bunching in the production process abstract this paper demonstrates that the variance of flows within the production process declines as the products move downstream from raw material deliveries toward completion thus the production process magnifies and transmits shocks within an industry to that industry s suppliers

structural instability and the production smoothing model of inventories the production smoothing model of inventories implies that inventories labor inputs sales and factor input prices are cointegrated if sales and factor prices are i 1 with one cointegrating vector for each state variable held these propositions are tested in six nondurable goods industries all industries provide evidence of cointegration fewer quasi fixed factors are found than previous research often assumed estimates of cointegrating vectors provide implausible parameter estimates rank stability tests with fixed or seqentially chosen breakpoints indicate that the cointegrating matrix has unstable rank parameter estimates of cointegrating vectors do not provide much support for the production smoothing model of inventories

fixed costs of adjustment coordination and industry investment we test whether smooth industry level investment dynamics result from explicit aggregation of asynchronous and possibly lumpy firm level investment we compare the deviations of optimal from actual firm behavior across industries categorized by their ratios of idiosyncratic uncertainty to the sum of idiosyncratic and aggregate uncertainty the deviations are represented by the residuals of a cointegrating regression that is derived from the firm s first order condition under no adjustment costs in support of models with asynchronous firm decisions we find a significant negative relationship across industries between idiosyncratic uncertainty and the persistence of these residuals

measuring noise in inventory models this paper has two purposes one is to assess different models of inventory behavior in terms of their ability to approximate the realized data we do this initially for the pure production smoothing model and then for a sequence of generalizations our analysis both performs specification tests as well as measures the deviations of the data from each null model through use of a noise ratio statistic a second purpose is to explore whether observed cost shocks in particular raw materials prices help explain inventory movements we find that the production smoothing model of inventories augmented by buffer stock motives stockout avoidance motives and observed cost shocks well approximates monthly data

the long run implications of the production smoothing model of inventories an empirical test summary this paper provides an empirical test of the long run implications of the production smoothing model of inventories the dominant framework for inventory investment research in the past intertemporal models of a firm holding inventories of finished goods predict a long run relationship between inventories shipments factor input prices and the real interest rate which is tested here using cointegration test procedures these tests provide little support for the predictions of the production smoothing model in most of the data sets used test statistics indicate that inventories shipments factor input prices the nominal interest rate and the inflation rate maintain a long run equilibrium relationship but parameter estimates of cointegrating vectors are often implausible typically rejecting hypotheses implied by structural models of the production smoothing motive for holding inventories

inventories and interest rates a critique of the buffer stock model economists generally test for the effect of interest rates on inventories by including some measure of the real interest rate in a standard flexible accelerator buffer stock model this paper presentsseveral reasons for concluding that this approach is incorrect and demonstrates how interest rate effects can be introduced into decisionrules derived under the assumption of optimizing behavior by firms decision rules for finished good inventories output and price are estimated using monthly observations on the food and kindred product industry the results generally conform to the predictions of the theory copyright 1986 by american economic association

compositional change aggregation and dynamic factor demand estimates on a panel of manufacturing firms most empirical research on investment and dynamic factor demand has used aggregated data the large number of authors who have cited this as a source of problems strongly suggests possible benefits from analyzing individual firm data this paper presents an analysis of a panel dataset of us manufacturing firms several models based on cost minimization and a three factor cobb douglas technology are developed the differences concern whether the technology varies across two digit sic industries the presence of fixed adjustment lags and the determinants of adjustment costs identification relies on the rational expectations hypothesis and estimation on non linear 3sls the estimates indicate that versions with the adjustment lag perform better than others conditional elasticities reveal that factor demand responds rapidly to anticipated changes in output and factor prices a finding consistent with other recent work it appears that the factor demand of large firms is more price sensitive and less sensitive to output than small firms consistent with recent work on credit market imperfections comparison of the results based on the pooled and the industry varying technologies indicate that the use of aggregate data is indeed a source of problems

input and output inventories abstract this paper presents a new stage of fabrication inventory model with delivery usage and stocks of input materials that distinguishes between gross production and value added it extends the linear quadratic model of output inventories by adding the joint determination of input inventories empirically input inventories are more important than output inventories maximum likelihood estimation of the decision rules yields correctly signed and significant parameter estimates using data for nondurable and durable goods industries but the overidentifying restrictions of the model are rejected the value added specification dominates because adjustment costs on materials usage are critical to fitting the data

