M. Dolores Collado

Estimating dynamic models from time series of independent cross-sections

The purpose of this paper is to analyze the estimation of dynamic models from time series of independent cross-sections. The population is divided into groups with fixed membership (cohorts) and the cohort sample means are used as a panel subject to measurement errors. We propose measurement-error corrected estimators and analyze their asymptotic properties. We also calculate the asymptotic biases of the non-corrected estimators for the AR(1) model to check up to what extent the measurement-error correction is needed. Finally, we carry out the Monte Carlo simulations to evaluate the performance of our estimators in finite samples.

Separability and aggregate shocks in the life-cycle model of consumption: evidence from Spain

The purpose of this paper is to test the life-cycle permanent income hypothesis using an unbalanced panel from the Spanish family expenditure survey. Our model accounts for aggregate shocks and non-separability in the Euler equation among consumption goods, contrary to most of the Literature in this area. Our results do not indicate excess sensitivity of consumption growth to income.

Innovation and Job Creation and Destruction. Evidence from Spain

In this paper we examine the effect of innovation on job creation and job destruction in Spanish manufacturing. Our empirical analysis is based on firm-level longitudinal data from which we have information on employment and innovation activity. The estimation approach consists of a two-step procedure that takes into account the fact that firms endogenously choose positive, negative or zero growth in employment, in which the selection mechanism is an ordered probit. Our results point out the importance of innovation variables on employment growth: innovative firms create more jobs -and destroy fewer- than non-innovative, and the degree of technological effort has a strong positive effect on net employment creation.