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Researchers, policymakers and hospital managers often encounter numerous quality measures when assessing hospital quality. The purpose of this paper is to address the challenge of summarising, interpreting and comparing multiple quality measures across different quality dimensions by proposing a simple method of constructing a composite quality index. The method is applied to hospital administrative data to demonstrate its use in analysing hospital performance.

Logistic and fixed effects regression analyses are applied to secondary admitted patient data from all hospitals in the state of Victoria, Australia for the period 2000/2001–2011/2012.

The derived composite quality index was used to rank hospital performance and to assess changes in state-wide average hospital quality over time. Further regression analyses found private hospitals, day hospitals and non-acute hospitals were associated with higher composite quality, while small hospitals were associated with lower quality.

The method will enable policymakers and hospital managers to better monitor the performance of hospitals. It allows quality to be related to other attributes of hospitals such as size and volume, and enables policymakers and managers to focus on hospitals with relevant characteristics such that quantity and quality changes can be better understood, monitored and acted upon.

A simple method of constructing a composite quality is an indispensable practical tool in tracking the quality of hospitals when numerous measures are used to capture different aspects of quality. The derived composite quality can be used to summarise hospital performance and to identify factors associated with quality via regression analyses.

The purpose of this paper is to discuss strategies for benchmarking patient safety using Lombardy region administrative archives. Patient safety indicators and statistical methods are presented that allow risk adjustment. The analysis benchmarks regional health structures, focusing on two patient safety indicators: failure to rescue; and death in low mortality diagnostic related group.

Data were drawn from a research project promoted by the Italian Agency of Regional Health Services in 2002 to furnish statistical evidence regarding adverse events based on Agency for Healthcare Research and Quality indicators and methods. Hierarchical models for an equitable benchmark analyses are proposed.

Empirical analysis shows that hierarchical approaches, based on comparing health structures within homogenous specialties, disaggregates and moderates failure to rescue variabilities existing between hospitals, especially in oncology, intensive care and general medicine.

The paper proposes using hierarchical models for properly benchmarking health structures, resolving logistic regression drawbacks and limitations.

The paper strengthens the theory that accurate coding supported by software and administrative databases could provide a valuable and economical source for patient safety research.

The paper analyses and suggests strategies for consistent benchmark analyses based on patient safety outcomes, applicable to several situations and different health structure typologies.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

The purpose of this paper is to re‐examine the sources of momentum profits by focusing on momentum in monthly returns.

The paper utilizes a decomposition method proposed by Du and Watkins.

Different from previous studies, it is found that momentum may have multiple sources, and that risk or behavioral biases in isolation may not be sufficient to explain momentum.

The paper's finding that momentum may be at least partly due to risk is important for investors to understand the risk of momentum investing.

This paper focuses on the sources of momentum profits in monthly returns. The findings that momentum has multiple sources call for new explanations for momentum because all existing theories of momentum are either rational or behavioral. Furthermore, the finding that lead‐lag relationship plays an important role in momentum suggests that researchers should focus on mis‐reaction to common (market‐wide) information to explain momentum as emphasized by Lo and MacKinlay.

The use of clinical performance data is increasing rapidly. Yet, substantial variation exists across indicators designed to measure the same clinical event. We compared indicators from several indicator measurement systems to determine the consistency of results. Five measurement systems with well‐defined indicators were selected. They were applied to 24 hospitals. Indicators for mortality from coronary artery bypass graft surgery and mortality in the perioperative period were chosen from these measurement systems. Analyses results and concludes that it is faulty to assume that clinical indicators derived from different measurement systems will give the same rank order. Widespread demand for external release of outcome data from hospitals must be balanced by an educational effort about the factors that influence and potentially confound reported rates.

The purpose of this paper is to determine the impact of the passage and signing of P.L. 111-353, the Food Safety Modernization Act (FSMA), on the market value of agribusiness firms.

The authors conduct an event study of the shareholder value effects of FSMA. The short-window analyses estimate the three-, five-, and seven-day market responses to three key event dates: passage by the House, passage by the Senate, and the signing of FSMA by President Obama. The long-window analyses examine a time period that encompasses the three informational events, as well as the 30 months after the signing of FSMA. To control for the effects of market-wide fluctuations, the authors use two alternative models of the returns generating process to calculate abnormal returns, the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model.

