Blood alcohol and injury in Bhutan: targeted surveillance in a national referral hospital emergency department

Bhutan is a low-middle-income country with poor roads, rapidly increasing motor vehicle use and heavy alcohol consumption. We estimated the proportion of emergency department patients presenting with injury who had positive blood alcohol. We sought to breathalyse and interview all adult patients (≥18 years) presenting with injury at the Jigme Dorji Wangchuck National Referral Hospital in the capital city Thimphu, from April to October 2015. Breath tests and interviews were conducted with 339 (91%) of 374 eligible adult patients. A third (34%) were alcohol-positive and 22% had blood alcohol concentrations >0.08 g/dL. The highest alcohol-positive fractions were for assault (71%), falls (31%) and traffic crashes (30%). Over a third (36%) of patients had a delay of >2 h between injury and breath test. The results underestimate blood alcohol concentrations at the time of injury so the true prevalence of pre-injury alcohol impairment is greater than our estimates suggest. Countermeasures are urgently needed, particularly roadside random breath testing and alcohol controls.

Mean reversion versus random walk in G7 stock prices evidence from multiple trend break unit root tests

This paper provides evidence on the random walk hypothesis in G7 stock price indices using unit root tests which allow for one and two structural breaks in the trend. Of the seven countries we find, at best, evidence of mean reversion in the stock price index of Japan. Thus, overall, our results support the random walk hypothesis. We also consider the implications of the identified structural breaks for movement in stock prices over time. Our main conclusion from this exercise is that the second break in stock prices has had a detrimental effect on movements in stock prices in the G7 countries.

Mean reversion in stock prices: new evidence from panel unit root tests

Purpose – There are several studies that investigate evidence for mean reversion in stock prices. However, there is no consensus as to whether stock prices are mean reverting or random walk (unit root) processes. The goal of this paper is to re-examine mean reversion in stock prices.
Design/methodology/approach – The authors use five different panel unit root tests, namely the Im, Pesaran and Shin t-bar test statistic, the Levin and Lin test, the Im, Lee, and Tieslau Lagrangian multiplier test statistic, the seemingly unrelated regression test, and the multivariate augmented Dickey Fuller test advocated by Taylor and Sarno.
Findings – The main finding is that there is no mean reversion of stock prices, consistent with the efficient market hypothesis.
Research limitations/implications – One issue not considered by this study is the role of structural breaks. It may be the case that the efficient market hypothesis is contingent on structural breaks in stock prices. Future studies should model structural breaks.
Practical implications – The findings have implications for econometric modelling, in particular forecasting.
Originality/value – This paper adds to the scarce literature on the mean reverting property of stock prices based on panel data; thus, it should be useful for researchers.

Random walk versus multiple trend breaks in stock prices : evidence from 15 European markets

This letter extends research reported in Narayan and Smyth (2005) by employing multiple trend break unit root tests to examine the random walk hypothesis for 15 European stock market indices. The results provide strong support for the view that stock prices are characterized by a random walk.

Testing for the random walk hypothesis in the case of visitor arrivals : evidence from Indian tourism

Testing for the random walk hypothesis, which asserts that a series is a non-stationary process or a unit root process, in the case of visitor arrivals has important implications for policy. If, for instance, visitor arrivals are characterized by a unit root, then it implies that shocks to visitor arrivals are permanent. However, if visitor arrivals are without a unit root, this implies that shocks to visitor arrivals are temporary. This study provides evidence on the random walk hypothesis for visitor arrivals to India using the recently developed Im et al. (2003) and Maddala and Wu (1999) panel unit root tests. Both tests allow one to reject the random walk hypothesis, implying that shocks to visitor arrivals to India from the 10 major source markets have a temporary effect on visitor arrivals.

Are OECD stock prices characterized by a random walk? Evidence from sequential trend break and panel data models

This paper examines whether stock prices for a sample of 22 OECD countries can be best represented as mean reversion or random walk processes. A sequential trend break test proposed by Zivot and Andrews is implemented, which has the advantage that it can take account of a structural break in the series, as well as panel data unit root tests proposed by Im et al., which exploits the extra power in the panel properties of the data. Results provide strong support for the random walk hypothesis.

The influence of sighing respirations on infant lung function measured using multiple breath washout gas mixing techniques

There is substantial interest in studying lung function in infants, to better understand the early life origins of chronic lung diseases such as asthma. Multiple breath washout (MBW) is a technique for measuring lung function that has been adapted for use in infants. Respiratory sighs occur frequently in young infants during natural sleep, and in accordance with current MBW guidelines, result in exclusion of data from a substantial proportion of testing cycles. We assessed how sighs during MBW influenced the measurements obtained using data from 767 tests conducted on 246 infants (50% male; mean age 43 days) as part of a large cohort study. Sighs occurred in 119 (15%) tests. Sighs during the main part of the wash-in phase (before the last 5 breaths) were not associated with differences in standard MBW measurements compared with tests without sighs. In contrast, sighs that occurred during the washout were associated with a small but discernible increase in magnitude and variability. For example, the mean lung clearance index increased by 0.36 (95% CI: 0.11-0.62) and variance increased by a multiplicative factor of 2 (95% CI: 1.6-2.5). The results suggest it is reasonable to include MBW data from testing cycles where a sigh occurs during the wash-in phase, but not during washout, of MBW. By recovering data that would otherwise have been excluded, we estimate a boost of about 10% to the final number of acceptable tests and 6% to the number of individuals successfully tested.

New tools for understanding the local asymptotic power of panel unit root tests

Abstract Motivated by the previously documented discrepancy between actual and predicted power, the present paper provides new tools for analyzing the local asymptotic power of panel unit root tests. These tools are appropriate in general when considering panel data with a dominant autoregressive root of the form ^ρi=1+^ciN-^κT-^τ, where i=1,...,N indexes the cross-sectional units, T is the number of time periods and ^ci is a random local-to-unity parameter. A limit theory for the sample moments of such panel data is developed and is shown to involve infinite-order series expansions in the moments of ^ci, in which existing theories can be seen as mere first-order approximations. The new theory is applied to study the asymptotic local power functions of some known test statistics for a unit root. These functions can be expressed in terms of the expansions in the moments of ^ci, and include existing local power functions as special cases. Monte Carlo evidence is provided to suggest that the new results go a long way toward bridging the gap between actual and predicted power.

A random coefficient approach to the predictability of stock returns in panels

© The Author, 2014. Most studies of the predictability of returns are based on time series data, and whenever panel data are used, the testing is almost always conducted in an unrestricted unit-by-unit fashion, which makes for a very heavy parametrization of the model. On the other hand, the few panel tests that exist are too restrictive in the sense that they are based on homogeneity assumptions that might not be true. As a response to this, the current study proposes new predictability tests in the context of a random coefficient panel data model, in which the null of no predictability corresponds to the joint restriction that the predictive slope has zero mean and variance. The tests are applied to a large panel of stocks listed at the New York Stock Exchange. The results suggest that while the predictive slopes tend to average to zero, in case of book-to-market and cash flow-to-price the variance of the slopes is positive, which we take as evidence of predictability.