The Determinants of the Nondefaultable Spreads of Corporate Bonds: Evidence from China

Table 7

Impact of liquidity proxies on the nondefault spread for the full sample based on equation (1).

Model	C	Vol_diff	Day_diff	Range_diff	Vol_diff × coupon	Day_diff × coupon	Range_diff × coupon	Adj-R^2 (%)
1	0.1166	−0.0002	0.0003	0.0804				0.1540
	(7.77)	(−2.95)	(0.21)	(1.86)
2	0.1214	−0.0012	0.0008	0.0824	0.0001			0.2406
	(8.04)	(−3.06)	(0.50)	(1.91)	(2.62)
3	0.1248	−0.0002	0.0639	0.0752		−0.0086		0.7978
	(8.32)	(−3.37)	(6.66)	(1.74)		(−6.71)
4	0.1165	−0.0002	0.0003	0.2541			−0.025	0.1445
	(7.77)	(−2.97)	(0.20)	(0.86)			(−0.60)
5	0.1270	−0.0007	0.0616	0.0416	0.0001	−0.0082	0.005	0.7942
	(8.41)	(−1.82)	(6.31)	(0.14)	(1.32)	(−6.31)	(0.12)

The table shows the impact of liquidity proxies on the nondefault spread for the full sample based on equation (1). The nondefault spread is regressed on the liquidity proxies by controlling credit risk and interaction. The meanings of liquidity proxies are shown in Tables 1 and 2. The interaction between liquidity and credit risk is represented by the cross-terms. The sample period is July 2006 to June 2016. The t-statistics are given in parentheses, and , , and represent significance at the 10%, 5%, and 1% level, respectively.