Height data offer insights into the well-being of populations and historical periods for which other indicators are lacking. Researchers modeling historical heights have typically relied on the restrictive assumption of a normal (Gaussian) distribution, only the mean of which is affected by age,...

We use experimental data to disentangle signaling and budgetary effects of price on wine demand. The experimental design allow us to isolate in a simple and intuitive way the two effects. The signaling effect is present and nonlinear: it is strongly positive between EUR3 and EUR5, and...

A relevant question for the organization of large scale research assessments is whether bibliometric evaluation and informed peer review where reviewers know where the work was published, yield similar results. It would suggest, for instance, that less costly bibliometric evaluation might - at...

Recent literature on panel data has emphasized the importance of accounting for time-varying unobserved heterogeneity, which may stem either from time-varying omitted variables or macro-level shocks that affect each individual unit differently. In this paper, we propose a computationally...

We propose a strategy for ranking scientific journals starting from a set of available quantitative indicators that represent imperfect measures of the unobservable "value" of the journals of interest. After discretizing the available indicators, we estimate a latent class model for polytomous...

We consider estimation of a linear regression model using data where some covariate values are missing but imputations are available to fill in the miss- ing values. This situation generates a tradeoff between bias and precision when estimating the regression parameters of interest. Using only...

We investigate the relationship between ageing, cognitive abilities and retirement using the Survey on Health, Ageing and Retirement in Europe (SHARE), a household panel that offers the possibility of comparing several European countries using nationally representative samples of the population...

A procedure for efficient estimation of the trimmed mean of a random variable conditional on a set of covariates is proposed. For concreteness, the focus is on a financial application where the trimmed mean of interest corresponds to the conditional expected shortfall, which is known to be a...

This paper considers estimation of a linear regression model using data where some covariate values are missing but imputations are available to fill-in the missing values. The availability of imputations generates a trade-off between bias and precision in the estimators of the regression...