Developing Typologies of City-Regional Growth

The economic performance of city-regions is closely linked to the performance of the national economy. However, the performance of the national economy can also depend on the performance of one or more major city-regions, that act as growth poles. Because of their sectoral structure and other characteristics, some cities are better equipped to become growth poles than others. This paper studies 46 major city-regions across Europe. The sectoral structure and changes in the sectoral structure of city-regions are studied using data from CE’s European Regional Database, itself based on Eurostat’s Regio database. The data analysis attempts to explain city-region performance by drawing parallels between sectoral structure and economic performance. The data analysis is supplemented by local anecdotal evidence provided by CE’s annual European reporting system ‘European Regional Prospects’, for example the historical importance of river and seafront activities. The paper goes on to discuss the extent to which the sectoral structure of cities can explain why some city-regions grow faster than others. The data analysis will be used to group cities in ‘hard’ typologies according to sectoral specialisation. These sectoral typologies are then compared with typologies according to the local, ‘softer’, evidence provided by CE’s regional consultants. This evidence will also be used to draw out the more subtle influences on city-region growth and these will be used to group cities in ‘soft’ typologies.

ACE Bounds; SEMs with Equilibrium Conditions

Discussion of "Instrumental Variables: An Econometrician's Perspective" by Guido W. Imbens [arXiv:1410.0163].Comment: Published in at http://dx.doi.org/10.1214/14-STS485 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Congenial Causal Inference with Binary Structural Nested Mean Models

Structural nested mean models (SNMMs) are among the fundamental tools for inferring causal effects of time-dependent exposures from longitudinal studies. With binary outcomes, however, current methods for estimating multiplicative and additive SNMM parameters suffer from variation dependence between the causal SNMM parameters and the non-causal nuisance parameters. Estimating methods for logistic SNMMs do not suffer from this dependence. Unfortunately, in contrast with the multiplicative and additive models, unbiased estimation of the causal parameters of a logistic SNMM rely on additional modeling assumptions even when the treatment probabilities are known. These difficulties have hindered the uptake of SNMMs in epidemiological practice, where binary outcomes are common. We solve the variation dependence problem for the binary multiplicative SNMM by a reparametrization of the non-causal nuisance parameters. Our novel nuisance parameters are variation independent of the causal parameters, and hence allows the fitting of a multiplicative SNMM by unconstrained maximum likelihood. It also allows one to construct true (i.e. congenial) doubly robust estimators of the causal parameters. Along the way, we prove that an additive SNMM with binary outcomes does not admit a variation independent parametrization, thus explaining why we restrict ourselves to the multiplicative SNMM

Nested Markov Properties for Acyclic Directed Mixed Graphs

Directed acyclic graph (DAG) models may be characterized in at least four different ways: via a factorization, the d-separation criterion, the moralization criterion, and the local Markov property. As pointed out by Robins (1986, 1999), Verma and Pearl (1990), and Tian and Pearl (2002b), marginals of DAG models also imply equality constraints that are not conditional independences. The well-known `Verma constraint' is an example. Constraints of this type were used for testing edges (Shpitser et al., 2009), and an efficient marginalization scheme via variable elimination (Shpitser et al., 2011). We show that equality constraints like the `Verma constraint' can be viewed as conditional independences in kernel objects obtained from joint distributions via a fixing operation that generalizes conditioning and marginalization. We use these constraints to define, via Markov properties and a factorization, a graphical model associated with acyclic directed mixed graphs (ADMGs). We show that marginal distributions of DAG models lie in this model, prove that a characterization of these constraints given in (Tian and Pearl, 2002b) gives an alternative definition of the model, and finally show that the fixing operation we used to define the model can be used to give a particularly simple characterization of identifiable causal effects in hidden variable graphical causal models.Comment: 67 pages (not including appendix and references), 8 figure

