Double unit root tests for cross-sectionally dependent panel data

This paper proposes various double unit root tests for cross-sectionally dependent panel data. The cross-sectional correlation is handled by the projection method [P.C.B. Phillips and D. Sul, Dynamic panel estimation and homogeneity testing under cross section dependence, Econom. J. 6 (2003), pp. 217–259; H.R. Moon and B. Perron, Testing for a unit root in panels with dynamic factors, J. Econom. 122 (2004), pp. 81–126] or the subtraction method [J. Bai and S. Ng, A PANIC attack on unit roots and cointegration, Econometrica 72 (2004), pp. 1127–1177]. Pooling or averaging is applied to combine results from different panel units. Also, to estimate autoregressive parameters the ordinary least squares estimation [D.P. Hasza and W.A. Fuller, Estimation for autoregressive processes with unit roots, Ann. Stat. 7 (1979), pp. 1106–1120] or the symmetric estimation [D.L. Sen and D.A. Dickey, Symmetric test for second differencing in univariate time series, J. Bus. Econ. Stat. 5 (1987), pp. 463–473] are used, and to adjust mean functions the ordinary mean adjustment or the recursive mean adjustment are used. Combinations of different methods in defactoring to eliminate the cross-sectional dependency, integrating results from panel units, estimating the parameters, and adjusting mean functions yields various available tests for double unit roots in panel data. Simple asymptotic distributions of the proposed test statistics are derived, which can be used to find critical values of the test statistics.

We perform a Monte Carlo experiment to compare the performance of these tests and to suggest optimal tests for a given panel data. Application of the proposed tests to a real data, the yearly export panel data sets of several Latin–American countries for the past 50 years, illustrates the usefulness of the proposed tests for panel data, in that they reveal stronger evidence of double unit roots than the componentwise double unit root tests of Hasza and Fuller [Estimation for autoregressive processes with unit roots, Ann. Stat. 7 (1979), pp. 1106–1120] or Sen and Dickey [Symmetric test for second differencing in univariate time series, J. Bus. Econ. Stat. 5 (1987), pp. 463–473].     

Figures of grief: metaphors from a bereavement writing group

In a community-based bereavement writing group, patterns of metaphor emerged and helped the group members identify and deal with particularly challenging aspects of death and grief, including taboo subjects such as abuse and suicide. The metaphors show how a bereavement writing group functioned to address the needs of people coping with different kinds of grief effectively and efficiently. Analysis of the specific metaphors suggests why figurative language enabled the group to bond quickly and strongly, delve into the complex emotions death elicits, and integrate experiences of loss and grief safely and productively. The patterns of metaphors the group produced in their writing about death and grief are discussed in terms of bereavement processes, and the topics the group used to elicit the figures of speech are presented for further refinement and use.     

Improving the accuracy and operational predictability of project cost forecasts: an adaptive combination approach

Conducting an early warning forecast to detect potential cost overrun is essential for timely and effective decision-making in project control. This paper presents a forecast combination model that adaptively identifies the best forecast and optimises various combinations of commonly used project cost forecasting models. To do so, a forecast error simulator is formulated to visualise and quantify likely error profiles of forecast models and their combinations. The adaptive cost combination (ACC) model was applied to a pilot project for numerical illustration as well as to real world projects for practical implementation. The results provide three valuable insights into more effective project control and forecasting. First, the best forecasting model may change in individual projects according to the project progress and the management priority (i.e. accuracy, outperformance or large errors). Second, adaptive combination of simple, index-based forecasts tends to improve forecast accuracy, while mitigating the risk of large errors. Third, a post-mortem analysis of seven real projects indicated that the simple average of two most commonly used cost forecasts can be 31.2% more accurate, on average, than the most accurate alternative forecasts.     

