Skip to main content

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