Medicare Part D relies upon drug plan competition. Plans have enormous scope to design benefits and to set premiums, but they may not charge differential premiums based on risk. We use the formulary and benefit design of all Medicare prescription drug plans and pharmacy claims data to construct a simulation model of out-of-pocket drug spending. We use this simulation model to examine individual incentives in Medicare Part D for adverse selection. We find that high drug users have much stronger incentives to enroll in generous plans than do low users, thus there is significant scope for adverse selection.

Counter to extant stylized facts, using newly available data on country allocations in US investors' foreign equity portfolios we find that (i) US investors do not exhibit returns-chasing behavior, but, consistent with partial portfolio rebalancing, tend to sell past winners; and (ii) US investors increase portfolio weights on a country's equity market just prior to its strong performance, behavior inconsistent with an informational disadvantage. Over the past two decades, US investors' foreign equity portfolios outperformed a value-weighted foreign benchmark by 160 basis points per year. JEL: C58, G11, G15

We examine market behavior of the stock and option markets upon the arrival of noisy information in the form of CNBC’s Mad Money recommendations. If stock and option markets are not equally efficient, they should respond differently to noisy information, with the less efficient market more susceptible to noise. We find that the stock market is less efficient than the option market. The abnormal difference between option-implied and actual stock returns is negative and significant upon exposure to noisy information. This difference may yield an economically significant monthly trading profit of up to 5%. We conclude that the stock market is more susceptible to noisy information than the option market and is therefore less efficient.

ABSTRACT: Recent accounting scandals have resulted in regulatory initiatives designed to strengthen audit committee oversight of corporate financial reporting and have led to a concern that U.S. GAAP has become too rules-based. We examine issues related to these initiatives using two experiments. CFOs in our experiments exhibit more agreement and are less likely to report aggressively under a less precise (more principles-based) standard than under a more precise (more rules-based) standard. Our results also indicate that CFOs applying a more precise standard are less likely to report aggressively in the presence of a strong audit committee than a weak audit committee. We find no effect of audit committee strength when the standard is less precise. Finally, we find support for a three-path mediating model examining mechanisms driving the effect of standard precision on aggressive reporting decisions. These results should be of interest to U.S. policymakers as they continue to contemplate a shift to more principles-based accounting standards (e.g., IFRS).

Little is known about the relationship between variation in drug and non-drug medical treatment and how areas may substitute one type of care for the other. Using pharmacy and medical claims data for Medicare beneficiaries, we examine whether areas with more drug use have lower non-drug medical costs and how the quality of prescribing and primary care are associated with medical costs. We find that areas with higher drug spending do not have lower non-drug medical spending; however, poorer-quality prescribing and primary care are associated with higher medical spending in general and inpatient spending in particular.

ABSTRACT This study explores decisions related to formal empirical tests of business models and interpretations and uses of those tests. Business models describe managers' rationales as to how their organizations will achieve success. This study documents a test of one company's business model under seemingly favorable conditions for such a test—a successful single-product firm following a consistent strategy over a long period of time with stable management and publicly traded stock. Although the findings provide only weak support for the hypothesized business model, the confidence of the company's top managers in their business model remained high. Further analyses reveal that the managers' response to the test results is consistent with that expected of Bayesian-rational agents. Our analyses provide the basis for development of a framework for understanding the expected value of testing business models in various circumstances. This framework might explain apparent contradictions between previous studies containing normative statements regarding the value of testing business models. Data Availability: The data used in this study are derived from a proprietary dataset and public sources.

ABSTRACT: We examine whether the two distinct post-earnings-announcement drifts associated with seasonal random-walk-based and analyst-based earnings surprises are attributable to the trading activities of distinct sets of investors. We predict and find that small (large) traders continue to trade in the direction of seasonal random-walk-based (analyst-based) earnings surprises after earnings announcements. We also find that when small (large) traders react more thoroughly to seasonal random-walk- (analyst-) based earnings surprises at the earnings announcements, the respective drift attenuates. Further evidence suggests that delayed small trades associated with random-walk-based surprises are consistent with small traders’ failure to understand time-series properties of earnings, whereas delayed large trades associated with analyst-based surprises are more consistent with a longer price discovery process. We also find that the analyst-based drift has declined in recent years.

We often deal with uncertain events for which no probabilities are known. Several normative models have been proposed. Descriptive studies have usually been qualitative, or they estimated ambiguity aversion through one single number. This paper introduces the source method, a tractable method for quantitatively analyzing uncertainty empirically. The theoretical key is the distinction between different sources of uncertainty, within which subjective (choice-based) probabilities can still be defined. Source functions convert those subjective probabilities into willingness to bet. We apply our method in an experiment, where we do not commit to particular ambiguity attitudes but let the data speak. (JEL D81)

ABSTRACT: We investigate whether short sellers and analysts differ in their use of information that is predictive of future returns. We find that short interest is significantly associated in the expected direction with all 11 variables examined. In contrast, analysts tend to positively recommend stocks with high growth, high accruals, and low book-to-market ratios, despite these variables having a negative association with future returns. We then investigate the profitability of using short interest in trading. We find abnormal returns (1.11 percent per month) from a zero-investment strategy that (1) shorts firms with highly favorable analyst recommendations (buy signal) but high short interest (sell signal), and (2) buys firms with highly unfavorable analyst recommendations (sell signal) but low short interest (buy signal). Short interest, therefore, appears to capture predictive information that can be used by investors in trading against analysts’ recommendations to increase returns.

US health care expenditures reached $2.5 trillion in 2009, representing 17.6 percent of gross domestic product (GDP) and $8,086 per person (US Department of Health and Human Services Centers for Medicare and Medicaid Services 2011). Since health care represents a large and growing share of the economy, and factors such as population aging imply that chronic disease treatment will continue to expand as a share of health expenditures, developing methods for assessing the value of quality improvement for chronic disease spending is of increasing importance for accurately measuring real economic activity. This paper develops a method for assessing the value of quality changes associated with health care for patients living with one important chronic disease, diabetes mellitus, using 11 years of detailed data on spending and quality of care for over 800 patients. We first provide an overview of measurement issues for health care quality, and then present our data, methods, results, and a brief discussion.