Mandatory IFRS Adoption and the Role of Accounting Earnings in CEO Turnover

We study whether mandatory adoption of International Financial Reporting Standards (IFRS) is associated with changes in the sensitivity of CEO turnover to accounting earnings and how the impact of IFRS adoption varies with country‐level institutions and firm‐level incentives. We find that CEO turnover responds more to a firm's accounting performance after adoption. This increase in turnover‐to‐earnings sensitivity is concentrated in countries with stronger enforcement of financial reporting and is more prominent for mandatory adopters that have strong firm‐level compliance incentives. In addition, we link the change in turnover‐to‐earnings sensitivity directly to accounting changes due to IFRS adoption and find a stronger adoption effect when firms report large overall accounting changes and large de‐recognition of loss provisions upon adoption. Some of the above findings are sensitive to the exclusion of UK firms, which account for more than half of our sample.     

Causes and consequences of goodwill impairment losses

The paper examines the reaction of market participants to the announcement of a goodwill impairment loss, the nature of the information conveyed by the loss, and whether a cause of goodwill impairment can be traced back to overpayment for targets at the time of prior acquisitions. Our evidence suggests that both investors and financial analysts revise their expectations downward on the announcement of an impairment loss. We find that the negative impact of the loss is significant under different reporting regimes, that is, pre-SFAS-142, transition period and post-SFAS-142, though it is lower in the post period. We further show that goodwill impairment serves as a leading indicator of a decline in future profitability. Our tests also reveal that proxies for overpayment for targets can predict the subsequent goodwill impairment. Indirect evidence suggests that firms with potentially impaired goodwill that did not report an impairment loss may have used their managerial discretion to avoid taking the loss.     

Mobil Oil: Defending market leadership in synthetic lubricants in China. Comment on Mobil Oil: Defending market leadership in synthetic lubricants in China

China's lubricant market was dominated by PetroChina and Sinopec. Foreign brands together controlled about 25% of the market, and these brands offered the higher‐grade lubricants. Most vehicle lubricants used in China were low‐grade lubricants. However, this was expected to change. Continued economic growth and rising incomes had led to increased demand for cars. New models and luxury cars would likely stimulate demand for higher‐grade lubricants. The case focused on synthetic lubricants of which Mobil was the market leader. Mobil's leadership position here was being threatened. Local brands were gradually improving in quality, and a few have secured rights to supply joint venture car manufacturers. Armed with deep pockets, their aggressive advertising had helped their brands gain prominence. The case required some recommendations on how Mobil should respond. © 2008 Wiley Periodicals, Inc.     

Drug wastage and costs to the healthcare system in the care of patients with non-small cell lung cancer in the United States

Background: Lung cancer is one of the most prevalent cancers in the US. This study was designed to evaluate the actual drug wastage and cost to the healthcare system using patient-level retrospective observational electronic medical record (EMR) data from a cohort of lung cancer patients in the US.

Methods: Data from the Flatiron Health advanced non-small cell lung cancer (NSCLC) cohort was used for this study. Drug administered amount (in mg) was used to determine an optimal set of available vial sizes to minimize waste. Drug wastage was defined as the difference between the drug amount in the optimal set of vials and the administered amount. Wholesale acquisition costs were used to value the cost of drugs, with and without vial sharing assumptions. The amount and cost of waste were quantified over the 2-year study period (January 2015–December 2016).

Results: There were 8,467 eligible patients included in this study, providing data from 103,826 unique drug administrations across multiple lines of therapy. Overall wastage was 4.37% of the total medication used to care for patients. While costs per administration were low, the total cost of wastage for the study population represented $16,630,112 across the 2-year study period. Assuming that vial sharing occurred at the site level slightly reduced waste to 3.74% (reducing costs to $15,953,212 over 2 years).

