BlueLinx can benefit from innovative inventory management methods for commodity forward buys

Commodity prices often fluctuate significantly from one purchasing opportunity to the next. These fluctuations allow firms to benefit from forward buying (buying for future demand in addition to current demand) when prices are low. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. We compare our heuristic with existing methods via simulation using real demand data from BlueLinx, a two-stage distributor of building products. The results show that our combined heuristic performs better than any existing methods considering forward buying or safety stock separately. We also compare our heuristic to the optimal inventory management policy by full enumeration for a smaller data set. The proposed heuristic is shown to be close to optimal. This study is the first to decide both the optimal number of future periods to buy for uncertain purchase price and the appropriate purchasing quantity with safety stock for uncertain demand simultaneously. The experience suggests that the proposed combined heuristic is simple and can be very beneficial for any company where forward buying is possible.     

UK macroeconomic volatility: Historical evidence over seven centuries

Breaking ground from all previous studies, we estimate a time-varying Vector Autoregression model that examines the time-period 1270–2016 — the entire economic history of the U.K. Focusing on permanent and transitory shocks in the economy, we study the fluctuation in conditional volatilities and time-varying long-run responses of output growth and inflation. Unlike all previous studies that use time invariant linear models, our approach reveals that the pre 1600 period is a turbulent economic period of high volatility that is only repeated in the 20th century. The repeating patterns in the conditional volatilities follow from aggregate supply shocks, while most of the inflation responses follow from aggregate demand shocks. Thus, we uncover that despite the technological growth and the various changes in the structure of the U.K. economy in the last century, the recurring patterns call for an examination of the true impact of the various policies on the economy.     

Ambiguity framed

In his exposition of subjective expected utility theory, Savage (1954) proposed that the Allais paradox could be reduced if it were recast into a format which made the appeal of the independence axiom of expected utility theory more transparent. Recent studies consistently find support for this prediction. We consider a salience-based choice model which explains this frame-dependence of the Allais paradox. We then derive the novel prediction that the presentation format responsible for reductions in Allais-style violations of expected utility theory will also reduce Ellsberg-style violations of subjective expected utility theory. This format makes the appeal of Savage’s “sure thing principle” more transparent. We design an experiment to test this prediction and find strong support for such frame-dependence of ambiguity aversion in Ellsberg-style choices. In particular, we observe markedly less ambiguity-averse behavior in Savage’s matrix format than in a more standard “prospect” format. This finding poses a new challenge for the leading models of ambiguity aversion.     

Sculpted landscapes: art & place in Cleveland's Cultural Gardens, 1916-2006

Perhaps the world's first peace garden, the Cleveland Cultural Gardens embody the history of twentieth-century America and reveal the complex interrelations between art and place. This essay uses the Cleveland Cultural Gardens as a lens through which to explore how art and place have intersected over time. It explores how communities have negotiated questions of national, ethnic, and American identity and embedded those identities into the vernacular landscape. It considers how the particulars of place were embedded into a public garden and asks whether it is possible for public art to transcend its place—both in terms of geography and history. In some sense, the Gardens have transcended their place, but in others respects, their fortunes were bound inextricably to that place, to the economic, demographic, and cultural contours that shaped and reshaped Northern Ohio. As works of art, the Cleveland Cultural Gardens both have reflected the history of Cleveland and American industrial cities during the 20th century and revealed something of the dynamics that underscored the changing character of public art and gardens in American cities.     

Ambiguity,pessimism, and rational religious choice

Using a subclass of the α-maximin expected-utility preference model, in which the decision maker’s degree of ambiguity and degree of pessimism are each parameterized, we present a theory of religious choice in the Pascalian decision theory tradition, one that can resolve dilemmas, address the “many Gods objection,” and address the ambiguity inherent in religious choice. Parameterizing both the degree of ambiguity and the degree of pessimism allows one to examine how the two interact to impact choice, which is useful regardless of the application. Applying this model to religious choice is a move beyond subjective expected-utility theory, allowing us to show that a change in either the degree of ambiguity or the degree of pessimism can lead a decision maker to “convert” from one religion to another.     

Visualizing uncertainty in reliability functions with application to aero engine overhaul

Summary.  We propose an approach for estimating the date of lost confidence of jet engines, which are devices with multiple components subject to disruption. A mixed Weibull distribution is estimated from a large data set subject to censoring at various times. Parametric uncertainty is derived analytically and mapped visually onto the functions of use in reliability theory, including the hazard function. We demonstrate the use of the method on a database of disruption times for components in 325 jet engines.     

CAUSAL GRAPHICAL MODELS IN SYSTEMS GENETICS: A UNIFIED FRAMEWORK FOR JOINT INFERENCE OF CAUSAL NETWORK AND GENETIC ARCHITECTURE FOR CORRELATED PHENOTYPES

Causal inference approaches in systems genetics exploit quantitative trait loci (QTL) genotypes to infer causal relationships among phenotypes. The genetic architecture of each phenotype may be complex, and poorly estimated genetic architectures may compromise the inference of causal relationships among phenotypes. Existing methods assume QTLs are known or inferred without regard to the phenotype network structure. In this paper we develop a QTL-driven phenotype network method (QTLnet) to jointly infer a causal phenotype network and associated genetic architecture for sets of correlated phenotypes. Randomization of alleles during meiosis and the unidirectional influence of genotype on phenotype allow the inference of QTLs causal to phenotypes. Causal relationships among phenotypes can be inferred using these QTL nodes, enabling us to distinguish among phenotype networks that would otherwise be distribution equivalent. We jointly model phenotypes and QTLs using homogeneous conditional Gaussian regression models, and we derive a graphical criterion for distribution equivalence. We validate the QTLnet approach in a simulation study. Finally, we illustrate with simulated data and a real example how QTLnet can be used to infer both direct and indirect effects of QTLs and phenotypes that co-map to a genomic region.     

The Significance of Education for Mortality Compression in the United States

Recent studies of old-age mortality trends assess whether longevity improvements over time are linked to increasing compression of mortality at advanced ages. The historical backdrop of these studies is the long-term improvement in a population's socioeconomic resources that fueled longevity gains. We extend this line of inquiry by examining whether socioeconomic differences in longevity within a population are accompanied by old-age mortality compression. Specifically, we document educational differences in longevity and mortality compression for older men and women in the United States. Drawing on the fundamental cause of disease framework, we hypothesize that both longevity and compression increase with higher levels of education and that women with the highest levels of education will exhibit the greatest degree of longevity and compression. Results based on the Health and Retirement Study and the National Health Interview Survey Linked Mortality File confirm a strong educational gradient in both longevity and mortality compression. We also find that mortality is more compressed within educational groups among women than men. The results suggest that educational attainment in the United States maximizes life chances by delaying the biological aging process.