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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