(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Discrete and continuous compositions

This paper examines a dataset which is modeled well by thePoisson-Log Normal process and by this process mixed with LogNormal data, which are both turned into compositions. Thisgenerates compositional data that has zeros without any need forconditional models or assuming that there is missing or censoreddata that needs adjustment. It also enables us to model dependenceon covariates and within the composition

Compositional evolution with mass transfer in closed systems

Evolution of compositions in time, space, temperature or other covariates is frequentin practice. For instance, the radioactive decomposition of a sample changes its composition with time. Some of the involved isotopes decompose into other isotopes of thesample, thus producing a transfer of mass from some components to other ones, butpreserving the total mass present in the system. This evolution is traditionally modelledas a system of ordinary di erential equations of the mass of each component. However,this kind of evolution can be decomposed into a compositional change, expressed interms of simplicial derivatives, and a mass evolution (constant in this example). A rst result is that the simplicial system of di erential equations is non-linear, despiteof some subcompositions behaving linearly.The goal is to study the characteristics of such simplicial systems of di erential equa-tions such as linearity and stability. This is performed extracting the compositional differential equations from the mass equations. Then, simplicial derivatives are expressedin coordinates of the simplex, thus reducing the problem to the standard theory ofsystems of di erential equations, including stability. The characterisation of stabilityof these non-linear systems relays on the linearisation of the system of di erential equations at the stationary point, if any. The eigenvelues of the linearised matrix and theassociated behaviour of the orbits are the main tools. For a three component system,these orbits can be plotted both in coordinates of the simplex or in a ternary diagram.A characterisation of processes with transfer of mass in closed systems in terms of stability is thus concluded. Two examples are presented for illustration, one of them is aradioactive decay

A house price index defined in the potential outcomes framework

Current methods for constructing house price indices are based on comparisons of sale prices of residential properties sold two or more times and on regression of the sale prices on the attributes of the properties and of their locations. The two methods have well recognised deficiencies, selection bias and model assumptions, respectively. We introduce a new method based on propensity score matching. The average house prices for two periods are compared by selecting pairs of properties, one sold in each period, that are as similar on a set of available attributes (covariates) as is feasible to arrange. The uncertainty associated with such matching is addressed by multiple imputation, framing the problem as involving missing values. The method is applied to aregister of transactions ofresidential properties in New Zealand and compared with the established alternatives.

The impact of tax credits on labour supply

One of the principle aims of the Working Families' Tax Credit in the UK was to increase the participation of single mothers. The literature to date concludes there was approximately a five-percentage-point increase in employment of single mothers. The differences-in-differences methodology that is typically used compares single mother with single women without children. However, the characteristics of these groups are very different, and change over time in relative covariates are likely to violate the identifying assumption. We find that when we control for differential trends between women with and without children, the employment effect of the policy falls significantly. Moreover, the effect is borne solely by those working full-time (30 hours or more), while having no effect on inducing people into the labor market from inactivity. Looking closely at important covariates over time, we can see sizeable changes in the relative returns to employment between the treatment and control groups.

Measurement and explanation of socioeconomic inequality in health with longitudinal data

This paper presents a method for the measurement of changes in health inequality and income-related health inequality over time in a population.For pure health inequality (as measured by the Gini coefficient) andincome-related health inequality (as measured by the concentration index),we show how measures derived from longitudinal data can be related tocross section Gini and concentration indices that have been typicallyreported in the literature to date, along with measures of health mobilityinspired by the literature on income mobility. We also show how thesemeasures of mobility can be usefully decomposed into the contributions ofdifferent covariates. We apply these methods to investigate the degree ofincome-related mobility in the GHQ measure of psychological well-being inthe first nine waves of the British Household Panel Survey (BHPS). Thisreveals that dynamics increase the absolute value of the concentrationindex of GHQ on income by 10%.

