Laura Hospido

The Cycle of Earnings Inequality: Evidence from Spanish Social Security Data

We use detailed information on labor earnings and employment from social security records to document the evolution of earnings inequality in Spain from 1988 to 2010. Male earnings inequality was strongly countercyclical: it increased around the 1993 recession, showed a substantial decrease during the 1997-2007 expansion, and then a sharp increase during the recent recession. This evolution was partly driven by the cyclicality of employment and earnings in the lower-middle part of the distribution. We emphasize the importance of the housing boom and subsequent housing bust, and show that demand shocks in the construction sector had large effects on aggregate labor market outcomes.

Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages

In this paper I consider a model for the heterogeneity and dynamics of the conditional mean and the conditional variance of standarized individual wages. In particular, I propose a dynamic panel data model with individual effects both in the mean and in a conditional ARCH type variance function. I posit a distribution for earning shocks and I build a modified likelihood function for estimation and inference in a fixed-T context. Using a newly developed bias-corrected likelihood approach makes it possible to reduce the estimation bias to a term of order 1 over T squared. The small sample performance of bias corrected estimators is investigated in a Monte Carlo simulation study. The simulation results show that the bias of the maximum likelihood estimator is substantially corrected for designs that are broadly calibrated to the PSID. The empirical analysis is conducted on data drawn from the 1968-1993 PSID. I find that it is important to account for individual unobserved heterogeneity and dynamics in the variance, and that the latter is driven by job mobility. I also find that the model explains the non-normality observed in logwage data.

Retirement patterns of couples in Europe

AbstractIn this paper we study the retirement patterns of couples in a multi-country setting using data from the Survey of Health, Aging and Retirement in Europe. In particular we test whether women’s (men’s) transitions out of the labor force are directly related to the actual realization of their husbands’ (wives’) transition, using the institutional variation in country-specific early and full statutory retirement ages to instrument the latter. Exploiting the discontinuities in retirement behavior across countries, we find a significant joint retirement effect for women of 21 percentage points. For men, the estimated effect is insignificant. Our empirical strategy allows us to give a causal interpretation to the effect we estimate. In addition, this effect has important implications for policy analysis.JEL CodesJ26, D10, C21

The Spanish Productivity Puzzle in the Great Recession

While Spain has traditionally underperformed its European peers in terms of labor productivity, the trend reverses after 2007. The evolution of aggregate productivity in Spain during the Great Recession is shaped largely, albeit not exclusively, by the adverse conditions in the labor market. Using a longitudinal sample of Spanish manufacturing and services companies between 1995 and 2012, we show that the recent increase in Spanish aggregate productivity is also responsive to the behavior of total factor productivity (TFP) and to composition effects. By combining the information at firm level on balance sheet items, collective agreements and imports-exports, we are able to establish that a collective agreement at the firm level and access to external markets are positively related to TFP performance during the whole period. In addition, our estimates indicate that firm TFP was negatively correlated to the proportion of temporary workers during the expansionary period, 1995-2007, whereas the sign of that correlation reversed during the crisis, 2008-2012. Finally, we relate this sign reversal to the changing composition of temporary workers in the labor market.

Earnings inequality in Spain: new evidence using tax data

We use tax files from 2004 to 2010 to document the recent evolution of earnings inequality in Spain. We find that inequality went in parallel with the evolution of the unemployment rate during the period. This evolution is consistent with the evidence from Social Security records recently documented in Bonhomme and Hospido (2012). Quantitatively, the 90/10 percentile ratio of daily earnings experienced a 10% increase between 2007 and 2010, which is partly but not fully explained by changes in labour force composition. We also use the tax data to study the evolution of the gender earnings gap, and find that it has decreased throughout the distribution during the period. Lastly, we tentatively exploit the panel dimension of the data to explore the permanent and temporary dimensions of Spanish inequality.

Modelling heterogeneity and dynamics in the volatility of individual wages

In this paper I consider a model for the heterogeneity and dynamics of the conditional mean and the conditional variance of standarized individual wages. In particular, I propose a dynamic panel data model with individual effects both in the mean and in a conditional ARCH type variance function. I posit a distribution for earning shocks and I build a modified likelihood function for estimation and inference in a fixed-T context. Using a newly developed bias-corrected likelihood approach makes it possible to reduce the estimation bias to a term of order 1 over T squared. The small sample performance of bias corrected estimators is investigated in a Monte Carlo simulation study. The simulation results show that the bias of the maximum likelihood estimator is substantially corrected for designs that are broadly calibrated to the PSID. The empirical analysis is conducted on data drawn from the 1968-1993 PSID. I find that it is important to account for individual unobserved heterogeneity and dynamics in the variance, and that the latter is driven by job mobility. I also find that the model explains the non-normality observed in logwage data. (This abstract was borrowed from another version of this item.)

Job Changes and Individual-Job Specific Wage Dynamics

This paper develops an error components model that is used to examine the impact of job changes on the dynamics and variance of individual log earnings. I use data on work histories drawn from the Panel Study of Income Dynamics (PSID), that makes possible to do the distinction between voluntary an involuntary job-to-job changes. The potential endogeneity of job mobility in relation to earnings es circumvented by means of an instrument variable estimation method that also allows to control for unobserved individual-job specific heterogeneity.

Estimating Nonlinear Models with Multiple Fixed Effects: A Computational Note*

In this paper we consider estimation of nonlinear panel data models that include multiple individual fixed effects. Estimation of these models is complicated both by the difficulty of estimating models with possibly thousands of coefficients and also by the incidental parameters problem; that is, noisy estimates of the fixed effects when the time dimension is short contaminate the estimates of the common parameters due to the nonlinearity of the problem. We propose a simple variation of existing bias-corrected estimators, which can exploit the additivity of the effects for numerical optimization. We exhibit the performance of the estimators in simulations.

Estimating non-linear models with multiple fixed effects:a computational note

In this paper we consider estimation of nonlinear panel data models that include multiple individual fixed effects. Estimation of these models is complicated both by the diffi culty of estimating models with possibly thousands of coeffi cients and also by the incidental parameters problem; that is, noisy estimates of the fi xed effects when the time dimension is short contaminate the estimates of the common parameters due to the nonlinearity of the problem. We propose a simple variation of existing bias-corrected estimators, which can exploit the additivity of the effects for numerical optimization. We exhibit the performance of the estimators in simulations.