The 33 references with contexts in paper Christopher F Baum, Chi Wan (2009) “Macroeconomic Uncertainty and Credit Default Swap Spreads” / RePEc:boc:bocoec:724

1
Arnold, I. J. M. and Vrugt, E. B. (2008), ‘Fundamental uncertainty and stock market volatility’,Applied Financial Economics18, 1425–1440.
Total in-text references: 1
  1. In-text reference with the coordinate start=5589
    Prefix
    Our results nicely complement the empirical findings re1Tang and Yan (2006) and Tang and Yan (2008b) model firms’ default risk as depending on (among other factors) the volatility of aggregate economic growth. However, their model contains a fixed level of volatility, while we focus upon variations in macroeconomic volatility as a factor influencing CDS spreads. 3 ported by
    Exact
    Arnold and Vrugt (2008) and
    Suffix
    Arshanapalli, d’Ouville, Fabozzi and Switzer (2006). Specifically, Arnold and Vrugt document a positive link between stock market volatility and macroeconomic uncertainty; Arshanapalli et al. show that both stock and bond markets have higher volatility during the period of macroeconomic announcements.

3
Baum, C. F. (2001), ‘DENTON: Stata module to interpolate a quarterly flow series from annual totals via proportional Denton method’, Statistical Software Components, Boston
Total in-text references: 1
  1. In-text reference with the coordinate start=9045
    Prefix
    The first measure is the conditional variance of the growth rate of a monthly measure of real gross domestic product. We derive the monthly GDP series via the proportional Denton procedure using the monthly index of industrial production as an interpolating variable (see
    Exact
    Baum (2001))
    Suffix
    from quarterly real GDP (International Financial Statistics series 99BRZF). This measure is designed to reflect the overall uncertainty of the macroeconomic environment. The second measure is derived from the monthly index of industrial production (International Financial Statistics series 66IZF).

5
Baum, C. F., Caglayan, M., Ozkan, N. and Talavera, O. (2006), ‘The impact of macroeconomic uncertainty on non-financial firms’ demand for liquidity’,Review of Financial Economics15, 289–304.
Total in-text references: 1
  1. In-text reference with the coordinate start=7936
    Prefix
    Finally, we conclude in Section IV. 4 II. Data sources and construction In this section, we detail the data sources used in our study and how variables are constructed. Identifying macroeconomic uncertainty In our investigation, as in
    Exact
    Driver, Temple and Urga (2005), Byrne and Davis (2002) and Baum, Caglayan, Ozkan and Talavera (2006),
    Suffix
    we employ aGARCHmodel to proxy for macroeconomic uncertainty. We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g.

6
Baum, C. F., Chakraborty, A. and Liu, B. (2010), ‘The impact of macroeconomic uncertainty on firms’ changes in financial leverage’,International Journal of Finance & Economics 15, 22–30.
Total in-text references: 1
  1. In-text reference with the coordinate start=4059
    Prefix
    The effect of macroeconomic uncertainty on CDS spreads is ambiguous.1On the one hand, greater macroeconomic uncertainty may increase the firm’s default risk as firms are more likely to be credit constrained. For instance, Korajczyk and Levy (2003) shows that macroeconomic conditions affect a firm’s ability to borrow.
    Exact
    Baum, Stephan and Talavera (2009) and Baum, Chakraborty and Liu (2010)
    Suffix
    report strong empirical evidence that macroeconomic uncertainty plays an important role in determining both the level and changes of the firm’s leverage. Therefore, uncertainty increases CDS spreads.

7
Baum, C. F., Stephan, A. and Talavera, O. (2009), ‘The effects of uncertainty on the leverage of nonfinancial firms’,Economic Inquiry47(2), 216–225.
Total in-text references: 1
  1. In-text reference with the coordinate start=4059
    Prefix
    The effect of macroeconomic uncertainty on CDS spreads is ambiguous.1On the one hand, greater macroeconomic uncertainty may increase the firm’s default risk as firms are more likely to be credit constrained. For instance, Korajczyk and Levy (2003) shows that macroeconomic conditions affect a firm’s ability to borrow.
    Exact
    Baum, Stephan and Talavera (2009) and Baum, Chakraborty and Liu (2010)
    Suffix
    report strong empirical evidence that macroeconomic uncertainty plays an important role in determining both the level and changes of the firm’s leverage. Therefore, uncertainty increases CDS spreads.

