International Differences in Wage Inequality: A New Glance with European Matched Employer–Employee Data

Abstract

Using international harmonized matched employer-employee micro data from the European Structure of Earnings Survey for nine European countries, this article examines the origin of international differences in wage inequality. Wage inequality is highly correlated with the magnitude of inter-firm wage differentials. Workplace- and job-related factors generally have a more significant impact on within-country wage inequality than individual characteristics. European countries differ significantly not only in the extent of wage inequality but also in the relative influence of factors shaping wage inequality. Although cross-country differences in labour force composition play a part in the explanation, differences in the distribution and in labour market prices attached to workplace and job characteristics are the primary factors contributing to international differences in wage inequality. Copyright (c) Blackwell Publishing Ltd/London School of Economics 2008.

Nuevas funciones de la negociación colectiva y alteración de su marco normativo

“…Otra consecuencia importante de la presión sindical en el mercado de trabajo español es la tendencia a comprimir la dispersión salarial. Las diferencias salariales entre trabajadores, regiones y sectores se redujeron notablemente, por lo menos durante los años setenta y ochenta, como se ha podido constatar en diversos trabajos que han tratado de estudiar esta cuestión desde diversos puntos de vista (Davis y Haltinwanger, 1991;Lorences et al, 1995;Blau y Kahn, 1999;Palacio y Simón, 2004;Izquierdo y Lacuesta, 2006;Simón et al, 2006;Bande et al, 2007;Simón, 2010a;Simón, 2010b, y Cuadrado et al, 2011 ). Una consecuencia directa de la escasa dispersión salarial es que, combinada con altas tasas de desempleo, se convierte en un factor disuasorio de la movilidad laboral, lo cual a su vez influye negativamente sobre la eficiencia de la asignación de los recursos (Sánchez Molinero, 1999).…”

Quality Indicators for Statistical Disclosure Methods: A Case Study on the Structure of Earnings Survey

“…In summary, the most important analyses using SES data are related to Wage differentials and interindustry wage differentials: Differences in earnings for workers employed in different industries and occupations has long been recognised as an important issue for the labour market and several studies have been carried out (Caju et al , 2009aMessina et al 2010;Dybczak and Galuscak 2010;Simón 2010;Pointner and Stiglbauer 2010). Pointner and Stiglbauer (2010) use several workplacespecific dummy variables for the employee's occupation (ISCO 1) within the firm, the sector (NACE-2 digits) of the employer, for firm size and location (NUTS-1 digits), and a control for private ownership of the firm as predictors.…”

“…The microdata group pursues three directions of research one of which is on wage differentials and modelling of earnings. The SES data is one of the main data sources for this group, used by many authors (see, e.g., Caju et al 2010Caju et al , 2009aMessina et al 2010;Dybczak and Galuscak 2010;Simón 2010;Pointner and Stiglbauer 2010).…”

Determinants of hourly wages inequality in selected European metropolises. The results from the multilevel modelling

“…Such observations were provided both at the country (see e.g. Simón, 2010) and regional level (see e.g. De Groot et al, 2011).…”