The paper introduces a new nonparametric estimator of the spectral density that is given in smoothing the periodogram by the probability density of Beta random variable (Beta kernel). The estimator is proved to be bounded for short memory data, and diverges at the origin for long memory data....

In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss. These measures result in a rule of thumb, a...

Almost sure convergence for ratios of delta functions establishes global and local strong consistency for a variety of estimates and data generations. For instance, the empirical probability function from independent identically distributed random vectors, the empirical distribution for...

We consider the problem of uniform asymptotics in kernel functional estimation where the bandwidth can depend on the data. In a unified approach we investigate kernel estimates of the density and the hazard rate for uncensored and right-censored observations. The model allows for the fixed...

In this paper we propose a test for the significance of categorical predictors in nonparametric regression models. The test is fully data-driven and employs cross-validated smoothing parameter selection while the null distribution of the test is obtained via bootstrapping. The proposed approach...

The literature analyzing the efficiency of financial institutions has evolved rapidly over the last twenty years. Most research has focused on the input side, analyzing either cost, input technical efficiency or input allocative efficiency, whereas comparatively fewer studies have examined the...

In this paper, we consider the estimation problem of a correlation coefficient between unobserved variables of interest. These unobservable variables are distorted in a multiplicative fashion by an observed confounding variable. Two estimators, the moment-based estimator and the direct plug-in...

There is a longstanding controversy over precisely what it is that banks produce. However, there is little evidence on the sensitivity of bank cost efficiency results when different output definitions are applied. This paper does exactly that. In particular, we compare nonparametric efficiency...

In a partial linear model, some non-stochastic linear restrictions are imposed under a multicollinearity setting. Semiparametric ridge and non-ridge type estimators, in a restricted manifold are defined. For practical use, it is assumed that the covariance matrix of the error term is unknown and...