The short-window analyses show no evidence of a significant reaction to the passage of FSMA by the House or the Senate, but evidence of a significant negative reaction to the signing of FSMA by President Obama. The long window results which span the of passage by House, passage by the Senate and signing by the President indicate a decline in the average market value of agribusiness firms on the order of – 10 percent over the period. Additionally, the authors find some evidence that this effect is not evenly spread out across different types of agribusiness firms (wholesale, grocery, and processing).

The study is the first to examine the impact of P.L.111-353 on the market value of agribusiness firms.

The purpose of this paper is to examine whether the investor reaction to 10-K filings has changed since the implementation of Regulation Full Disclosure (FD) and the Sarbanes–Oxley Act (SOX) and examine whether the market still underreacts to 10-K content and exhibits the continuation of filing day returns (FDRs) documented by You and Zhang (2009) after the passage of these regulations.

The sample consists of 39,270 10-K filings over the sample period of 1996 to 2012. Performance of portfolios created based on FDRs around 10-K filings is examined. Regression models are used for multivariate analysis. Carhart αs are obtained using the four-factor risk adjustment model.

By comparing investor reaction to 10-K filings pre- and post-regulation, the paper shows a significant change in stock price behavior since the implementation of FD and SOX. Analogous to Burks (2011), results suggest improved price efficiency around 10-K filings. In the long-run of up to one year following the filing, the continuation of FDRs documented by You and Zhang (2009) disappears post-2000, especially after the implementation of SOX. Overall findings suggest that investors price the information in 10-K filings significantly differently after FD and SOX than before.

The sample ends in 2012. Therefore, this study does not examine the implications of the Dodd-Frank Act.

The paper contributes to the literature related to the impact of FD and SOX and market reaction to filings of financial reports. The current literature documents that there is a continuation of FDRs up to a year. This paper shows that the continuation has disappeared since FD and SOX were implemented.

The purpose of this paper is to determine the impact of the Supreme Court’s ruling that POM Wonderful could sue Coca-Cola, a competitor, for misrepresentation of their products. This decision has the potential to alter the legal environment for soft drink and food processing firms.

The author conducted an event study of the shareholder value effects of the court decision. The analysis estimates the market responses to the decisions. To control the effects of market-wide fluctuations, the author uses two alternative models of the returns generating process to calculate abnormal returns, the capital asset pricing model (CAPM) and the Fama-French 3-factor models.

The author hypothesizes that soft drink firms will be negatively impacted by the Supreme Court’s decision, because it may limit their ability to market beverages with a low percentage of expensive juices. Consistent with this argument, the author finds that the stock prices of publicly traded soft drink firms reacted negatively to the announcement of the Supreme Court’s decision. The author also hypothesizes that there may be a spillover effect to food processing firms. These firms may also be at risk to being sued by competitors for exaggerated claims. Contrary to this argument, the author finds no spillover effect to other types of food processing firms. Thus, the decision did leave an aftertaste for the soft drink industry but not the food processing industry.

This study is the first to examine the impact of the right to sue competitors in the food industry for misrepresentation of products.

Reviews previous research on exchange rate forecasting, identifies some problems in building a predictive model and examines the profitability of using various technical rules (as used by traders) in the USD/DM and USD/BP foreign exchange markets. Takes 1989‐1996 data, divided into two sub‐periods with different macroeconomic features; and compares the results from the technical rules in detail and with a buy and hold strategy. Finds that no rules produced statistically significant profits for the whole period (although they did for the first sub‐period) and some evidence that buy and hold is superior, especially if risk is taken into account. Considers the implications of the findings and the underlying reasons for them.

Measures of health status and prior service use have been considered promising predictors of future health expenditures, particularly when used for risk-adjustment models in capitation payment systems. While the use of health status as a future predictor has its difficulty in terms of measurement accuracy and implementation costs, using prior utilization as the base for the calculation of future health expenditures also has its concerns. Based on a three-stage cross-lagged model in a longitudinal study design, this study showed that prior utilization has both a direct and an indirect effect on subsequent utilization. However, the real net effect of prior utilization on subsequent utilization can be overestimated by 25%, if the effect of health status is not taken into account.