"A Distributional Framework for Matched Employer Employee Data"
Stéphane Bonhomme (University of Chicago), Thibaut Lamadon (University of Chicago) and Elena Manresa (MIT Sloan)

Paper Abstact 
We propose a framework to estimate earnings distributions and worker and firm unobserved heterogeneity on matched panel data. We introduce two models: a static model that allows for interaction effects between workers and firms, and a dynamic model that allows in addition for Markovian dynamics in earnings and mobility decisions. We establish identification in short panels. We develop a tractable two-step estimation approach where firms are classified into heterogeneous classes in a first step. Finally, we apply our method to Swedish matched employer employee panel data and report estimated earnings functions, sorting patterns, and variance decompositions.

Buenos Aires Seminars in Economics (Universidad de San Andrés and Universidad Torcuato Di Tella. BASE aims to bring to Buenos Aires top international researchers in the fields of labor economics, development, political economy, trade, among others, to interact with local academia.