn central railway in 1970 third learning from default may generate default correlation for example to the extent that the defaults of enron and worldcom revealed accounting irregularities that could be present in other firms they may have had a direct impact on the conditional default probabilities of other firms our primary objective is to examine whether cross firm default correlation that is associated with observable factors determining conditional default probabilities the first channel on its own is sufficient to account for the degree of time clustering in defaults that we find in the data

the domino effect of credit defaults test of asymmetric default correlations using realised default data using the research framework of a domino effect in firms we first make theoretical contributions by addressing several testable hypotheses regarding asymmetrical default correlations we then employ lucas s method to provide empirical evidence based on realised historical default data in the united states from 1992 to 2013 our empirical results are consistent with the following notions first default correlations increase with the time horizon second firms with low credit quality small size illiquidity and a high beta exhibit higher default correlations credit risk management without considering asymmetrical default correlations could underestimate portfolio risk due to default clustering

analysis of an inventory system under backorder correlated deterministic demand and geometric supply process abstract in this article we propose a single item periodic review model that investigates the effects of changes in the demand process that occur after stockout realizations we investigate a system where the demands in successive periods are deterministic but affected by the backorder realizations in order to capture the effects of changes in the demand process we use a geometric type supply availability we analytically derive the necessary components for obtaining profit related performance measures and provide computational analysis

reliability evaluation and adjustment of supply chain network design with demand fluctuations this study focuses on supply chain network design problems by considering economies of scale and demand fluctuations a reliability evaluation method is developed to evaluate the performance of plants under demand fluctuations in addition two mathematical programming models are developed to determine the optimal adjustment decisions regarding production reallocation among plants under different fluctuating demands the judgments to adjust or to do nothing are investigated by comparing the results if the adjustment is made or not made results show that making adjustments benefits the manufacturers by reducing total production cost and avoiding revenue loss which outweighs the extra costs especially for high value added products results also suggest that the manufacturer should ignore a short period abnormal state since the benefits to respond to it might not compensate the high allocation costs the results of this study provide a reference for the manufacturer in their decision making process of network planning with demand fluctuations when they have to cope with benefits and costs during abnormal states

coordinating inventory control and pricing strategies under batch ordering in this paper we investigate joint pricing and inventory control problems in a finite horizon single product periodic review setting with certain uncertain supply capacities the demands in different periods are random variables whose distributions depend on the posted price exhibiting the additive form the order quantity in each period is required to be of integral multiples of a given specific batch size denoted by q inventory replenishment incurs a linear ordering cost referred to as the cost rate function the sum of holding and backorder costs can either be convex or quasi convex the objective is to determine a joint ordering and pricing decision that can maximize the total expected profit over the planning horizon we first consider the case in which the cost rate function is convex and show that the modifiedr q list price policy is optimal for the system with certain and limited capacities a special case of which is the r q list price policy when capacities become unlimited as supply capacities become random the optimal policy follows a new structure wherein the optimal order up to level and posted price must be coordinated to make the optimal safety stock level follow the r q policy we further consider the case of a quasi convex cost rate function which may arise when a service level constraint is used as a surrogate for the shortage cost we demonstrate that the r q list price policy is optimal for the system without supply capacity constraints in addition extensions to several other models are discussed the enabling technique is based on the notion of q jump convexity and its variants

production control in the face of storable raw material random supply and an outside market we study a periodic review production inventory control problem where both the supply of raw material and demand for the finished product are exogenous and random the raw material can be stored for future use can be purchased from or sold to an outside market we study both the lost sales and backlogging cases under both strict convex and linear raw material purchasing selling costs convexity of the purchasing selling cost implies that the more the firm purchases from or sells to the outside market the more expensive or less valuable the raw material becomes for all cases we find the partial characterizations for the optimal policies which all turn out to be very intuitively appealing in particular for each of the linear cost cases the optimal policy degenerates into a combination of two base stock policies one for the raw material inventory and the other for the finished product inventory

