Can an effective audit committee help to mitigate earnings management in Chinese firms listed in Hong Kong?

This paper attempts to determine whether the adoption of recommended corporate governance practices by Chinese firms is associated with less earnings management proxied by abnormal accruals. We examine the role of the audit committee and ownership concentration in preventing earnings management using Chinese firms listed in Hong Kong. The results of this preliminary analysis show that the frequency of audit committee meetings is associated with reduced levels of abnormal accruals, our measure of earnings management. We conclude that audit committee activity is an important factor in constraining the propensity of managers to engage in earnings management. In contrast, we find that the size of the audit committee is associated with increased levels of abnormal accruals and suggest that increasing the size of the audit committee creates information asymmetry between the audit committee and management that reduces the monitoring capacity of the audit committee. We do not find any association between audit committee independence, financial and industry experience, or ownership concentration and abnormal accruals.

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Expected safety performance of rural signalized intersections in South Korea

Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Load frequency control for rural distributed generation

In rural low-voltage networks, distribution lines are usually highly resistive. When many distributed generators are connected to such lines, power sharing among them is difficult when using conventional droop control, as the real and reactive power have strong coupling with each other. A high droop gain can alleviate this problem but may lead the system to instability. To overcome4 this, two droop control methods are proposed for accurate load sharing with frequency droop controller. The first method considers no communication among the distributed generators and regulates the output voltage and frequency, ensuring acceptable load sharing. The droop equations are modified with a transformation matrix based on the line R/X ration for this purpose. The second proposed method, with minimal low bandwidth communication, modifies the reference frequency of the distributed generators based on the active and reactive power flow in the lines connected to the points of common coupling. The performance of these two proposed controllers is compared with that of a controller, which includes an expensive high bandwidth communication system through time-domain simulation of a test system. The magnitude of errors in power sharing between these three droop control schemes are evaluated and tabulated.

Community engagement and groundwater investigation in a rural/peri urban basaltic aquifier system, Tamborine Mountain, South East Queensland

The Tamborine Mt area is a popular residential and tourist area in the Gold Coast hinterland, SE Qld. The 15km2 area occurs on elevated remnant Tertiary Basalts of the Beechmont Group, which comprise a number of mappable flow units originally derived from the Tweed volcanic centre to the south. The older Albert Basalt (Tertiary), which underlies the Beechmont Basalt at the southern end of the investigation area, is thought to be derived from the Focal Peak volcanic centre to the south west. The Basalts contain a locally significant ‘un-declared’ groundwater resource, which is utilised by the Tamborine Mt community for: • domestic purposes to supplement rainwater tank supplies, • commercial scale horticulture and • commercial export off-Mountain for bottled water. There is no reticulated water supply, and all waste water is treated on-site through domestic scale WTPs. Rainforest and other riparian ecosystems that attract residents and tourist dollars to the area, are also reliant on the groundwater that discharges to springs and surface streams on and around the plateau. Issues regarding a lack of compiled groundwater information, groundwater contamination, and groundwater sustainability are being investigated by QUT, utilising funding provided by the Federal Government’s ‘Caring for our Country’ programme through SEQ Catchments Ltd. The objectives of the two year project, which started in April 2009, are to: • Characterise the nature and condition of groundwater / surface water systems in the Tamborine Mountain area in terms of the issues being raised; • Engage and build capacity within the community to source local knowledge, encourage participation, raise awareness and improve understanding of the impacts of land and water use; • Develop a stand-alone 3D Visualisation model for dissemination into the community and use as a communication tool.

Repeat participation in colorectal cancer screening utilizing fecal occult blood testing : a community-based project in a rural setting

Background and Aim: To investigate participation in a second round of colorectal cancer screening using a fecal occult blood test (FOBT) in an Australian rural community, and to assess the demographic characteristics and individual perspectives associated with repeat screening. ---------- Methods: Potential participants from round 1 (50–74 years of age) were sent an intervention package and asked to return a completed FOBT (n = 3406). Doctors of participants testing positive referred to colonoscopy as appropriate. Following screening, 119 participants completed qualitative telephone interviews. Multivariable logistic regression models evaluated the association between round-2 participation and other variables.---------- Results: Round-2 participation was 34.7%; the strongest predictor was participation in round 1. Repeat participants were more likely to be female; inconsistent screeners were more likely to be younger (aged 50–59 years). The proportion of positive FOBT was 12.7%, that of colonoscopy compliance was 98.6%, and the positive predictive value for cancer or adenoma of advanced pathology was 23.9%. Reasons for participation included testing as a precautionary measure or having family history/friends with colorectal cancer; reasons for non-participation included apathy or doctors’ advice against screening.---------- Conclusion: Participation was relatively low and consistent across rounds. Unless suitable strategies are identified to overcome behavioral trends and/or to screen out ineligible participants, little change in overall participation rates can be expected across rounds.