Anàlisi factorial confirmatòria per a variables categòriques: Aplicació al qüestionari de discapacitat WHODAS-II

Objective: To describe the methodology of Confirmatory Factor Analyis for categorical items and to apply this methodology to evaluate the factor structure and invariance of the WHO-Disability Assessment Schedule (WHODAS-II) questionnaire, developed by the World HealthOrganization.Methods: Data used for the analysis come from the European Study of Mental Disorders(ESEMeD), a cross-sectional interview to a representative sample of the general population of 6 european countries (n=8796). Respondents were administered a modified version of theWHODAS-II, that measures functional disability in the previous 30 days in 6 differentdimensions: Understanding and Communicating; Self-Care, Getting Around, Getting Along withOthers, Life Activities and Participation. The questionnaire includes two types of items: 22severity items (5 points likert) and 8 frequency items (continuous). An Exploratory factoranalysis (EFA) with promax rotation was conducted on a random 50% of the sample. Theremaining half of the sample was used to perform a Confirmatory Factor Analysis (CFA) inorder to compare three different models: (a) the model suggested by the results obtained in theEFA; (b) the theoretical model suggested by the WHO with 6 dimensions; (c) a reduced modelequivalent to model b where 4 of the frequency items are excluded. Moreover, a second orderfactor was also evaluated. Finally, a CFA with covariates was estimated in order to evaluatemeasurement invariance of the items between Mediterranean and non-mediterranean countries.Results: The solution that provided better results in the EFA was that containing 7 factors. Twoof the frequency items presented high factor loadings in the same factor, and one of thempresented factor loadings smaller than 0.3 with all the factors. With regard to the CFA, thereduced model (model c) presented the best goodness of fit results (CFI=0.992,TLI=0.996,RMSEA=0.024). The second order factor structure presented adequate goodness of fit (CFI=0.987,TLI=0.991, RMSEA=0.036). Measurement non-invariance was detected for one of the items of thequestionnaire (FD20 ¿ Embarrassment due to health problems).Conclusions: AFC confirmed the initial hypothesis about the factorial structure of the WHODAS-II in 6factors. The second order factor supports the existence of a global dimension of disability. The use of 4of the frequency items is not recommended in the scoring of the corresponding dimensions.

Predictors of death among patients who completed tuberculosis treatment: a population-based cohort study.

Background: Mortality among patients who complete tuberculosis (TB) treatment is still high among vulnerable populations. The objective of the study was to identify the probability of death and its predictive factors in a cohort of successfully treated TB patients. Methods: A population-based retrospective longitudinal study was performed in Barcelona, Spain. All patients who successfully completed TB treatment with culture-confirmation and available drug susceptibility testing between 1995 1997 were retrospectively followed-up until December 31, 2005 by the Barcelona TB Control Program. Socio-demographic, clinical, microbiological and treatment variables were examined. Mortality, TB Program and AIDS registries were reviewed. Kaplan-Meier and a Cox regression methods with time-dependent covariates were used for the survival analysis, calculating the hazard ratio (HR) with 95% confidence intervals (CI). Results: Among the 762 included patients, the median age was 36 years, 520 (68.2%) were male, 178 (23.4%) HIV-infected, and 208 (27.3%) were alcohol abusers. Of the 134 (17.6%) injecting drug users (IDU), 123 (91.8%) were HIV-infected. A total of 30 (3.9%) recurrences and 173 deaths (22.7%) occurred (mortality rate: 3.4/100 person-years of follow-up). The predictors of death were: age between 4160 years old (HR: 3.5; CI:2.15.7), age greater than 60 years (HR: 14.6; CI:8.924), alcohol abuse (HR: 1.7; CI:1.22.4) and HIV-infected IDU (HR: 7.9; CI:4.713.3). Conclusions: The mortality rate among TB patients who completed treatment is associated with vulnerable populations such as the elderly, alcohol abusers, and HIV-infected IDU. We therefore need to fight against poverty, and promote and develop interventions and social policies directed towards these populations to improve their survival.

