Implementation of the Walrasian correspondence by market games

In this paper we present a set of axioms guaranteeing that, in exchange economies with or without indivisible goods, the set of Nash, Strong and active Walrasian Equilibria all coincide in the framework of market games.

Market effects of foreign exchange coordinated intervention

In this article we develop a theoretical microstructure model of coordinated central bank intervention based on asymmetric information. We study the economic implications of coordination on some measures of market quality and show that the model predicts higher volatility and more significant exchange rate changes when central banks coordinate compared to when they intervene unilaterally. Both these predictions are in line with empirical evidence. Keywords: coordinated foreign exchange intervention, market microstructure. JEL Classification: D82, E58, F31, G14

The generic Hanna Neumann conjecture and post correspondence problem

"Vegeu el resum a l'inici del document del fitxer adjunt."

Health intervention and decline in infant mortality rates. Milk depots in Spain (1900-1936)

The role of public health has been a central topic on the classical debate about the historical mortality decline in Europe. One of these health initiatives were the Milk Depots. Spain set up those centres from the late 19th century until the beginning of the Civil War. The goal of this paper is to evaluate the effect of this health intervention on the infant mortality decline during this period. This study works out three kinds of sources: Statistical Yearbooks, Official documents and local records produced by the same Milk Depot. It analyses data available for all the country and one local case such as the Barcelona’s Milk Depot (1904-1935). The main methodological issue deals with the measurement of the effect of the Milk Depot activities on the pattern of changes of infant mortality. Results suggest that Milk Depots have a positive but quite moderate effect on the improving of overall levels of child survival.

Reduction in catheter-related bloodstream infections in critically ill patients through a multiple system intervention.

Els catéters venosos centrals són necessaris per al maneig del pacient crític però poden ser l´origen d´una bacteriemia. Aquest estudi prospectiu de cohort té com a objectiu determinar la utilitat de l´aplicació d´unes mesures bàsiques de prevenció per disminuir la incidència de bacteriemia associada a catéter. Els resultats de l´estudi confirmen que l´aplicació d´aquest sistema d´intervenció múltiple basat en l´evidencia redueix de forma significativa les bacteriemies associades a catéter a la nostra UCI.

Comparing correspondence analysis and the log-ratio alternative for representing categorical data

We compare correspondance análisis to the logratio approach based on compositional data. We also compare correspondance análisis and an alternative approach using Hellinger distance, for representing categorical data in a contingency table. We propose a coefficient which globally measures the similarity between these approaches. This coefficient can be decomposed into several components, one component for each principal dimension, indicating the contribution of the dimensions to the difference between the two representations. These three methods of representation can produce quite similar results. One illustrative example is given

Weighted Logratio Biplots, Correspondence Analysis and Spectral Maps

Starting with logratio biplots for compositional data, which are based on the principle of subcompositional coherence, and then adding weights, as in correspondence analysis, we rediscover Lewi's spectral map and many connections to analyses of two-way tables of non-negative data. Thanks to the weighting, the method also achieves the property of distributional equivalence

The effectiveness of market intervention policies to improve diet quality and to reduce the prevalence of obesity in Spain

Our project aims at analyzing the relevance of economic factors (mainly income and other socioeconomic characteristics of Spanish households and market prices) on the prevalence of obesity in Spain and to what extent market intervention prices are effective to reduce obesity and improve the quality of the diet, and under what circumstances. In relation to the existing literature worldwide, this project is the first attempt in Spain trying to get an overall picture on the effectiveness of public policies on both food consumption and the quality of diet, on one hand, and on the prevalence of obesity on the other. The project consists of four main parts. The first part represents a critical review of the literature on the economic approach of dealing with the obesity prevalence problems, diet quality and public intervention policies. Although another important body of obesity literature is dealing with physical exercise but in this paper we will limit our attention to those studies related to food consumption respecting the scope of our study and as there are many published literature review dealing with the literature related to the physical exercise and its effect on obesity prevalence. The second part consists of a Parametric and Non-Parametric Analysis of the Role of Economic Factors on Obesity Prevalence in Spain. The third part is trying to overcome the shortcomings of many diet quality indices that have been developed during last decades, such as the Healthy Eating Index, the Diet Quality Index, the Healthy Diet Indicator, and the Mediterranean Diet Score, through the development of a new obesity specific diet quality index. While the last part of our project concentrates on the assessment of the effectiveness of market intervention policies to improve the healthiness of the Spanish Diet Using the new Exact Affine Stone Index (EASI) Demand System.

