The Role of Professional Networks and Firm Hierarchies for Individual Careers and Wage Inequality

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The purpose of this project is to investigate, from a theoretical perspective, the role of professional networks and firm hierarchies for individual wage dynamics, income inequality and intergenerational mobility. Existing empirical literature reports growing wage inequality in developed economies, which largely takes the form of a widening wage gap between high and low skill workers (wage polarization). In this project we aim to investigate whether an increase in importance of social networks on the labor market can contribute to a rise in wage inequality and an increase in the positive correlation of wage income between generations. The innovative aspect of our project relative to the existing literature is a unified treatment of the evolution of professional networks and career paths of workers in hierarchical firms. In the first stage of the project we will develop a search and matching model of the labour market with heterogeneous skill groups, experience accumulation and hierarchical firms. In the second stage the evolution of professional networks will be endogenized capturing the fact that social ties are often established between coworkers on the same hierarchical level. Taking into account that social ties play a role in career development, the emerging homophily in the social network in this framework may intensify the endogenous sorting of high (low) skill workers to higher (lower) hierarchical positions within firms. A crucial goal of the project is to gain a sound understanding of the effect of these mechanisms on individual career prospects and wage inequality. Finally, it will be explored how the intergenerational correlation of wages is amplified if children have access to the professional network of their parents. Whereas we expect to provide characterizations of the equilibrium with endogenous promotion times in hierarchical firms by analytical means, we will rely on (agent-based) simulations of the models with endogenous networks in the second stage of the project.