Incidencia de la incapacidad temporal por contingencia común y profesional en la muestra continua de vidas laborales en 2009

Objetivo: Describir la incidencia de la incapacidad temporal por contingencia común (ITcc) y profesional (ITcp) iniciada en 2009 en afiliados a la Seguridad Social (SS) que forman parte de la Muestra Continua de Vida Laboral.Métodos: Cohorte formada por 873.008 afiliados a la SS en España que registraron 163.008 episodios de IT con un tiempo acumulado total en riesgo de 675.923,6 trabajadores-año. Se estimó la tasa de incidencia de todos los primeros episodios de IT y por trastornos musculo-esqueléticos (TME) según variables demográficas y laborales. Posteriormente se calcularon las razones de tasas crudas (RTc) y ajustadas (RTa) mediante un modelo de regresión Poisson.Resultados: La incidencia de la ITcc e ITcp fue de 23,1 y 1,0 casos por 100 trabajadores-año, respectivamente. La incidencia por ITcc fue superior en mujeres, en menores de 26 años y en Navarra (32,8 casos por 100 trabajadores-año), y por ITcp las mayores incidencias se observaron en hombres y en Galicia. Por diagnóstico, los TME presentaron 424,7 casos y 3,6 casos por 10.000 trabajadores-año según contingencia común y profesional respectivamente. Por otra parte, los trabajadores temporales tuvieron más riesgo de desarrollar ITcp (RTa=1,09;IC95%=1,04-1,15) e ITcc (RTa=1,02;IC95%=1,01-1,03) respecto a los permanentes.Conclusiones: La incidencia de la IT sigue un mismo patrón según edad, régimen de afiliación y relación laboral. Por tipo de contingencia se observaron diferencias en la ocupación, sexo, tamaño de empresa, comunidad autónoma y actividad económica. Es necesario estudiar con más detenimiento las diferencias observadas por actividad económica y tipo de relación contractual.

Disentangling the link between health and social capital: A comparison of immigrant and native-born populations in Spain

An increasing body of research has pointed to the relevance of social capital in studying a great variety of socio-economic phenomena, ranging from economics growth and development to educational attainment and public health. Conceptually, our paper is framed within the debates about the possible links between health and social capital, on one hand, and within the hypotheses regarding the importance of social and community networks in all stages of the dynamics of international migration, on the other hand. Our primary objective is to explore the ways social relations contribute to health differences between the immigrants and the native-born population of Spain. We also try to reveal differences in the nature of the social networks of foreign-born, as compared to that of the native-born persons. The empirical analysis is based on an individual-level data coming from the 2006 Spanish Health Survey, which contains a representative sample of the immigrant population. To assess the relationship between various health indicators (self-assessed health, chronic conditions and long-term illness) and social capital, controlling for other covariates, we estimate multilevel models separately for the two population groups of interest. In the estimates we distinguish between individual and community-level social capital. While the Health Survey contains information that allows us to define individual social capital measures, the collective indicators come from other official sources. In particular, for the subsample of immigrants, we proxy community-level networks and relationships by variables contained in the Spanish National Survey of Immigrants 2007. The results obtained so far point to the relevance of social capital as a covariate in the health equation, although, the significance varies according to the specific health indicator used. Additionally, and contrary to what is expected, immigrants’ social networks seem to be inferior to those of the native-born population in many aspects; and they also affect immigrant’s health to a lesser extent. Policy implications of the findings are discussed. Keywords: health status, social capital, immigration, Spain

Sex differences in hospital readmission among colorectal cancer patients.

Background: While several studies have analysed sex and socioeconomic differences in cancer incidence and mortality, sex differences in oncological health care have been seldom considered. Objective: To investigate sex based inequalities in hospital readmission among patients diagnosed with colorectal cancer. Design: Prospective cohort study. Setting: Hospital Universitary in L¿Hospitalet (Barcelona, Spain). Participants: Four hundred and three patients diagnosed with colorectal between January 1996 and December 1998 were actively followed up until 2002. Main outcome measurements and methods: Hospital readmission times related to colorectal cancer after surgical procedure. Cox proportional model with random effect (frailty) was used to estimate hazard rate ratios and 95% confidence intervals of readmission time for covariates analysed. Results: Crude hazard rate ratio of hospital readmission in men was 1.61 (95% CI 1.21 to 2.15). When other significant determinants of readmission were controlled for (including Dukes¿s stage, mortality, and Charlson¿s index) a significant risk of readmission was still present for men (hazard rate ratio: 1.52, 95% CI 1.17 to 1.96). Conclusions: In the case of colorectal cancer, women are less likely than men to be readmitted to the hospital, even after controlling for tumour characteristics, mortality, and comorbidity. New studies should investigate the role of other non-clinical variable such as differences in help seeking behaviours or structural or personal sex bias in the attention given to patients.

