Thesis etd-11222018-100436 |
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Thesis type
Tesi di laurea magistrale
Author
MALAVASI, CHIARA
URN
etd-11222018-100436
Thesis title
Well-being inequality in Germany. An analysis of life expectancy and mortality in Germany after the reunification.
Department
ECONOMIA E MANAGEMENT
Course of study
ECONOMICS
Supervisors
relatore Prof. Fiaschi, Davide
Keywords
- Germany
- life expectancy
- mortality
- well-being
Graduation session start date
10/12/2018
Availability
Withheld
Release date
10/12/2088
Summary
The scope of this work is to analyse the main determinants of well-being and well-being inequality among German families after the fall of the Berlin Wall through the present day, with well-being being proxied by surviving probability and life expectancy; the analysis exploits the German Socio-Economic Panel (SOEP), a longitudinal survey on German private households and persons, collected by the German Institute for Economic Research (DIW).
The existence of a relation between income and mortality is well known since Preston (1975); moreover, during the last two decades, a variety of other factors have been recognised to have an impact on mortality rates, such as education (Murtin et alii, 2011, Case and Deaton, 2017), health status (OECD, 2017), residence (OECD, 2016), occupation (OECD, 2017) or gender. Thus, we first give an overview of the characteristics of the sample and we carry on various types of analysis to validate the use of survey data for the estimation of life expectancy; then, we move forward with the estimation of life expectancy among different population groups, identified by gender, residence, income, occupation status, education and household composition. Next, in the framework of developing a regression model of the surviving probability on its main determinants, we analyse the relation between income and health status and verify its presence through a difference in difference approach; then, we develop the model as a system of simultaneous equations, which takes into account the relation between income and health status, and present results obtained through the instrumental variable approach. Finally, the possibility of adopting a multilevel model is explored.
The existence of a relation between income and mortality is well known since Preston (1975); moreover, during the last two decades, a variety of other factors have been recognised to have an impact on mortality rates, such as education (Murtin et alii, 2011, Case and Deaton, 2017), health status (OECD, 2017), residence (OECD, 2016), occupation (OECD, 2017) or gender. Thus, we first give an overview of the characteristics of the sample and we carry on various types of analysis to validate the use of survey data for the estimation of life expectancy; then, we move forward with the estimation of life expectancy among different population groups, identified by gender, residence, income, occupation status, education and household composition. Next, in the framework of developing a regression model of the surviving probability on its main determinants, we analyse the relation between income and health status and verify its presence through a difference in difference approach; then, we develop the model as a system of simultaneous equations, which takes into account the relation between income and health status, and present results obtained through the instrumental variable approach. Finally, the possibility of adopting a multilevel model is explored.
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