Using a very large sample of matched author-referee pairs, we examine how referees' and authors' genders affect the referees' recommendations. Relying on changing author-referee matches, we find no evidence of gender differences among referees in charitableness, nor is there any effect of the...

We measure the impact of individuals' looks on life satisfaction and happiness. Using six data sets, from Canada, Germany, the United Kingdom, and the United States, we construct beauty measures in a number of different ways. Beauty raises happiness: A one standard-deviation change in beauty...

Using a very large sample of matched author-referee pairs, we examine how the gender of referees and authors affects the former's recommendations. Relying on changing matches of authors and referees, we find no evidence of gender differences among referees in charitableness toward authors; nor...

We measure the impact of individuals' looks on their life satisfaction or happiness. Using five data sets from the U.S., Canada, the U.K., and Germany, we construct beauty measures in different ways that allow putting a lower bound on the true effects of beauty on happiness. Personal beauty...

SUMMARY This paper considers estimation of censored panel‐data models with individual‐specific slope heterogeneity. The slope heterogeneity may be random (random slopes model) or related to covariates (correlated random slopes model). Maximum likelihood and censored least‐absolute...

This paper considers computation of fitted values and marginal effects in the Box-Cox regression model. Two methods, 1 the “smearing” technique suggested by Duan (see Ref. [10]) and 2 direct numerical integration, are examined and compared with the “naive” method often used in econometrics.

A rank estimator proposed by Aragón and Quiróz (1995) for the linear regression model with current-status data is shown to be -consistent and asymptotically normal. Monte Carlo simulations investigate the performance of the estimator and the proposed covariance matrix estimator.

This paper shows that the bootstrap does not consistently estimate the asymptotic distribution of the maximum score estimator. The theory developed also applies to other estimators within a cube-root convergence class. For some single-parameter estimators in this class, the results suggest a...