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Table 2 Spatial panel data estimation by region. Fixed effects, 2005–2018

From: A spatial analysis of precariousness and the gender wage gap in Mexico, 2005–2018

SAR models Fixed effects
Manufacturing sector High tertiary Low tertiary Total tertiary sector
Precariousness difference − 0.29 a − 0.32 a − 0.47a − 0.45a − 0.09 − 0.09 − 0.25a − 0.26 a
(− 2.75) (− 2.96) (− 4.21) (− 4.01) (− 1.22) (−1.26) (− 2.87) (− 2.98)
Training difference 0.009 0.01 0.05 c 0.05c − 0.02 − 0.01 − 0.003 − 0.004
(0.73) (0.71) (1.93) (1.87) (− 1.08) (−0.99) (− 0.15) (− 0.19)
Difference in experience 0.39 b 0.37b 0.42 b 0.38 c 0.06 0.007 0.14 0.11
(2.41) (2.22) (2.05) (1.82) (0.36) (0.04) (0.82) (0.61)
Difference in occupation 0.38a 0.46 b 0.45 a − 0.23 − 0.17 c − 1.29 a 0.17 b − 0.17
(3.92) (2.02) (4.51) (− 0.45) (− 1.89) (−2.65) (2.19) (− 0.35)
Difference in education 0.61b   1.64a   1.59 a   1.61 a  
(2.41)   (4.41)   (5.87)   (5.35)  
Difference in primary education   − 0.07   0.05   0.09   − 0.02
  (− 0.95)   (0.39)   (0.91)   (− 0.159)
Difference in secondary education   − 0.05   0.09   0.14   − 0.08
  (− 0.54)   (0.49)   (0.87)   (− 0.46)
Difference in under/post-graduate studies   0.05   0.47a   0.78 a   0.38 c
  (0.81)   (2.76)   (3.44)   (1.93)
Rho 0.01 0.01 0.08 0.07 0.03 0.04 0.11 c 0.12 b
(0.15) (0.17) (1.38) (1.33) (0.52) (0.77) (1.89) (2.15)
LM1 5.57a 4.91a 5.45a 5.04a 4.32a 3.26a 7.57a 6.55a
LM2 − 0.97 1.00 1.94c 1.88b 0.93 0.84 2.54b 2.1b
CLMlambda 0.09 0.05 1.36 1.43 0.54 0.75 1.94b 2.17b
Hausman spatial 13.72b 30.44a 5.53 3.29 10.86c 11.33 7.83 3.11
  1. a, b, cLevels of significance: 1%, 5%, and 10%, respectively
  2. t statistics for each estimated coefficient are shown in parentheses
  3. Source: Authors’ extrapolation based on information from the National Survey of Occupation and Employment