scholarly journals Earnings Dynamics in Germany

2021 ◽  
Author(s):  
Ana Sofia Pessoa
Keyword(s):  
Earnings Dynamics

Family, Community and Long-Term Socioeconomic Inequality: Evidence from Siblings and Youth Peers

2020 ◽  
Author(s):  
Paul Bingley ◽  
Lorenzo Cappellari ◽  
Konstantinos Tatsiramos
Keyword(s):  
Life Cycle ◽  
Socioeconomic Inequality ◽  
Working Life ◽  
Community Effects ◽  
Men And Women ◽  
Sibling Correlation ◽  
Earnings Dynamics ◽  
Sibling Correlations ◽  
Youth Community

Abstract Using administrative data for the population of Danish men and women, we develop an empirical model which accounts for the joint earnings dynamics of siblings and youth community peers. We provide the first decomposition of the sibling correlation of permanent earnings into family and community effects allowing for life cycle dynamics and extending the analysis to consider other outcomes. We find that family is the most important factor influencing sibling correlations of earnings, education and unemployment. Community background matters for shaping the sibling correlation of earnings and unemployment early in the working life, but its importance quickly diminishes.

scholarly journals Reputation Cycles and Earnings Dynamics

2018 ◽  
Author(s):  
Boyan Jovanovic ◽  
Julien Prat
Keyword(s):  
Earnings Dynamics

Employment Transitions and Earnings Dynamics in the SAGE Model

2017 ◽  
pp. 351-379
Author(s):  
Asghar Zaidi ◽  
Maria Evandrou ◽  
Jane Falkingham ◽  
Paul Johnson ◽  
Anne Scott
Keyword(s):  
Earnings Dynamics ◽  
Employment Transitions

scholarly journals A Distributional Framework for Matched Employer Employee Data

Econometrica ◽  
2019 ◽  
Vol 87 (3) ◽  
pp. 699-739 ◽  
Author(s):  
Stéphane Bonhomme ◽  
Thibaut Lamadon ◽  
Elena Manresa
Keyword(s):  
Firm Heterogeneity ◽  
Unobserved Heterogeneity ◽  
Structural Models ◽  
Static Model ◽  
Small Contribution ◽  
Nonlinear Interactions ◽  
Worker Mobility ◽  
Earnings Dynamics ◽  
Earnings Dispersion ◽  
Employee Data

We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural models of wages and worker mobility. We establish identification in short panels, and develop tractable two‐step estimators where firms are classified in a first step. Applying our method to Swedish administrative data, we find that log‐earnings are approximately additive in worker and firm heterogeneity. Our estimates imply the presence of strong sorting patterns between workers and firms, and a small contribution of firms—net of worker composition—to earnings dispersion. In addition, we document that wages have a direct effect on mobility, and that, beyond their dependence on the current firm, earnings after a job move also depend on the previous employer.

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