Search results

We present a comparison of coverage and values for five inequality data sets that have worldwide or major international coverage and independent measurements that are intended to present consistent coefficients that can be compared directly across countries and time. The comparison data sets are those published by the Luxembourg Income Studies (LIS), the OECD, the European Union’s Statistics on Incomes and Living Conditions (EU-SILC), and the World Bank’s World Development Indicators (WDI). The baseline comparison is with our own Estimated Household Income Inequality (EHII) data set of the University of Texas Inequality Project. The comparison shows the historical depth and range of EHII and its broad compatibility with LIS, OECD, and EU-SILC, as well as problems with using the WDI for any cross-country comparative purpose. The comparison excludes the large World Incomes Inequality Database (WIID) of UNU-WIDER and the Standardized World Income Inequality Database (SWIID) of Frederick Solt; the former is a bibliographic collection and the latter is based on imputations drawn, in part, from EHII and the other sources used here.

The purpose of this paper is to determine the occurrence of job level, salary and job authority demotions in the workplace through the analysis of Belgian Statistics on Income and Living Conditions (SILC)-data of 2007-2011.

Three hypotheses are tested: H1: there is a gender inequality in job authority demotions. H2: the level of education and the probability of being subject to a job level, salary or job authority demotion are negatively correlated. H3: age is negatively correlated with job level, salary or job authority demotion probabilities. The cross-sectional data of the SILC cover a specific time period with data on inter alia living conditions. The longitudinal data give information on inter alia income and non-monetary variables over a period of four years. The authors estimate multivariate regression models for binary demotion variables. These analyses allow the authors to estimate the odds of being demoted. The authors discuss the demotion rates, the bivariate correlations and the regression analysis.

The data analysis result in the fact that base salary demotions are not commonly applied as literature and the Belgian law on salary protection endorses. Fringe benefits demotions, as for instance the abolition of a company car or a bonus are, however, more frequent. There is a gender gap with regard to job authority demotion. Highly educated respondents are less confronted with job authority demotions. Age is negatively correlated with base salary/fringe benefits or job authority demotion probabilities, but not with job-level demotions. H1 is thus confirmed. H2 and H3 only partly confirmed.

Several analyses were restricted because the EU-SILC did not question all dimensions of demotion in detail.

This study contributes to the scarce literature on demotion and to empirical studies on demotions regarding job level, salary and job authority.

The current economic crisis has significantly increased unemployment, showing higher persistence than expected. However, since microdata from household surveys are issued with delay, they do not allow a prompt analysis of the impact of the economic cycle on households’ living conditions. The purpose of this paper is to propose a microsimulation methodology to achieve an evaluation of the impact of economic shocks in terms of household’s living conditions to guide policy makers.

The microsimulation technique developed in this paper is based on a nowcasting approach by using different sources of data and by taking into account a whole set of potential transitions across the different statuses of the labour market and the related changes in income. To validate this microsimulation method, the authors apply it to Italy, a country that has been deeply affected by the crisis.

Data have been drawn from the European Statistics on Income and Living Conditions Survey for Italy (IT SILC) and from the Labour Force Survey for Italy. The latter data allow us to take into account the changes in the labour market status of individuals due to economic shocks. The validation results support the capability of the model to simulate the effect of the cycle before actual data on income are available.

The results obtained would encourage the use of the suggested methodology to anticipate the effect of the economic cycle on household’s income therefore enabling the design of effective policies to sustain household income with positive practical and social implications.

Distinct from other microsimulation techniques the methodology proposed in this paper allows us to take into account behavioural effects and the change in the composition of employment and unemployment. Moreover, the authors contribute to the existing literature by considering a whole set of transitions across different labour market statuses and the related changes in income.

This chapter studies trends in income distributions and inequality in the European Union using data from the European Union Statistics on Income and Living Conditions. The author models the income distribution for each country under a Dagum distribution assumption and using maximum likelihood techniques. The author uses parameter estimates to form distributions for regions defined as finite mixtures of the country distributions. Specifically, the author studies the groups of ‘new’ and ‘old’ countries depending on the year they joined the European Union. The author provides formulae and estimates for the regional Gini coefficients and Lorenz curves and their decomposition for all the survey years from 2007 through 2011. The estimates of this study show that the ‘new’ European Union countries have become richer and less unequal over the observed years, while the ‘old’ ones have undergone a slight increase in inequality which is however not significant at conventional levels.

The analysis presented in this chapter defines three different synthetic measurements of disincentives for formal work: two standard measurements, namely, the tax wedge and the marginal effective tax rate (METR); and a new, innovative measurement called formalization tax rate (FTR). The novelty of the latter is that it measures disincentives stemming not only from labor taxation but also from benefit withdrawal due to formalization. A descriptive analysis across a large number of OECD and Eastern European countries reveals that the disincentives for formal work – when measured through the FTR – are especially high for low-wage earners. This suggests that formal work might not pay in this segment of the labor market, in particular for the so-called mini-jobs and midi-jobs (low-paying part-time work).

Another novelty of the chapter is its empirical approach. Using EU-SILC 2008 data and OECD Tax and Benefit data for six Eastern European countries (Bulgaria, the Czech Republic, Estonia, Latvia, Poland, and Slovakia), we match disincentives for formal work to individual observations in a large data set. Applying a probit regression, the analysis finds a significant positive correlation between FTR or METR and the incidence of being informal. In other words, controlling for individual and job characteristics, the higher the FTR or the METR that individuals are facing is, the more likely they are to work informally. The tax wedge, on the other hand, yields a negative correlation. This indicates that the tax wedge is not sufficiently capturing disincentives for formal work. We also conclude that in cross-country analysis, it might be more useful to use the tax wedge that applies to low-wage earners as opposed to average wage earners.

