Leaving the labour market: event-history analysis of the female workers' transition to housework in Denmark, Germany, Great Britain and Spain

This paper is aimed at exploring the determinants of female activity from a dynamic perspective. An event-history analysis of the transition form employment to housework has been made resorting to data from the European Household Panel Survey. Four countries representing different welfare regimes and, more specifically, different family policies, have been selected for the analysis: Britain, Denmark, Germany and Spain. The results confirm the importance of individual-level factors, which is consistent with an economic approach to female labour supply. Nonetheless, there are significant cross-national differences in how these factors act over the risk of abandoning the labour market. First, the number of trnasitions is much lower among Danish working women than among British, German or Spanish ones, revealing the relative importance of universal provision of childcare services, vis-à-vis other elements of the family policy, as time or money.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

A time-domain method for the analysis of thermal impedance response preserving the convolution form

The study of the thermal behavior of complex packages as multichip modules (MCM¿s) is usually carried out by measuring the so-called thermal impedance response, that is: the transient temperature after a power step. From the analysis of this signal, the thermal frequency response can be estimated, and consequently, compact thermal models may be extracted. We present a method to obtain an estimate of the time constant distribution underlying the observed transient. The method is based on an iterative deconvolution that produces an approximation to the time constant spectrum while preserving a convenient convolution form. This method is applied to the obtained thermal response of a microstructure as analyzed by finite element method as well as to the measured thermal response of a transistor array integrated circuit (IC) in a SMD package.

Of Coalition and Speed: Passage and Duration of Statutes in Uruguay's Parliament, 1985-2000

We report preliminary findings from analysis of a database under construction. The paper explores the legislative process in search for some of the alleged consequences of cabinet coalitions in a presidential system. Coalition effects should be less evident in the success of executive initiatives: strategic behavior hampers this intuitive measure of performance. Better measures, because less subject to strategic considerations, are the odds of passage of legislators' bills and the time proposals take to be approved. Thus measured, coalition effects are discernible. Analysis of the universe of proposals processed in the fragmented Uruguayan Parliament between 1985 and 2000 reveals that coalition, observed about half the period, swells success rates of coalition members by 60% on average (and by as much as 150% for those close to the president). Event history analysis shows that coalitions cut the wait for an executive bill by 3 months, 1/6th the average wait. The reverse effect is felt on the duration of legislators' bills.

An empirical analysis of wealth taxation: equity Vs.tax compliance

Capital taxation is currently under debate, basically due to problems of administrative control and proper assessment of the levied assets. We analyze both problems focusing on a capital tax, the annual wealth tax (WT), which is only applied in five OECD countries, being Spain one of them. We concentrate our analysis on top 1% adult population, which permits us to describe the evolution of wealth concentration in Spain along 1983-2001. On average top 1% holds about 18% of total wealth, which rises to 19% when tax incompliance and under-assessment is corrected for housing, the main asset. The evolution suggests wealth concentration has risen. Regarding WT, we analyze whether it helps to reduce wealth inequality or, on the contrary, it reinforces vertical inequity (due to especial concessions) and horizontal inequity (due to the de iure and to de facto different treatment of assets). We analyze in detail housing and equity shares. By means of a time series analysis, we relate the reported values with reasonable price indicators and proxies of the propensity to save. We infer net tax compliance is extremely low, which includes both what we commonly understand by (gross) tax compliance and the degree of under-assessment due to fiscal legislation (for housing). That is especially true for housing, whose level of net tax compliance is well below 50%. Hence, we corroborate the difficulties in taxing capital, and so cast doubts on the current role of the WT in Spain in reducing wealth inequality.

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets

Who benefits from parental leave in Spain? : a life course analysis

This paper analyses the extent to which individual and workplacecharacteristics and regional policies influence the use and duration ofparental leave in Spain. The research is based on a sample of 125,165people, and 6,959 parental leaves stemming from the ‘Sample ofWorking Life Histories’ (SWLH), 2006. The SWLH consists of administrative register data which include information from threedifferent sources: Social Security, Municipality and Income TaxRegisters. We adopt a simultaneous equations approach to analyse theuse (logistic regression) and duration (event history analysis) ofparental leave, which allows us to control for endogeneity and censoredobservations. We argue that the Spanish parental leave scheme increases gender and social inequalities insofar as reinforces genderrole specialization, and only encourages the reconciling of work andfamily life among workers with a good position in the labour market(educated employees with high and stable working status).

