Understanding Sectoral Differences in Downward Real Wage Rigidity: Workforce Composition, Institutions, Technology and Competition

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper can be downloaded without charge from http://www.ecb.europa.eu or from the Social Science Research Network electronic library at http://ssrn.com/abstract_id=1333606. Terms of use: Documents inIn 2009 all ECB publications feature a motif taken from the €200 banknote. UNDERSTANDING SECTORAL DIFFERENCES IN DOWNWARD Wage Dynamics NetworkThis paper contains research conducted within the Wage Dynamics Network (WDN). The WDN is a research network consisting of economists from the European Central Bank (ECB) and the national central banks (NCBs) of the EU countries. The WDN aims at studying in depth the features and sources of wage and labour cost dynamics and their implications for monetary policy. The specific objectives of the network are: i) identifying the sources and features of wage and labour cost dynamics that are most relevant for monetary policy and ii) clarifying the relationship between wages, labour costs and prices both at the firm and macro-economic level.The WDN is chaired by Frank Smets (ECB). Giuseppe Bertola (Università di Torino) and Julian Messina (Universitat de Girona) act as external consultants and Ana Lamo (ECB) as Secretary.The refereeing process of this paper has been co-ordinated by a team composed of Gabriel Fagan (ECB, chairperson), Philip Vermeulen (ECB), Giuseppe Bertola, Julian Messina, Jan Babecký (CNB), Hervé Le Bihan (Banque de France) and Thomas Mathä (Banque centrale du Luxembourg).The paper is released in order to make the results of WDN research generally available, in preliminary form, to encourage comments and suggestions prior to final publication. The views expressed in the paper are the author's own and do not necessarily reflect those of the ESCB. ECB Working Paper Series No 1006February 2009 Abstract 4 Non-technical summary 5

Loss aversion and the asymmetric transmission of monetary policy

“…While the former appears relatively more important for the US, both forms of rigidity are necessary to match the cross-sectional distribution of wages. A number of other studies deliver evidence in support of downward real wage rigidity, using large panels of OECD countries (e.g., Fabiani et al, 2006;Bauer et al, 2007;Du Caju et al, 2009;Messina et al, 2009Messina et al, , 2010Babecky et al, 2010). 17 Along with this substantial body of empirical evidence based on micro data, we also …nd contributions that reach similar conclusions by examining experimental data (e.g., Goette et al, 2004 andFarber, 2008), industry-level data (Holden and Wulfsberg, 2009) and macro data (Benigno et al, 2012).…”

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

“…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).…”

“…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.…”

“…Messina et al (2010) used a model to predict the log hourly wages with firm size, firm size squared, age class, female employment proportion and proportion of high-and lowskilled workers as predictors. Caju et al (2009a) used age, capital-labour ratio, profit elasticity and the percentage of blue-collar workers covered by single-employer collective agreements to model the log hourly earnings. Low-pay dynamics: In some countries, great changes in the distribution of earnings are observed (see, e.g., Dell'Aringa et al 2000; Geissberger 2009) with a widening of inequality and an increase in dispersion.…”

Simulation and quality of a synthetic close-to-reality employer–employee population

“…(2) Wage differentials and inter-industry wage differentials: differences in earnings for workers employed in different industries and occupations has long been recognized as an important issue for the labor market and several studies were carried out [8][9][10]16,32,36,42]. Pointner and Stiglbauer [36] uses several workplace-specific dummies 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 for the predictors.…”