The purpose of this study is to show the importance of adequately considering quality measures within the use of composite indicators (CIs). Policy support often relies on high quality indicators. Often, the underlying data of relevant indicators are coming mainly from sample surveys. Obviously, the reliability of the indicators then heavily relies on the sampling design and other quality aspects.

Starting from the well-known work on sensitivity analysis of indicators, this study integrates the sampling process as an additional source of variability. The methodology is evaluated in a close-to-reality simulation environment using relevant and important surveys with different sampling designs. As an example, this study uses data related to the statistics of income and living conditions (SILC). The study is based on a design-based simulation framework.

In general, the normalisation method is dominating as source of the total variance of CI. In our study, we show that the sampling process also becomes rather relevant and generally dominates the influence of different weighting methods. We show that in some scenarios approximately 40 per cent of the variability in the sensitivity analysis comes from the sampling process. The quality of ranking derived from CIs then suffers considerably from the sampling design. When using data sources from different quality, e.g. in regional comparisons, one may expect some cases with biased CI values which may become useless for applications.

The impact of sampling heavily depends on the data gathering process. In case of sample data, the sampling designs play an important role. However, the design effect still depends on the variables taken into account and has to be considered carefully.

The findings show the importance of considering the quality framework the European Code of Practice also for CIs. This additional information shall foster to understand possible over- or misinterpretations of CIs, especially when deriving rankings from the indicators. Specialised statistical methods shall be integrated in future research, particularly when focusing on regional indicators.

CIs are often used for policy monitoring. In general, the data gathering process is not considered adequately by end-users. This becomes especially important when being interested in regional indicators. The present paper shows possible implications of the sampling designs on CI outcomes with the focus on comparative studies.

The purpose of this paper is to achieve a greater understanding of the transitions young adults experience into and out of the labour market and the influence that gender and married/cohabiting status have on employment careers.

The paper focuses on young adults (25-34 years old) in four European countries – Italy, the Netherlands, the UK and Norway – that are representative of different youth transition regimes. Using longitudinal data from EU-SILC survey (for the years 2006-2012) and event history analysis, the authors investigate the effect of the particular set of institutional features of each country, the effect of the cohort of entry and the effect of gender differences in determining transitions across labour market status.

Findings show that the filter exercised by the national institutions has a selective impact on the careers of young adults, with some institutional contexts more protective than others. In this respect, the condition of inactivity emerges as an interesting finding: on one side, it mainly involves women in a partnership, on the other side it is more common in protective youth regimes, suggesting that it may be a chosen rather than suffered condition.

The paper contributes to existing literature by: focusing on a specific category, young adults from 25 to 34 years old, which is increasingly recognised as a critical stage in the life course though it receives less attention than its younger counterpart (15-24); integrating the importance of family dynamics on work careers by analysing the different effects played by married/cohabiting status for men and women.

The purpose of this paper is to offer a contribution to our understanding of the changing relations of the middle classes with the Italian welfare state. The paper argues that the new interplay between public and private welfare is based on a very simplified analysis of Italian society.

The paper aims to integrate a variety of different theoretical approaches. The paper makes extensive use of the EU-SILC database, as well as the recently updated historic series of consumer studies undertaken by the Italian National Institute of Statistics. The data used in the paper were also drawn from the biennial cross-sectional Survey on Household Income and Wealth carried out by the Bank of Italy.

The analysis suggests that the problems of Italian society include not only a high incidence of poverty, but also increasing financial constraints for households placed between the established middle class and people in conditions of persistent poverty. The current public-private mix in service delivery appears less and less capable of protecting this social stratum against the growing risk of instability across all life domains, let alone of creating opportunities and fostering social mobility.

The paper explores some ways in which current politics of welfare have been designed with the view of fundamentally changing the welfare regime. It highlights how the public and private welfare mix has been purposefully organized in order to introduce a new model of social protection that aims to overcome certain specific characteristics of Southern European welfare states. It examines the sustainability of this model compared to the real living conditions of the Italian middle classes.

The Italian school-to-work transition (STWT) is astonishingly slow and long in comparison to the other EU countries. We analyze its determinants comparing the Italian case with Austria, Poland and the UK.

The analysis is based on a Cox survival model with proportional hazard. The smoothed hazard estimates allow us to identify the nonlinear path of the hazard function.

The authors reckon that the actual length of the transition to a stable job is around 30 months in Italy. Conversely, it is less than one year in the other countries. Women are particularly penalized, despite being on average more educated than men. Tertiary or vocational education at high secondary school strongly increases the hazard rate to a regular job. The smoothed hazard estimates suggest positive duration dependence at the beginning of the transition and slightly negative thereafter.

Stimulating economic growth and investing in education and training are important pre-conditions for shortening the transition.

Despite the duration of the STWT is one of the most important indicators to measure the efficiency of the STWT, it is not easy to measure. The authors build on their previous research work on this topic, but relaxing the assumption of a monotonic hazard rate and using the flexible baseline hazard approach to test for the existence of nonlinear duration dependence. Furthermore, they extend the analysis by including student-workers who attended a vocational path of education, in order to detect its effectiveness in allowing young people finding a job sooner.