8
Blanco, R., Brennan, S. and Marsh, I. W. (2005), ‘An empirical analysis of the dynamic relation between investment-grade bonds and credit default swaps’,Journal of Finance 60(5), 2255–2281.
Total in-text references: 1
  1. In-text reference with the coordinate start=2473
    Prefix
    ), Houweling, Mentink and Vorst (2005), as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk. Furthermore,
    Exact
    Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004)
    Suffix
    have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008), have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk.

10
Byrne, J. P. and Davis, E. P. (2002), Investment and uncertainty in the G7, Discussion papers, National Institute of Economic Research, London.
Total in-text references: 1
  1. In-text reference with the coordinate start=7936
    Prefix
    Finally, we conclude in Section IV. 4 II. Data sources and construction In this section, we detail the data sources used in our study and how variables are constructed. Identifying macroeconomic uncertainty In our investigation, as in
    Exact
    Driver, Temple and Urga (2005), Byrne and Davis (2002) and Baum, Caglayan, Ozkan and Talavera (2006),
    Suffix
    we employ aGARCHmodel to proxy for macroeconomic uncertainty. We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g.

11
Campbell, J. Y. and Taksler, G. B. (2003), ‘Equity volatility and corporate bond yields’, Journal of Finance58(6), 2321–2350.
Total in-text references: 1
  1. In-text reference with the coordinate start=3022
    Prefix
    Consequently, several recent papers, including Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008), have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk. A number of recent studies have investigated the empirical determinants of credit spreads.
    Exact
    Campbell and Taksler (2003)
    Suffix
    document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads. More recently, Zhang, Zhou and Zhu (2005) 2 further document that equity volatility and jump processes have strong explanatory power in the pricing of CDS.

12
Chen, L., Lesmond, D. A. and Wei, J. (2007), ‘Corporate yield spreads and bond liquidity’, Journal of Finance62(1), 119–149.
Total in-text references: 1
  1. In-text reference with the coordinate start=2018
    Prefix
    As a standardized swap contract, CDS can be traded over the counter, which enables investors to hedge or speculate on credit risk in a relatively cost-effective way. CDS spreads fluctuate over time to reflect changes in the creditworthiness of the reference entities. As documented in
    Exact
    Longstaff, Mithal and Neis (2005), Chen, Lesmond and Wei (2007), Houweling, Mentink and Vorst (2005),
    Suffix
    as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk.

13
Coles, J. L., Daniel, N. D. and Naveen, L. (2006), ‘Managerial incentives and risk-taking’, Journal of Financial Economics79(2), 431 – 468.
Total in-text references: 1
  1. In-text reference with the coordinate start=7006
    Prefix
    For instance, Graham, Harvey and Puri (2009) provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g. John and John (1993) and Jin (2002)) and empirically (e.g.
    Exact
    Rajgopal and Shevlin (2002), Knopf, Nam and Thornton (2002) and Coles, Daniel and Naveen (2006)),
    Suffix
    that firms’ compensation structures may offer managers with incentives for risk-taking and thus affect firms’ credit quality. Our primary finding of a positive effect of macroeconomic uncertainty on credit spreads is largely unaffected after further controlling for issuers’ fixed effects.

14
Driver, C., Temple, P. and Urga, G. (2005), ‘Profitability, capacity, and uncertainty: A model of UK manufacturing investment’,Oxford Economic Papers57(1), 120–141.
Total in-text references: 1
  1. In-text reference with the coordinate start=7936
    Prefix
    Finally, we conclude in Section IV. 4 II. Data sources and construction In this section, we detail the data sources used in our study and how variables are constructed. Identifying macroeconomic uncertainty In our investigation, as in
    Exact
    Driver, Temple and Urga (2005), Byrne and Davis (2002) and Baum, Caglayan, Ozkan and Talavera (2006),
    Suffix
    we employ aGARCHmodel to proxy for macroeconomic uncertainty. We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g.

