Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach

Table 2

Estimation results for Bayesian bivariate Tobit quantile/mean regression models.

Variable	Quantile					Mean Regression
	0.25	0.50	0.75	0.90	0.95
Accident Rate of MD
Low visibility	0.013	0.020	0.026	0.081	0.188	0.024
	(5.51)	(7.20)	(3.78)	(2.46)	(6.89)	(4.32)
Average speed limit	-0.005	-0.007	-0.016	-0.019	-0.037	-0.009
	(-2.71)	(-3.51)	(-3.08)	(-0.78)	(-1.81)	(-1.72)
No. of mandatory signs	-0.002	-0.004	-0.004	-0.009	-0.010	-0.001
	(-5.18)	(-7.17)	(-3.23)	(-1.96)	(-1.99)	(-5.16)
No. of invalid traffic signs per km	0.006	0.015	0.028	0.065	0.048	0.155
	(2.60)	(5.49)	(4.28)	(2.06)	(1.87)	(6.18)
Constant	0.586	0.832	1.397	1.474	3.215	0.808
	(4.66)	(5.67)	(3.96)	(0.86)	(2.28)	(2.16)
Accident Rate of DI
Low visibility	0.007	0.015	0.032	0.093	0.183	0.019
	(4.15)	(5.48)	(5.62)	(2.67)	(6.95)	(4.88)
Average speed limit	-0.004	-0.007	-0.008	-0.020	-0.032	-0.012
	(-3.11)	(-3.26)	(-1.98)	(-1.79)	(-1.56)	(-3.26)
No. of warning signs	-0.001	-0.001	-0.001	-0.003	-0.003	-0.001
	(-3.45)	(-4.30)	(-3.55)	(-3.15)	(-2.55)	(-5.48)
No. of invalid traffic signs per km	0.005	0.011	0.026	0.072	0.087	0.102
	(3.41)	(4.02)	(4.77)	(3.72)	(3.35)	(6.31)
Constant	0.385	0.665	0.721	1.385	2.332	0.963
	(4.29)	(4.49)	(2.39)	(1.96)	(1.66)	(3.99)
Goodness-of-fit
No. of Observations		460
	1.123	0.982	0.973	0.984	1.128	1.137
	0.724	0.652	0.638	0.658	0.730	0.731
Correlation	0.758	0.766	0.791	0.764	0.753	0.765
DIC	1783.452	1635.683	1583.364	1642.538	1827.693	1858.634

Significant at the 5% level.