Ageing Population: Identifying the Determinants of Ageing in the Least Developed Countries

Population Research and Policy Review - The issue of population ageing is no longer exclusively centred on developed countries. Empirical studies have proven that the rise in the proportion of the...     

Deepwater Horizon oil spill exposure and child health: a longitudinal analysis

Population and Environment - The BP Deepwater Horizon oil spill (DHOS) created widespread concern about threats to health among residents of the Louisiana Gulf Coast. This study uses data from the...     

Ethnicity and fertility desires in Ghana

Journal of Population Research - The extant literature shows that fertility desires are an important indicator for understanding and predicting the future course of fertility; however, little work...     

Sample size calculations for noninferiority trials for time-to-event data using the concept of proportional time

Noninferiority trials intend to show that a new treatment is ‘not worse'' than a standard-of-care active control and can be used as an alternative when it is likely to cause fewer side effects compared to the active control. In the case of time-to-event endpoints, existing methods of sample size calculation are done either assuming proportional hazards between the two study arms, or assuming exponentially distributed lifetimes. In scenarios where these assumptions are not true, there are few reliable methods for calculating the sample sizes for a time-to-event noninferiority trial. Additionally, the choice of the non-inferiority margin is obtained either from a meta-analysis of prior studies, or strongly justifiable ‘expert opinion'', or from a ‘well conducted'' definitive large-sample study. Thus, when historical data do not support the traditional assumptions, it would not be appropriate to use these methods to design a noninferiority trial. For such scenarios, an alternate method of sample size calculation based on the assumption of Proportional Time is proposed. This method utilizes the generalized gamma ratio distribution to perform the sample size calculations. A practical example is discussed, followed by insights on choice of the non-inferiority margin, and the indirect testing of superiority of treatment compared to placebo.KEYWORDS: Generalized gamma, noninferiority, non-proportional hazards, proportional time, relative time, sample size     

An elastic-net penalized expectile regression with applications

To perform variable selection in expectile regression, we introduce the elastic-net penalty into expectile regression and propose an elastic-net penalized expectile regression (ER-EN) model. We then adopt the semismooth Newton coordinate descent (SNCD) algorithm to solve the proposed ER-EN model in high-dimensional settings. The advantages of ER-EN model are illustrated via extensive Monte Carlo simulations. The numerical results show that the ER-EN model outperforms the elastic-net penalized least squares regression (LSR-EN), the elastic-net penalized Huber regression (HR-EN), the elastic-net penalized quantile regression (QR-EN) and conventional expectile regression (ER) in terms of variable selection and predictive ability, especially for asymmetric distributions. We also apply the ER-EN model to two real-world applications: relative location of CT slices on the axial axis and metabolism of tacrolimus (Tac) drug. Empirical results also demonstrate the superiority of the ER-EN model.     

Industrial Policy Capture in Taiwan and South Korea

Whatever the theoretical merits of an industrial policy, in practice state incentives in support of infant industry are difficult to withdraw once they have been granted. Infant maturation is thereby delayed, resulting in ‘policy capture’ which confers rents on the assisted firms at the expense of consumers and/or taxpayers. The process is well-documented in poorly managed economies pursuing autarkic industrial policies (Auty, 1994a). This article examines evidence of policy capture in well-managed economies pursuing competitive industrial policies. Examples are drawn from the heavy (and chemical) industry drives of South Korea (hereafter Korea) and Taiwan, but the research is first set in the context of the industrial policy debate.     

Vendor Selection with Bundling*

Product bundling has become increasingly prevalent not only in consumer goods but also in the industrial sector. We study a purchasing problem in which a buyer must obtain necessary numbers of various stock items from a variety of vendors who charge different prices, have limited capacities and different levels of quality, and offer bundled products at discounted prices. We examine relationships among different bundling scenarios and show that the most general scenario is one in which free items are given to the buyer when sufficient quantities are purchased. We develop a mixed integer linear program that finds the purchasing strategy for the buyer that minimizes the total purchase cost. We present computational results which indicate that the problem is very tractable to solve optimally on a personal computer with standard optimization software. Finally, three extensions of the model are discussed.     

The Effects of Personality Type on Choices Made in Strategic Decision Situations*

Jung's personality-theory typology is used as a framework for exploring the effects of cognitive style on the type and radicalness of choices made in strategic decision situations. Extending the work of Haley and Stumpf [23], it is proposed that individuals with different personality-type preferences exhibit cognitive styles that are associated with specific biases in the pattern of choices they make. Through participation in an interactive behavioral simulation, 407 participants confronted over one hundred ill-structured decision situations and proposed whatever actions they perceived appropriate. The results support the hypothesized relationships that individuals with different personality-type preferences (i.e., sensing-thinking, intuition-thinking, sensing-feeling, and intuition-feeling) take patterns of actions that reflect specific biases (i.e., selective perception, positivity, social desirability, and reasoning-by-analogy, respectively). The implications of these findings for evaluating the likely effectiveness of strategic decisions and making senior-level staffing decisions are discussed.     

A Comment on Second-Order Polynomial Regression Models

In a recent article, Chatterjee and Greenwood [1] addressed the problem of multicollinearity in polynomial regression models. They noted that there is a high correlation between X and X²; therefore, a second-order polynomial model suffers the consequences of collinearity. Chatterjee and Greenwood [1] suggested a method they believe will overcome the problem. The contention of the present comment is that the suggested method accomplishes nothing and, indeed, has the potential to lead the unwary researcher to the wrong inference and misinterpretation of his results.