taking stock a critical assessment of recent research on inventories empirical and theoretical aspects of inventory behavior became hot topics in the 1950s and early 1960s no one seemed to notice the tension that was developing between the emerging macroeconomic and microeconomic views of inventories macroeconomists routinely thought of inventories as a destabilizing factor yet the prevailing micro theory viewed inventories as a stabilizing factor it was a fascinating question that was barely explored instead somewhat inexplicably interest in inventories dried up as if inventories were of minor economic significance and little intrinsic interest by the early 1980s then economists once again knew something they had known in the 1950s that inventory investment is of first order importance in business cycles but they were also beginning to realize that the standard production smoothing buffer stock model of inventories was in deep trouble this paper focuses on developments since that realization

a note on the econometric use of constant dollar inventory series abstract one dollar of finished goods inventories does not represent the same amount of physical goods as one dollar of sales when department of commerce constant dollar series are used this can cause seriously biased regression estimates

accounting for output fluctuations in manufacturing there is a substantial body of evidence to the effect that output is more volatile than sales among manufacturing industries numerous explanations have been advanced to account for this excess output volatility some examples are pro cyclical inventory movements induced by a stockout avoidance motive cost and technology shocks and decreasing marginal costs this article assesses the contribution of these different motives to output volatility for six different manufacturing industries linear quadratic models are estimated for each of the industries and then dynamic simulations are employed to determine the volatility of output when one or more of the factors are removed from the model technology shocks provide the most significant contribution to output volatility the stockout avoidance motive is also important cost shocks provide a very small contribution and marginal production costs are increasing at the margin and thus stabilize output it is also shown that output volatility declines when curre

production sales and the change in inventories an identity that doesn t add up we examine two measures of monthly manufacturing production the first is the index of industrial production the second is constructed from the accounting identity that output equals sales plus the change in inventories we show that the means variances and serial correlation coefficients of the log growth rates differ substantially between the two series and the cross correlations are in most cases less than 0 4 a model of classical measurement error indicates that in 15 of 20 two digit industries measurement error accounts for over 35 of the variation in the monthly growth rates of seasonally adjusted industrial production

the stabilizing effect of inventory in supply chains this paper presents a hierarchical model framework for the analysis of the stabilizing effect of inventories in multiechelon manufacturing distribution supply chains this framework is used to compare the variance of demand to the variance of replenishment orders at different echelons of the system e g retailer wholesaler empirical data and experience with management games suggest that in most industries inventory management policies can have a destabilizing effect by increasing the volatility of demand as it passes up through the chain the bullwhip effect our model helps to explain these observations and indicates mechanisms that can promote stabilization the analysis results also define sufficient conditions for the existence of stabilization and relate these conditions to the optimality of myopic control policies

do socially responsible fund managers really invest differently to date research into socially responsible investment sri and in particular the socially responsible investment funds industry has focused on whether investing in sri assets has any differential impact on investor returns prior findings generally suggest that on a risk adjusted basis there is no difference in performance between sri and conventional funds this result has led to questions about whether sri funds are really any different from conventional funds this paper examines whether the portfolio allocation across industry sectors and the stock picking ability of sri managers are different when compared to conventional fund managers the study finds that sri funds exhibit different industry betas consistent with different portfolio positions but that these differences vary from year to year it is also found that there is little difference in stock picking ability between the two groups of fund managers

nonconvex costs and the behavior of inventories this paper explores one possible explanation for the apparent excess volatility of production relative to sales nonconvexities in the technology facing firms it is shown that if firms operate in a region of declining marginal costs then small shifts in demand can cause production to jump substantially estimates for six production to stock industries as well as the automobile industry suggest that all these industries behave as if they were operating in the region of nonconvex costs the results have important implications not only for inventory investment but also for the cyclical behavior of productivity and prices

the resurgence of inventory research what have we learned abstract recent empirical and theoretical research on business inventories is surveyed and critically evaluated while most inventory research has had macroeconomic motivations we focus on its microtheoretic basis and on potential conflicts between theory and evidence the paper asks two principal questions first how can inventories which are allegedly used by firms to stabilize production nonetheless be a destabilizing factor at the macroeconomic level second why if firms are following the production smoothing model is production more variable than sales in many industries we suggest that the so called s s model may help answer both questions

