Table 4.

Regression estimation results of three models.

	OLS		SLM		SEM
	Estimate	Standard error	Estimate	Standard error	Estimate	Standard error
Intercept term	−1.0775**	0.3489	−1.1898**	0.3424	−1.009**	0.3546
City level	3.4198**	0.4153	3.5789**	0.4088	3.3914**	0.3993
Number of medical colleges	2.0067**	0.1690	2.0133**	0.1650	1.9341**	0.1627
Urbanization rate	0.0160**	0.0069	0.0136**	0.0068	0.0122*	0.0070
Permanent population	0.0024**	0.0003	0.0023**	0.0003	0.0024**	0.0003
Population density	0.0003*	0.0003	0.0003	0.0002	0.0004**	0.0002
GDP per capita	7e-006**	0.0002	6.47e-006**	3.25e-006	9.31e-006**	3.40e-006
Altitude	3e-006	0.0001	5.0548e-005	0.0001	−9.0097e-006	0.0001
λ					0.2374**	0.7461
ρ			01331**	0.4468
R 2	0.8203		0.8253		0.8266
AIC	1,324.1943		1,314.66		1,312.9
Moran's I (error)	3.2361**
LM (lag)	9.9004**
Robust LM (lag)	3.1209*
LM (error)	8.7240**
Robust LM (error)	2.0446
Lagrange Multiplier (SARMA)	11.8449**
Log likelihood			−648.33		−648.45
LR			9.0251**		8.7832**

^**Represents 5% significance level,

^*Represents 10% significance level; binary queen contiguity weight matrix is used.