Appendix 1.A: A Procedure of Constructing the CROI
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Improvement in the ratings is based on the average of Moody’s and Standard & Poor’s ratings for each country aggregated using EMBIG weights.
The model represents a type of forecasting model for spreads and, as such, does not distinguish between supply and demand factors for debt securities and their influence on spreads.
Rating agencies, however, may in turn argue that higher debt spreads increase borrowing costs and implying a greater risk of default. Thus, changes to ratings are not “behind the curve” but accurately reflect the increased risk of default as spreads widen.
To be included in the EMBI index, bonds had to meet strict liquidity criteria. For this reason, there were only five countries in the original EMBI. Their series start at the end of 1991. The EMBI Global, introduced in January 1998, uses more relaxed liquidity criteria. Countries’ admission requirements under the EMBI Global are different from those under the EMBI. Countries to be included in the EMBI must be rated BBB+ or lower by Standard & Poor’s. On the other hand, countries under the EMBI Global only need to satisfy one of the following criteria: (i) classified as having low or middle per capita income by the World Bank; (ii) has restructured external or local debt in past 10 years; or (iii) currently has restructured external or local debt outstanding.
Nigeria, for example, has missing observations during the period between April 1998 and April 1999. Likewise, Pakistan has missing observations during the period of February 2003 through March 2004. In case of the Philippines, its EMBI series terminated in January 1997 (Table 1).
Similarly, when a sovereign retires a debt instrument or amortizes principal of the debt, and if the issue’s current outstanding face value falls short of a required level under the criteria, the issue is removed from the country’s index. Market weight data are made available by J.P. Morgan Chase. This monthly series starts in December 1993.
Sy (2002) uses EMBI Plus sovereign spreads, noting the additional advantage that they control for floating coupons, principal collateral, and rolling interest guarantees.
There have been seven monthly observations which country’s long-term credit rating and/or outlook changed twice during the same month, though they are counted as one monthly change.
Using Fed Funds futures rates, Kuttner (2001) disentangled expected from unexpected policy actions, and concluded that the impact of unexpected rate decisions on the interest rates of both short- and long-term maturities were significantly positive.
See Global Financial Stability Report (2004).
A Hausman test indicates that we cannot reject the null hypothesis of no systematic difference between the estimates of the random effect and those of the fixed-effect models. However, because we suspect that a country specific factor is not completely independent of the CROI or the LTCR, we apply the fixed-effect model of panel regression.
Algeria and Cote d’Ivoire are excluded due to lack of the data on sovereign credit ratings and outlook. A total of 3,038 monthly observations are included for estimation. Initially, the basic model included Argentina, but because the crisis values for its spreads in 2001–2002 represented extreme outliers relative to any other historical period, Argentina is excluded from the remainder of the empirical work.
As with the basic model, a Hausman test indicates that we cannot reject the null hypothesis of no systematic difference between the estimates of the random effect and those of the fixed-effect models. However, because we suspect that a country specific factor is not completely independent of the CROI or the LTCR, we apply the fixed-effect model of panel regression.
The sample mean of V_FF is 12.2 percent, with a standard deviation of 6.6 percent.
One standard deviation of the VIX is roughly 6.4 percent during the sample period of 1991 through 2007.
At the dawn of the LTCM crisis on August 31, 1998, S&P 500 Index fell 6.8 percent from the previous day, and the VIX surged to 44.3. The VIX was jittery through the end of October 1998. It reached a historical high of 45.7 October 8, 1998.
The tests were performed using the code provided by Chiang and Kao (2002). These tests can only be performed on balanced panels. Thus, we use two balanced samples, one including only June 1995 through February 2007 for Brazil, Mexico, Poland, South Africa, and Venezuela, and one shorter but broader panel for the period from January 1998 to February 2007 which additionally includes Colombia, Lebanon, Malaysia, Panama, Peru, Philippines, Russia, and Turkey. The results are robust across both panels.
Aggregate EMBI series through November 1997, and aggregate EMBI Global series from January 1998 through February 2005 are spliced as to create the combined series.
The decomposition is done for each country by calculating the share of the change in the log of the EMBIG spread that the model attributes to each variable for the chosen time period. These shares are then multiplied by the change in the model spread over the same period.
The rating variable (Ri) takes a cardinal number in log such that AAA=1, AA+=2, …, and SD=22.
Where STB is a dummy variable for a “stable” outlook, POS for a “positive” outlook, NEG for a “negative” outlook, R is for log-term credit ratings in log, and SPRD is log of spreads in basis points. We suppressed (n) for indicating the n-th observation of the sample.
We divided the rating spectrum in a number of ways to see what combinations of rating groups provide the best fit and plausible significance levels for estimated coefficients.
This univariate regression is based on the long-term credit ratings (R) only, without the three categories.
Based on Breusch-Pagan/Cook-Weisberg test for heteroskedasticity, the null hypothesis is defined as a constant variance for the fitted value of SPRD.