Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

Organizational Changes and Job Satisfaction among Support Staff

ABSTRACT

The purpose of this study is to identify job satisfaction amongst support staff employed by a nonprofit company undergoing organizational changes. The Job Satisfaction Survey (JSS) scale was used to measure overall job satisfaction and was conducted among 38 workers and the data was analyzed using content analysis. The findings indicate that workers were satisfied with some sections of their job but also dissatisfied with some others, scoring an average job satisfaction amongst the participating groups. Factors such as good relations with colleagues, training opportunities, and work flexibility were identified to assist with increasing worker satisfaction. Further suggestions for enhancing employees’ job satisfaction are provided.     

On the relation between Hodges-Lehmann efficiency and Pitman efficiency

The relation between Hodges–Lehmann efficiency and Pitman efficiency is studied in the context of testing one-sided hypotheses about a real-valued parameter. It is first shown that for tests based on sums of independently and identically distributed observations local Hodges-Lehmann efficiency is equivalent to Pitman efficiency. Then, it is proved that this equivalence also carries over to tests based on two broad classes of M -estimators for the location problem. In all cases considered explicit formulas of the Hodges-Lehmann efficacies are obtained.     

On a Simultaneous Characterization of the Poisson and Bernoulli Distributions

Kimeldorf et al. (1981) established a simultaneous characterization of the Poisson and Bernoulli distributions. In this note two variants of the authors' characterizing condition are considered each of which is shown also to characterize simultaneously the Poisson and Bernoulli distributions.     

Optimal Inattention to the Stock Market With Information Costs and Transactions Costs

Information costs, which comprise costs of gathering and processing information about stock values and costs of deciding how to respond to this information, induce a consumer to remain inattentive to the stock market for finite intervals of time. Whether, and how much, a consumer transfers assets between accounts depends on the costs of undertaking such transactions. In general, optimal behavior by a consumer facing both information costs and transactions costs is state‐dependent, with the timing of observations and the timing and size of transactions depending on the state. Surprisingly, if the fixed component of the transactions cost is sufficiently small, then eventually, with probability 1, a time‐dependent rule emerges: the interval between observations is constant and on each observation date, the consumer converts enough assets to liquid assets to finance consumption until the next observation. If the fixed component of transactions costs is large, the optimal rule remains state‐dependent indefinitely.     

The use of GARCH models in VaR estimation

We evaluate the performance of an extensive family of ARCH models in modeling the daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.     

Reasons That Could Lead People to Divorce in an Evolutionary Perspective: Evidence from Cyprus

In the current research, we aimed to identify the reasons that could drive people to get a divorce. In Study 1, we employed qualitative research methods, and we identified 62 reasons that could potentially drive people to get a divorce. Using quantitative research methods, in Study 2 we classified these reasons into 7 broader factors. We found that being a harmful spouse was the most important factor for divorce, followed by incompatibility and in-law problems. We also found significant sex differences in several factors such as women indicating a higher willingness than men to divorce a harmful spouse. In addition, participants with children were less willing to divorce a harmful spouse than those who had no children. Finally, using second-order principal components analysis, we classified the 7 factors into 2 broader domains of reasons for getting a divorce.     

Prior distributions for variance parameters in a sparse-event meta-analysis of a few small trials

In rare diseases, typically only a small number of patients are available for a randomized clinical trial. Nevertheless, it is not uncommon that more than one study is performed to evaluate a (new) treatment. Scarcity of available evidence makes it particularly valuable to pool the data in a meta-analysis. When the primary outcome is binary, the small sample sizes increase the chance of observing zero events. The frequentist random-effects model is known to induce bias and to result in improper interval estimation of the overall treatment effect in a meta-analysis with zero events. Bayesian hierarchical modeling could be a promising alternative. Bayesian models are known for being sensitive to the choice of prior distributions for between-study variance (heterogeneity) in sparse settings. In a rare disease setting, only limited data will be available to base the prior on, therefore, robustness of estimation is desirable. We performed an extensive and diverse simulation study, aiming to provide practitioners with advice on the choice of a sufficiently robust prior distribution shape for the heterogeneity parameter. Our results show that priors that place some concentrated mass on small τ values but do not restrict the density for example, the Uniform(−10, 10) heterogeneity prior on the log(τ²) scale, show robust 95% coverage combined with less overestimation of the overall treatment effect, across varying degrees of heterogeneity. We illustrate the results with meta-analyzes of a few small trials.     

Strawderman-type estimators for a scale parameter with application to the exponential distribution

It is shown that Strawderman's [1974. Minimax estimation of powers of the variance of a normal population under squared error loss. Ann. Statist. 2, 190–198] technique for estimating the variance of a normal distribution can be extended to estimating a general scale parameter in the presence of a nuisance parameter. Employing standard monotone likelihood ratio-type conditions, a new class of improved estimators for this scale parameter is derived under quadratic loss. By imposing an additional condition, a broader class of improved estimators is obtained. The dominating procedures are in form analogous to those in Strawderman [1974. Minimax estimation of powers of the variance of a normal population under squared error loss. Ann. Statist. 2, 190–198]. Application of the general results to the exponential distribution yields new sufficient conditions, other than those of Brewster and Zidek [1974. Improving on equivariant estimators. Ann. Statist. 2, 21–38] and Kubokawa [1994. A unified approach to improving equivariant estimators. Ann. Statist. 22, 290–299], for improving the best affine equivariant estimator of the scale parameter. A class of estimators satisfying the new conditions is constructed. The results shed new light on Strawderman's [1974. Minimax estimation of powers of the variance of a normal population under squared error loss. Ann. Statist. 2, 190–198] technique.