Diabetes mellitus and cancer risk in a network of case-control studies.

Diabetes has been associated to the risk of a few cancer sites, though quantification of this association in various populations remains open to discussion. We analyzed the relation between diabetes and the risk of various cancers in an integrated series of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1,468 oral and pharyngeal, 505 esophageal, 230 gastric, 2,390 colorectal, 185 liver, 326 pancreatic, 852 laryngeal, 3,034 breast, 607 endometrial, 1,031 ovarian, 1,294 prostate, and 767 renal cell cancer cases and 12,060 hospital controls. The multivariate odds ratios (OR) for subjects with diabetes as compared to those without-adjusted for major identified confounding factors for the cancers considered through logistic regression models-were significantly elevated for cancers of the oral cavity/pharynx (OR = 1.58), esophagus (OR = 2.52), colorectum (OR = 1.23), liver (OR = 3.52), pancreas (OR = 3.32), postmenopausal breast (OR = 1.76), and endometrium (OR = 1.70). For cancers of the oral cavity, esophagus, colorectum, liver, and postmenopausal breast, the excess risk persisted over 10 yr since diagnosis of diabetes. Our data confirm and further quantify the association of diabetes with colorectal, liver, pancreatic, postmenopausal breast, and endometrial cancer and suggest forthe first time that diabetes may also increase the risk of oral/pharyngeal and esophageal cancer. [Table: see text] [Table: see text].

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

The network origins of aggregate fluctuations

This paper argues that in the presence of intersectoral input-output linkages, microeconomicidiosyncratic shocks may lead to aggregate fluctuations. In particular, itshows that, as the economy becomes more disaggregated, the rate at which aggregatevolatility decays is determined by the structure of the network capturing such linkages.Our main results provide a characterization of this relationship in terms of the importanceof different sectors as suppliers to their immediate customers as well as theirrole as indirect suppliers to chains of downstream sectors. Such higher-order interconnectionscapture the possibility of "cascade effects" whereby productivity shocks to asector propagate not only to its immediate downstream customers, but also indirectlyto the rest of the economy. Our results highlight that sizable aggregate volatility isobtained from sectoral idiosyncratic shocks only if there exists significant asymmetryin the roles that sectors play as suppliers to others, and that the "sparseness" of theinput-output matrix is unrelated to the nature of aggregate fluctuations.

Iowa Sales and Use Tax Annual Statistical Report 1998

Iowa Sales and Use Tax Annual Statistical Report 1998

Iowa Sales and Use Tax Annual Statistical Report 1999

Iowa Sales and Use Tax Annual Statistical Report 1999

Iowa Sales and Use Tax Annual Statistical Report 2000

Iowa Sales and Use Tax Annual Statistical Report 2000

Iowa Sales and Use Tax Annual Statistical Report 2001

Iowa Sales and Use Tax Annual Statistical Report 2001

Iowa Sales and Use Tax Annual Statistical Report 2002

Iowa Sales and Use Tax Annual Statistical Report 2002

Iowa Sales and Use Tax Annual Statistical Report 2003

Iowa Sales and Use Tax Annual Statistical Report 2003

Iowa Sales and Use Tax Annual Statistical Report 2004

Iowa Sales and Use Tax Annual Statistical Report 2004

Iowa Sales and Use Tax Annual Statistical Report 2005

Iowa Sales and Use Tax Annual Statistical Report 2005

Iowa Sales and Use Tax Annual Statistical Report 2006

Iowa Sales and Use Tax Annual Statistical Report 2006

Iowa Sales and Use Tax Annual Statistical Report 2007

Iowa Sales and Use Tax Annual Statistical Report 2007

Aggregate fluctuations and the network structure of intersectoral trade

This paper analyzes the flow of intermediate inputs across sectors by adopting a network perspective on sectoral interactions. I apply these tools to show how fluctuationsin aggregate economic activity can be obtained from independent shocks to individualsectors. First, I characterize the network structure of input trade in the U.S. On thedemand side, a typical sector relies on a small number of key inputs and sectors arehomogeneous in this respect. However, in their role as input-suppliers sectors do differ:many specialized input suppliers coexist alongside general purpose sectors functioningas hubs to the economy. I then develop a model of intersectoral linkages that can reproduce these connectivity features. In a standard multisector setup, I use this modelto provide analytical expressions linking aggregate volatility to the network structureof input trade. I show that the presence of sectoral hubs - by coupling productiondecisions across sectors - leads to fluctuations in aggregates.