15
Elton, E. J., Gruber, M. J., Agrawal, D. and Mann, C. (2004), ‘Factors affecting the valuation of corporate bonds’,Journal of Banking & Finance28(11), 2747–2767.
Total in-text references: 1
  1. In-text reference with the coordinate start=2133
    Prefix
    CDS spreads fluctuate over time to reflect changes in the creditworthiness of the reference entities. As documented in Longstaff, Mithal and Neis (2005), Chen, Lesmond and Wei (2007), Houweling, Mentink and Vorst (2005), as well as in
    Exact
    Elton, Gruber, Agrawal and Mann (2004),
    Suffix
    corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk.

16
Ghosal, V. and Loungani, P. (2000), ‘The differential impact of uncertainty on investment in small and large business’,The Review of Economics and Statistics82, 338–349. 12
Total in-text references: 1
  1. In-text reference with the coordinate start=8284
    Prefix
    uncertainty In our investigation, as in Driver, Temple and Urga (2005), Byrne and Davis (2002) and Baum, Caglayan, Ozkan and Talavera (2006), we employ aGARCHmodel to proxy for macroeconomic uncertainty. We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g.
    Exact
    Ghosal and Loungani (2000))
    Suffix
    or survey-based measures based on the dispersion of forecasts (e.g. Graham and Harvey (2001); Schmukler, Mehrez and Kaufmann (1999)). To ensure the robustness of our empirical findings, we construct three proxies for macroeconomic uncertainty from the conditional variance of the GDP growth rate, the index of industrial production and the returns on the S&P 500 Composite Index.

17
Graham, J. R. and Harvey, C. R. (2001), ‘The theory and practice of corporate finance: Evidence from the field’,Journal of Financial Economics60, 187–243.
Total in-text references: 1
  1. In-text reference with the coordinate start=8380
    Prefix
    We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g. Ghosal and Loungani (2000)) or survey-based measures based on the dispersion of forecasts (e.g.
    Exact
    Graham and Harvey (2001); Schmukler, Mehrez and Kaufmann (1999)). To
    Suffix
    ensure the robustness of our empirical findings, we construct three proxies for macroeconomic uncertainty from the conditional variance of the GDP growth rate, the index of industrial production and the returns on the S&P 500 Composite Index.

18
Graham, J. R., Harvey, C. R. and Puri, M. (2009), Managerial Attitudes and Corporate
Total in-text references: 1
  1. In-text reference with the coordinate start=6703
    Prefix
    Our models control for firms’ unobserved heterogeneity (e.g. managerial attributes, corporate governance and the company’s executive compensation policies) that may affect firms’ credit conditions. For instance,
    Exact
    Graham, Harvey and Puri (2009)
    Suffix
    provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g.

20
Houweling, P., Mentink, A. and Vorst, T. (2005), ‘Comparing possible proxies of corporate bond liquidity’,Journal of Banking & Finance29(6), 1331–1358.
Total in-text references: 1
  1. In-text reference with the coordinate start=2018
    Prefix
    As a standardized swap contract, CDS can be traded over the counter, which enables investors to hedge or speculate on credit risk in a relatively cost-effective way. CDS spreads fluctuate over time to reflect changes in the creditworthiness of the reference entities. As documented in
    Exact
    Longstaff, Mithal and Neis (2005), Chen, Lesmond and Wei (2007), Houweling, Mentink and Vorst (2005),
    Suffix
    as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk.

21
Houweling, P. and Vorst, T. (2005), ‘Pricing default swaps: Empirical evidence’,Journal of
Total in-text references: 1
  1. In-text reference with the coordinate start=2742
    Prefix
    Furthermore, Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004) have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including
    Exact
    Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008),
    Suffix
    have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk. A number of recent studies have investigated the empirical determinants of credit spreads. Campbell and Taksler (2003) document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads.

23
Hull, J., Predescu, M. and White, A. (2004), ‘The relationship between credit default swap spreads, bond yields, and credit rating announcements’,Journal of Banking & Finance 28(11), 2789–2811.
Total in-text references: 1
  1. In-text reference with the coordinate start=2742
    Prefix
    Furthermore, Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004) have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including
    Exact
    Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008),
    Suffix
    have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk. A number of recent studies have investigated the empirical determinants of credit spreads. Campbell and Taksler (2003) document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads.

