76 research outputs found

    Group versus individual discrimination among young workers: a distributional approach

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    We evaluate the gender wage gap and the unexplained gender wage differential for workers 15-29 year old during the period 1990-1997, using a particularly rich set of data from the Italian Social Security System covering all individuals in the labour markets of two Italian provinces. We estimate separate earnings functions for men and women correcting for endogeneity of education and we evaluate gender discrimination by studying the entire distribution of the unexplained wage gap as suggested by Jenkins (1994). We evaluate discrimination against females by means of bivariate density functions. This innovation makes it possible to condition the density distribution on the marginal distribution of any characteristic and to evaluate more precisely the existence of group and individual discrimination. Our analysis suggests that discrimination is not evenly distributed among women, in relation to their characteristics; in particular, there is evidence of lower discrimination against highly educated females. Moreover in 1997, compared to 1990, discrimination increased in a appreciable way, affecting human capital rich females more significantly. While our work is based in a very local context the richness of the data and the methodological innovation give the results a wider application.wage differentials, wage discrimination, gender

    The flexibility penalty in a long-term perspective

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    In this paper we study the effect of flexibility on both wages and the likelihood of work stabilisation, by focusing on flexibility when entering the labour market and on periods of career interruption. Our main goal is to evaluate how having entered the labour market with fixed-term contracts or having experienced periods of interruption of work can affect the likelihood of being given a permanent contract and the level of wages received in subsequent jobs. Unlike other works in the existing literature, this study deals with female and male workers separately. The analysis is carried out using a dataset put together by the Istituto per lo Sviluppo della Formazione Professionale dei Lavoratori – ISFOL (Institute for the Development of the Professional Training of Workers) based on a sample of Italian workers. The dataset is representative of the Italian population and contains detailed information on work experience previous to workers’ present occupation with details on types of contracts and causes of career interruptions. In the first part of the paper, we examine density functions of monthly and hourly wages relative to contractual characteristics of first jobs and the number of job changes and work interruptions. In the second part of the paper, we estimate separate earnings functions for the sample of men and women with full-time permanent contracts. We correct for selection in full-time work by estimating a first-stage equation of the probability to have a permanent job and including the Mill’s ratio in the second-stage wage function. Estimates show that flexibility affects men and women differently, both in terms of levels of wages, and the likelihood of accessing permanent jobs. Some differences also emerge with regard to the causes of career interruptions.Flexibility, Access to permanent jobs, wage penalty

    Gender differences in productivity rewards in Italy: the role of human capital

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    In this paper we evaluate the gender wage gap component due to differences in characteristics’ rewards in Italy. The main focus is on the relationship between human capital characteristics and gender differences in rewards. We propose a methodology that combines the quantile regression analysis with non-parametric procedures for the estimation of the probability density functions of reward differentials in order to evaluate the evolution of the gap due to human capital characteristics. The analysis is carried out on Italian data taken from the latest available cross-section of the European Community Household Panel (2001). Our study suggests that education can be a good productivity signal and helps reduce the range of the gap; furthermore, highly-educated women experience lesser gender-based pay differences as the length of the employment relationship increases.Gender wage gap, human capital, distributional analysis

    The Distribution of the Gender Wage Gap in Italy: Does Education Matter?

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    In this paper we evaluate the wage gap due to differences in rewards to characteristics by studying the entire distribution of the individual unexplained wage gap. We use quantile regressions and an adaptation of the procedure suggested by Machado and Mata (2005) to derive the marginal distributions of predicted and counterfactual female wages. Then, we estimate probability distributions of unexplained wage gap conditional to observed characteristics. The methodology allows to evaluate the probability of women with different characteristics to experience any level of discrimination. The main focus of the paper is on the relationship between human capital characteristics and outcomes in differences in pay. In particular, we focus our attention on different educational levels. Under the hypothesis that women invest in education to signal their productivity, we should detect a lower wage gap -due to differences in rewards to characteristics- among high educated females. Our analysis suggests that education can be a good signal but not for all females. We also show that education interacts differently with other human capital characteristics, such as general experience acquired in the labour market. The analysis is carried out on Italian data drawn from the last available cross-section of the European Community Household Panel (2001)Gender Wage Gap, Distributive Analysis, Human Capital

    Female long-term labour market outcomes: The role of early-life abilities and education

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    We study how early-life cognitive skills, non-cognitive abilities, and family characteristics influence educational choices and affect later employment outcomes and wages. The analysis was carried out on a cohort of UK females observed at different life stages by adopting the British National Child Development Study database. Our findings provide evidence of how early-life abilities and family characteristics affect both the educational attainment and later labour market outcomes of female workers. However, we found that educational levels interact with early-life abilities, productive characteristics in general, and other characteristics, giving rise to different employment outcomes and income prospects conditioned on educational attainment. Occupational outcomes and wages of low-educated women are more sensitive to factors that are not strictly linked to productivity

    Relaciones laborales entre inventores y generaciĂłn de conocimiento: un estudio sobre innovaciĂłn patentada

