Another look at yield spreads: the role of liquidity

Southern Economic Journal, April, 2008 by Dong Heon Kim

with anything known to banks at time t - 1, but [r.sup.L.sub.n,t] and [r.sup.F.sub.t] are not in the date t - 1 information set. However, Equation 26 can be estimated by instrumental variables using valid instruments. I consider 2SLS with constant, lagged federal funds rates, and lagged quantities of new loans as instruments. I employ Hansen's (1982) method in order to check the overidentifying restrictions and, thus, test these conjectures about the correct set of instruments. Hansen's test statistic has an asymptotic [chi square] distribution with r - k degrees of freedom if the model is correctly specified, where r is the number of instruments and k is the number of estimated coefficients. According to Model II, [alpha] = [[delta].sub.0], [phi] = 1, [[gamma].sub.1] = [-n.sup.-1], and [[gamma].sub.2] = -[[delta].sub.1]. Table 2 shows the results. In both cases, the estimated coefficients on the spread are close to unity. Indeed, the t-statistic for testing the null hypothesis that the coefficient of the spread is unity is -0.564 for the one-month CP rate and -0.053 for the three-month CP rate, respectively, and thus in both cases implies that the estimated coefficients are not statistically significantly different from unity at the 5% level, in contrast with the estimated coefficients on the spread in Model I. In addition, following Hansen's (1982) method, [[chi square].sub.1] for the one-month CP rate and [[chi square].sub.2] for the three-month CP rate are 1.288 and 5.816, respectively, so the null hypothesis that Model II is correctly specified is accepted at the 5% level. These results imply that these instruments are valid. (19)

All the estimated coefficients have the signs predicted by the theoretical model developed in section 2, and all estimated coefficients are statistically significant at the conventional level except the coefficients on [L.sub.t]. In particular, the estimated coefficients on the liquidity premium are close to the values that the theoretical model implies (-0.25 for the one-month CP rate and -0.084 for the three-month CP rate) and statistically significant, indicating that liquidity plays an important role in explaining the term premium. However, among two components reflecting the risk premium, the constant is statistically significant, whereas the estimated coefficients on Lt are not significantly different from zero.

Another Application: Euro-Dollar Rates

Since I did not have a direct measure of the loan rate, I used the CP rates as a proxy for the bank loan rate instead. However, as pointed out in Kashyap, Stein, and Wilcox (1993), bank loans are special, and the commercial paper might be an imperfect substitute. In addition, Stigum (1990) and Cook and LaRoche (1993) state that historically the CP market has been remarkably free of default risk in contrast to bank loans. From this point of view, the CP rate might not be a good choice of proxy. To investigate this issue, I consider the Euro-dollar (hereafter ED) rate as another proxy. Even though the ED is a liability and the ED rate is a deposit rate, it is subject to default risk and can fluctuate in accordance with banks' liquidity demand. The one-month and three-month ED rates are taken from Statistical Release provided by the Federal Reserve Board of Governors for the sample.