24
Jin, L. (2002), ‘Ceo compensation, diversification, and incentives’,Journal of Financial Economics66(1), 29–63.
Total in-text references: 1
  1. In-text reference with the coordinate start=6946
    Prefix
    For instance, Graham, Harvey and Puri (2009) provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g.
    Exact
    John and John (1993) and Jin (2002)) and
    Suffix
    empirically (e.g. Rajgopal and Shevlin (2002), Knopf, Nam and Thornton (2002) and Coles, Daniel and Naveen (2006)), that firms’ compensation structures may offer managers with incentives for risk-taking and thus affect firms’ credit quality.

25
John, T. A. and John, K. (1993), ‘Top-management compensation and capital structure’, Journal of Finance48(3), 949–974.
Total in-text references: 1
  1. In-text reference with the coordinate start=6946
    Prefix
    For instance, Graham, Harvey and Puri (2009) provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g.
    Exact
    John and John (1993) and Jin (2002)) and
    Suffix
    empirically (e.g. Rajgopal and Shevlin (2002), Knopf, Nam and Thornton (2002) and Coles, Daniel and Naveen (2006)), that firms’ compensation structures may offer managers with incentives for risk-taking and thus affect firms’ credit quality.

26
Knopf, J. D., Nam, J. and Thornton, J. H. (2002), ‘The volatility and price sensitivities of managerial stock option portfolios and corporate hedging’,Journal of Finance 57(2), 801–813.
Total in-text references: 1
  1. In-text reference with the coordinate start=7006
    Prefix
    For instance, Graham, Harvey and Puri (2009) provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g. John and John (1993) and Jin (2002)) and empirically (e.g.
    Exact
    Rajgopal and Shevlin (2002), Knopf, Nam and Thornton (2002) and Coles, Daniel and Naveen (2006)),
    Suffix
    that firms’ compensation structures may offer managers with incentives for risk-taking and thus affect firms’ credit quality. Our primary finding of a positive effect of macroeconomic uncertainty on credit spreads is largely unaffected after further controlling for issuers’ fixed effects.

27
Korajczyk, R. A. and Levy, A. (2003), ‘Capital structure choice: macroeconomic conditions and financial constraints’,Journal of Financial Economics68(1), 75–109.
Total in-text references: 1
  1. In-text reference with the coordinate start=3952
    Prefix
    The effect of macroeconomic uncertainty on CDS spreads is ambiguous.1On the one hand, greater macroeconomic uncertainty may increase the firm’s default risk as firms are more likely to be credit constrained. For instance,
    Exact
    Korajczyk and Levy (2003)
    Suffix
    shows that macroeconomic conditions affect a firm’s ability to borrow. Baum, Stephan and Talavera (2009) and Baum, Chakraborty and Liu (2010) report strong empirical evidence that macroeconomic uncertainty plays an important role in determining both the level and changes of the firm’s leverage.

28
Longstaff, F. A., Mithal, S. and Neis, E. (2005), ‘Corporate yield spreads: Default risk or liquidity? new evidence from the credit default swap market’,Journal of Finance 60(5), 2213–2253.
Total in-text references: 1
  1. In-text reference with the coordinate start=2018
    Prefix
    As a standardized swap contract, CDS can be traded over the counter, which enables investors to hedge or speculate on credit risk in a relatively cost-effective way. CDS spreads fluctuate over time to reflect changes in the creditworthiness of the reference entities. As documented in
    Exact
    Longstaff, Mithal and Neis (2005), Chen, Lesmond and Wei (2007), Houweling, Mentink and Vorst (2005),
    Suffix
    as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk.

29
Norden, L. and Weber, M. (2004), ‘Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements’,Journal of Banking & Finance 28(11), 2813–2843.
Total in-text references: 1
  1. In-text reference with the coordinate start=2473
    Prefix
    ), Houweling, Mentink and Vorst (2005), as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk. Furthermore,
    Exact
    Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004)
    Suffix
    have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008), have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk.

30
Pan, J. and Singleton, K. J. (2008), ‘Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads’,Journal of Finance63(5), 2345–2384.
Total in-text references: 1
  1. In-text reference with the coordinate start=2742
    Prefix
    Furthermore, Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004) have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including
    Exact
    Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008),
    Suffix
    have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk. A number of recent studies have investigated the empirical determinants of credit spreads. Campbell and Taksler (2003) document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads.