industry evidence of enhanced production stability since 1984 abstract mcconnell and perez quiros have recently provided evidence that the growth rate of gdp has stabilized since 1984 they conclude that the enhanced stability can be attributed to improvements in inventory management in the durables sector this study examines the behavior of output in two digit sic manufacturing industries in an effort to determine whether this increase in stability is evident in less aggregated data after accounting for changes in demand volatility output stabilized in four of the six 2 digit durables industries modeled here total durables output stabilized by 9 these improvements appear to be the result of milder short run output responses to demand shocks this suggests that output has become less responsive to demand shocks and casts doubt on enhanced flexibility of production that should be characteristic of improved production management

inventories and sticky prices note in a recent contribution to this review alan blinder provides an interesting analysis of the relationship between optimal inventory decisions and the process of price adjustment arguing that inventory permits separation of production and sale decisions and allows the firm greater flexibility in responding to anticipated demand disturbances blinder shows that the responsiveness of relative prices depends critically upon the cost of storage and the temporal structure of the demand shocks few economists would fault the intuitive substance of blinder s basic proposition and the proposition is justified with characteristic precision the analysis however is considerably less general than blinder maintains the formal argument of his paper relies upon a simple model of a monopolist capable of backlogging orders and storing unsold goods as the model is constructed order backlogs assume a role of fundamental importance in any stationary equilibrium this feature of the model vitiates blinder s extension of his result to situations in which order backlogs are prohibited the basic monopoly model developed in sections i and ii of blinder s paper places no restriction upon the sign of inventory negative inventory is interpreted as net unfilled orders while no distinction is drawn between reductions in gross inventory and additions to the order backlog as a result the cost of holding inventory is symmetric around an arbitrary minimum point the only role of inventory is to permit the time paths of production and sales to differ gross inventory allows production to antedate sales while order backlogs generate revenue before production costs are borne under these circumstances if future costs and revenues are discounted it is natural to expect any stationary equilibrium level of net inventory to be negative this can be shown to be true of blinder s model it is useful to distinguish in general between the nonstochastic stationary level of inventory n and the stochastic stationary level n the former is realized when the current expected demand disturbance eo is zero and production equals sales the latter which differs from customary usage represents the level of inventory expected to prevail when adjustment to the current nonzero expected demand disturbance is complete if the demand disturbance is not a random walk so that p 1 in blinder s 5 the two equilibria coincide relatively little attention is devoted to either stationary solution because blinder s main interest is in the optimal current solution level n1 the stochastic stationary level is crucially important however since it represents the goal toward which the current choice must provide an optimal first step to verify that both nand n are negative whenever production is strictly positive note that blinder s necessary condition 7 with the coefficient cl set equal to zero together with the definition of xa as the deviation of the shadow value of inventory q from its nonstochastic stationary value q implies

has production management improved since 1984 kim and nelson 1999 and others have recently presented evidence of a dramatic decline in the volatility of real gross domestic product gdp when the data are plotted the break date is easily identified as 1984 kim and nelson conclude that the enhanced stability is broadly based but statistical analysis by mcconnell and perez quiros 2000 hereafter mpq points to reductions in inventory volatility in the durables sector as the source of the newfound stability although inventory investment is a very small component of gdp changes in inventory investment are one of the most volatile components of changes in gdp ramey and west 1999 calculate that declines in inventory investment typically account for 49 of reductions in u s gdp during recessions inventories in the durables sector are substantially more volatile than in the nondurables sector and thus inventory investment in this sector is more likely to contribute to macroeconomic instability the 1984 break date is intriguing because it coincides with the rising popularity of new production management techniques such as just in time jit 1 hall 1983 describes jit as an emphasis on producing exactly what is needed and conveying it to where it is needed precisely when required he cites several components to the successful implementation of jit but one of the major components is flexible production implying rapid response and the ability to profitably produce only what is immediately required in this ideal environment no unfilled orders or finished goods are accumulated and whatever raw materials and work in process must be accumulated are quickly processed more generally the more flexible and well coordinated the production process the more quickly output can respond to a demand shock 2 the questions addressed here are as follows 1 is there evidence of structural change in output 2 did the structural change if any occur around 1984 3 did output track demand more closely following the structural change the answers to all three questions must be yes to support the contention that improved production management is responsible for the stabilization of gdp the analysis is carried out at the industry level to identify those industries that satisfy the criteria the quality of production management is measured as the difference between the log of output and the log of new orders both measured monthly new orders represent demand and are equivalent to sales among firms that hold no unfilled orders if the firm achieves the ideal efficiency then output is identical to demand more generally efficiency is reflected in the time required for the firm to return inventories and unfilled orders to their target values following a shock to demand or output an increase in efficiency implies a more rapid output response to demand shocks so that any differences between output and demand are resolved more rapidly structural change is identified with tests for structural change with unknown break dates developed by andrews 1993 and andrews and ploberger 1994 following herrera and pesavento s 2004 industry level analysis the tests allow for multiple breaks their tests for stability are conducted on univariate autoregressive models of sales and inventories by stages of fabrication here the growth rate of output or the difference between the log of output and the log of new orders is the dependent variable allowing for a direct observation of structural change in the variable of interest in addition the models are richer in that variables such as new orders and raw materials are included on the right hand side to determine the sensitivity of the break date to potential sources of any change in output behavior several studies in addition to herrera and pesavento s 2004 have examined industry level data for evidence of structural change that might indicate improvements in production management

