A new likelihood approach is proposed for the problem of semiparametric estimation of a conditional distribution or density under censoring. Consistency and asymptotic normality for two versions of the maximum likelihood estimator of the parameter vector in the single index model are proved. The...

We present a new method for estimating the frontier of a multidimensional sample. The estimator is based on a kernel regression on high order moments. It is assumed that the order of the moments goes to infinity while the bandwidth of the kernel goes to zero. The consistency of the estimator is...

Motivated by the optimality condition of a quantile loss minimization problem, a new family of closed-form density estimators based on truncated means is developed and found to achieve smaller mean squared errors in estimating the tails of the normal and gamma distributions when compared to the...

This paper investigates how students' collegiate athletic participation affects their subsequent labor market success. It uses newly developed distributional tests to establish that the wage distribution of former college athletes is significantly different from non-athletes and that athletic...

In the common nonparametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes obtained from the standardized nonparametric residuals under the null hypothesis (of...

The authors revisit the debt overhang question. They first use nonparametric techniques to isolate a panel of countries on the downward sloping section of a debt Laffer Curve. In particular, overhang countries are ones where a threshold level of debt is reached in sample, beyond which (initial)...

Employing power kernels suggested in earlier work by the authors (2003), this paper shows how to re.ne methods of robust inference on the mean in a time series that rely on families of untruncated kernel estimates of the long-run parameters. The new methods improve the size properties of...

We revisit the debt overhang question. We first use non-parametric techniques to isolate a panel of countries on the downward sloping section of a debt Laffer curve. In particular, overhang countries are ones where a threshold level of debt is reached in sample, beyond which (initial) debt ends...

In the common nonparametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes obtained from the standardized nonparametric residuals under the null hypothesis (of...