Table 2. Correlations among regressors.

	C(t)	R(t)	X(t)	C(t − 1)	R(t − 1)	X(t − 1)
C(t)	1	−0.008	−0.109	−0.091	−0.096	0.136
R(t)	−0.022	1	0.104	−0.041	7.43 × 10−5	0.021
X(t)	−0.120	0.106	1	0.065	0.051	0.268
C(t − 1)	−0.150	−0.033	0.063	1	−0.008	−0.109
R(t − 1)	−0.105	−0.023	0.059	−0.022	1	0.105
X(t − 1)	0.140	0.030	0.258	−0.118	0.107	1
	C(t)	R(t)	X(t)	QL(t)	QR(t)	QC(t)
C(t)	1	−0.008	−0.109	−0.224	0.218	−0.071
R(t)	−0.022	1	0.104	0.001	0.052	0.107
X(t)	−0.120	0.106	1	−0.037	0.038	0.043
QL(t)	−0.253	0.002	−0.020	1	−0.191	0.192
QR(t)	0.253	0.049	0.022	−0.259	1	0.463
QC(t)	−0.087	0.095	0.049	0.155	0.430	1

Shown are Pearson’s correlation coefficients between explanatory variables used in the multiple linear regression models. Top, regression model 1 (eq. 4); bottom, regression model 2 (eq. 5). Lower diagonal, DMS; upper diagonal, DLS.