Labour Market Institutions and Income Inequality

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. Abstract: The recent debate on trends in inequality in industrial countries has been marred by the lack of consensus about the relevant concept of inequality. Labour economists are concerned with inequality in earnings, macroeconomists with movements in the wage share, while policy-makers tend to focus on household income inequality. We provide a unifying framework to study the relationship between these three concepts of inequality and the way in which labour market institutions affect them. Institutions emerge as a key determinant of inequality, yet they play different roles depending on the extent to which they complement or substitute each other. As a result, we are able to propose a set of inequality minimizing institutions. Institutions that decrease inequality are, however, associated with higher unemployment, and our analysis allows us to quantify the magnitude of this trade-off. Terms of use: Documents in

Unions and Income Inequality: A Heterogeneous Panel Co‐integration and Causality Analysis

“…Notes 1 When the unemployment rate is very high, a large fraction of the population is receiving unemployment benefits and thus nearly the same income. In this (unrealistic) case, an increase in unemployment might cause a decrease in average income inequality simply because an increasing proportion of people have the same income (Checchi and Garc ıa-Peñalosa, 2008). 2 The standard time-series approach is to first differentiate the variables to remove the non-stationarity in the data and to avoid spurious results.…”

“…Similarly, the results of Calder on et al (2005) suggest, based on panel data for 121 developed and developing countries between 1970 and 2000, that union density has a significant equalizing effect on the distribution of income. Checchi and Garc ıa-Peñalosa (2008), in contrast, use unbalanced panel data for 16 industrial countries over the period 1969-2004 and find no significant relationship between unionization and income inequality. Scheve and Stasavage (2009) report results for an unbalanced panel of 13 industrialized countries over the period 1916-2000.…”

“…However, it is well known since the work of Atkinson and Brandolini (2001) that the Deininger-Squire data suffer from deficiencies such as sparse coverage, problematic measurements, and the combination of diverse data types into a single data set, thus limiting the comparabilitynot only across countries but also over time. Other studies therefore rely on Gini data from the Luxembourg Income Study (LIS) database (see, for example, Checchi and Garc ıa-Peñalosa, 2008;Gustafsson and Johansson, 1999;Mahler, 2004) or the World Income Inequality Database (WIID) (see, for example, Checchi and Garc ıa-Peñalosa, 2010). The problem with all these sources is the lack of consistent and continuous inequality data over time.…”

Do Interactions between Finance and Labour Market Institutions Affect the Income Distribution?

“…Empirical evidence is more mixed on the relationship between stronger Employment Protection Legislation (EPL) and wage dispersion. Checchi and Garcia-Peñalosa (2008) find no robust relationship, whereas Koeniger et al (2007) find evidence that the strictness of employment protection legislation is positively and significantly correlated with a more compressed wage structure on a sample of 11 OECD countries for the 1973-1998 period.…”

“…2 Income inequality and wage inequality are closely related. Checchi and Garcia-Peñalosa (2008) find that income inequality, measured by the Gini coefficient, can be expressed as a function of population proportions, the wage share and the wage differential between the skilled and unskilled workers. 3 The concept of financial development is, however, more complex and can be considered as multidimensional (Cihak et al, 2012).…”