Evolutionary agglomeration theory: increasing returns, diminishing returns, and the industry life cycle

According to Marshall’s agglomeration theory, Krugman’s New Economic Geography models, and Porter’s cluster policies, firms should receive increasing returns from a trinity of agglomeration economies: a local pool of skilled labour, local supplier linkages, and local knowledge spillovers. Recent evolutionary theories suggest that whether agglomeration economies generate increasing returns or diminishing returns depends on time, and especially the evolution of the industry life cycle. At the start of the twenty-first century, we re-examine Marshall’s trinity of agglomeration economies in the city-region where he discovered them. The econometric results from our multivariate regression models are the polar opposite of Marshall’s. During the later stages of the industry life cycle, Marshall’s agglomeration economies decrease the economic performance of firms and create widespread diminishing returns for the economic development of the city-region, which has evolved to become one of the poorest city-regions in Europe.

School-related predictors of smoking, drinking and drug use: Evidence from the Belfast Youth Development Study

Objective

To examine whether students’ school engagement, relationships with teachers, educational aspirations and involvement in fights at school are associated with various measures of subsequent substance use.
Methods

Data were drawn from the Belfast Youth Development Study (n = 2968). Multivariate logistic models examined associations between school-related factors (age 13/14) and substance use (age 15/16).
Results

The two factors which were consistently and independently associated with regular substance use among both males and females were student–teacher relationships and fighting at school: positive teacher-relationships reduced the risk of daily smoking by 48%, weekly drunkenness by 25%, and weekly cannabis use by 52%; being in a fight increased the risk of daily smoking by 54%, weekly drunkenness by 31%, and weekly cannabis use by 43%. School disengagement increased the likelihood of smoking and cannabis use among females only.
Conclusion

Further research should focus on public health interventions promoting positive relationships and safety at school.

Clinical correlates of serum pigment epithelium-derived factor in type 2 diabetes patients

Aim: To determine if serum pigment epithelium-derived factor (PEDF) levels in Type 2 diabetes are related to vascular risk factors and renal function. Methods: PEDF was quantified by ELISA in a cross-sectional study of 857 male Veterans Affairs Diabetes Trial (VADT) subjects, and associations with cardiovascular risk factors and renal function were determined. In a subset (n = 246) in whom serum was obtained early in the VADT (2.0 ± 0.3 years post-randomization), PEDF was related to longitudinal changes in renal function over 3.1 years. Results: Cross-sectional study: In multivariate regression models, PEDF was positively associated with serum triglycerides, waist-to-hip ratio, serum creatinine, use of ACE inhibitors or angiotensin receptor blockers, and use of lipid-lowering agents; it was negatively associated with HDL-C (all p < 0.05). Longitudinal study: PEDF was not associated with changes in renal function over 3.1 years (p > 0.09). Conclusions: Serum PEDF in Type 2 diabetic men was cross-sectionally associated with dyslipidemia, body habitus, use of common drugs for blood pressure and dyslipidemia, and indices of renal function; however, PEDF was not associated with renal decline over 3.1 years.

Alcohol use and positive screening results for depression and anxiety are highly prevalent among chinese children with strabismus

Purpose: To study associations between strabismus and alcohol use, anxiety, and depression among 10- to 17-year-old children in Guangdong, southern China. Design: Cross-sectional, population-based study. Methods: Among 7537 children aged 6-17 years from 9 randomly selected primary and middle schools, ocular alignment was assessed with the Hirschberg light reflex, cover-uncover testing, and alternate cover testing at distance (6 m) and near (40 cm). Additionally, 4000 children (53.1%) aged 10+ years received self-administered questionnaires containing screening questions on alcohol use, anxiety, and depression. Results: Examinations were completed on 7464 of 7537 subjects (99.0%), including 3928 boys (52.6%), with a mean age of 11.1 ± 1.8 years. The prevalence of any strabismus, including exotropia (2.7%), esotropia (0.2%), and intermittent exotropia (3.9%), was 6.8%. Strabismus was more prevalent in urban students (7.3%) and female subjects (7.4%) compared to rural students (6.0%) and male subjects (6.2%) (all P <.05). In multivariate regression models, any strabismus was associated with older age and rural vs urban residence. Among 3903 children (97.6%) answering questionnaires, history of alcohol use (62.3% vs 36.3%) and positive screening responses for depression (26.0% vs 11.6%) and anxiety (10.3% vs 4.9%) were significantly (P <.01 for all) more common among children with strabismus. Conclusion: These Chinese children with strabismus had a significantly higher prevalence of alcohol use and possible markers of emotional problems than children without strabismus. Further research should focus on the appropriateness of classifying surgical treatment for strabismus as "cosmetic" (ineligible for reimbursement) under China's rural health insurance.

