عدم تقارن اطلاعات تامین کنندگان و مشتریان و گسترش بازدهی اوراق قرضه شرکتی

This study investigates the information asymmetry effects of suppliers and customers on a firm’s bond yield spreads by employing American bond market data from 2001 to 2008. This study finds that both suppliers’ and customers’ information asymmetry effects significantly explain a firm’s bond yield spreads. Besides, the information asymmetry effects of more important suppliers and customers are more significant than those of less important ones. The results are robust even after controlling for other well-known firm specific and economic variables

The recent global financial crisis reveals that supplier/customer relationship magnifies the domino effects of firms’ default risk and liquidity crunch among business counterparties because business relationship provides a connection for transmitting a firm’s risks to its business counterparties. The risks transmitted through a firm and its suppliers and customers are the variations of inventory flows, cash flows and information flows. The inventory and cash flows occur between a firm and its suppliers and customers whenever they have business transactions and constitute the main components of a firm’s working capital which is related to a firm’s trade credit policy, inventory policy and customers’ demand uncertainty (Merville and Tavis, 1973, Tsai, 2008 and Hill et al., 2010). These two flows are mainly driven by market conditions as well as firm-specific characteristics. The information asymmetry (later denoted as IA) of a firm’s suppliers and customers augments the uncertainty (variation) of inventory flow (Blinder, 1986, West, 1986 and Kahn, 1987),1 and in turn affects the variations of the firm’s cash flow and operating performance (Porter, 1979, Chopra and Meindl, 2001 and Tsai, 2008). As a result, the IA of a firm’s business counterparties materially affects its asset value distribution and therefore its credit quality. Few existing studies consider the suppliers’ and customers’ IA effects on a firm’s credit risk (measured by bond yield spreads). Lu et al. (2010) find that a firm’s IA plays a significant role in determining its bond yield spreads.2 Other studies discuss the wealth effects of financial distress between a firm and its suppliers and customers. They investigate the effects of bankruptcy announcements on the equity values of a bankrupt firm’s competitors (Lang and Stulz, 1992), customers, and suppliers (Hertzel et al., 2008). Kale and Shahrur (2007) explore the relationship between corporate capital structure and the characteristics of suppliers and customers without investigating the issues of credit risk.3 To address this issue, the current study empirically examines whether or not business counterparties’ (suppliers’ and customers’) IA significantly influences a firm’s bond yield spreads when controlling for well-known variables affecting corporate bond yield spreads, such as the firm’s own leverage ratio, equity volatility, maturity, coupon, issuance amount, credit rating, R&D intensity, and firm size. Literature also shows that the variations of suppliers’ and customers’ flows (inventory flow, cash flow and information flow) have salient influence on a firm’s inventory behavior (Kahn, 1987) and cash flow (Tsai, 2008). More specifically, if a firm’s suppliers have a higher degree of IA, the firm faces higher uncertainty in the supply of production inputs or inventory and higher uncertainty in the costs of both production and goods sold, which affect not only the firm’s inventory behavior but also the firm’s cash outflows (Blinder, 1986, West, 1986 and Kahn, 1987). Besides, if a firm’s customers have a higher degree of IA, the firm encounters higher uncertainty in the customers’ demand (or sales) and higher uncertainty in the collection of account receivables, which affect the firm’s trade credit policy (Smith, 1987, Lee and Stowe, 1993 and Pike et al., 2005), operating performance and cash inflows (Tsai, 2008). These lead to the deduction that the variations of business counterparties’ operating performance influence a firm’s asset value distribution and hence its credit risk (and also its bond yield spreads) (Merton, 1974 and Duffie and Lando, 2001). The current research uses American bond market data from 2001 to 2008 to examine the suppliers’ and customers’ IA effects on a firm’s bond yield spreads. The sample covers 57,457 monthly bond observations (among them, 24,745 with supplier identifications, 15,965 with customer identifications and 6151 with both supplier and customer identifications). This paper uses the structural credit model framework of Merton (1974) and Duffie and Lando (2001) to assess and test the hypotheses that the IA of a firm’s suppliers and customers positively relates to its credit risk and bond yield spreads. Similar to Lu et al., 2010 and Chen et al., 2011, and Akins et al. (2012), the current study uses the probability of information-based trading estimated by an extended PIN model (ADJPIN) (Duarte and Young, 2009)4 as a market-based proxy for the degree of a firm’s IA. The proxy for the information asymmetry between a firm and its business counterparties assumes that the relation between a firm and its business counterparties is similar to that between informed and uninformed investors of an asset. Higher IA of a firm’s business counterparties causes the firm to face higher information uncertainty which increases the firm’s credit risk. Empirical results of this study show that both suppliers’ and customers’ IA play an important role in explaining a firm’s bond yield spreads. When controlling for the firm’s suppliers’/customers’ sizes and R&D intensities, the firm’s own leverage ratio, equity volatility, firm size, R&D intensity, credit rating, and other well-known spread determinant variables, the influence of suppliers’ (customers’) IA on bond yield spreads is higher than (approximately equal to) that of credit rating. In addition, the IA effects of more important suppliers/customers are more economically significant than those of less important ones. The remainder of this paper is organized as follows. Section 2 introduces the concept of information asymmetry and the main proxy proposed by Duarte and Young (2009). Section 3 presents the hypotheses. Section 4 summarizes major variables used in the empirical examinations. Section 5 presents and analyzes empirical results. Finally, Section 6 offers concluding remarks.

The recent financial tsunami is aggravated by the contagion effect among business connected firms, which reveals that credit risk is transmitted through business counterparties due to the connection of the variations of inventory flows, cash flows and information flows among them. Literature documents that information flow is the most important key driver to enhance value creation of business relationship. This is the first study to explore the information asymmetry effects of business counterparties on a firm’s bond yield spreads by using American bond market data from 2001 to 2008. Empirical results of this study show that the information asymmetry of a firm’s suppliers and customers has a significantly positive impact on its corporate bond yield spreads when controlling for spread determinant variables well known in the literature and credit ratings. This study also finds that the information asymmetry effects of more important business counterparties are more significant than those of less important ones. These results show that information asymmetry effects of a firm’s business counterparties help traditional structural models explain corporate credit risk (and also the corporate bond yield spreads).