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Table 4 Parallel trend test

From: Does the trans-provincial immediate reimbursement reduce health gap between urban and rural floating population? Evidence from China

 

Parallel trend test

PSM-DID (kernel)

PSM-DID (radius)

Province fixed effects

Province × Year

 

Trans-provincial treatments

Trans-urban treatments

Trans-provincial treatments

Trans-urban treatments

Trans-provincial treatments

Trans-urban treatments

Trans-provincial treatments

Trans-urban treatments

Trans-provincial treatments

Trans-urban treatments

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Hospitalsit × 

Medicareit

0.098

0.137

0.034***

0.047***

0.032***

0.048***

0.033***

0.027*

0.034***

0.050***

 

(0.078)

(0.099)

(0.008)

(0.016)

(0.008)

(0.016)

(0.008)

(0.015)

(0.008)

(0.016)

Hospitalsit

−0.143**

−0.135*

−0.0085

−0.002

−0.004

−0.001

−0.006

0.015

0.004

−0.017

 

(0.068)

(0.074)

(0.007)

(0.013)

(0.007)

(0.013)

(0.008)

(0.014)

(0.012)

(0.014)

Medicareit

0.003

−0.026**

−0.005

−0.020**

−0.004

−0.021**

−0.007

−0.014

−0.007

−0.017**

 

(0.014)

(0.013)

(0.007)

(0.009)

(0.007)

(0.009)

(0.007)

(0.009)

(0.007)

(0.009)

Genderit

0.054***

0.038***

0.020***

0.023***

0.042***

0.030***

0.041***

0.034***

0.041***

0.034***

 

(0.008)

(0.009)

(0.003)

(0.003)

(0.005)

(0.006)

(0.005)

(0.006)

(0.005)

(0.006)

Ageit

−0.012***

−0.015***

0.055***

0.062***

−0.012***

−0.012***

−0.010***

−0.013***

−0.010***

−0.013***

 

(0.001)

(0.001)

(0.007)

(0.009)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

Educationit

0.026***

0.023***

0.080***

0.132***

0.018***

0.022***

0.017***

0.017***

0.017***

0.017***

 

(0.004)

(0.005)

(0.007)

(0.009)

(0.003)

(0.003)

(0.003)

(0.003)

(0.003)

(0.003)

Reasonsit

−0.016***

−0.006**

−0.052***

−0.058***

−0.017***

−0.014***

−0.018***

−0.010***

−0.018***

−0.010***

 

(0.003)

(0.003)

(0.006)

(0.008)

(0.002)

(0.002)

(0.002)

(0.003)

(0.002)

(0.003)

Marriageit

0.070***

0.056***

−0.010***

−0.012***

0.061***

0.061***

0.056***

0.061***

0.056***

0.060***

 

(0.012)

(0.013)

(0.000)

(0.000)

(0.007)

(0.009)

(0.007)

(0.009)

(0.007)

(0.009)

Incomeit

0.087***

0.158***

0.001

0.001

0.078***

0.128***

0.080***

0.102***

0.079***

0.103***

 

(0.011)

(0.014)

(0.000)

(0.001)

(0.007)

(0.009)

(0.007)

(0.009)

(0.007)

(0.009)

Expenditureit

−0.048***

−0.079***

−0.010***

−0.010***

−0.050***

−0.056***

−0.048***

−0.053***

−0.049***

−0.054***

 

(0.009)

(0.012)

(0.002)

(0.002)

(0.006)

(0.008)

(0.006)

(0.008)

(0.006)

(0.008)

Year

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

  

Province

      

Yes

Yes

  

Province × Year

        

Yes

Yes

Constant

3.744**

3.512***

3.907**

3.516***

3.912***

3.481***

3.812***

3.599***

3.828***

3.607***

 

(0.081)

(0.102)

(0.043)

(0.077)

(0.051)

(0.060)

(0.051)

(0.062)

(0.050)

(0.067)

Observations

11,829

9,820

28,029

19,416

28,179

19,542

28,179

19,542

28,179

19,542

R-squared

0.114

0.159

0.092

0.145

0.098

0.147

0.101

0.163

0.102

0.165

  1. Notes: In Table 4 ((3)-(4)), we conducted the PSM-DID method. In Panel C, we used a kernel matching at the bandwidth of 0.06. In Table 4 ((5)-(6)), we used a radius matching at the caliper value of 0.1