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Table 3 Probit model estimates of the determinant of membership in fisher group

From: Can producer groups improve technical efficiency among artisanal shrimpers in Nigeria? A study accounting for observed and unobserved selectivity

MEMBERSHIP Unmatched sample Matched sample
Probit coefficients Marginal effects Probit coefficients Marginal effects
AGE 0.01
(0.01)
0.00
(0.00)
0.01
(0.01)
0.00
(0.00)
EXPERIENCE 0.03**
(0.01)
0.01**
(0.00)
0.03**
(0.01)
0.01**
(0.00)
EDUCYEAR 0.04*
(0.02)
0.01*
(0.01)
0.04*
(0.02)
0.01*
(0.01)
REPEAT  − 0.34
(0.35)
 − 0.08
(0.08)
 − 0.34
(0.35)
 − 0.08
(0.08)
FEMLABSHR  − 0.13*
(0.07)
 − 0.03*
(0.02)
 − 0.13*
(0.07)
 − 0.03*
(0.02)
FEMAS 0.71***
(0.21)
0.17***
(0.05)
0.70***
(0.21)
0.16***
(0.05)
AKWA-IBOM  − 1.07***
(0.37)
 − 0.25***
(0.08)
 − 1.06***
(0.37)
 − 0.25***
(0.09)
ONDO  − 1.01***
(0.23)
 − 0.24***
(0.05)
 − 1.01***
(0.23)
 − 0.24***
(0.05)
MOBILE 0.28
(0.32)
0.07
(0.08)
0.28
(0.32)
0.07
(0.08)
EXTENSION 0.38
(0.47)
0.09
(0.11)
0.37
(0.50)
0.09
(0.12)
CREDIT 0.21
(0.23)
0.05
(0.05)
0.19
(0.23)
0.05
(0.05)
CUSTOMERS  − 0.11**
(0.05)
 − 0.03**
(0.01)
 − 0.11**
(0.05)
 − 0.03**
(0.01)
SHOCK  − 0.15
(0.23)
 − 0.04
(0.05)
 − 0.15
(0.23)
 − 0.04
(0.05)
TAROAD 0.73**
(0.30)
0.17**
(0.07)
0.72**
(0.30)
0.17**
(0.07)
LEADER  − 0.34
(0.29)
 − 0.08
(0.07)
 − 0.33
(0.29)
 − 0.08
(0.07)
COOP 0.55**
(0.26)
0.13**
(0.06)
0.54**
(0.26)
0.13**
(0.06)
EXTENSION residual 0.16
(0.27)
  0.17
(0.28)
 
CREDIT residual  − 0.04
(0.35)
  0.03
(0.36)
 
Constant  − 1.50**
(0.60)
   − 1.49**
(0.61)
 
Log-likelihood  − 149.15    − 148.72  
LR chi2(18) 112.86   105.77  
Number of obs 353   350  
  1. ***p < 0.01, **p < 0.05, *p < 0.1. The parameters in the model were estimated using Eq. (13). Standard errors are presented in parentheses
  2. Source: Authors’ calculation based on survey data