Table 6 Fixed-effects (FE) models
From: Explaining provincial government health expenditures in China: evidence from panel data 2007–2013
Model 1 | Model 2 | Model 3 | Model 4 | |
|---|---|---|---|---|
Number of provinces | 31 | 29 (Tibet and Qinghai excluded) | 31 | 29 (Tibet and Qinghai excluded) |
Years | 2007–2013 | 2007–2013 | 2009–2013 | 2009–2013 |
Real per capita budgetary deficits | 0.019** (0.009) | 0.042*** (0.006) | 0.009 (0.012) | 0.031*** (0.009) |
Economy | 84.042** (40.975) | 124.566*** (31.532) | 85.828 (64.939) | 145.280** (55.846) |
Openness | 0.539 (8.048) | −3.593 (7.674) | −12.485 (9.183) | −13.167 (9.569) |
Industrial structure | −17.628 (11.124) | −18.217** (8.769) | −34.009 (21.513) | −28.022 (18.270) |
Unemployment rate | −816.269 (2848.755) | −2101.171 (1383.514) | 0.471 (2550.578) | −1789.106 (1473.1) |
Dependency rate of the aged | 961.461*** (208.640) | 769.547*** (161.244) | 1136.961*** (246.679) | 865.509*** (213.074) |
Factors = 0 | 0.100 | 0.001 | 0.214 | 0.030 |
Year dummies = 0 | 0.000 | 0.000 | 0.005 | 0.010 |
Panel effects = 0 | p value = 0.000 | p value = 0.000 | p value = 0.000 | p value = 0.000 |
Hausman test | p value = 0.000 | p value = 0.000 | p value = 0.000 | p value = 0.000 |
Heteroskedasticity test (Modified Wald) | p value = 0.000 | p value = 0.000 | p value = 0.000 | p value = 0.000 |
Autocorrelation test | p value = 0.000 | p value = 0.004 | p value = 0.000 | p value = 0.001 |
N | 214 | 203 | 154 | 145 |
R-squared (within) | 0.9580 | 0.9732 | 0.9133 | 0.9416 |