We develop an adjustment procedure to construct U.S. monthly time series of involuntary part-time employment stocks and flows from 1976 until today. Armed with these new data, we provide a comprehensive account of the dynamics of involuntary part-time work. Transitions from full-time to...

In this paper we investigate the impact of a reduction in the pension replacement rate on the schooling choice and on inequality. We develop an overlapping generations model in which individuals differ by their life expectancy and in the cost of attending schooling. Individuals optimally choose...

We investigate the differential impact that pension systems have on the labor supply and the accumulation of physical and human capital for individuals that differ by their learning ability and levels of life expectancy. Our analysis is calibrated to the US economy using a general equilibrium...

This paper develops a macroeconomic model that combines an incomplete-markets overlapping-generations economy with a job ladder featuring sequential wage bargaining, endogenous search effort of employed and non-employed workers, and differences in match quality. The calibrated model offers a...

Most macroeconomic data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper...

This paper proposes a new panel model of cross-sectional dependence. The model has a number of potential structural interpretations that relate to economic phenomena such as herding in financial markets. On an econometric level it provides a flexible approach to the modelling of interactions...

The estimation of structural dynamic factor models (DFMs) for large sets of variables is attracting considerable attention. In this paper we briefly review the underlying theory and then compare the impulse response functions resulting from two alternative estimation methods for the DFM....

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new parametric methodology for estimating factors from large datasets based on state space models and...