the nature and causes of unemployment in the federal republic of germany since the seventies an empirical investigation the leading economic problem of our time is the high and persistent level of unemployment as of early 1985 there are no signs that the severity of unemployment will weaken within the near future this paper discusses first some basic developments of labour supply and labour demand in the federal republic of germany frg the composition of the labour supply and the structure of the labour demand for persons and hours worked as well as the dynamics of the unemployment pool the next section reviews very briefly some empirical findings explaining the rise in the nairu where we make the distinction between the no shock and the actual nairu following suggestions put by the organizers of the conference we then elaborate on the employment function in the empirically oriented literature most employment functions use labour services i e total hours worked as the dependent variable thus assuming homogeneity of labour demand with respect to jobs and working hours in the german political arena however the distinction between persons employed and hours worked is particularly important first it figures in the employment aims of labour unions who request reductions in weekly working hours in order to induce higher manning second the distinction arises in the context of overtime work for it has been suggested that the reduction in overtime to standard working hours could create more than 1 million new jobs in germany we present some estimated labour demand functions which take into account these two dimensions of labour demand jobs and hours and which are used to elaborate on the direction and magnitude of the employment effects of reductions in wage costs and increases in overtime premia

supply and demand uncertainty reduction efforts and cost comparison abstract in industries like health care consumer goods and agriculture shortages are widely observed and the consequences can be costly one of the main drivers of such shortages is the uncertain nature of supply and demand to reduce uncertainties sufficient information about supply and demand can be obtained by gathering relevant data e g auditing suppliers and conducting market research in this paper we conduct an analysis to examine the impacts of supply uncertainty demand uncertainty and uncertainty reduction efforts on production quantity and total cost we show that in the absence of uncertainty reduction efforts when the financial consequences of shortages are large or when the unit benefit is large supply uncertainty is more costly than demand uncertainty in addition exerting supply uncertainty reduction effort always causes the firm to produce fewer units than exerting demand uncertainty reduction effort although supply uncertainty reduction effort delivers a larger degree of improvement to total cost and hence is more efficient reduced supply uncertainty still leads to a higher system cost than does reduced demand uncertainty

the adjustment of the real interest rate to inflation this paper reports tests of carmichael and stebbing s 1983 inverted fisher hypothesis that it is the real rather than the nominal interest rate which adjusts to changes in the expected inflation rate unlike the earlier analysis the results presented here are based on a properly specified estimating equation derived from a short run open economy macro model the results support the inverted fisher hypothesis in the short run but indicate that there is some overshooting of the real interest rate so that after four quarters about 75 of the effect of an expected inflation change is reflected in real rates while the remainder leads to an increase in the nominal rate

optimal soft order revisions under demand and supply uncertainty and upstream information abstract demand patterns for products with short life cycles or seasonal demand do not follow a discernible pattern for individual sales events and seasons due to uncertainty associated with effectiveness of product promotions willingness of major retailers to carry product and their support competition and other unforeseen marketplace events factors these atypical demand patterns can be volatile and unsuitable for traditional demand forecasting in such cases buyers utilize market signals to regularly update demand forecasts under these settings sharing early soft order i e order forecast with the supplier reduces buyer s risk of supply shortages in this study we propose an optimal order revision policy for a buyer facing atypical demand and supply uncertainty for a single selling season based on a stochastic dynamic program we demonstrate the value of soft orders as well as supplier s inventory position information for the buyer we make several key contributions i we introduce a decision model for buyer to optimally revise soft orders under supply uncertainty with or without supplier s inventory position information under a deposit scheme ii we characterize the relationship between the optimal soft order and final firm order under demand forecasts and revisions demonstrating that optimal orders may be aggressive conservative or match the demand forecast iii we identify settings under which inventory position information of the supplier is beneficial to the buyer iv we offer a mechanism for identifying the minimum unit deposit cost that will lead to truthful soft orders from the buyer a detailed analysis explores the structure of the optimal ordering policies as well as the effect of cost parameters and sources of uncertainty on buyer performance

liquidity and the law of one price the case of the futures cash basis deviations from no arbitrage relations should be related to market liquidity because liquidity facilitates arbitrage at the same time a wide futures cash basis may trigger arbitrage trades and in turn affect liquidity we test these ideas by studying the dynamic relation between stock market liquidity and the index futures basis there is evidence of two way granger causality between the short term absolute basis and liquidity and liquidity granger causes longer term absolute bases shocks to the absolute basis predict future stock market liquidity the evidence suggests that liquidity enhances the efficiency of the futures cash pricing system copyright 2007 by the american finance association