Passive smoking in babies: The BIBE Study (Brief Intervention in babies. Effectiveness)

Background: There is evidence that exposure to passive smoking in general, and in babies in particular, is an important cause of morbimortality. Passive smoking is related to an increased risk of pediatric diseases such as sudden death syndrome, acute respiratory diseases, worsening of asthma, acute-chronic middle ear disease and slowing of lung growth.The objective of this article is to describe the BIBE study protocol. The BIBE study aims to determine the effectiveness of a brief intervention within the context of Primary Care, directed to mothers and fathers that smoke, in order to reduce the exposure of babies to passive smoking (ETS).Methods/DesignCluster randomized field trial (control and intervention group), multicentric and open. Subject: Fathers and/or mothers who are smokers and their babies (under 18 months) that attend pediatric services in Primary Care in Catalonia.The measurements will be taken at three points in time, in each of the fathers and/or mothers who respond to a questionnaire regarding their baby's clinical background and characteristics of the baby's exposure, together with variables related to the parents' tobacco consumption. A hair sample of the baby will be taken at the beginning of the study and at six months after the initial visit (biological determination of nicotine). The intervention group will apply a brief intervention in passive smoking after specific training and the control group will apply the habitual care.Discussion: Exposure to ETS is an avoidable factor related to infant morbimortality. Interventions to reduce exposure to ETS in babies are potentially beneficial for their health. The BIBE study evaluates an intervention to reduce exposure to ETS that takes advantage of pediatric visits. Interventions in the form of advice, conducted by pediatric professionals, are an excellent opportunity for prevention and protection of infants against the harmful effects of ETS.

Measures of fit in multiple correspondence analysis of crisp and fuzzy coded data

When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

Canonical correspondence analysis in social science research

The use of simple and multiple correspondence analysis is well-established in socialscience research for understanding relationships between two or more categorical variables.By contrast, canonical correspondence analysis, which is a correspondence analysis with linearrestrictions on the solution, has become one of the most popular multivariate techniques inecological research. Multivariate ecological data typically consist of frequencies of observedspecies across a set of sampling locations, as well as a set of observed environmental variablesat the same locations. In this context the principal dimensions of the biological variables aresought in a space that is constrained to be related to the environmental variables. Thisrestricted form of correspondence analysis has many uses in social science research as well,as is demonstrated in this paper. We first illustrate the result that canonical correspondenceanalysis of an indicator matrix, restricted to be related an external categorical variable, reducesto a simple correspondence analysis of a set of concatenated (or stacked ) tables. Then weshow how canonical correspondence analysis can be used to focus on, or partial out, aparticular set of response categories in sample survey data. For example, the method can beused to partial out the influence of missing responses, which usually dominate the results of amultiple correspondence analysis.

Ratio maps and correspondence analysis

We compare two methods for visualising contingency tables and developa method called the ratio map which combines the good properties of both.The first is a biplot based on the logratio approach to compositional dataanalysis. This approach is founded on the principle of subcompositionalcoherence, which assures that results are invariant to considering subsetsof the composition. The second approach, correspondence analysis, isbased on the chi-square approach to contingency table analysis. Acornerstone of correspondence analysis is the principle of distributionalequivalence, which assures invariance in the results when rows or columnswith identical conditional proportions are merged. Both methods may bedescribed as singular value decompositions of appropriately transformedmatrices. Correspondence analysis includes a weighting of the rows andcolumns proportional to the margins of the table. If this idea of row andcolumn weights is introduced into the logratio biplot, we obtain a methodwhich obeys both principles of subcompositional coherence and distributionalequivalence.

The contributions of rare objects in correspondence analysis

Correspondence analysis, when used to visualize relationships in a table of counts(for example, abundance data in ecology), has been frequently criticized as being too sensitiveto objects (for example, species) that occur with very low frequency or in very few samples. Inthis statistical report we show that this criticism is generally unfounded. We demonstrate this inseveral data sets by calculating the actual contributions of rare objects to the results ofcorrespondence analysis and canonical correspondence analysis, both to the determination ofthe principal axes and to the chi-square distance. It is a fact that rare objects are oftenpositioned as outliers in correspondence analysis maps, which gives the impression that theyare highly influential, but their low weight offsets their distant positions and reduces their effecton the results. An alternative scaling of the correspondence analysis solution, the contributionbiplot, is proposed as a way of mapping the results in order to avoid the problem of outlying andlow contributing rare objects.

Consistency and the Walrasian allocations correspondence

We characterize the Walrasian allocations correspondence, in classesof exchange economies with smooth and convex preferences, by means of consistency requirements and other axioms. We present three characterizationresults; all of which require consistency, converse consistency and standard axioms. Two characterizations hold also on domains with a finite number ofpotential agents, one of them requires envy freeness (with respect to trades) and the other--core selection; a third characterization, that requires coreselection, applies only to a variable number of agents domain, but is validalso when the domain includes only a small variety of preferences.

Power transformations in correspondence analysis

Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.