Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets

Abstract

To identify disruptions in credit markets, research on the role of asset prices in economic fluctuations has focused on the information content of various corporate credit spreads. We re-examine this evidence using a broad array of credit spreads constructed directly from the secondary bond prices on outstanding senior unsecured debt issued by a large panel of nonfinancial firms. An advantage of our “ground-up” approach is that we are able to construct matched portfolios of equity returns, which allows us to examine the information content of bond spreads that is orthogonal to the information contained in stock prices of the same set of firms, as well as in macroeconomic variables measuring economic activity, inflation, interest rates, and other financial indicators. Our portfolio-based bond spreads contain substantial predictive power for economic activity and outperform—especially at longer horizons—standard default-risk indicators. Much of the predictive power of bond spreads for economic activity is embedded in securities issued by intermediate-risk rather than high-risk firms. According to impulse responses from a structural factor-augmented vector autoregression, unexpected increases in bond spreads cause large and persistent contractions in economic activity. Indeed, shocks emanating from the corporate bond market account for more than 30 percent of the forecast error variance in economic activity at the two- to four-year horizon. Overall, our results imply that credit market shocks have contributed significantly to US economic fluctuations during the 1990–2008 period.

Introduction

After markets for securitized credit products collapsed dramatically in the second half of 2007, growth in a number of industrialized economies slowed markedly, suggesting that disruptions in financial markets can have important macroeconomic consequences. The fact that sharp and sudden deteriorations in financial conditions are typically followed by a prolonged period of economic weakness is a feature of a growing number of economic downturns in the US and abroad. During periods of credit market turmoil, financial asset prices, owing to their forward-looking nature, are especially informative of linkages between the real and financial sides of economy: movements in asset prices can provide early-warning signals for such economic downturns and can be used to gauge the degree of strains in financial markets.

Past research on the role of asset prices in signaling future economic conditions and in propagating economic fluctuations has emphasized the information content of default-risk indicators such as corporate credit spreads—the difference in yields between various corporate debt instruments and government securities of comparable maturity—for the state of the economy and risks to the economic outlook.¹ In a recent paper, Philippon (2008) provided a theoretical framework in which the predictive content of corporate bond spreads for economic activity—absent any financial frictions—reflects a general decline in economic fundamentals stemming from a reduction in the expected present value of corporate cash flows prior to a cyclical downturn. Rising credit spreads can also reflect disruptions in the supply of credit resulting from the worsening in the quality of corporate balance sheets or from the deterioration in the health of financial intermediaries that supply credit—the financial accelerator mechanism emphasized by Bernanke et al. (1999). In this context, a contraction in credit supply causes asset values to fall, incentives to default to increase, and yield spreads on private debt instruments to widen before economic downturns, as lenders demand compensation for the expected increase in defaults.

In terms of forecasting macroeconomic conditions, the empirical success of this vein of research is considerable. Nevertheless, results vary substantially across different financial instruments underlying the credit spreads under consideration as well as across different time periods. For example, the spread of yields between nonfinancial commercial paper and comparable-maturity Treasury bills—the so-called paper-bill spread—has lost much of its forecasting power since the early 1990s.² In contrast, yield spreads based on indexes of high-yield corporate bonds, which contain information from markets that were not in existence prior to the mid-1980s, have done particularly well at forecasting output growth during the previous decade, according to Gertler and Lown (1999) and Mody and Taylor (2004). Stock and Watson (2003b), however, found mixed evidence for the high-yield spread as a leading indicator during this period, largely because it falsely predicted an economic downturn in the autumn of 1998. This dichotomy of findings is perhaps not surprising, because as financial markets evolve, the information content of specific financial assets prices may change as well. The fragility of results may also reflect the fact that this research has generally relied on a single credit spread index, rather than on multiple indexes reflecting a broad cross-section—in terms of both default risk and maturity—of private debt instruments.

In addition to focusing on a single credit spread index, researchers often ignore the information content of other asset prices when evaluating the forecasting ability of different default-risk indicators. Although it is straightforward to control for the general level of equity prices in such analysis, it is usually not possible to obtain equity valuations of the borrowers whose debt securities are used to construct the credit spreads under consideration.³ Such information could potentially be used to distinguish movements in corporate credit spreads that are due to general trends in financial asset prices associated with a given class of borrowers from the movements in spreads that are specifically related to developments in credit markets.

When assessing the information content of corporate credit spreads for economic activity, it is also important to control accurately for the maturity structure of the underlying credit instruments. The widely used paper-bill spreads, for example, are based on short maturity instruments—typically between one and six months—whereas the specific maturity structure of corporate bond spread indexes such as the high-yield spread or Baa–Aaa spread—though much longer—is not generally known. In general, short-term credit instruments reflect near-term default risk, whereas longer maturity instruments are likely better at capturing expectations about future economic conditions one to two years ahead, a forecast horizon typically associated with business cycle fluctuations. Thus, a correct assessment of the ability of credit spreads to forecast at business cycle frequencies likely requires careful attention to the maturity structure of securities used to construct credit spreads.