Conclusions: Drug wastage is an important concern and has implications on healthcare costs in NSCLC. Evaluation of these real-world data suggest that pharmacists and physicians are able to reduce drug wastage by optimizing vial combinations and sharing vials among patients. Even small amounts of reduction in wastage could be useful in reducing healthcare costs in the US; however, caution is needed with drug rounding efforts to ensure patients do not receive a sub-optimal dose of medication.     

Marginalizing pattern-mixture models for categorical data subject to monotone missingness

Many models to analyze incomplete data that allow the missingness to be non-random have been developed. Since such models necessarily rely on unverifiable assumptions, considerable research nowadays is devoted to assess the sensitivity of resulting inferences. A popular sensitivity route, next to local influence (Cook in J Roy Stat Soc Ser B 2:133–169, 1986; Jansen et al. in Biometrics 59:410–419, 2003) and so-called intervals of ignorance (Molenberghs et al. in Appl Stat 50:15–29, 2001), is based on contrasting more conventional selection models with members from the pattern-mixture model family. In the first family, the outcome of interest is modeled directly, while in the second family the natural parameter describes the measurement process, conditional on the missingness pattern. This implies that a direct comparison ought not to be done in terms of parameter estimates, but rather should pass by marginalizing the pattern-mixture model over the patterns. While this is relatively straightforward for linear models, the picture is less clear for the nevertheless important setting of categorical outcomes, since models ordinarily exhibit a certain amount of non-linearity. Following ideas laid out in Jansen and Molenberghs (Pattern-mixture models for categorical outcomes with non-monotone missingness. Submitted for publication, 2007), we offer ways to marginalize pattern-mixture-model-based parameter estimates, and supplement these with asymptotic variance formulas. The modeling context is provided by the multivariate Dale model. The performance of the method and its usefulness for sensitivity analysis is scrutinized using simulations.     

Modelling Strategies for Repeated Multiple Response Data

This article discusses modelling strategies for repeated measurements of multiple response variables. Such data arise in the context of categorical variables where one can select more than one of the categories as the response. We consider each of the multiple responses as a binary outcome and use a marginal (or population‐averaged) modelling approach to analyse its means. Generalized estimating equations are used to account for different correlation structures, both over time and between items. We also discuss an alternative approach using a generalized linear mixed model with conditional interpretations. We illustrate the methods using data from a panel study in Australia called the Household, Income, and Labour Dynamics Survey.     

A behavioral science approach to effective sales presentations

This paper has identified and briefly described a number of verbal behaviors which the salesman can use in the initial contact phase of the sales interview. The initial contact phase of selling is made more effective by using a combination of the responses described in the literature of the behavioral sciences. Experienced and neophyte salesmen can learn these behaviors with brief training using the materials presented here in a role playing situation. Such training should increase their effectiveness in the selling situation.     

Monetary policy credibility and macrodynamics: evidence from Ghana

We compute a time-varying metric of monetary policy credibility based on Ghana’s experience, using both symmetric and asymmetric approaches. We then follow-up with some empirical evidence to address the linkages between macroeconomic developments and central bank credibility. The empirical results reveal high and low credibility cycles with an average duration of 2 years over the study period. Particularly, higher levels of credibility were associated with stable domestic currency and lower nominal interest rates. This reinforces the notion that efficient monetary policy delivers higher central bank credibility with better outcomes for macroeconomic variables. In contrast, the level of credibility tends to worsen in the wake of weakening macro fundamentals which are not adequately countered by monetary policy decisions. There is therefore the need for efficient monetary policy formulation to achieve a stable macroeconomic environment in Ghana. This will in the long-run build policy credibility towards attaining the central bank’s medium-term inflation target.     

Benefits for Poor Children

For years the intellectual battle between universalists and selectivists dominated the argument on state benefits. The academic case for selectivity, to concentrate help on the helpless, has been won and is now accepted by Dr David Owen and Mrs Margaret Thatcher alike. Here Dr Ivy Papps applies the analysis to child benefits.