A Case Study Evaluating the Risk of Infection from Middle Eastern Respiratory Syndrome Coronavirus (MERS‐CoV) in a Hospital Setting Through Bioaerosols

Middle Eastern respiratory syndrome, an emerging viral infection with a global case fatality rate of 35.5%, caused major outbreaks first in 2012 and 2015, though new cases are continuously reported around the world. Transmission is believed to mainly occur in healthcare settings through aerosolized particles. This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. The exposure scenario includes a single index patient emitting virus‐containing aerosols into the air by coughing, leading to short‐ and long‐range airborne exposures for other patients in the same room, nurses, healthcare workers, and family visitors. Aerosol transport modeling was coupled with Monte Carlo simulation to evaluate the risk of MERS illness for the exposed population. Results from a typical scenario show the daily mean risk of infection to be the highest for the nurses and healthcare workers (8.49 × 10^?4 and 7.91 × 10^?4, respectively), and the lowest for family visitors and patients staying in the same room (3.12 × 10^?4 and 1.29 × 10^?4, respectively). Sensitivity analysis indicates that more than 90% of the uncertainty in the risk characterization is due to the viral concentration in saliva. Assessment of risk interventions showed that respiratory masks were found to have a greater effect in reducing the risks for all the groups evaluated (>90% risk reduction), while increasing the air exchange was effective for the other patients in the same room only (up to 58% risk reduction).     

Do Young Children's Representations of Discipline and Empathy Moderate the Effects of Punishment on Emotion Regulation?

This study examined whether children's representations of parenting (perceptions of authoritative discipline and empathy) moderated the association between harsh punishment—including corporal punishment (CP) and verbal punishment (VP)—and children's emotion regulation at the age of five years. Participants were 559 low‐income mother‐child dyads. Maternal self‐reports and home observations were used to measure punishment. Children's representations were assessed using the MacArthur Story Stem Battery. Children's emotion regulation was assessed by observer rating via the Leiter International Performance Scale–Revised. Hierarchical multiple regressions revealed that children's authoritative disciplinary representations moderated the effects of both VP and CP on children's emotion regulation. Empathic representations moderated the effects of VP only on children's emotion regulation. The current findings highlight the role of children's internal representations as potential protective factors in the context of harsher forms of punishment.     

Local Control Strategy: Simple Analyses of Air Pollution Data Can Reveal Heterogeneity in Longevity Outcomes

Claims from observational studies that use traditional model specification searches often fail to replicate, partially because the available data tend to be biased. There is an urgent need for an alternative statistical analysis strategy, that is not only simple and easily understood but also is more likely to give reliable insights when the available data have not been designed and balanced. The alternative strategy known as local control first generates local, nonparametric effect‐size estimates (fair treatment comparisons) and only then asks whether the observed variation in these local estimates can be predicted from potential confounding factors. Here, we illustrate application of local control to a historical air pollution data set describing a “natural experiment” initiated by the federal Clean Air Act Amendments of 1970. Our reanalysis reveals subgroup heterogeneity in the effects of air quality regulation on elderly longevity (one size does not fit all), and we show that this heterogeneity is largely explained by socioeconomic and environmental confounders other than air quality.     

Subjective Well-Being and Life Satisfaction in the Kingdom of Tonga

This paper describes an initial attempt to assess the subjective well being of a sample of 227 Tongans via self-report. Using items adapted from the Subjective Well Being Inventory (SUBI; Nagpal and Sell, 1985; Sell and Nagpal, 1992), participants rated their level of overall life satisfaction along with their perceptions of well-beingin a number of other more specific life domains. Results indicated that mean ratings of global life satisfaction were generally positive. A factor analysis of the remaining domain-specific well-being items indicated that items loaded on to one of two factors dealing with overall positive or negative evaluations of these life areas. Importantly, these scale items stressed the importance of social and kin relations in contributing to overall well-being. In terms of demographic variables, mature respondents reported greater levels of overall life satisfaction and well-being as compared to youthful respondents. Implications and directions for future research are discussed.