what s in a p reassessing best practices for conducting and reporting hypothesis testing research social science research has recently been subject to considerable criticism regarding the validity and power of empirical tests published in leading journals and business scholarship is no exception transparency and replicability of empirical findings are essential to build a cumulative body of scholarly knowledge yet current practices are under increased scrutiny to achieve these objectives jibs is therefore discussing and revising its editorial practices to enhance the validity of empirical research in this editorial we reflect on best practices with respect to conducting reporting and discussing the results of quantitative hypothesis testing research and we develop guidelines for authors to enhance the rigor of their empirical work this will not only help readers to assess empirical evidence comprehensively but also enable subsequent research to build a cumulative body of empirical knowledge

counterparty risk and the pricing of defaultable securities motivated by recent financial crises in east asia and the united states where the downfall of a small number of firms had an economy wide impact this paper generalizes existing reduced form models to include default intensities dependent on the default of a counterparty in this model firms have correlated defaults due not only to an exposure to common risk factors but also to firm specific risks that are termed counterparty risks numerical examples illustrate the effect of counterparty risk on the pricing of defaultable bonds and credit derivatives such as default swaps it has been well documented in moody s reports on historical default rates of corporate bond issuers that the number of defaults the number of credit rating downgrades and credit spreads are all strongly correlated with the business cycle this has motivated reduced form models such as duffie and singleton 1999 and lando 1994 1998 which assume that the intensity of default is a stochastic process that derives its randomness from a set of state variables such as the short term interest rate this approach has the convenient features that conditioning on the state variables defaults become independent events and default correlation arises due to the common inf luence of these state variables on the other hand a default intensity that depends linearly on a set of smoothly varying macroeconomic variables is unlikely to account for the clustering of defaults around an economic recession this is evident from a casual inspection of the exhibits in the latest moody s report see keenan 2000 within the usual affine framework one can model the state variables as jump diffusions see duffie pan and single

periodic review production models with variable capacity random yield and uncertain demand we investigate a production planning problem in a periodic review environment with variable production capacity random yields and uncertain demand the implications of random yields and variable capacity for lot sizing previously have been explored separately but not jointly many production environments are likely to be subject to both types of uncertainties to minimize the total discounted expected costs production holding and shortage costs we formulate the problem as a stochastic dynamic program for the finite horizon problem we prove that the objective function is quasi convex and that the structure of the optimal policy is characterized by a single critical point for the initial stock level at each period that is if the initial stock is greater than this critical point the optimal planned production is zero otherwise it is greater than zero expressions for solving the critical point and the optimal planned production are obtained we further show that the solution for the finite horizon problem converges to that of the infinite horizon problem

dynamic replenishment production and pricing decisions in the face of supply disruption and random price sensitive demand abstract we study a joint decision problem for replenishment production pricing strategies in the face of both supply and demand uncertainties the supply of the raw material suffers from a potential supply disruption while the demand for the finished goods is price sensitive and random we assume that the raw material is storable and unfilled demands are fully backordered we characterize the optimal policies for raw material replenishment finished goods production and pricing we find that the optimal replenishment policy is an order up to type for a given finished goods stock level while it is a threshold type for a given raw material stock level for either a given finished goods stock level or a given raw material stock level the optimal production policy is a threshold type and the optimal pricing policy is a modified list price type respectively

optimal policies for inventory systems with finite capacity and partially observed markov modulated demand and supply processes we analyze a single item periodic review inventory system with random yield and finite capacity operating in a random environment the primary objective is to extend the model of gallego and hu 2004 to the more general case when the environment is only partially observable although our analysis is specific to inventory systems it can also be applied to production systems by replacing the fixed capacity supplier with a fixed capacity producer using sufficient statistics we consider single period multiple period and infinite period problems to show that a state dependent modified inflated base stock policy is optimal moreover we show that the multiple period cost converges to the infinite period cost as the length of the planning horizon increases

continuous review inventory control when capacity is variable abstract many complex production inventory systems are characterized by uncertain capacities due to unexpected breakdowns unplanned repairs etc we analyze the effects of variable capacity on optimal lot sizing in continuous review environments two models are considered the basic eoq model and the order quantity reorder point model with backlogging for both cases we obtain the optimality conditions for generally distributed variable capacity we then show that the optimal order quantities for both models and the optimal reorder point for the second one are greater than those without variable capacity when the variable capacity distribution is exponential we develop effective procedures for finding the optimal solutions

