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Table 6 Heterogeneity analysis

From: Can public hospital reform reduce medical resource mismatches? Evidence from China

 

Mismatch

(1)

(2)

(3)

(4)

(5)

Panel A: Quantile Regression

5%

25%

50%

75%

95%

PHR

-0.183*

-0.188*

-0.139

-0.168***

-0.173***

 

(0.107)

(0.112)

(0.0917)

(0.0575)

(0.0352)

Observations

3,600

3,600

3,600

3,600

3,600

Panel B: Cumulative Policy Effects

≤2012

≤2013

≤2014

≤2015

≤2016

PHR

-0.483***

-0.523***

-0.185*

-0.167***

-0.156***

 

(0.0425)

(0.0348)

(0.0980)

(0.0440)

(0.0314)

Observations

900

1,200

1,500

1,800

2,100

City FE

Y

Y

Y

Y

Y

Year FE

Y

Y

Y

Y

Y

Controls

Y

Y

Y

Y

Y

Robust

Y

Y

Y

Y

Y

  1. *** p < 0.01, ** p < 0.05, * p < 0.1; City FE stands for city fixed effects to control for the effect of heterogeneity across cities; Year FE stands for year fixed effects to control for the effect of heterogeneity across years; Controls stands for a set of control variables; Robust stands for the use of robust standard errors to control for the effect of heteroskedasticity in the error term