This paper investigates factors associated with high‐quality Enterprise Risk Management ( ERM ) programs in financial services firms, and whether ERM quality enhances performance and signals credibility to the financial markets. ERM , developed with the assistance of the accounting profession, provides a framework and plan to integrate management of all sources of risk. Challenged by measurement difficulties common to research on management control systems, prior ERM studies present mixed findings. Using ERM quality ratings of financial companies by Standard & Poor's, we find that higher ERM quality is associated with greater complexity, less resource constraint, and better corporate governance. Controlling for such characteristics, we find that higher ERM quality is associated with improved accounting performance. Results show a market reaction to signals of enhanced management control from initial ERM quality ratings and rating revisions, and a stronger response to earnings surprises for firms with higher ERM quality. Focusing on the recent global financial crisis, our analysis suggests that there is no relation between ERM quality and market performance prior to and during the market collapse. However, returns of higher ERM quality companies are higher during the market rebound. Overall, results reveal that firm performance and value are enhanced by high‐quality controls that integrate risk management efforts across the firm, enabling better oversight of managers' risk‐taking behavior and aligning that behavior with the strategic direction of the company.

AbstractWe develop an activity‐focused process model of how new ideas can be transformed into front line practice by reviving attention to the importance of habitualization as a key component of institutionalization. In contrast to established models that explain how ideas diffuse or spread from one organization to another, we employ a micro‐level perspective to study the subsequent intra‐organizational processes through which these ideas are transformed into new workplace practices. We followed efforts to transform the organizationally accepted idea of ‘interdisciplinary teamwork’ into new everyday practices in four cases over a six year time period. We contribute to the literature by focusing on de‐habitualizing and re‐habitualizing behaviours that connect micro‐level actions with organizational level theorizing. Our model illuminates three phases that we propose are essential to creating and sustaining this connection: micro‐level theorizing, encouraging trying the new practices, and facilitating collective meaning‐making.

Microlending provides a valuable alternative to traditional financing for entrepreneurs in impoverished countries. Drawing from theory on political rhetoric and the concept of warm-glow giving, we examine characteristics of entrepreneurial narratives that are related to how quickly entrepreneurs receive funding. Using a sample of 6051 narratives from entrepreneurs in developing countries, we demonstrate that narratives higher in language indicating blame and present concern lead to more rapid funding, while narratives higher in accomplishment, tenacity, and variety lead to slower funding. Our findings suggest that the presentation of investment profiles should be carefully managed to maximize funding likelihood.

Some environments constrain the information that managers and decision makers can observe. We examine judgment in censored environments where a constraint, the censorship point, systematically distorts the observed sample. Random instances beyond the censorship point are observed at the censorship point, whereas uncensored instances are observed at their true value. Many important managerial decisions occur in censored environments, such as inventory, risk taking, and employee evaluation decisions. In this research, we demonstrate a censorship bias—individuals tend to rely too heavily on the observed censored sample, biasing their belief about the underlying population. We further show that the censorship bias is exacerbated for higher degrees of censorship, higher variance in the population, and higher variability in the censorship points. In four studies, we find evidence of the censorship bias across the domains of demand estimation and sequential risk taking. The bias causes individuals to make costly decisions and behave in an overly risk-averse manner. This paper was accepted by Teck Ho, judgment and decision making.

Abstract A heated debate exists as to whether discontinuities in earnings distributions are indicative of earnings management. While many studies attribute discontinuities in earnings distributions to earnings management, other studies argue that earnings discontinuities are artifacts of sample selection and research design. Overall, there is limited direct evidence of a connection between earnings discontinuities and earnings management. In this study, we provide direct evidence linking earnings management to earnings discontinuities for a sample of firms that settle securities class action lawsuits and restate earnings from the alleged GAAP violation period. We compare the distribution of restated (“unmanaged”) earnings to originally reported (“managed”) earnings. We find that discontinuities are not present in the distribution of analyst forecast errors and earnings changes using unmanaged earnings but are present using managed earnings. The discontinuity in the earnings level distribution is attenuated, but not eliminated, on an unmanaged basis. These shifts among our sample of firms are caused by earnings management and cannot be explained by sample selection or research design issues. Our findings are important because many studies use earnings discontinuities as a proxy for intentional earnings manipulations and we provide the first direct evidence of a link between these two phenomena.

We introduce the pathwise optimization (PO) method, a new convex optimization procedure to produce upper and lower bounds on the optimal value (the “price”) of a high-dimensional optimal stopping problem. The PO method builds on a dual characterization of optimal stopping problems as optimization problems over the space of martingales, which we dub the martingale duality approach. We demonstrate via numerical experiments that the PO method produces upper bounds of a quality comparable with state-of-the-art approaches, but in a fraction of the time required for those approaches. As a by-product, it yields lower bounds (and suboptimal exercise policies) that are substantially superior to those produced by state-of-the-art methods. The PO method thus constitutes a practical and desirable approach to high-dimensional pricing problems. Furthermore, we develop an approximation theory relevant to martingale duality approaches in general and the PO method in particular. Our analysis provides a guarantee on the quality of upper bounds resulting from these approaches and identifies three key determinants of their performance: the quality of an input value function approximation, the square root of the effective time horizon of the problem, and a certain spectral measure of “predictability” of the underlying Markov chain. As a corollary to this analysis we develop approximation guarantees specific to the PO method. Finally, we view the PO method and several approximate dynamic programming methods for high-dimensional pricing problems through a common lens and in doing so show that the PO method dominates those alternatives. This paper was accepted by Wei Xiong, stochastic models and simulation.

By examining the impact of capital regulation on bank risk-taking using a local estimation technique, this paper attempts to quantify for the first time the heterogeneous response of banks towards this type of regulation in banking sectors of western-type economies. Subsequently, using this information, we examine the sources of heterogeneity. The findings suggest that the impact of capital regulation on bank risk is very heterogeneous across banks and the sources of this heterogeneity can be traced into both bank and industry characteristics, as well as into macroeconomic conditions. An important implication of the findings is that common capital regulatory umbrellas are not sufficient to promote financial stability, especially if they are not accompanied by supervisory effectiveness. On the basis of our findings, we contend that more focus should be placed on the actions needed to restrain excessive risk-taking of banks.

ABSTRACT Some claim that rules-based accounting standards shield firms from litigation, while others argue that violations of detailed rules give plaintiffs a “roadmap” to successful litigation. We inform this debate by investigating whether rules-based standards are associated with the incidence and outcome of securities class action litigation. Overall, our results suggest that rules-based standards are associated with a lower incidence of litigation but are not associated with litigation outcomes. These results are of interest in the debate regarding the switch from a more rules-based U.S. GAAP to a more principles-based IFRS. JEL Classifications: K22, K41, M41.

We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.