Why Italy and not Spain?: comparing two industrialization processes from a dissagregate time-series perspective

This study presents new evidence concerning the uneven processes of industrialization innineteenth century Spain and Italy based on a disaggregate analysis of the productivesectors from which the behaviour of the aggregate indices is comprised. The use of multivariate time-series analysis techniques can aid our understanding and characterization of these two processes of industrialization. The identification of those sectors with key rolesin leading industrial growth provides new evidence concerning the factors that governed thebehaviour of the aggregates in the two economies. In addition, the analysis of the existenceof interindustry linkages reveals the scale of the industrialization process, and wheresignificant differences exist, accounts for many of the divergences recorded in the historiography for the period 1850-1913.

Continuous-time random-walk model for financial distributions

We apply the formalism of the continuous-time random walk to the study of financial data. The entire distribution of prices can be obtained once two auxiliary densities are known. These are the probability densities for the pausing time between successive jumps and the corresponding probability density for the magnitude of a jump. We have applied the formalism to data on the U.S. dollardeutsche mark future exchange, finding good agreement between theory and the observed data.

Why Italy and not Spain?: comparing two industrialization processes from a dissagregate time-series perspective

This study presents new evidence concerning the uneven processes of industrialization innineteenth century Spain and Italy based on a disaggregate analysis of the productivesectors from which the behaviour of the aggregate indices is comprised. The use of multivariate time-series analysis techniques can aid our understanding and characterization of these two processes of industrialization. The identification of those sectors with key rolesin leading industrial growth provides new evidence concerning the factors that governed thebehaviour of the aggregates in the two economies. In addition, the analysis of the existenceof interindustry linkages reveals the scale of the industrialization process, and wheresignificant differences exist, accounts for many of the divergences recorded in the historiography for the period 1850-1913.

Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.

Positive time-frequency distributions based on joint marginal constraints

This correspondence studies the formulation of members ofthe Cohen-Posch class of positive time-frequency energy distributions.Minimization of cross-entropy measures with respect to different priorsand the case of no prior or maximum entropy were considered. It isconcluded that, in general, the information provided by the classicalmarginal constraints is very limited, and thus, the final distributionheavily depends on the prior distribution. To overcome this limitation,joint time and frequency marginals are derived based on a "directioninvariance" criterion on the time-frequency plane that are directly relatedto the fractional Fourier transform.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

Assessing trends in insured losses from floods in Spain 1971-2008

Economic impacts from floods have been increasing over recent decades, a fact often attributed to a changing climate. On the other hand, there is now a significant body of scientific scholarship all pointing towards increasing concentrations and values of assets as the principle cause of the increasing cost of natural disasters. This holds true for a variety of perils and across different jurisdictions. With this in mind, this paper examines the time history of insured losses from floods in Spain between 1971 and 2008. It as- sesses whether any discernible residual signal remains after adjusting the data for the increase in the number and value of insured assets over this period of time. Data on insured losses from floods were sourced from Consorcio de Com- pensacíon de Seguros (CCS). Although a public institution, CCS compensates homeowners for the damage produced by floods, and thus plays a role similar to that of a private insurance company. Insured losses were adjusted using two proxy measures: first, changes in the total amount of annual surcharges (premiums) paid by customers to CCS, and secondly, changes in the total value of dwellings per year. The adjusted data reveals no significant trend over the period 1971-2008 and serves again to confirm that at this juncture, societal in- fluences remain the prime factors driving insured and economic losses from natural disasters.

De ratones y hombres. Maus, de Art Spiegelman

This article analyses the cómic book Maus, by Art Spiegelman (1986-1991), from two angles: as a work of art dealing with the Holocaust, and as a cómic that subverts the fictional tradition of the genre, opening itself up to history and the narration of reality. Maus, the first cómic book to treat the topic of the Holocaust in depth, was written by a second-generation witness. It is a story of both physical survival and enduring trauma in the family. At the same time, an analysis of the stratevival and enduring trauma in the family. At the same time, an analysis of the strateof the traditional cómic reveals how Spiegelman has used the genre to recount, instead of fiction and for the first time, a historically authentic biographical tale