Visual impairment and multimorbidity in a representative sample of the Spanish population

BACKGROUND: In the context of population aging, visual impairment has emerged as a growing concern in public health. However, there is a need for further research into the relationship between visual impairment and chronic medical conditions in the elderly. The aim of our study was to examine the relationship between visual impairment and three main types of co-morbidity: chronic physical conditions (both at an independent and additive level), mental health and cognitive functioning. METHODS: Data were collected from the COURAGE in Europe project, a cross-sectional study. A total of 4,583 participants from Spain were included. Diagnosis of chronic medical conditions included self-reported medical diagnosis and symptomatic algorithms. Depression and anxiety were assessed using CIDI algorithms. Visual assessment included objective distance/near visual acuity and subjective visual performance. Descriptive analyses included the whole sample (n = 4,583). Statistical analyses included participants aged over 50 years (n = 3,625; mean age = 66.45 years) since they have a significant prevalence of chronic conditions and visual impairment. Crude and adjusted binary logistic regressions were performed to identify independent associations between visual impairment and chronic medical conditions, physical multimorbidity and mental conditions. Covariates included age, gender, marital status, education level, employment status and urbanicity. RESULTS: The number of chronic physical conditions was found to be associated with poorer results in both distance and near visual acuity [OR 1.75 (CI 1.38-2.23); OR 1.69 (CI 1.27-2.24)]. At an independent level, arthritis, stroke and diabetes were associated with poorer distance visual acuity results after adjusting for covariates [OR 1.79 (CI 1.46-2.21); OR 1.59 (CI 1.05-2.42); OR 1.27 (1.01-1.60)]. Only stroke was associated with near visual impairment [OR 3.01 (CI 1.86-4.87)]. With regard to mental health, poor subjective visual acuity was associated with depression [OR 1.61 (CI 1.14-2.27); OR 1.48 (CI 1.03-2.13)]. Both objective and subjective poor distance and near visual acuity were associated with worse cognitive functioning. CONCLUSIONS: Arthritis, stroke and the co-occurrence of various chronic physical diseases are associated with higher prevalence of visual impairment. Visual impairment is associated with higher prevalence of depression and poorer cognitive function results. There is a need to implement patient-centered care involving special visual assessment in these cases.

Multimorbidity patterns in a national representative sample of the Spanish adult population.

BACKGROUND: In the context of population aging, multimorbidity has emerged as a growing concern in public health. However, little is known about multimorbidity patterns and other issues surrounding chronic diseases. The aim of our study was to examine multimorbidity patterns, the relationship between physical and mental conditions and the distribution of multimorbidity in the Spanish adult population. METHODS: Data from this cross-sectional study was collected from the COURAGE study. A total of 4,583 participants from Spain were included, 3,625 aged over 50. An exploratory factor analysis was conducted to detect multimorbidity patterns in the population over 50 years of age. Crude and adjusted binary logistic regressions were performed to identify individual associations between physical and mental conditions. RESULTS: THREE MULTIMORBIDITY PATTERNS ROSE: 'cardio-respiratory' (angina, asthma, chronic lung disease), 'mental-arthritis' (arthritis, depression, anxiety) and the 'aggregated pattern' (angina, hypertension, stroke, diabetes, cataracts, edentulism, arthritis). After adjusting for covariates, asthma, chronic lung disease, arthritis and the number of physical conditions were associated with depression. Angina and the number of physical conditions were associated with a higher risk of anxiety. With regard to multimorbidity distribution, women over 65 years suffered from the highest rate of multimorbidity (67.3%). CONCLUSION: Multimorbidity prevalence occurs in a high percentage of the Spanish population, especially in the elderly. There are specific multimorbidity patterns and individual associations between physical and mental conditions, which bring new insights into the complexity of chronic patients. There is need to implement patient-centered care which involves these interactions rather than merely paying attention to individual diseases.