Earlier literature on the gender pay gap has taught us that occupations matter and so do firms. However, the role of the firm has received little scrutiny; occupations have most often been coded in a rather aggregate way, lumping together different jobs; and the use of samples of workers...

This paper estimates a wage equation with three high-dimensional fixed effects, using a longitudinal matched employer-employee dataset covering virtually all Portuguese wage earners over a little more than two decades. The variation in log real hourly wages is decomposed into different...

This paper examines the longevity of entrants. We find size to be an important determinant of the chances of survival, this being particularly relevant to de novo entrants as compared to entry by established firms. Current size is also found to be a better predictor of failure than initial size....

Using a longitudinal matched employer-employee dataset for Portugal over the 1986-2007 period, this study analyzes the wage responses to aggregate labor market conditions for newly hired workers and existing workers within the same firm. Accounting for worker, firm, and job title heterogeneity,...

Earlier literature on the gender pay gap has taught us that occupations matter and so do firms. However, the role of the firm has received little scrutiny; occupations have most often been coded in a rather aggregate way, lumping together different jobs; and the use of samples of workers...

In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the...

Using a longitudinal matched employer-employee data set for Portugal over the 1986-2005 period, this study analyzes the heterogeneity in wages responses to aggregate labor market conditions for newly hired workers and existing workers. Accounting for both worker and firm heterogeneity, the data...