THEORIES OF RISK: TESTING INVESTOR BEHAVIOR ON THE TAIWAN STOCK AND STOCK INDEX FUTURES MARKETS

This article considers four utility functions—concave, convex, S‐shaped, and reverse S‐shaped—to analyze the behavior of different types of investors on the Taiwan stock index and its corresponding index futures. Using stochastic dominance (SD) rules, we show that the existence of all four investor types is plausible. Risk averters prefer spot to futures, whereas risk seekers prefer futures to spot. Investors with S‐shaped utility functions prefer spot (futures) to futures (spot) when markets move upward (downward). Investors with reverse S‐shaped utility functions prefer futures (spot) to spot (futures) when markets move upward (downward). We show that both spot and futures markets can exist when only risk averters are present, but futures can dominate spot only if there is some risk‐seeking behavior. These results are robust with respect to subperiods, spot returns including dividends, and diversification. (JEL C14, G12, G15)     

Challenges of social workers' involvement in the recovery of the 5.12 Wenchuan Earthquake in China

This article explores the challenges of social workers' involvement in recovery work of the 5.12 Wenchuan Earthquake (12 May 2008). Six social workers working in three social work stations in Sichuan, China, were asked to report the challenges they faced in working with disaster survivors. Findings reveal that the social workers faced many challenges. These include lack of government support, low professional status of social work, rapid changes in the social environment in disaster‐affected areas, lack of supervision, lack of cooperation and coordination among social service agencies, and lack of experience and knowledge in working with disaster survivors. The practical, educational and policy implications of the findings are addressed.     

A modified common factor model for modelling mortality jointly for both sexes

Journal of Population Research - There is an increasing attention on the joint modelling of multiple populations. Populations are related in several ways, such as neighbouring countries, females...     

Family Control and Stock Market Reactions to Innovation Announcements

Although family firms are common around the world, studies on family‐controlled business are limited. Prior studies mainly focused on the influences of family ownership on overall firm performance, and the results were mixed. In this study we attempted to explore the impacts of family ownership on innovation by examining the association of family control and stock market reactions to innovation announcements. We found that firms with greater family control experienced significantly more negative stock market reactions to innovation announcements. The results further indicated that divergence of cash flow and voting rights was strongly and negatively correlated with announcement‐period abnormal returns. In addition, the findings suggested a significantly positive moderating effect of institutional ownership. The conclusions were robust under various measures of family control, and remained valid after controlling other influential factors for stock market reactions to innovation announcements.     

A simple procedure for the selection of significant effects

Summary.  Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.     

Improved likelihood-based inference for the stationary AR(2) model

An improved likelihood-based method based on Fraser et al. (1999) is proposed in this paper to test the significance of the second lag of the stationary AR(2) model. Compared with the test proposed by Fan and Yao (2003) and the signed log-likelihood ratio test, the proposed method has remarkable accuracy. Simulation studies are performed to illustrate the accuracy of the proposed method. Application of the proposed method on historical data is presented to demonstrate the implementation of this method. Furthermore, the method can be extended to the general AR(p) model.     

Cow, compass, bang

Do cows really sense the earth's magnetic field and point north? Yan Wong had five minutes of film time to explain the statistics of finding out.     

Sick building syndrome and perceived indoor environmental quality: A survey of apartment buildings in Hong Kong

The outbreak of a highly communicable disease, SARS, in Asia in 2003 has revealed the health risk of living in a high-density environment. To show the important connection between human health and environmental quality, this study surveys the prevalence of sick building syndrome (SBS) among apartment residents and their evaluation of indoor environmental quality (IEQ). Based on a sample of 748 households living in Hong Kong, two interesting findings are revealed: (1) nasal discomfort was the commonest home-related SBS symptom despite the absence of any central ventilation system in apartment buildings; (2) noise, rather than ventilation, was the major IEQ problem perceived by residents. Our statistical analysis further showed that residents with SBS symptoms were less satisfied with their IEQ than those without. That is, despite a positive evaluation of specific IEQ criteria with respect to the building residents lived in, if they reported feeling SBS related symptoms, the overall IEQ evaluation of their building could still be negative. This perception bias gives rise to a sample selection problem in measuring perceived IEQ, which has implications on housing management practices and the formulation of a healthy housing policy.     

Piecewise proportional hazards models with interval-censored data

We consider the piecewise proportional hazards (PWPH) model with interval-censored (IC) relapse times under the distribution-free set-up. The partial likelihood approach is not applicable for IC data, and the generalized likelihood approach has not been studied in the literature. It turns out that under the PWPH model with IC data, the semi-parametric MLE (SMLE) of the covariate effect under the standard generalized likelihood may not be unique and may not be consistent. In fact, the parameter under the PWPH model with IC data is not identifiable unless the identifiability assumption is imposed. We propose a modification to the likelihood function so that its SMLE is unique. Under the identifiability assumption, our simulation study suggests that the SMLE is consistent. We apply the method to our cancer relapse time data and conclude that the bone marrow micrometastasis does not have a significant prognostic factor.