Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency

This article considers panel data models in the presence of a large number of potential predictors and unobservable common factors. The model is estimated by the regularization method together with the principal components procedure. We propose a panel information criterion for selecting the regularization parameter and the number of common factors under a diverging number of predictors. Under the correct model specification, we show that the proposed criterion consistently identifies the true model. If the model is instead misspecified, the proposed criterion achieves asymptotically efficient model selection. Simulation results confirm these theoretical arguments.     

Age related variation of salivary testosterone values in healthy Japanese males

Objective. We examined age associated variation in salivary testosterone values among Japanese males as well as anthropometric measurements.

Methods. Salivary samples were collected in pretreated sodium azide treated tubes. The first series: 15–79-year-old males (n = 99); two morning and two evening samples were collected at home for two days. The second series: 90-year-old males (n = 29); one morning sample was collected. Testosterone values were determined using an iodine125-based radioimmunoassay kit modified for saliva.

Results. Results show 1) a significant decrease in salivary testosterone values from 20s to 40s and older, 2) no significant decline after 40 through 90 years old, 3) no significant age-related differences in the degree of intraindividual diurnal fluctuation across age groups of 40–70s, and 4) higher BMI is associated with the lower salivary testosterone among 40–70s.

Conclusions. These results suggest that neither a constant decrease of salivary testosterone values or markedly reduced intraindividual fluctations are universal aspects of aging. Older males may maintain relatively high testosterone levels compared to younger men and a relatively ‘robust’ neuroendocrinological system.     

日本冲绳本岛临海民居风景防护林的构建及对中国新民居建设的启示

为加快推进中国农村新民居建设,完善相关配套建设措施,笔者借鉴日本在防灾减灾理论和方法方面处于世界前列,以法律的形式保证规划先行的经验,通过对冲绳本岛相关历史资料分析、民意调查和实地调查,以及福木起源的追溯,福木数量和防护林密度的测算等,论证了福木风景防护林映衬红瓦木造建筑为冲绳典型集落(即村庄、村落)特征.风景防护林的构建源自于村民抵御自然灾害的本能和政府保一方平安的责任意识,最后发展为保护村民生活环境、保障社会安定的基础.同时防护林使冲绳自然环境更显生态美观,促进了旅游业的兴旺,旅游已成为冲绳的支柱产业.     

Nonlinear regression modeling via regularized radial basis function networks

The problem of constructing nonlinear regression models is investigated to analyze data with complex structure. We introduce radial basis functions with hyperparameter that adjusts the amount of overlapping basis functions and adopts the information of the input and response variables. By using the radial basis functions, we construct nonlinear regression models with help of the technique of regularization. Crucial issues in the model building process are the choices of a hyperparameter, the number of basis functions and a smoothing parameter. We present information-theoretic criteria for evaluating statistical models under model misspecification both for distributional and structural assumptions. We use real data examples and Monte Carlo simulations to investigate the properties of the proposed nonlinear regression modeling techniques. The simulation results show that our nonlinear modeling performs well in various situations, and clear improvements are obtained for the use of the hyperparameter in the basis functions.     

Can Certified Care Workers Become Long-term Settlers?: Case Study of 49 Filipinos under the Japan–Philippines Economic Partnership Agreement

This article focuses on the first group of Filipino certified care worker (kaigo fukushishi) candidates who joined Japan's caregiving workforce under the Japan–Philippines economic partnership agreement (EPA) in 2009. The arrival of this group marked the start of the arrival of Filipinos specifically to work and study for 3 years in a designated care facility in order to take Japan's unique national board exam in 2013. Based on the follow-up research on 49 of the first group of 190 Filipino candidates, this study examines the lives of those passing the board exam who decided to remain and continue to work in Japan. Being able to transfer to various care facilities for better employment conditions, their quality of life in Japan has improved, while the issues regarding their residential status and reuniting with their family have yet to be resolved.     

The Finite-Sample Performance of White's Test for Heteroskedasticity Under Stochastic Regressors

We study the finite-sample properties of White's test for heteroskedasticity in stochastic regression models where explanatory variables are random and not given. We investigate by simulation the effect of non independence of explanatory variables and error term and heteroskedasticity on White's test. A standard bootstrap method in the computationally convenient form is found to work well with respect to the size and power.     

Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile

The purpose of assessing adverse events (AEs) in clinical studies is to evaluate what AE patterns are likely to occur during treatment. In contrast, it is difficult to specify which of these patterns occurs in each patient. To tackle this challenging issue, we constructed a new statistical model including nonnegative matrix factorization by incorporating background knowledge of AE-specific structures such as severity and drug mechanism of action. The model uses a meta-analysis framework for integrating data from multiple clinical studies because insufficient information is derived from a single trial. We demonstrated the proposed method by applying it to real data consisting of three Phase III studies, two mechanisms of action, five anticancer treatments, 3317 patients, 848 AE types, and 99,546 AEs. The extracted typical treatment-specific AE patterns coincided with medical knowledge. We also demonstrated patient-level safety profiles using the data of AEs that were observed by the end of the second cycle.     

A Simulation Study of White's Test for Heteroskedasticity in Fixed and Stochastic Regression Models

We study the finite-sample properties of White's test for heteroskedasticity in fixed and stochastic regression models. We compare by simulation White and bootstrap methods when the underlying distribution is symmetric as well as asymmetric. The superior performance of the bootstrap method in small samples does not hold when the underlying distribution is asymmetric.     

Stock return predictability: A factor-augmented predictive regression system with shrinkage method

To predict stock market behaviors, we use a factor-augmented predictive regression with shrinkage to incorporate the information available across literally thousands of financial and economic variables. The system is constructed in terms of both expected returns and the tails of the return distribution. We develop the variable selection consistency and asymptotic normality of the estimator. To select the regularization parameter, we employ the prediction error, with the aim of predicting the behavior of the stock market. Through analysis of the Tokyo Stock Exchange, we find that a large number of variables provide useful information for predicting stock market behaviors.