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    This study explores the knowledge-creation process that arises from inventors’ working relationships and its impact on company innovation. Innovation is measured by a company’s patenting activities. Our analysis is based on an original database built using OECD micro data obtained from patent applications at the European Patent Office (EPO). An empirical analysis was carried out on a body of firms located in the Italian region of Veneto. Our results reveal that the inventors’ working relationships have a significant impact on a company’s innovation – innovation which is also dependent upon both geography and timescales. Inventors’ working relationships thus produce productivity effects, in terms of patenting activity, both in the short and long term and these impacts are also dependent upon geographical distance. Keywords: working relationships; knowledge creation; patenting activity; inventor productivity.Este estudio explora el proceso de generaciĂłn de conocimiento que surge de las relaciones laborales entre inventores y su impacto en la innovaciĂłn empresarial. La innovaciĂłn se mide por la cantidad de patentes de una empresa. Nuestro anĂĄlisis parte de una base de datos propia construida a partir de micro datos de la OECD obtenida a partir de solicitudes de patentes en la Oficina Europea de Patentes (EPO). Se realiza un anĂĄlisis empĂ­rico sobre un grupo de empresas ubicadas en la regiĂłn italiana de VĂ©neto. Nuestros resultados revelan que las relaciones laborales entre inventores tienen un impacto significativo en la innovaciĂłn empresarial, innovaciĂłn que tambiĂ©n depende tanto de la geografĂ­a como de la dimensiĂłn temporal. Las relaciones laborales entre inventores, por tanto, tienen un efecto sobre la productividad en tĂ©rminos de patentes, tanto a corto como a largo plazo, y este impacto depende tambiĂ©n de la distancia geogrĂĄfica

    Education and wage differentials by gender in Italy

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    In this paper we evaluate wage differentials in Italy combining gender and education perspectives. The main goal of the article is to verify whether the extent of the gender pay gap varies between highly- and low-educated workers, and whether or not the role played by gender differences in characteristics and in market rewards is similar in the two groups. We apply quantile regression analysis and an adaptation of the procedure suggested by Machado and Mata (2005) to evaluate the predicted wage gap at different levels of education, at different points of the female wage distribution scale. The analysis is carried out on the Italian sample of the last available year of the European Community Household Panel (2001). We show that the extent and the trend of the gap predicted across the female distribution is sharply different between groups with diverse educational levels. In the case of low-educated workers, although the predicted gap is largely explained by differences in rewards, lower levels of education or experience are however responsible for the gap, especially on the right-hand side of the distribution. On the contrary, highly-educated females have better characteristics than highly-educated men that partially compensate the rather high difference in returns, in particular at the extremes of the distribution. It thus follows that the unexplained part of the predicted gap reveals a glass ceiling effect only for more highly-educated females.human capital; gender wage differentials; quantile regressions

    Human capital, technology intensity, and growth in a regional context

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    In this study, we develop an empirical analysis of the pattern of growth in one of the Italian best performing regions\u2014the Veneto region\u2014focusing mainly on the role played by human capital employed in sectors with different technological intensities. To do so, we build up an original dataset by merging data available at a very local level (Local Labour Systems-LLS) with our elaborations on data from an employee-employer dataset made available by the Local Labour Agency. The latter dataset includes all employment spells in the Veneto region. This original datasets are used to construct aggregate variables and to estimate growth equations for the cross-section of the Venetian LLSs. The results underline how growth in the Veneto region is positively affected by human capital employed in medium and medium-low technology industries

    Human capital, technology intensity and growth in a regional context

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    This paper contributes to the vast literature on the regional application of endogenous growth theory. A well-known feature of capitalist growth and development is the vast and persistent divergence in per capita income growth between regions. These differences have been explained theoretically and empirically using neoclassical approaches emphasising increasing returns at a regional level, with reference, for example, to the development of industrial districts. The new economics of urban and regional growth look at the \u2018local\u2019 dimension focussing on the role of the so-called knowledge economy as an explanation for uneven development across regions. Within this heterogeneity, the operation of human capital and knowledge spillovers play roles in differentiating growth rates. The study of the concentration of a specific mix of economic activities and human capital, with a \u2018fine grain\u2019 focus at the local level, is a useful tool to understand growth and spatial differentials. In this study, we develop an empirical analysis of the pattern of growth in the Veneto region, focusing mainly on the role played by human capital employed in sectors with different technological intensities. To do so, we built up an original dataset by merging data available at a very local level (Local Labour Systems-LLS), which was produced by the National Institute of Statistics, with our elaborations on data from an employee-employer dataset made available by the Local Labour Agency (Veneto Lavoro). The latter dataset included all employment spells in the Veneto region. Our new dataset allows both definition of the human capital content of every worker and classification of firms according to their technological intensity. This dataset is used to estimate growth equations for the cross-section of the Venetian LLSs and to test the validity of different growth models. The results underline how growth in the Veneto region is positively affected by human capital employed not in high to medium-high technology industries, but in medium to medium-low ones

    A growth model with gender inequality in employment, human capital, and socio-political participation

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    This paper proposes an endogenous growth model in which gender inequality in employment has an important role in explaining different development dimensions such as socio-political participation, educational attainments, and working hours, in developed countries. Our model’s predictions are in line with some stylized facts observed across European countries: more equal societies have higher socio-political participation, devote less time to work, and present higher educational attainments and rates of economic growth than less equal ones. Our model suggests that promoting female employment must be accompanied by pro-family policies in order to sustain economic growth and improve quality of life
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