How have US banks adopted the Financial Accounting Standards Board's Level 3 fair value disclosure rules?

We examine how banks have complied with the Financial Accounting Standards Board's disclosure rules on Level 3 recurring fair value measurements. We document widespread noncompliance with the basic disclosure requirements. We also find that the noncompliant banks are smaller in size and are associated with lower audit quality, lower institutional ownership and less effective internal controls. Our results should be of use to regulators, auditors and audit committees in the United States, Australia and other countries for assessing the likelihood of noncompliance with fair value disclosure rules and improving the quality of fair value disclosures provided to investors.     

Audit Firm Attributes and Auditor Litigation Risk

This study examines the association between auditors' litigation risk and audit firm attributes. Using professional liability insurance premiums as a proxy for auditors' litigation risk, we present evidence that the risk is lower in audit firms having: (1) separate non-audit and audit divisions; (2) a higher proportion of partners; and (3) a higher annual growth in number of CPAs employed. Additionally, we find that the risk is higher in audit firms having: (1) operating losses; and (2) high revenue growth. Our results are consistent with the idea that audit firms' financial condition and organizational structure affect their independence/ expertise, and, in turn, their litigation risk. Our results are broadly supportive of the PCAOB's (2015) and US Department of Treasury's (2008) views that investors, audit committees, management, and other regulators could benefit from having access to financial and organizational information about audit firms.     

Institutional underperformance: Should managers listen to the sell-side before trading?

Review of Quantitative Finance and Accounting - This study examines the performance of institutional trades in the context of recent analyst recommendation changes. We report several findings....     

Firms’ fundamentals,macroeconomic variables and quarterly stock prices in the US

This paper modeled the effects of firms’ fundamentals such as total assets and long-term debt and of macroeconomic variables such as unemployment and interest rates on quarterly stock prices of over 3000 US firms in the period 2000–07. The merged CRSP/Compustat database was augmented by macroeconomic variables and comprehensive dynamic models were estimated by maximum likelihood taking into account heterogeneity across firms. Likelihood ratio statistics were developed for sequentially testing hypotheses regarding the adequacy of macroeconomic variables in the models. The main findings were that the estimated coefficients of lagged stock prices in simple dynamic random effects models were in the interval 0.90–0.95. Second, comprehensive dynamic models for stock prices showed that the firms’ earnings per share, total assets, long-term debt, dividends per share, and unemployment and interest rates were significant predictors; there were significant interactions between firms’ long-term debt and interest rates. Finally, implications of the results for corporate policies are discussed.     

Have SFAS 166 and SFAS 167 improved the financial reporting for securitizations?

Critics have alleged that securitization accounting prior to 2010 was among the causes of the recent financial crisis. In response to this criticism, the Financial Accounting Standards Board (FASB) implemented two new accounting standards, SFAS 166 and SFAS 167, to improve the financial reporting for securitizations. Bank regulators have stated their belief that SFAS 166/167 will result in a consolidated balance sheet (and risk-based capital ratios based thereupon) that better reflects a bank's exposure to risk related to securitized assets. We document that, by ceding retained power or influence through the servicing/special servicing functions to third parties, SFAS 166/167 resulted in real effects to the extent that banks (particularly those that were weakly capitalized) achieved their accounting objectives in the post-SFAS 166/167 period through legitimate transaction structuring in line with the intent of the new rules. Further, we use capital market participants’ assessments of risk retention by sponsoring banks as a benchmark, and provide evidence consistent with bank regulators’ beliefs. In particular, following SFAS 166/167, equity investors of sponsoring banks do not consider (consider) as risk relevant securitized assets that receive off-balance sheet (on-balance sheet) treatment. Securitized assets that are consolidated under SFAS 166/167 exhibit the same risk relevance as assets that are not securitized, despite contractual provisions that would seem to imply substantial risk transfer.     

Business model innovation and decision making: uncovering mechanisms for coping with uncertainty

As a research subject, business model innovation spans the strategy, innovation, and entrepreneurship fields. Yet, despite the importance of the concept, prior work has paid little attention to how decision-makers cope with uncertainty and gain understanding about interdependencies in new business model configurations. To address this gap, we combine top-down theorising and evidence-based exploration and seek to unpack some of the coping mechanisms that operate in the evolutionary view of business model innovation. Using in-depth interviewing to collect data, our study reveals five strategies – customer centricity, value co-creation, capability evolution, ecosystem growth, and adaptive pricing – that decision-makers apply to cope with uncertainty in business model innovation. We find that coping mechanisms support decision making during the development of new business models. Furthermore, we find that the five coping strategies delineate decision making for value proposition, value creation, and value capture configurations in more detail than existing literature has described. Our findings have important implications for decision making in business model innovation.     

Do Community Supported Agriculture programmes encourage change to food lifestyle behaviours and health outcomes? New evidence from shareholders

Community Supported Agriculture (CSA) programmes have recently received attention for their potential to influence food lifestyle behaviours and health outcomes, though studies have mostly drawn from small samples (n?t-tests assess if paired means are statistically different, and multiple regressions of paired differences on socioeconomic factors, self-reported health, and years of CSA enrolment estimate the effect of respondent characteristics on behaviour change. The results strongly suggest that CSAs have the potential to positively impact shareholders’ food lifestyle behaviours and health outcomes, and that those reporting ‘poor health’ prior to CSA enrolment exhibited the most change overall. These results should be taken as an initial, yet promising, analysis of the impact of CSA participation on shareholder food lifestyle behaviours and health outcomes.     

Business model innovation in a knowledge revolution: An evolutionary theory perspective

For knowledge‐intensive industries, a need remains to increase clarity on the dynamics through which business model innovation occurs. Progress has been limited owing to complexities in these industries and to the underlying ontology of the business model concept itself. Through a conceptual methodology, our findings expose impediments to current business model theory and propose economic evolutionary theory as a useful alternative lens through which to address these limitations. This research contributes to the literature by broadening the traditional scope of the economic evolutionary view as relevant for business model innovation research and by offering a corresponding framework for future research.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Injury count model for quantification of risk of occupational injury

Reduction of risk of occupational injuries is one of the most challenging problems faced by industry. Assessing and comparing risks involved in different jobs is one of the important steps towards reducing injury risk. In this study, a comprehensive scheme is given for assessing and comparing injury risks with the development of injury count model, injury risk model and derived statistics. The hazards present in a work system and the nature of the job carried out by workers are perceived as important drivers of injury potential of a work system. A loglinear model is used to quantify injury counts and the event-tree approach with joint, marginal and conditional probabilities is used to quantify injury risk. A case study was carried out in an underground coal mine. Finally a number of indices are proposed for the case study mine to capture risk of injury in different jobs. The findings of this study will help in designing injury intervention strategies for the mine studied. The job-wise risk profiles will be used to prioritise the jobs for redesign. The absolute indices can be applied for benchmarking job-wise risks and the relative indices can be used for comparing job-wise risks across work systems.