31
Rajgopal, S. and Shevlin, T. (2002), ‘Empirical evidence on the relation between stock option compensation and risk taking’,Journal of Accounting and Economics33(2), 145–171.
Total in-text references: 1
  1. In-text reference with the coordinate start=7006
    Prefix
    For instance, Graham, Harvey and Puri (2009) provide strong evidence that managerial heterogeneity affects corporate financial policies such as acquisitions and capital structure. Moreover, a large body of literature shows, both theoretically (e.g. John and John (1993) and Jin (2002)) and empirically (e.g.
    Exact
    Rajgopal and Shevlin (2002), Knopf, Nam and Thornton (2002) and Coles, Daniel and Naveen (2006)),
    Suffix
    that firms’ compensation structures may offer managers with incentives for risk-taking and thus affect firms’ credit quality. Our primary finding of a positive effect of macroeconomic uncertainty on credit spreads is largely unaffected after further controlling for issuers’ fixed effects.

32
Schmukler, S., Mehrez, G. and Kaufmann, D. (1999), Predicting currency fluctuations and crises - do resident firms have an informational advantage?, Policy Research Working
Total in-text references: 1
  1. In-text reference with the coordinate start=8380
    Prefix
    We believe that this approach is more appropriate compared to alternatives such as proxies obtained from moving standard deviations of the macroeconomic series (e.g. Ghosal and Loungani (2000)) or survey-based measures based on the dispersion of forecasts (e.g.
    Exact
    Graham and Harvey (2001); Schmukler, Mehrez and Kaufmann (1999)). To
    Suffix
    ensure the robustness of our empirical findings, we construct three proxies for macroeconomic uncertainty from the conditional variance of the GDP growth rate, the index of industrial production and the returns on the S&P 500 Composite Index.

34
Tang, D. Y. and Yan, H. (2006), ‘Macroeconomic conditions, firm characteristics, and credit spreads’,Journal of Financial Services Research29(3), 177–210.
Total in-text references: 1
  1. In-text reference with the coordinate start=5262
    Prefix
    existing literature acknowledges the importance of the levels of macroeconomic factors in determining CDS spreads, we show that the second moments of these factors—macroeconomic uncertainty—have significant explanatory power over and above that of traditional macroeconomic factors such as the risk-free rate and the Treasury term spread. Our results nicely complement the empirical findings re1
    Exact
    Tang and Yan (2006) and Tang and Yan (2008b)
    Suffix
    model firms’ default risk as depending on (among other factors) the volatility of aggregate economic growth. However, their model contains a fixed level of volatility, while we focus upon variations in macroeconomic volatility as a factor influencing CDS spreads. 3 ported by Arnold and Vrugt (2008) and Arshanapalli, d’Ouville, Fabozzi and Switzer (2006).

35
Tang, D. Y. and Yan, H. (2008a), Liquidity and Credit Default Swap Spreads, Working paper series, EFA 2008 Conference. 13
Total in-text references: 1
  1. In-text reference with the coordinate start=3316
    Prefix
    Campbell and Taksler (2003) document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads. More recently, Zhang, Zhou and Zhu (2005) 2 further document that equity volatility and jump processes have strong explanatory power in the pricing of CDS.
    Exact
    Tang and Yan (2008a) and
    Suffix
    Bongaerts, de Jong and Driessen (2008) suggest the importance of illiquidity issues in pricing CDS. The primary objective of this paper is to examine the role of macroeconomic uncertainty in determining credit spreads.

36
Tang, D. Y. and Yan, H. (2008b), Market conditions, default risk and credit spreads, Discussion Paper Series 2: Banking and Financial Studies 2008,08, Deutsche Bundesbank, Research Centre
Total in-text references: 2
  1. In-text reference with the coordinate start=5262
    Prefix
    existing literature acknowledges the importance of the levels of macroeconomic factors in determining CDS spreads, we show that the second moments of these factors—macroeconomic uncertainty—have significant explanatory power over and above that of traditional macroeconomic factors such as the risk-free rate and the Treasury term spread. Our results nicely complement the empirical findings re1
    Exact
    Tang and Yan (2006) and Tang and Yan (2008b)
    Suffix
    model firms’ default risk as depending on (among other factors) the volatility of aggregate economic growth. However, their model contains a fixed level of volatility, while we focus upon variations in macroeconomic volatility as a factor influencing CDS spreads. 3 ported by Arnold and Vrugt (2008) and Arshanapalli, d’Ouville, Fabozzi and Switzer (2006).

