Terrorism and travel advisory effects on international tourism

The paper applies dynamic panel modeling to investigate the impact of terrorism and travel advice on global tourism. Annual arrivals data for 49 destinations and 15 leading countries of origin for the period 2010–2014 are used. Results indicate that casualties or fatalities from terrorism, absent travel advice, significantly reduce tourism demand. However, casualties (fatalities) combined with travel advice have a relatively larger adverse impact on tourism demand. The effects identified, however, are sensitive to country characteristics. Casualties (fatalities) as well as travel advice significantly weaken tourism demand for low-income countries but have no significant effect in high-income countries.     

A central limit theorem for the Hellinger loss of Grenander‐type estimators

We consider Grenander‐type estimators for a monotone function , obtained as the slope of a concave (convex) estimate of the primitive of λ. Our main result is a central limit theorem for the Hellinger loss, which applies to estimation of a probability density, a regression function or a failure rate. In the case of density estimation, the limiting variance of the Hellinger loss turns out to be independent of λ.     

Trade Credit in Small and Medium Size Firms: An Application of the System Estimator With Panel Data

Financing through suppliers is a subject that has been little studied in the economic literature in general and in corporate finance in particular. Although several hypotheses have been put forward to explain the different reasons behind this phenomenon, trade credit is not based on a general theory. This study provides empirical evidence about factors determining the use of trade credit for a sample of small and medium size firms, which are potentially the firms that would follow this financing route, since they are more rationed in credit markets. Using a panel of Canary-Island firms from 1990 to 1996, and by means of specifications with the system estimator, results reveal that trade credit leads to a reduction in asymmetric information between firms and their financial backers, as well as in transaction costs. Furthermore, we confirm the theory that companies with easier access to institutional finance act as a credit channel for those with greater difficulties to obtain external funds.     

Some asymptotic results of a non‐parametric conditional mode estimator for functional time‐series data

We consider the estimation of the conditional mode function when the covariates take values in some abstract function space. The main goal of this paper was to establish the almost complete convergence and the asymptotic normality of the kernel estimator of the conditional mode when the process is assumed to be strongly mixing and under the concentration property over the functional regressors. Some applications are given. This approach can be applied in time‐series analysis to the prediction and confidence band building. We illustrate our methodology by using El Nio data.     

The asymptotic distribution of Nagar's bias-adjusted TSLS estimator under partial identification

The asymptotic distribution of the Nagar bias-adjusted two-stage-least-squares estimator is studied under the assumption of partial identification when the number of instruments increases at the same rate as the sample size and the errors are normally distributed.     

A new process capability index

In this paper a new process capability index (C _pq ) has been introduced, which is easy to compute and performs well when compared with its natural competitor (C _pm ). Work done while he was Lukacs Visiting Professor on leave from the University of Maryland.     

Multinomial distributions applied to random sampling of particulate materials

When sampling a batch consisting of particulate material, the distribution of a sample estimator can be characterized using knowledge about the sample drawing process. With Bernoulli sampling, the number of particles in the sample is binomially distributed. Because this is rarely realized in practice, we propose a sampling design in which the possible samples have a nearly equal mass. Expected values and variances of the sample estimator are calculated. It is shown that the sample estimator becomes identical to the Horvitz–Thompson estimator in the case of a large batch-to-sample mass ratio and a large sample mass. Simulations and experiments were performed to test the theory. Simulations confirm that the round-off error due to the discrete nature of particles is negligible for large sample sizes. Sampling experiments were carried out with a mixture of PolyPropylene (PP) and PolyTetraFluorEthylene (PTFE) spheres suspended in a viscous medium. The measured and theoretical variations are in good agreement.     

Right censoring in a discrete life model

Although there are many sophisticated models for estimation of failure rate based on censored data in continuous distributions, not much work has been done in the discrete case. We introduce a discrete model for life lengths and consider its properties. For this model, we derive the corresponding maximum likelihood estimators of the parameters under Type I and Type II right-censoring. Received May 2000     

An application of approximate finite sample results to parameter estimation in a linear errors-in-variables model

In the simple errors-in-variables model the least squares estimator of the slope coefficient is known to be biased towards zero for finite sample size as well as asymptotically. In this paper we suggest a new corrected least squares estimator, where the bias correction is based on approximating the finite sample bias by a lower bound. This estimator is computationally very simple. It is compared with previously proposed corrected least squares estimators, where the correction aims at removing the asymptotic bias or the exact finite sample bias. For each type of corrected least squares estimators we consider the theoretical form, which depends on an unknown parameter, as well as various feasible forms. An analytical comparison of the theoretical estimators is complemented by a Monte Carlo study evaluating the performance of the feasible estimators. The new estimator proposed in this paper proves to be superior with respect to the mean squared error.     

Distributional and Inferential Properties of the Estimated Precision Cp Based on Multiple Samples

Process precision index C_p has been widely used in the manufacturing industry to provide numerical measures on process potential. Pearn et al. (1998) considered an unbiased estimator of C_p for one single sample. They showed that the unbiased estimator is the UMVUE. They also proposed an efficient test for C_p based on one single sample, and showed that the test is the UMP test. In this paper, we consider an unbiased estimator of C_p for multiple samples. We show that the unbiased estimator is the UMVUE of C_p, which is asymptotically efficient. We also consider an efficient test for C_p, and show that the test is the UMPtest for multiple samples. The practitioners can use the proposed test on theirin-plant applications to obtain reliable decisions.