And Yet It Moves: Intergenerational Mobility in Italy

Abstract

We estimate intergenerational income mobility in Italy using administrative data from tax returns. Our estimates of mobility are higher than prior work using survey data and indirect methods. The rankrank slope of parent-child income is 0.22, compared to 0.18 in Denmark and 0.34 in the United States. The probability that a child reaches the top quintile of the national income distribution starting from a family in the bottom quintile is 0.11. We uncover substantial geographical variation: upward mobility is much stronger in northern Italy, where provinces have higher measured school quality, more stable families, and more favorable labor market conditions. (JEL D31, J31, J62, R23)

Where is the Land of Hope and Glory? The geography of intergenerational mobility in England and Wales*

“…As this study does, several papers look further back and so are able to investigate the persistence of regional differences in mobility in the US. Focusing on educational attainment rather than income, Card, Domnisoru and Taylor (2018) Other studies have investigated geographical differences in intergenerational mobility in Sweden (Heidrich, 2017), Norway (Butikofer, Dalla Zuanna and Salvanes, 2018), Canada (Corak, 2019), Australia (Deutscher and Mazumder, 2019) and Italy (Acciari, Polo and Violante, 2019). Relative to the tax data used in these papers, the census data studied here offer a longer time series and a wider set of measures, though the sample is smaller, and lacks the detailed income and labour market data many of these studies have access to.…”

Where DESO Disappears: Spatial Inequality and Social Stratification at Labour Market Entry

“…Similarly in Italy, Acciari et al (2019) show the probability of a child born to parents in the bottom income quintile entering the top income quintile in adulthood ranges from 4.7% in Agrigento to 37.2% in Bolzano, against a national average of 10%. Spatial variation of this order of magnitude raises the possibility that country-level DESO estimates mask a similar degree of variation, a prospect also hinted at in previous research on youth labour market outcomes.…”

“…However a new strand of income mobility research increasingly suggests intergenerational reproduction processes do not operate in a uniform way within countries. In Canada (Corak 2019), Italy (Acciari, Polo, and Violante 2019), Sweden (Heidrich 2017), the United Kingdom (Bell, Blundell, and Machin 2018;Rohenkohl 2019;Carneiro et al 2020) and the United States (Chetty et al 2014;Bloome 2015;Chetty and Hendren 2018a;2018b), researchers have documented the existence of substantial sub-national heterogeneity in intergenerational income mobility levels. In the United States for example, Chetty et al (2014) show that the probability of a child in the bottom quintile of the national income distribution reaching the top quintile ranges from 4.4% in Charlotte to 12.9% in San Jose.…”

The importance of positional mobility for regional comparisons

“…Becker et al (2018); Becker and Tomes (1986)) if individuals use as a reference group the regional and not the national distribution. If that is not the case, the current practice of using the national distribution as reference group would be a correct way of measuring positional mobility, as Chetty et al (2015) and Acciari et al (2022) argue.…”

“…The rank-rank persistence coefficient measures the average degree of persistence at a specific rank of the outcome distribution. Since the work by Chetty et al (2014Chetty et al ( , 2015 it has become a common measure to compare mobility and persistence patterns across regions of a country, as it summarizes the persistence levels implied by the copula linking the origin and current distributions (see, for example, (Connolly et al, 2019;Corak, 2019;Heidrich, 2017;Acciari et al, 2022). Defining R i,t as the rank of individual i in the relevant distribution of the outcome at time t, and R i,t−1 as the rank of the same individual in the outcome distribution corresponding to time t − 1, the rank-rank persistence coefficient is the β coefficient of the following regression.…”