Factors associated with spectacle-wear compliance in school-aged Mexican children.

PURPOSE: To study the prevalence and determinants of compliance with spectacle wear among school-age children in Oaxaca, Mexico, who were provided spectacles free of charge. METHODS: A cohort of 493 children aged 5 to 18 years chosen by random cluster sampling from primary and secondary schools in Oaxaca, Mexico, all of whom had received free spectacles through a local program, underwent unannounced, direct examination to determine compliance with spectacle wear within 18 months after initial provision of spectacles. Potential determinants of spectacle wear including age, gender, urban versus rural residence, presenting visual acuity, refractive error, and time since dispensing of the spectacles were examined in univariate and multivariate regression models. Children not currently wearing their spectacles were asked to select the reason from a list of possibilities, and reasons for noncompliance were analyzed within different demographic groups. RESULTS: Among this sample of children with a mean age of 10.4 +/- 2.6 years, the majority (74.5%) of whom were myopic (spherical equivalent [SE] < or = -0.50 D), 13.4% (66/493) were wearing their spectacles at the time of examination. An additional 34% (169/493) had the spectacles with them but were not wearing them. In regression models, the odds of spectacle wear were significantly higher among younger (OR = 1.19 per year of age; 95% CI, 1.05-1.33) rural (OR = 10.6; 95% CI, 5.3-21.0) children and those with myopia < or = -1.25 D (OR = 3.97; 95% CI, 1.98-7.94). The oldest children and children in urban-suburban areas were significantly more likely to list concerns about the appearance of the glasses or about being teased than were younger, rurally resident children. CONCLUSIONS: Compliance with spectacle wear may be very low, even when spectacles are provided free of charge, particularly among older, urban children, who have been shown in many populations to have the highest prevalence of myopia. As screening programs for refractive error become increasingly common throughout the world, new strategies are needed to improve compliance if program resources are to be maximized.

Overweight duration in older adults and cancer risk: a study of cohorts in Europe and the United States

Recent studies have shown that cancer risk related to overweight and obesity is mediated by time and might be better approximated by using life years lived with excess weight. In this study we aimed to assess the impact of overweight duration and intensity in older adults on the risk of developing different forms of cancer. Study participants from seven European and one US cohort study with two or more weight assessments during follow-up were included (n = 329,576). Trajectories of body mass index (BMI) across ages were estimated using a quadratic growth model; overweight duration (BMI ≥ 25) and cumulative weighted overweight years were calculated. In multivariate Cox models and random effects analyses, a longer duration of overweight was significantly associated with the incidence of obesity-related cancer [overall hazard ratio (HR) per 10-year increment: 1.36; 95 % CI 1.12-1.60], but also increased the risk of postmenopausal breast and colorectal cancer. Additionally accounting for the degree of overweight further increased the risk of obesity-related cancer. Risks associated with a longer overweight duration were higher in men than in women and were attenuated by smoking. For postmenopausal breast cancer, increased risks were confined to women who never used hormone therapy. Overall, 8.4 % of all obesity-related cancers could be attributed to overweight at any age. These findings provide further insights into the role of overweight duration in the etiology of cancer and indicate that weight control is relevant at all ages. This knowledge is vital for the development of effective and targeted cancer prevention strategies.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.

Dynamic Density Forecasts for Multivariate Asset Returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.

Modified Information Criteria and Selection of Long Memory Time Series Models

The problem of model selection of a univariate long memory time series is investigated once a semi parametric estimator for the long memory parameter has been used. Standard information criteria are not consistent in this case. A Modified Information Criterion (MIC) that overcomes these difficulties is introduced and proofs that show its asymptotic validity are provided. The results are general and cover a wide range of short memory processes. Simulation evidence compares the new and existing methodologies and empirical applications in monthly inflation and daily realized volatility are presented.

An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study

This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.

Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach

Slow release drugs must be manufactured to meet target specifications with respect to dissolution curve profiles. In this paper we consider the problem of identifying the drivers of dissolution curve variability of a drug from historical manufacturing data. Several data sources are considered: raw material parameters, coating data, loss on drying and pellet size statistics. The methodology employed is to develop predictive models using LASSO, a powerful machine learning algorithm for regression with high-dimensional datasets. LASSO provides sparse solutions facilitating the identification of the most important causes of variability in the drug fabrication process. The proposed methodology is illustrated using manufacturing data for a slow release drug.