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Table 3 The direct and indirect effects of the spatial Durbin model

From: What has driven the spatial spillover of China’s out-of-pocket payments?

Variable Direct effect Indirect effect Total effect
Logged per capita income (RMB) 0.398*** 0.206* 0.604***
(0.086) (0.130) (0.109)
Aging level (%) 0.127* 0.616*** 0.743
(−0.879) (1.652) (1.600)
Mortality rate (%) 0.156* 0.353* 0.509**
(0.107) (0.217) (0.24)
Ratio of visits in hospitals and those in primary institutions 0.013* 0.034** 0.047*
(0.010) (0.015) (0.015)
Share of primary health care beds (%) −0.09** −0.401*** −0.491***
(0.049) (0.100) (0.094)
Ratio of health technicians in hospitals and those in primary institutions 0.020 −0.014*** 0.006**
(0.022) (0.056) (0.058)
Maternal mortality rate (%) −0.014 −0.060 − 0.074
(0.020) (0.222) (−0.074)
Logged gross Domestic Product (RMB) 0.050 −0.092 −0.042
(0.08) (0.155) 0.164)
Logged education level (Year) −0.381*** −0.045 − 0.426*
(0.066) (0.093) (0.079)
Logged government health expenditure (RMB) 0.210*** −0.046 0.164***
(−0.045) (0.061) (0.060)
Urbanization level (%) 0.745*** 0.243 0.988
(−0.485) (1.090) (1.156)
ρ/λ 0.453**
R-sq 0.963
Log-likelihood 375.614
  1. Note: 1 Stand-error shown in parentheses, ***, ** and * indicate significance at the 1, 5 and 10% levels, respectively
  2. 2 Per capita OPP, Per capita income, GDP, Education level and Government health expenditure take natural logarithm forms