does it really hurt to be responsible prior literature on socially responsible investment has contended that excluding sin stocks from a portfolio negative screening will reduce performance and increase risk further incorporating stocks of firms with positive social responsibility scores positive screening will improve performance and reduce risk we simulate portfolios designed to mimic typical equity mutual funds holdings and investigate these propositions we remove the potentially confounding influences of differences in manager skill transaction costs and fees and conduct a clean experiment on the effect of positive and negative portfolio screening we find no difference in the return or risk of screened and unscreened portfolios we conclude that a typical socially responsible fund will neither gain nor lose from screening its portfolio

gauging the performance of the linear quadratic inventory model the explanatory and predictive abilities of the infinite horizon linear quadratic inventory model are gauged using the flexible accelerator model as a baseline tests of explanatory power for six nondurables industries indicate that the flexible accelerator has superior explanatory power for inventories and output in the majority of industries tests of predictive ability during the late 1990s also support the superiority of the flexible accelerator model

production smoothing evidence from physical product data we reconsider the paradox that the variance of production often exceeds the variance of shipments a result that casts doubt on the production smoothing model of inventory behavior most studies of production smoothing have analyzed two digit sic dollar value data from commerce department surveys in contrast this paper examines disaggregated physical product data and finds that production is smoother than shipments in about two thirds of the 38 industry or product groupings considered however doubts about the model persist most notably euler equation estimates of the model s cost parameters are usually imprecise and often do not have the signs postulated by production smoothing models

the behavior of manufacturers inventories evidence from us industry level data abstract recent empirical research on inventory behavior makes extensive use of disaggregated data both from the 20 two digit manufacturing industries identified in the standard industrial classification sic system and physical product data from lower levels of aggregation economists have traditionally grouped these industries by durability of final product or by the presence or absence of unfilled orders for comparison recent research by mattey and strongin economic review federal reserve bank of san francisco 2 1997 3 17 suggests that production technology affects the flow of material through the production process and the use of labor and capital in manufacturing a review of the empirical inventory literature reveals patterns that can be explained by differences in production technology in studies that use both two digit industry data and disaggregated physical product data from four and five digit industries thus there may be more heterogeneity in disaggregated inventory data than was previously thought

estimating the linear quadratic inventory model maximum likelihood versus generalized method of moments abstract we compare generalized method of moments gmm and maximum likelihood ml estimators of the parameters of a linear quadratic inventory model using nondurable manufacturing data and monte carlo simulations data based gmm estimates for five normalizations vary widely generally rejecting the model the ml estimate generally supports the model monte carlo experiments reveal that the gmm estimates are often biased apparently due to poor instruments statistically insignificant economically implausible and dynamically unstable the ml estimates are generally unbiased even in misspecified models statistically significant economically plausible and dynamically stable asymptotic standard errors for ml are 3 to 15 times smaller than for gmm

why good firms do bad things the effects of high aspirations high expectations and prominence on the incidence of corporate illegality recent high profile corporate scandals involving prominent high performing firms cast doubt on assertions that the costs of getting caught decrease the likelihood such high performers will act illegally we explain this paradox by using theories of loss aversion and hubris to examine a sample of s p 500 manufacturers results demonstrate that both performance above internal aspirations and performance above external expectations increase the likelihood of illegal activities the sample firms prominence enhanced the effects of performance above expectations on the likelihood of illegal actions prominent and less prominent firms displayed different patterns of behavior when their performance failed to meet aspirations

nominal data and the production smoothing hypothesis abstract this paper shows that when price variations are not properly purged from the data the estimated ratios of production variances to sales variances are likely to be biased upward leading to more frequent rejections of the production smoothing hypothesis the results point to the importance of removing price variations from the data before testing the hypothesis