integrating dynamic pricing and replenishment decisions under supply capacity uncertainty this paper examines an integrated decision making process regarding pricing for uncertain demand and sourcing from uncertain supply which are often studied separately in the literature our analysis of the integrated system suggests that the base stock list price policy fails to achieve optimality even under deterministic demand instead the optimal policy is characterized by two critical values a reorder point and a target safety stock under this policy a positive order is issued if and only if the inventory level is below the reorder point when this happens the optimal order and price are coordinated to achieve a constant target safety stock which aims at hedging the demand uncertainty we further investigate the profit improvement obtained from deploying dynamic pricing as opposed to static pricing our results indicate that either supply limit or supply uncertainty may induce a significant benefit from dynamic pricing and the compound effect of supply limit and uncertainty can be much more pronounced than the individual effects whether or not the supply capacity is limited has a major implication on the value of dynamic pricing under unlimited supply dynamic pricing is more valuable when procurement cost is high or when demand is more sensitive to price with limited supply however the capacity restriction tends to be relaxed reducing the value of dynamic pricing

writing as a responsibility of science a reply to laband and taylor it must have been around 1968 in the coffee room of the social science building at chicago that milton friedman and the late george stigler had a jovial and public conversation about being economists that made a big impression on me milton was lamenting the stupidity of tariffs and george broke in from a foot above saying something as follows milton you re such a preacher if people want free trade they ll get it if they don t want it no amount of jawboning by economists will change their minds ah that s where we differ george we admire markets but you think they ve already worked and why not people are self interested and they vote their pocketbooks that s enough to make the market work they bought tariffs tariffs must be what they want no they pursue their interests but often do not know what their interests are people need education the average citizen has no idea that a tariff hurts him education try educating a lobbyist for the textile industry as i said that s where we differ i m a teacher and think that people do some things because they are ignorant and i m a scientist an economic scientist people do what they do because they are wise laband and taylor are stiglerites they believe with dr pangloss that we are in the best of all possible worlds the friedmanites which is my own tribe believe that we could be in it if we would only stop to think the stiglerites assume rationality the friedmanites teach it the stiglerites want to praise the world the friedmanites to change it the stiglerites detest policy what is is the friedmanites embrace it what might be can be the stiglerites are pessimistic in the manner of the master the friedmanites are optimistic laband and taylor the reader can see have a pessimistic and stiglerite explanation of why they have not learned to write competently they defend themselves against advice such as i give in the original paper by saying that it is presumptuous of anyone to claim unique knowledge of the marginal benefit to authors of investment in better presentation if the investment we were talking about was oil drilling i d agree with their economics i ve written a book called if you re so smart that makes a similar point about economic experts going around offering advice but the investment in question here is where laband and taylor go wrong is economic education laband taylor and i are economic educators in the educational industry we are the oil drillers the experts we educate our student roughnecks in the craft teaching them because we do know better or else we should not be standing up there tuth 10 50 12 10 part of the craft laband and taylor agree is attending to elements of presentation so the initial mistake in their paper is economic they think that because some advice is silly and misinformed all advice must be even advice from teachers to students stiglerites tend to drive themselves into such extreme skepticism but no one can actually live as an extreme skeptic i d like to see what laband and taylor say to a student who thinks that markets are bad for you do they agree mildly that it s just a matter of opinion another stigler story george opposed requirements in the graduate curriculum at chicago around 1970 he killed off the requirement in the history of thought which was his own field and tried repeatedly to kill off economic history he succeeded in 1980 when i left the faculty his argument which is heard in many other departments of economics was that the graduate students should be free to choose listen up milton after all they are just like consumers what george and laband and taylor never answered was the teacher s point which milton made in the discussions about the history of thought requirement we are teachers we do know better graduate students because they are not educated already that s why they are students often make bad decisions about their curricula

inventory management with random supply and imperfect information a hidden markov model in most of the papers on inventory models operating in a random environment the state of the environment in each period is assumed to be fully observed with perfect information however this assumption is not realistic in most real life situations and we provide a remedy in this paper by assuming that the environment is only partially observed with imperfect information we accomplish this by analyzing two formulations of single item models with periodic review and random supply in a random environment in the first one supply is random due to random capacity of production and random availability of transportation we show that state dependent base stock policy is optimal if the capacity and all costs are observed while demand and availability are unobserved in the second model we consider a model with random availability only with fixed ordering cost we show that state dependent s s policy is optimal if the availability process is observable