Intergenerational Earnings Inequality in Italy : New Evidences and Main Mechanisms

This chapter provides new and detailed estimates of intergenerational earnings inequality in Italy and sheds light on mechanisms behind association of gross and net earnings between fathers and sons. Being not available panel data following subsequent generations in Italy, we make use of a recently built dataset that merges information provided by IT-SILC 2005 (i.e., the Italian component of EU-SILC 2005) with detailed information about the whole working life of those interviewed in IT-SILC recorded in the administrative archives managed by the Italian National Social Security Institute (INPS). This dataset allows us to rely on the two-sample two-stage least squares method (TSTSLS) to predict father earnings and, then, compute point in time intergenerational elasticities (IGE) and imputed rank to rank slopes. Furthermore, the characteristics of the dataset allow us to extend point in time estimates considering, for both sons and “pseudo-fathers”, average earnings in a 5-year period and observing sons at various ages, thus assessing the robustness of our estimates to attenuation and life cycle biases. Confirming previous evidence (Mocetti 2007; Piraino 2007), we find that Italy is characterized by a relatively high earnings inequality in cross country comparison – the size of the estimated β is usually over 0.40 – and the size of the intergenerational association increases when older sons and multi-annual averages are considered. We also investigate mechanisms behind this association both: i) including a set of possible mediating factors of the parental influence (e.g., sons’ education, occupation, labour market experience) among the control variables when regressing sons’ earnings on fathers’ earnings and ii) following the sequential decomposition approach suggested by Blanden et al. (2007). Results show that a limited share of the intergenerational association is attributable to sons’ educational and occupational attainment, while the largest part of the association is mediated by sons’ employability along the career, i.e., by their effective experience since the entry in the labour market. 1 Sapienza University of Rome Introduction In the last few decades, a growing body of international literature has focused on intergenerational transmission of social and economic advantages (and disadvantages). Economists have focused their attention on measuring the degree of income persistence across two generations and, more specifically, on the estimation of the intergenerational elasticity coefficient β that captures how much of the income difference between two parents still is preserved between their children (see Blanden, 2013). Due to constraints that effect women participation in the labour market, literature on intergenerational mobility usually focuses on the association between fathers and sons’ earnings. Even if reliable estimates of the intergenerational earnings elasticity (IGE) are available only for few nations, a generally accepted ranking has emerged from cross-country empirical studies on economic mobility as concerns developed countries (Solon, 2002; Corak, 2013; D'Addio, 2007; Bjorklund & Jantti, 2009; Blanden, 2013): Nordic European countries emerge as the most mobile, while the US, the UK and Southern European countries are reported to be the most unequal. According to the few available estimates (Mocetti, 2007, Piraino, 2007), Italy belongs to the low-mobility group. Actually, due to the unavailability of datasets jointly recording information on children and parents’ earnings or income, Italy has received a limited attention in the intergenerational mobility literature. Nonetheless, the IGE in Italy has been estimated in recent years by means of the two-sample two-stage least squares (TSTSLS) method, which allows researchers to overcome the lack of data regarding actual fathers’ incomes (Mocetti 2007; Piraino, 2007). More specifically, when long panel data recording income information for both generations of parents and children observed at middle ages are not available, the TSTSLS empirical approach exploits two independent samples of children and pseudo-fathers and some childreported retrospective information about fathers to obtain a prediction of fathers’ earnings in the first stage and the IGE in the second. Mocetti (2007) and Piraino (2007), following this approach by using various cross-sections of the Survey of Household Income and Wealth (SHIW) carried out by the Bank of Italy, computed point in time measures (i.e. concerning a single year) of intergenerational net earnings elasticity. They obtained estimated values amounting, respectively, to 0.50 and 0.44. An alternative measure of mobility, i.e. the rank to rank slope, has recently proved to be more robust across samples and specifications (Dahl & Delaire 2008; Chetty et al. 2014) and with respect to both life-cycle and attenuation bias (Gregg et al. 2014) than the IGE. However, to the best