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S45-S1 Social mobility & Inequality

Tracks
Special Session
Thursday, August 29, 2019
4:30 PM - 6:00 PM
IUT_Room 205

Details

Convenor(s): Alessandra Michelangeli / Chair: Alessandra Michelangeli


Speaker

Mr Bence Boje-Kovacs
Ph.D. Student
Kraks Fond – Institute for Urban Economic Research

Do your neighbours matter? Evidence from Building Demolitions in Denmark

Author(s) - Presenters are indicated with (p)

Bence Boje-Kovacs (p), Georges Poquillon

Discussant for this paper

Alessandra Michelangeli

Abstract

This paper provides evidence of the effect one’s environment has on their socio- economic outcomes. We study the forced moves of households out of their dwellings in the public housing sector in Denmark, preceding the closure of the building they live in. Specifically, we combine the exogenous tenure of displaced individuals with the characteristics of their neighbours to measure the short-term exposure to their environment at the building level. We find that being exposed to employed neighbours on the short-term significantly increases income and the likelihood of finding a job in the three years following the rehousing of displaced households. On the opposite, the short-term exposure to unemployed peers increases the chances to remain unemployed after relocation. Long-term exposure has a more substantial effect than short-term exposure, but is not longer-lasting.
Dr. Matthias Geissler
Post-Doc Researcher
Tu Dresden

Labor market integration of second generation immigrants

Author(s) - Presenters are indicated with (p)

Antje Fanghänel, Matthias Geissler (p)

Discussant for this paper

Alessandra Michelangeli

Abstract

Long-term integration of immigrants into societies of target countries necessitates integration into the labor market. Contrary to first generation immigrants, their offspring (second generation migrants) are subject to the same formal institutions as native peers, but empirical evidence suggests that they underperform in the labor market, what leads to persistent inequalities. Augmenting research on labor market entry and income differentials, we focus on under-employment and over-education between second generation immigrants and their native peers. Using German Microcensus data, we employ decomposition for binary outcomes to identify major sources of performance gaps. We find differences in labor market outcomes such as unemployment, underemployment and over-education. In line with previous literature, our decomposition results show that higher unemployment of second generation immigrants is mostly due to lower educational attainments. Furthermore there is a large unexplained variance, which hints at the persistence of informal institutions like values, norms and attitudes passed on within families. The unexplained variance shrinks when looking at underemployment and vanishes completely when focusing on over-education.
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Prof. Alessandra Michelangeli
Associate Professor
Università di Milano Bicocca - DEMS

Intergenerational social mobility in Italy and Sweden: the role of institutional factors

Author(s) - Presenters are indicated with (p)

Alessandra Michelangeli (p), John Osth , Umut Turk

Discussant for this paper

Alessandra Michelangeli

Abstract

The literature on Intergenerational Social Mobility (ISM) measure the dependency of children’s life chances on their parents. A number of contributions show that the degree of this dependency varies because of several factors specific to the person or to the society where the individual lives. Personal-specific factors include inherited abilities, gender, and ethnicity. Meanwhile, the degree of socio-economic development, the welfare system and other institutional factors shape society and are supposed to play a key role on upward mobility of young generations.
In this paper, we investigate upward mobility in Italy and Sweden. These are two European the extent to which city characteristics affect the likelihood of a generation to reach a better social status than previous generation in Italy and Sweden, two European countries characterized by very different institutional environment and welfare systems.
We use data provided by the National Institute of Statistics of the two countries containing information on offspring and their family background. We merge these data with provincial-level data (NUTS 3) on socio-economic conditions, and institutional factors.
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