Abstract

ABSTRACT We examine the characteristics of firms that adopt enterprise risk management (ERM) and find support for the hypothesis that firms adopt ERM for direct economic benefit rather than to merely comply with regulatory pressure. Using chief risk officer (CRO) hires as a proxy for ERM adoption we find that firms that are larger, more volatile, and have greater institutional ownership are more likely to adopt ERM. In addition, when the CEO has incentives to take risk, the firm is also more likely to hire a CRO. Finally, banks with lower levels of Tier I capital are also more likely to hire a CRO. INTRODUCTION In recent years, researchers have paid increasing attention to the growing prominence of enterprise risk management (ERM). In most cases this research has focused on the ERM process itself and the potential gains from adoption. For example, Nocco and Stulz (2006) argue that market imperfections render invalid the frictionless market view that a firm should not expend resources on managing idiosyncratic risk. Instead, they argue that an integrated, holistic, approach to risk management can be used to create shareholder value. Other papers discuss ERM in broad terms and mostly assume that ERM has or will be adopted. For example, Aabo, Fraser, and Simkins (2005) provide a road map for implementation, and Beasley, Clune, and Hermanson (2005) examine the factors associated with the degree of adoption. There has, however, been little work examining the characteristics of firms that actually implement ERM. In this article, we examine factors that are hypothesized to be drivers of ERM implementation using a sample of 138 firms from 1992 to 2005. Because we are unable to directly observe whether a firm adopts ERM, we identify ERM adoption using the firm's decision to hire a chief risk officer (CRO). The goal of our study is to examine the characteristics of firms that choose to adopt ERM by using various proxies for the factors that are hypothesized to drive ERM adoption. Our work is related to Liebenberg and Hoyt (2003) who use a logistic model to examine the particular characteristics of firms hiring a CRO. (1) Liebenberg and Hoyt find that size and leverage are both related to the decision to implement ERM; however, many of the other factors in their regression model are insignificant. Their insignificant results are likely due to a small number of firms hiring a CRO (n = 26) and the use of the logistic model. In this application, a logistic model is not necessarily the appropriate method for testing the significance of a one-time event that can occur through time. We improve upon the method of Liebenberg and Hoyt in three ways. First, we use a larger sample of firms. Second, we analyze a wider range of possible determinants of CRO hiring. And third, we use a Cox proportional hazard model to measure the importance of the variables in the regression analysis. The hazard model allows us to examine a large sample of companies, of which only a proportion choose to hire a CRO, and generates more reliable standard errors than a logit model. Our research builds on the existing risk management literature that suggests a range of factors that may influence the decision to employ traditional risk management. The factors that we examine cover a broad range of variables that measure financial, asset, market, and managerial characteristics. Financial characteristics represent indirect measures of the likelihood of financial distress. Firms that face greater risk of financial distress and the implicit and explicit costs contained therein may benefit from ERM when ERM reduces the chance of costly lower tail cash flow outcomes. Asset characteristics measure the potential costs of financial distress, such as the inability to pursue growth options. Market characteristics measure the potential costs associated with volatile security performance, such as a higher cost of capital. Finally managerial characteristics measure the degree to which the CEO's stock and option-based compensation encourages risk-taking or risk-avoiding behavior. …

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