  2. In-text reference with the coordinate start=5979
    Prefix
    Specifically, Arnold and Vrugt document a positive link between stock market volatility and macroeconomic uncertainty; Arshanapalli et al. show that both stock and bond markets have higher volatility during the period of macroeconomic announcements. One study that is closely related to our paper is
    Exact
    Tang and Yan (2008b).
    Suffix
    Based on structural credit risk models, Tang and Yan examine the impact of market conditions on credit spreads, showing that CDS spreads are decreasing in GDP growth rate, but increasing in GDP growth volatility.

37
Teixeira, J. C. A. (2007), ‘An empirical analysis of structural models of corporate debt pricing’,Applied Financial Economics17, 1141–1165.
Total in-text references: 1
  1. In-text reference with the coordinate start=21204
    Prefix
    findings, drawn from a sizable panel dataset, further understanding of determinants of CDS spreads and provide strong empirical evidence of the importance of macroeconomic volatility in credit derivative markets, which should not be ignored in economic policy and credit risk management. Furthermore, given the difficulty of structural models in accurately estimating and predicting credit spreads
    Exact
    (Teixeira (2007)),
    Suffix
    an interesting direction of future research is to incorporate macroeconomic uncertainty to improve the performance of credit risk models. 11

38
Zhang, B. Y., Zhou, H. and Zhu, H. (2005), Explaining credit default swap spreads with the equity volatility and jump risks of individual firms, Finance and Economics Discussion Series 2005-63, Board of Governors of the Federal Reserve System (U.S.).
Total in-text references: 2
  1. In-text reference with the coordinate start=3178
    Prefix
    A number of recent studies have investigated the empirical determinants of credit spreads. Campbell and Taksler (2003) document that firm-specific return volatility is able to explain about one-third of the variation in bond spreads. More recently,
    Exact
    Zhang, Zhou and Zhu (2005)
    Suffix
    2 further document that equity volatility and jump processes have strong explanatory power in the pricing of CDS. Tang and Yan (2008a) and Bongaerts, de Jong and Driessen (2008) suggest the importance of illiquidity issues in pricing CDS.

  2. In-text reference with the coordinate start=15632
    Prefix
    A high dividend payout ratio implies a decrease in the firm’s cash reserves, and may also indicate that the firm lacks profitable investment opportunities. The 8 positive sign of the dividend payout ratio is consistent with
    Exact
    Zhang et al. (2005).
    Suffix
    Table 7 provides results for BBB-rated issuers, also comprising about 40% of the sample, with broadly similar results and an elasticity of 0.56 forsprtrn. Interestingly, the included macroeconomic factors—the short rate and the Treasury term spread—exhibit positive and significant coefficients in this rating category as well.

39
Zhu, H. (2006), ‘An empirical comparison of credit spreads between the bond market and the credit default swap market’,Journal of Financial Services Research29(3), 211–235. 14
Total in-text references: 1
  1. In-text reference with the coordinate start=2473
    Prefix
    ), Houweling, Mentink and Vorst (2005), as well as in Elton, Gruber, Agrawal and Mann (2004), corporate bond yields are largely driven by liquidity factors and tax effects, which might bias quoted bond yields as a gauge of credit risk. In contrast, CDS spreads, expressed in basis points per annum, provide a more direct and readily-available alternative measurement of credit risk. Furthermore,
    Exact
    Blanco, Brennan and Marsh (2005), Zhu (2006), and Norden and Weber (2004)
    Suffix
    have reported that CDS spreads tend to be more responsive to changes in the stock market and firms’ credit conditions than bond yields. Consequently, several recent papers, including Houweling and Vorst (2005), Hull, Predescu and White (2004) and Pan and Singleton (2008), have relied on CDS spreads to directly measure the credit risk attributable to issuers’ default risk.