The outsourcing of household tasks and labour contract in domestic work

This paper empirically illustrates that flexible work arrangements may be found unsuitable for outsourcing certain household tasks. For this purpose we analyse the relationship between tasks performed by domestic workers and the nature of the labour contract. Our study draws on a dataset from a sample of Portuguese domestic workers, and uses a fuzzy clustering approach to identify bundles of tasks together with contract features. The results achieved suggest a segmentation of domestic workers into four groups: two comprising carers, who enjoy a standard type of contract, and another two groups of cleaners with flexible and informal work arrangements. However, there is no distinct boundary between these groups. The overlapping that occurs between tasks and contracts justifies the use of the fuzzy approach to data analysis.FC

Employers’ perception of the role of higher education in Portugal: The varying solutions for skill problems

Higher education is under great pressure to provide skills that smooth graduates’ transition into the labour market, prepare them for the world of work and, ultimately, contribute to their employability. This supply-side perspective does not, per se, reflect employers’ view of the mission of higher education. Our research provides empirical evidence on how employers in Portugal perceive the role of higher education. It relies on data gathered in 2020 through an original online survey applied to N = 162 employers in Portugal. A k-means clustering distinguishes three groups of employers: those that acknowledge the autonomy of higher education; those who prefer to train their workforce; and those that blame higher education for their skill problems. The latter employers report skill shortages and propose different answers to mitigate them. Ultimately, the findings indicate that there is no one-size-fits-all solution for skill problems; firms have agency in finding appropriate solutions.info:eu-repo/semantics/publishedVersio

Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium

Measures of stock of skills alternative to human capital have raised fresh difficulties, especially in data managing. We propose to empirically compare the efficiency of a hierarchical cluster analysis and a fuzzy clustering in reducing discrete skill data. The outcomes of both methods are subsequently used to measure the impact of skills on earnings in addition to human capital. The proposed methodological comparison was made using an original dataset of retail bankers’ skills assessed by supervisors. Empirical evidence shows that the fuzzy approach is more efficient than the hierarchical clustering: the resulting clusters are fewer and easier to interpret. Furthermore, the earnings equation enriched with skill variables allowed us to correct the education premium, and provides information on monetary incentives related to individual skills. Our paper attempts to raise researchers’ and practitioners’ awareness of data reducing methods, and their implications for wage determinants.info:eu-repo/semantics/publishedVersio

Understanding firms compensation policy using fuzzy sets

It has been noted in the literature that firms rarely follow a single theoretical model when designing their compensation policy. This study illustrates how a fuzzy cluster analysis can be helpful in understanding the way employees are rewarded according to firms' specificity and market conditions. For this purpose, we convert linked employer-employee data (LEED) into firm level data prior to fuzzy clustering. Then, we explore the particular distribution of firms on the emerged fuzzy partition to sort them by compensation policy and, eventually, to examine the potential factors behind a specific option.info:eu-repo/semantics/acceptedVersio

Validation of archetypal analysis

We use an information-theoretic criterion to assess the goodness-of-fit of the output of archetypal analysis (AA), also intended as a fuzzy clustering tool. It is an adaptation of an existing AIC-like measure to the specifics of AA. We test its effectiveness using artificial data and some data sets arising from real life problems. In most cases, the results achieved are similar to those provided by an external similarity index. The average reconstruction accuracy is about 93%.info:eu-repo/semantics/acceptedVersio

An empirical comparison between grade of membership and principal component analysis

WOS:000321021700005 (Nº de Acesso Web of Science)It is the purpose of this paper to contribute to the discussion initiated by Wachter about the parallelism between principal component (PC) and a typological grade of membership (GoM) analysis. The author tested empirically the close relationship between both analysis in a low dimensional framework comprising up to nine dichotomous variables and two typologies. Our contribution to the subject is also empirical. It relies on a dataset from a survey which was especially designed to study the reward of skills in the banking sector in Portugal. The statistical data comprise thirty polythomous variables and were decomposed in four typologies using an optimality criterion. The empirical evidence shows a high correlation between the first PC scores and individual GoM scores. No correlation with the remaining PCs was found, however. In addtion to that, the first, PC also proved effective to rank individuals by skill following the particularity of data distribution meanwhile unveiled in GoM analysis

Firms’ wage policies: New evidence from linked employer-employee data

The research on wage policies has been triggered by the interest in identifying whether labour market or institutional forces shape the wage settings inside firms. This paper draws on linked employer-employee data and uses a fuzzy c-means clustering analysis to identify typical wage policies of medium and large firms in Portugal. Empirical evidence suggests that firms are segmented into four clusters that can be labelled according to wage rules as “Regulated”, “Asymmetric”, “Hierarchical” and “Discretionary”. The first two clusters comprise low wage firms, and are highly responsive to market conditions. The firms belonging to the latter clusters take advantage of discretionary power to differentiate the workforce. Our findings therefore illustrate different dimensions of wage flexibility. Furthermore, we found that employment flexibility and wage adjustments can coexist, and affects female, young, and blue collar workers in particular.FC

COVID-19 in Europe: From outbreak to vaccination

Background: COVID-19 is a pandemic of unprecedented proportions in recent human history. To date, the world has paid a high toll in terms of human lives lost, and on economic, financial, and social repercussions. In Europe, countries tried to mobilize all resources available to contain the COVID-19 effects, but the outcomes are diverse across countries. There have also been massive efforts geared towards finding safe and effective vaccines and to distribute them massively to the population. The main objective of this paper is to describe the COVID-19 prevalence in Europe. Secondly, it aims to identify epidemiological typologies allowing to distinguish the countries in terms of their response to the pandemic, and finally assess the effect of vaccination on pandemic control. Methods: The study covers 30 European countries: EU 27 in addition to Norway, Switzerland, and United Kingdom. Four epidemiological variables are analyzed at two distinct moments, at the end of 2020 and at the beginning of 2022: total number of cases per million, total number of deaths per million, total number of tests per thousand, and case fatality rate. In a second step, it uses a fuzzy approach, namely archetypal analysis, to identify epidemiological typologies, and positions countries by their response to the pandemic. Finally, it assesses how vaccination, stringency measures, booster doses and population age affect the case fatality rate, using a multiple regression model. Results: The outcomes unveil four epidemiological typologies for both periods. The clearest sign of change in the two periods concerns the case fatality rate that is found to be low in a single typology in 2020 but occurs in three typologies in 2022, although to different degrees. There is also statistical evidence of the positive impact of the primary vaccination on mortality reduction; however, the same does not hold for the booster dose and stringency measures. Conclusions: The study shows that primary vaccination is the most effective measure to reduce mortality by COVID-19 suggesting that vaccination provides hope for an end to the pandemic. However, a worldwide access to vaccination is needed to make this happen.info:eu-repo/semantics/publishedVersio

Beyond Harvesting: Digital Library Components as OAI Extensions

Reusability always has been a controversial topic in Digital Library (DL) design. While componentization has gained momentum in software engineering in general, there has not yet been broad DL standardization in component interfaces. Recently, the Open Archives Initiative (OAI) has begun to address this by creating a standard protocol for accessing metadata archives. It is proposed that this protocol be extended to act as the glue that binds together various components of a typical DL. In order to test the feasibility of this approach, a set of protocol extensions was created, implemented, and integrated as components of production and research DLs. The performance of these components was analyzed from the perspective of execution speed, network traffic, and data consistency. On the whole, this work has simultaneously revealed the feasibility of such OAI extensions for component interaction, and has identified aspects of the OAI protocol that constrain such extensions