We examine wage bargaining when employers and labor unions do not always take all general equilibrium effects into account but learn a steady state. If agents do hardly consider general equilibrium effects, low real wages and low unemployment results. With an intermediate view, when partial...

We construct and estimate by maximum likelihood an equilibrium search model where wages are set by Nash bargaining and idiosyncratic productivity follows a geometric Brownian motion. The proposed framework enables us to endogenize job destruction and to estimate the rate of learning-by-doing....

Assuming a two-period model with endogenous choices of labour, education, and saving, it is shown to be second-best efficient not to distort the choice of education. In general this implies distorting the saving decision. Hence a strict order of policy priority is derived. Efficient tax policy...

This paper extends the job market signaling model of Spence (1973) by allowing firms to learn the ability of their employees over time. Contrary to the model without employer learning, we find that the Intuitive Criterion does not always select a unique separating equilibrium. When the Intuitive...

We use nine waves of BHPS data to examine interactions between spouses in terms of a behaviour with important health repercussions: cigarette smoking. Correlation between partners' behaviours may be due to correlated effects, as a consequence of matching or information revealed by others'...

The paper analyzes the contemporary organizational restructuring of production and work within firms. We emphasize the shift from a "Tayloristic" organization of work (characterized by significant specialization by tasks) to a "holistic" organization (featuring job rotation, integration of tasks...

Standard search models are unreliable for structural inference of the underlying sources of wage inequality because they are inconsistent with observed residual wage dispersion. We address this issue by modeling skill development and duration dependence in unemployment benefits in a random on...

This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage "once you understand OLS, you can work your...