Why England? Demand, growth and inequality during the Industrial Revolution

Why was England first? And why Europe? We present a probabilistic model that builds on big-push models by Murphy, Shleifer and Vishny (1989), combined with hierarchical preferences. The interaction of exogenous demographic factors (in particular the English low-pressure variant of the European marriage pattern)and redistributive institutions such as the old Poor Law combined to make an Industrial Revolution more likely. Essentially, industrialization is the result of having a critical mass of consumers that is rich enough to afford (potentially) mass-produced goods. Our model is then calibrated to match the main characteristics of the English economy in 1750 and the observed transition until 1850.This allows us to address explicitly one of the key features of the British IndustrialRevolution unearthed by economic historians over the last three decades the slowness of productivity and output change. In our calibration, we find that the probability of Britain industrializing is 5 times larger than France s. Contrary to the recent argument by Pomeranz, China in the 18th century had essentially no chance to industrialize at all. This difference is decomposed into a demographic and a policy component, with the former being far more important than the latter.

Forecasting and turning point predictions in a Bayesian panel VAR model

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.

Drug utilization studies and data registries in primary care

This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment.Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

Design effect and interviewer effects: Evidence from the Spanish ESS3-2006 Data

In 2007 the first Quality Enhancement Meeting on sampling in the European SocialSurvey (ESS) took place. The discussion focused on design effects and inteviewereffects in face-to-face interviews. Following the recomendations of this meeting theSpanish ESS team studied the impact of interviewers as a new element in the designeffect in the response s variance using the information of the correspondent SampleDesign Data Files. Hierarchical multilevel and cross-classified multilevel analysis areconducted in order to estimate the amount of responses variation due to PSU and tointerviewers for different questions in the survey. Factor such as the age of theinterviewer, gender, workload, training and experience and respondent characteristicssuch as age, gender, renuance to participate and their possible interactions are alsoincluded in the analysis of some specific questions like trust in politicians and trustin legal system . Some recomendations related to future sampling designs and thecontents of the briefing sessions are derived from this initial research.

Fixed and random effects in Classical and Bayesian regression

This paper proposes a common and tractable framework for analyzingdifferent definitions of fixed and random effects in a contant-slopevariable-intercept model. It is shown that, regardless of whethereffects (i) are treated as parameters or as an error term, (ii) areestimated in different stages of a hierarchical model, or whether (iii)correlation between effects and regressors is allowed, when the sameinformation on effects is introduced into all estimation methods, theresulting slope estimator is also the same across methods. If differentmethods produce different results, it is ultimately because differentinformation is being used for each methods.

Incentives and promotion in wage hierarchies

Most of the large firms organization schemes consist in hierarchical structures of tiers with different wage levels. Traditionally the existence of this kind of organizations has been associated to the separation of productive and managerial or supervision tasks and to differences in the skills of the workers. However, many firms now employ workers with similar skills, and then the hierarchical structure can be related to an incentive scheme to ensure that workers supply effort. The model we present investigates how firm owners should determine the optimal wage distribution in order to maximize profits.

Synchronization reveals topological scales in complex networks

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.

Impact of community structure on information transfer

The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.

Incentives and promotion in wage hierarchies

Most of the large firms organization schemes consist in hierarchical structures of tiers with different wage levels. Traditionally the existence of this kind of organizations has been associated to the separation of productive and managerial or supervision tasks and to differences in the skills of the workers. However, many firms now employ workers with similar skills, and then the hierarchical structure can be related to an incentive scheme to ensure that workers supply effort. The model we present investigates how firm owners should determine the optimal wage distribution in order to maximize profits.

Workers' perception of workplace bullying: a cross-cultural study

This study is one of the first studies to approach workplace bullying cross-culturally. It sought to compare employees' understanding of workplace bullying in two different world regions: Central America and Southern Europe, regarding three aspects of workplace bullying: psychological vs. physical harassment, hierarchical vs. horizontal bullying, and direct vs. indirect aggression. A convenience sample of 246 workers provided their own definition of workplace bullying through a single, open-ended question. The results showed that employees from Central America emphasized the physical component of workplace bullying more than the Southern European employees. However, similarities in the conceptualization of workplace bullying across both cultures were found as well. Both Southern European and Central American employees defined workplace bullying mainly as a hierarchical phenomenon, where the aggression took the form of direct strategies. Such differences and similarities bring to the field some positive inputs for the development and implementation of different strategies for dealing effectively with this phenomenon.

Workers' perception of workplace bullying: a cross-cultural study

This study is one of the first studies to approach workplace bullying cross-culturally. It sought to compare employees' understanding of workplace bullying in two different world regions: Central America and Southern Europe, regarding three aspects of workplace bullying: psychological vs. physical harassment, hierarchical vs. horizontal bullying, and direct vs. indirect aggression. A convenience sample of 246 workers provided their own definition of workplace bullying through a single, open-ended question. The results showed that employees from Central America emphasized the physical component of workplace bullying more than the Southern European employees. However, similarities in the conceptualization of workplace bullying across both cultures were found as well. Both Southern European and Central American employees defined workplace bullying mainly as a hierarchical phenomenon, where the aggression took the form of direct strategies. Such differences and similarities bring to the field some positive inputs for the development and implementation of different strategies for dealing effectively with this phenomenon.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

Confirmatory factor analysis of an integrated model of psycopathology assessed with MMPI-2-RF and the MCMI-III

We presented an integrated hierarchical model of psychopathology that more accurately captures empirical patterns of comorbidity between clinical syndromes and personality disorders.In order to verify the structural validity of the model proposed, this study aimed to analyze the convergence between the Restructured Clinical (RC) scales and Personality scales (PSY-5) of the MMPI-2-RF and the Clinical Syndrome and Personality Disorder scales of the MCMI-III.The MMPI-2-RF and MCMI-III were administered to a clinical sample of 377 outpatients (167 men and 210 women).The structural hypothesiswas assessed by using a Confirmatory Factor Analytic design with four common superordinate factors. An independent-cluster-basis solution was proposed based on maximum likelihood estimation and the application of several fit indices.The fit of the proposed model can be considered as good and more so if we take into account its complexity.

Polymorphisms in DNA-repair genes in a cohort of prostate cancer patients from different areas in Spain: heterogeneity between populations as a confounding factor in association studies

Background: Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. Objective: To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. Design, Setting, and Participants: A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArrayH NT Cycler. Outcome Measurements and Statistical Analysis: Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. Results and Limitations: We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. Conclusion: Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.