This paper considers credit spreads constructed directly from monthly data on prices of senior unsecured corporate debt traded in the secondary market over the 1990–2008 period, issued by about 900 US nonfinancial corporations. In contrast to many other corporate financial instruments, long-term senior unsecured bonds represent a class of securities with a long history containing a number of business cycles, an attribute that is most useful in the valuation process of debt instruments. In addition, the rapid pace of financial innovation over the past 20 years has not affected the basic structure of these securities. Thus, the information content of spreads constructed from yields on senior unsecured corporate bonds is likely to provide more consistent signals regarding economic outcomes relative to spreads based on securities with a shorter history or securities whose structure or relevant market has undergone a significant structural change.

We exploit the cross-sectional heterogeneity of our data by constructing an array of credit-spread portfolios sorted by the issuer's ex-ante expected probability of default and the bond's remaining term-to-maturity. In the construction of these “bond portfolios,” we rely on the monthly firm-specific expected default frequencies (EDFs) constructed by the Moody's/KMV (MKMV) corporation. Because they are based on observable information in equity markets, EDFs provide a more timely and potentially more objective assessment of credit risk compared with the issuer's credit rating. Importantly, by building bond portfolios from the “ground up,” we can also construct portfolios of stock returns—sorted by the same credit-risk categories—corresponding to the firms that issued those bonds. These matched portfolios of stock returns, in turn, serve as controls for news about firms’ future earnings as these corporate borrowers experience shocks to their creditworthiness.

Two empirical methods are employed to assess the role of credit market factors in economic fluctuations. First, the analysis documents the predictive content of corporate bond spreads in our credit-risk portfolios for measures of economic activity such as the growth of nonfarm payroll employment (EMP) and industrial production (IP), and we compare the forecasting power of credit spreads in our EDF-based bond portfolios to that of other default-risk indicators emphasized in the literature. The results show that at shorter forecast horizons, the information content of credit spreads in our EDF-based bond portfolios for these monthly measures of economic activity is comparable to that of standard credit spread indexes. At longer forecast horizons, however, our portfolios of credit spreads outperform—both in-sample and out-of-sample—standard default-risk indicators by almost a factor of two. The results from these forecasting exercises indicate that the predictive power of corporate bond spreads comes from the middle of the credit-quality spectrum, a result also documented by Mueller (2007) who examined the predictive content of corporate bond spread indexes across different rating categories. Our results also indicate that at longer forecasting horizons, the predictive power of corporate bond spreads is concentrated at long maturities. At these forecasting horizons, the predictive content of publicly available long maturity investment-grade corporate bond spread indexes—such as those rated between BBB and AA—is comparable to that of our low-risk long maturity EDF portfolios. All told, these results imply that the forecasting ability of credit spreads is well captured by a single index that measures credit spreads of long maturity bonds issued by firms with low to medium probability of default.

The second empirical approach assesses the impact on the macroeconomy of movements in credit spreads in our EDF-based bond portfolios within a structural factor-augmented vector autoregression (FAVAR) framework proposed by Bernanke and Boivin (2003), Bernanke et al. (2005), and Stock and Watson (2005), an approach particularly well suited to our case given the large number of variables under consideration. Within the FAVAR framework, we identify credit market shocks from the corporate bond spreads that are orthogonal to general measures of economic activity, inflation, real interest rates, and various financial indicators, as well as to equity returns of firms whose outstanding bonds were used to construct credit spreads in our EDF-based portfolios. According to the results from our FAVAR analysis, an unanticipated worsening of business credit conditions—identified through the widening of corporate bond spreads that is orthogonal to other contemporaneous information—predicts substantial and long-lasting declines in economic activity. The decomposition of the forecast error variance implies that these credit market shocks account, on average, for more than 30 percent of the variation in economic activity (as measured by industrial production) at the two- to four-year horizon. We also find that incorporating information from the stock market does not alter any of our conclusions. Thus to the extent that equity returns capture news about firms’ future earnings, our FAVAR specification identifies shocks to credit spreads that are orthogonal to such news and hence are specific to events that lead to disruptions in the corporate bond market.⁴ Overall, our results suggest that disturbances specific to credit markets account for a substantial fraction of the volatility in US economic activity during the 1990–2008 period.

The remainder of this paper is organized as follows. Section 2 discusses the characteristics of our underlying security-level data, the construction of portfolios based on expected default risk, and presents the key summary statistics of our EDF-based financial indicators. Section 3 presents our forecasting exercises. Section 4 contains results of our FAVAR analysis. Section 5 concludes.