Are fully independent audit committees really necessary?

Accounting scandals and concerns about the quality of financial statements have led to many calls for improved audit committee effectiveness. Prior research indicates that audit committee independence is positively related to effective oversight of the financial reporting process. Unfortunately, prior research has not provided an answer as to how much independence on the audit committee is enough. This is an important unanswered question because while Section 301 of the Sarbanes-Oxley Act of 2002 (SOX) currently requires all listed companies to maintain an audit committee that is 100% independent there has been much debate regarding easing the SOX requirements for smaller and foreign companies. In this paper we examine whether the regulatory requirements of a completely independent audit committee are necessary to obtain the monitoring benefits related to audit committee independence that have been documented in prior literature. Our results suggest that the benefits of audit committee independence are consistently achieved only when the audit committee is completely independent. These results provide support for the SOX requirement of 100% independent audit committees.     

HETEROGENEITY IN ORDERED CHOICE MODELS: A REVIEW WITH APPLICATIONS TO SELF‐ASSESSED HEALTH

Discrete variables that have an inherent sense of ordering across outcomes are commonly found in large data sets available to many economists, and are often the focus of research. However, assumptions underlying the standard ordered probit (which is usually used to analyse such variables) are not always justified by the data. This study provides a review of the ways in which the ordered probit might be extended to account for additional heterogeneity. Differing from other reviews in scope, application and relevance in economic settings, a series of issues pertaining to choices of variables, and the economic assumptions underlying each model are discussed in the context of measuring the underlying health of respondents. The models are applied to a wave of the household, income and labour dynamics in Australia survey, in order to check the appropriateness of such assumptions in an applied context.     

The relationship between smoking,quitting smoking and obesity in Australia: a seemingly unrelated probit approach

Smoking and obesity are two leading causes of preventable death. Further understanding of the relationship between these two risk factors can assist in reducing avoidable morbidity and mortality. This study investigates the empirical association between obesity and the propensity to smoke and to quit smoking, using a Seemingly Unrelated (SUR) probit approach that takes into consideration the potential for reverse causality and unobserved heterogeneity. Using Australian health survey data, this article demonstrates the usefulness of the SUR probit approach in generating information on the relationship between unobserved factors influencing both smoking behaviour and obesity, and in providing estimates of the conditional probabilities of each risk factor. Results suggest the two risk factors are not independent. The presence, size and direction of correlation between the unobserved factors are found to vary by smoking behaviour and by gender. Estimates of conditional probabilities demonstrate smokers have a lower probability of obesity, particularly among females, and ex-smokers have a higher probability of obesity, particularly among males. These findings suggest that health policies targeted at one risk factor may have unintended implications for the other.     

The Fixed Weighting Nature of A Cross-Evaluation Model

Cross-evaluation has been touted as a powerful extension of Data Envelopment Analysis that provides, not only a unique ordering among the Decision Making Units (DMUs), but also eliminates unrealistic weighting schemes without requiring the elicitation of weight restrictions from application area experts. The goal of this paper is to prove, in the single-input, multiple-output case, cross-evaluation implicitly uses a single fixed set of weights. We demonstrate how this unseen fixed set of weights may still be unrealistic.     

The efficiency of immunization of infants by local government

The paper makes use of data envelopment analysis (DEA) to measure the cost and production efficiency of local government programmemes for childhood immunization in urban and rural settings in Australia. Model specification is tested for validity, methods are used for ranking efficient units and advanced statistical methods are used to establish confidence intervals around the efficiency estimates. Given the small data set, the cost and production models are valid, and it is concluded that while neither urban nor rural programmes are particularly efficient, there is more room for improvement in rural programmes. Ways of changing methods of delivery are suggested which may increase efficiency.     

Revolution, evolution, or status quo? Guidelines for efficiency measurement in health care

This paper discusses ways forward in terms of making efficiency measurement in the area of health care more useful. Options are discussed in terms of the potential introduction of guidelines for the undertaking of studies in this area, in order to make them more useful to policy makers and those involved in service delivery. The process of introducing such guidelines is discussed using the example of the development of guidelines in economic evaluation of health technologies. This presents two alternative ways forward—‘revolution’, the establishment of a panel to establish initial guidelines, or ‘evolution’—the more gradual development of such guidelines over time. The third alternative of ‘status quo’, representing the current state of play, is seen as the base case scenario. It is concluded that although we are quite a way on in terms of techniques and publications, perhaps revolution, followed by evolution is the way forward.     

A latent class model for obesity

We extend the discrete data latent class literature by explicitly defining a latent variable for class membership as a function of both observables and unobservables, thereby allowing the equations defining the class membership and observed outcomes to be correlated. The procedure is then applied to modelling observed obesity outcomes, based upon an underlying ordered probit equation.     

Non Parametric Efficiency Measurement

Efficiency measurement using non parametric methods is increasing rapidly. One important initial step in measuring efficiency is deciding which software package to make use of. Here Data Envelopment Analysis (DEA) efficiency packages are reviewed, including those which undertake Malmquist productivity analysis. While most packages are commercially available, the one which is not a commercial product has an obvious initial advantage.