Who Benefits from Marriage?*

The phenomenon that married men earn higher average wages than unmarried men – the marriage premium – is well known. However, the robustness of the premium across the wage distribution and the underlying causes of the marriage premium are unclear. Focusing on the entire wage distribution and employing recently developed semi‐non‐parametric tests for quantile treatment effects, our findings cast doubt on the robustness of the premium. We find that the premium is explained by selection above the median, whereas a positive premium is obtained only at very low wages. The causal effect at low wages may be attributable to employer discrimination.     

Non-causality in bivariate binary time series

In this paper we develop a dynamic discrete-time bivariate probit model, in which the conditions for Granger non-causality can be represented and tested. The conditions for simultaneous independence are also worked out. The model is extended in order to allow for covariates, representing individual as well as time heterogeneity. The proposed model can be estimated by Maximum Likelihood. Granger non-causality and simultaneous independence can be tested by Likelihood Ratio or Wald tests. A specialized version of the model, aimed at testing Granger non-causality with bivariate discrete-time survival data is also discussed. The proposed tests are illustrated in two empirical applications.     

Modeling the diffusion of scientific publications

This paper illustrates that salient features of a panel of time series of annual citations can be captured by a Bass type diffusion model. We put forward an extended version of this diffusion model, where we consider the relation between key characteristics of the diffusion process and features of the articles. More specifically, parameters measuring citations’ ceiling and the timing of peak citations are correlated with specific features of the articles like the number of pages and the number of authors. Our approach amounts to a multi-level non-linear regression for a panel of time series. We illustrate our model for citations to articles that were published in Econometrica and the Journal of Econometrics. Amongst other things, we find that more references lead to more citations and that for the Journal of Econometrics peak citations of more recent articles tend to occur later.     

Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris

This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via a spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error component specification. We generalize the approach of Wang and Kockelman (2007) and propose joint and conditional Lagrange multiplier tests for spatial autocorrelation and random effects for this spatial SUR panel model. The small sample performance of the proposed estimators and tests are examined using Monte Carlo experiments. An empirical application to hedonic housing prices in Paris illustrate these methods. The proposed specification uses a system of three SUR equations corresponding to three types of flats within 80 districts of Paris over the period 1990-2003. We test for spatial effects and heterogeneity and find reasonable estimates of the shadow prices for housing characteristics.     

Labor turnover before plant closure: “Leaving the sinking ship” vs. “Captain throwing ballast overboard”

Involuntary job loss in administrative data is commonly identified by exploiting the exogenous nature of mass layoffs or plant closures. However, prior knowledge can lead to selection in the labor turnover of distressed firms. This paper proposes a simple method to determine if and when selective turnover sets in. Based on a rich administrative data set for Austria, we show that separations up to two quarters before plant closure should be included in the treatment group. Moreover, we find that early leavers are associated with significantly lower costs of job loss due to plant closure.     

Wages and Ageing: Is There Evidence for the ‘Inverse‐U’ Profile?*

How individual wages change with time is one of the crucial determinants of labour market decisions including the timing of retirement. The focus of this paper is the relationship between age and wages with special attention given to individuals nearing retirement. The analysis is presented in a comparative context for Britain and Germany looking at two longitudinal data sets (BHPS and SOEP, respectively) for the years 1995–2004. We show the importance of cohort effects and selection out of employment which determine the downward‐sloping part of the ‘inverse‐U’ profile observed in cross‐sections. There is little evidence that wages fall with age.     

Birth-spacing,fertility and neonatal mortality in India: Dynamics,frailty, and fecundity

Using microdata on 30,000 childbirths in India and dynamic panel data models, we analyse causal effects of birth-spacing on subsequent neonatal mortality and of mortality on subsequent birth intervals, controlling for unobserved heterogeneity. Right censoring is accounted for by jointly estimating a fertility equation, identified by using data on sterilization. We find evidence of frailty, fecundity, and causal effects in both directions. Birth intervals explain only a limited share of the correlation between neonatal mortality of successive children in a family. We predict that for every neonatal death, 0.37 additional children are born, of whom 0.30 survive.     

Censored regression quantiles with endogenous regressors

This paper develops a semiparametric method for estimation of the censored regression model when some of the regressors are endogenous (and continuously distributed) and instrumental variables are available for them. A “distributional exclusion” restriction is imposed on the unobservable errors, whose conditional distribution is assumed to depend on the regressors and instruments only through a lower-dimensional “control variable,” here assumed to be the difference between the endogenous regressors and their conditional expectations given the instruments. This assumption, which implies a similar exclusion restriction for the conditional quantiles of the censored dependent variable, is used to motivate a two-stage estimator of the censored regression coefficients. In the first stage, the conditional quantile of the dependent variable given the instruments and the regressors is nonparametrically estimated, as are the first-stage reduced-form residuals to be used as control variables. The second-stage estimator is a weighted least squares regression of pairwise differences in the estimated quantiles on the corresponding differences in regressors, using only pairs of observations for which both estimated quantiles are positive (i.e., in the uncensored region) and the corresponding difference in estimated control variables is small. The paper gives the form of the asymptotic distribution for the proposed estimator, and discusses how it compares to similar estimators for alternative models.     

A simple ordered data estimator for inverse density weighted expectations

We consider estimation of means of functions that are scaled by an unknown density, or equivalently, integrals of conditional expectations. The “ordered data” estimator we provide is root n$n$ consistent, asymptotically normal, and is numerically extremely simple, involving little more than ordering the data and summing the results. No sample-size-dependent smoothing is required. A similarly simple estimator is provided for the limiting variance. The proofs include new limiting distribution results for functions of nearest-neighbor spacings. Potential applications include endogenous binary choice, willingness to pay, selection, and treatment models.     

Housing tenure choice and the dual income household

Housing tenure choice has been the subject of a very large literature. Many treatments have sought to estimate the effect of household income on the likelihood of home ownership. To date, no study has ever disaggregated the household income of married couples into the separate labor income components to see if one partner’s income has a different effect than the other. Using a derived likelihood function to control for censoring in the wife’s income, this paper estimates the effect of separate incomes on housing tenure choice, accounting for possible endogeneity of the wife’s income. To compare the results of this estimation method, the paper also estimates the standard IV models, 2SLS and IV probit. While the results show that there is no endogeneity of the wife’s income, ignoring the censoring of the endogenous variable (when a large fraction of observations are censored) can possibly lead to biased coefficient estimates. Also, this paper confirms the importance of total household income, which has a larger effect than the total disaggregated components.     

The motherhood wage gap: What about job amenities?

Women with children tend to earn lower hourly wages than women without children — a shortfall known as the ‘motherhood wage gap’. While many studies provide evidence for this empirical fact and explore several hypotheses about its causes, the impact of motherhood on job dimensions other than wages has scarcely been investigated. In order to assess changes in women's jobs around motherhood, I use data from the German Socio-Economic Panel and employ a first difference analysis. The results reveal that women when having children accommodate at their original employer primarily through adjustments in working hours. Yet, when changing the employer women adjust their jobs in several dimensions, such as different aspects of the work schedule (working hours, work at night or according to a flexible schedule) as well as the level of stress. Further analysis provides some limited support for the motherhood wage gap being explained by adjustments in the work conditions.