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Table 3 Effect of the minimum wage on log wage gap (log(pth) - log(p60)) of selected percentiles, all workers (1985–2010)

From: Does the minimum wage reduce wage inequality? Evidence from Thailand

Percentile

OLS

2SLS

Predicted median

 

(1)

(2)

(1)

(2)

(1)

(2)

5

0.72***

0.585***

3.973***

–0.815

1.256***

–1.041

 

(0.082)

(0.042)

(1.003)

(0.622)

(0.401)

(0.669)

10

0.654***

0.578***

2.669***

–0.308

0.956***

–0.395

 

(0.059)

(0.035)

(0.67)

(0.404)

(0.255)

(0.483)

20

0.537***

0.55***

0.622***

–0.304

0.462***

–0.389

 

(0.031)

(0.031)

(0.214)

(0.387)

(0.08)

(0.442)

25

0.489***

0.524***

0.154

–0.093

0.334***

–0.119

 

(0.029)

(0.026)

(0.235)

(0.322)

(0.084)

(0.404)

30

0.433***

0.481***

–0.128

–0.031

0.225***

–0.04

 

(0.03)

(0.025)

(0.224)

(0.257)

(0.082)

(0.333)

40

0.319***

0.367***

–0.252

0.093

0.118*

0.119

 

(0.027)

(0.022)

(0.157)

(0.153)

(0.068)

(0.217)

75

0.008

–0.015

0.502**

-0.08

0.113

–0.102

 

(0.034)

(0.028)

(0.207)

(0.198)

(0.078)

(0.264)

90

0.293***

0.254***

0.915**

0.152

0.471***

0.191

 

(0.058)

(0.046)

(0.407)

(0.36)

(0.171)

(0.488)

95

0.525***

0.495***

0.4

0.128

0.657***

0.162

 

(0.05)

(0.041)

(0.443)

(0.382)

(0.164)

(0.518)

F-test (weak IV)

  

30.923

17.996

  

Year dummy

Yes

Yes

Yes

Yes

Yes

Yes

Province dummy

Yes

Yes

Yes

Yes

Yes

Yes

Provincial trend

No

Yes

No

Yes

No

Yes

  1. Note: These coefficients are marginal effect calculated from linear and square terms of the effective minimum. Standard errors are clustered at provincial level and displayed in parentheses while ***, ** and * indicate significant at 1%, 5% and 10% level respectively. Model (1) controls for time and province fixed effect while model (2) also controls for provincial trend