Developing Typologies of City-Regional Growth

The economic performance of city-regions is closely linked to the performance of the national economy. However, the performance of the national economy can also depend on the performance of one or more major city-regions, that act as growth poles. Because of their sectoral structure and other characteristics, some cities are better equipped to become growth poles than others. This paper studies 46 major city-regions across Europe. The sectoral structure and changes in the sectoral structure of city-regions are studied using data from CE's European Regional Database, itself based on Eurostat's Regio database. The data analysis attempts to explain city-region performance by drawing parallels between sectoral structure and economic performance. The data analysis is supplemented by local anecdotal evidence provided by CE's annual European reporting system 'European Regional Prospects', for example the historical importance of river and seafront activities. The paper goes on to discuss the extent to which the sectoral structure of cities can explain why some city-regions grow faster than others. The data analysis will be used to group cities in 'hard' typologies according to sectoral specialisation. These sectoral typologies are then compared with typologies according to the local, 'softer', evidence provided by CE's regional consultants. This evidence will also be used to draw out the more subtle influences on city-region growth and these will be used to group cities in 'soft' typologies

Adiposity, Cardiometabolic Risk, and Vitamin D Status: The Framingham Heart Study

OBJECTIVE: Because vitamin D deficiency is associated with a variety of chronic diseases, understanding the characteristics that promote vitamin D deficiency in otherwise healthy adults could have important clinical implications. Few studies relating vitamin D deficiency to obesity have included direct measures of adiposity. Furthermore, the degree to which vitamin D is associated with metabolic traits after adjusting for adiposity measures is unclear. RESEARCH DESIGN AND METHODS: We investigated the relations of serum 25-hydroxyvitamin D (25[OH]D) concentrations with indexes of cardiometabolic risk in 3,890 nondiabetic individuals; 1,882 had subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) volumes measured by multidetector computed tomography (CT). RESULTS: In multivariable-adjusted regression models, 25(OH)D was inversely associated with winter season, waist circumference, and serum insulin (P < 0.005 for all). In models further adjusted for CT measures, 25(OH)D was inversely related to SAT (−1.1 ng/ml per SD increment in SAT, P = 0.016) and VAT (−2.3 ng/ml per SD, P < 0.0001). The association of 25(OH)D with insulin resistance measures became nonsignificant after adjustment for VAT. Higher adiposity volumes were correlated with lower 25(OH)D across different categories of BMI, including in lean individuals (BMI <25 kg/m2). The prevalence of vitamin D deficiency (25[OH]D <20 ng/ml) was threefold higher in those with high SAT and high VAT than in those with low SAT and low VAT (P < 0.0001). CONCLUSIONS: Vitamin D status is strongly associated with variation in subcutaneous and especially visceral adiposity. The mechanisms by which adiposity promotes vitamin D deficiency warrant further study.National Institutes of Health's National Heart, Lung, and Blood Institute (N01-HC-25195, R01-DK-80739): American Heart Associatio

A Statistical Social Network Model for Consumption Data in Food Webs

We adapt existing statistical modeling techniques for social networks to study consumption data observed in trophic food webs. These data describe the feeding volume (non-negative) among organisms grouped into nodes, called trophic species, that form the food web. Model complexity arises due to the extensive amount of zeros in the data, as each node in the web is predator/prey to only a small number of other trophic species. Many of the zeros are regarded as structural (non-random) in the context of feeding behavior. The presence of basal prey and top predator nodes (those who never consume and those who are never consumed, with probability 1) creates additional complexity to the statistical modeling. We develop a special statistical social network model to account for such network features. The model is applied to two empirical food webs; focus is on the web for which the population size of seals is of concern to various commercial fisheries.Comment: On 2013-09-05, a revised version entitled "A Statistical Social Network Model for Consumption Data in Trophic Food Webs" was accepted for publication in the upcoming Special Issue "Statistical Methods for Ecology" in the journal Statistical Methodolog

Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes

Several methods have been proposed for partially or point identifying the average treatment effect (ATE) using instrumental variable (IV) type assumptions. The descriptions of these methods are widespread across the statistical, economic, epidemiologic, and computer science literature, and the connections between the methods have not been readily apparent. In the setting of a binary instrument, treatment, and outcome, we review proposed methods for partial and point identification of the ATE under IV assumptions, express the identification results in a common notation and terminology, and propose a taxonomy that is based on sets of identifying assumptions. We further demonstrate and provide software for the application of these methods to estimate bounds. Supplementary materials for this article are available online