of our knowledge, no studies have so far estimated rank to rank slopes for Italy Therefore, the aim of this chapter is to provide new estimates of the earnings mobility in Italy by means of a proper dataset, that, compared to the SHIW, allows us to observe children and pseudo-fathers earnings for more than one-year. To this aim, we use the AD-SILC dataset, that has been developed merging information provided in IT-SILC (2005) – where a retrospective section on parental characteristics is recorded – with information on the whole working history since the entry in the labour market of all individuals interviewed in IT-SILC provided by the administrative archives managed by the Italian National Social Security Institute (INPS). Thus, we can exploit the longitudinal nature of these data to apply the TSTSLS procedure, computing multi-year earnings values for both generations. INPS data record earnings gross of taxes and contribution paid by the worker, thus they allow use to compute indexes of intergenerational inequality of gross earnings, thus computing the size of income persistence produced by the labour market, before the redistributive effect of taxes and transfers. In order to compare our results with those provided by Mocetti (2007) and Piraino (2007), who focused on net 2 More specifically, intergenerational elasticity capture both the re-ranking across generations and the differences in the amount of inequality within each generation (due to changes in income distribution across generations). Thus, the IGE is very sensitive to changes in inequality and it may not capture changes in positional income mobility only, but also the evolution of cross-sectional earnings inequality (Lefranc, 2011). This may be problematic when we want to compare the degree of intergenerational mobility across countries with different level of cross-sectional inequality. earnings, we also reconstructed net earnings for both generations to estimate the intergenerational elasticity of net earnings. However, the aim of this chapter does not limit to compute summary measures of intergenerational inequality (as the IGE or the rank to rank slope). Indeed, we also aim at assessing which are the main mechanisms behind the correlation between parents’ and children’ earnings. In particular, we aim at analysing whether the bulk of intergenerational inequality is explained by educational and occupational attainments of children coming from different backgrounds or a significant association between parents’ and children’ earnings emerges also controlling for these children’s outcomes. To this end, we first compare our baseline results adding in our estimates of the link between parents’ and children’s earnings further variables, that can mediate the relationship between fathers’ circumstances and children earnings, namely children’s, education, contractual arrangement and experience in the labour market. Moreover, we apply a sequential decomposition approach (Blanden et al. 2007; Hirvonen, 2010; Buchner at al., 2012; Macmillan, 2013; Blanden et al, 2014) to disentangle the share of the IGE explained by various children’s characteristics that might be affected by parental circumstances. According to the Becker and Tomes theoretical framework (1979 and 1986), when capitals markets are not perfect and public investment in education does not fully compensate for them, investment in children human capital by parents coming from disadvantaged background are limited, since parents face liquidity constraints. Literature on intergenerational mobility based on this theoretical framework recognizes education as the main transmission mechanism of persistence across generations: children coming from a more disadvantaged background receive a lower level of investments education and, consequently, later in life they will have less job opportunity and lower earnings. However, this “human capital view” has been challenged by some scholars that recognize the importance of a “direct” effect of family background on earnings, not mediated by “formal” educational attainments. (e.g., Breen & Goldthorpe, 2001; Goldthorpe & Jackson, 2008; Franzini & Raitano, 2009; Franzini et al, 2013; Hudson and Sessions 2011, Raitano & Vona, 2015). The decomposition approach, as mentioned, measures to which extent the IGE is explained by sons’ characteristics (e.g. education or occupation). The explained part is measured accounting for both the relationship between parent’s earnings and children’s characteristics and the return to those characteristics in the labour market. Thus, the intergenerational elasticity can be decomposed in two parts: the indirect effect of parental background acting through children’s endowment of different characteristics and a residual direct effect not explained by these characteristics. The reminder of this chapter is structured as follows. Section 1.1 presents the main findings of the empirical literature on intergenerational mobility, focusing on the differences between the empirical a