Research on the Impact of Expressway on the County Economy Based on a Spatial DID Model: The Case of Three Provinces of China

Table 11

The estimation results of the spatial difference-in-differences (SDID) model.

Variables	Guangdong	Hubei	Qinghai
secper	0.4649 (9.00)	0.6488 (9.17)	1.4044 (14.47)
total_pop_ln	0.1014 (2.32)	0.0494 (0.3)	−0.1797 (−2.97)
invest_ln	0.0402 (5.55)	0.0362 (4.56)	0.0394 (2.35)
fin_reve_ln	0.1035 (6.75)	0.0827 (6.41)	0.044 (2.16)
fin_exp_ln	0.1646 (6.58)	0.0232 (1.36)	−0.0434 (−1.49)
exp	−0.0127 (−0.87)	−0.0467 (−4.02)	0.0276 (0.6)
Wsecper	−0.1501 (−1)	−1.3039 (−6.82)	−0.2616 (−1.01)
Wtotal_pop_ln	0.0413 (0.25)	−1.6083 (−3.7)	−0.6312 (−3.56)
Winvest_ln	−0.0316 (−1.64)	0.0194 (0.84)	−0.022 (−0.64)
Wfin_reve_ln	−0.0127 (−0.34)	0.1518 (4.18)	−0.0172 (−0.5)
Wfin_exp_ln	0.0159 (0.32)	0.2135 (4.05)	0.152 (1.49)
Wexp	0.1492 (4.22)	0.109 (2.97)	0.3204 (2.22)
rho	0.2644 (5.02)	0.3997 (6.99)	0.3292 (4.55)
sigma2_e	0.0129 (23.26)	0.009 (21.46)	0.031 (16.38)
LogL	820.1518	870.7909	168.6213

Note. , , and ; t statistics in parentheses.