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Table 3 Probit results of contract farming participation

From: Does contract farming affect technical efficiency? Evidence from soybean farmers in Northern Ghana

Explanatory variables

Unmatched sample

Matched sample

Coeff.

Z-stat

Marginal effect

Coeff.

Z-stat

Marginal effect

Gender of the farmer

− 0.184

− 1.36

− 0.073

− 0.181

− 1.33

− 0.071

Basic education

0.265*

1.68

0.105

0.269*

1.66

0.106

Secondary education

0.369*

1.82

0.146

0.369*

1.81

0.146

Tertiary education

0.173

0.63

0.069

0.184

0.67

0.073

Household size

0.037***

2.56

0.014

0.031**

2.01

0.012

Soybean farming experience

0.019**

2.42

0.008

0.019**

2.32

0.007

Land size

0.051*

1.76

0.020

0.044

1.34

0.017

Household assets Index

− 0.167***

− 3.43

− 0.065

− 0.158***

− 3.00

− 0.062

Farmer specialization

0.023*

1.87

0.009

0.021

1.33

0.008

Off-farm activities

0.033

0.25

0.013

0.023

0.17

0.009

Labor

0.001

0.55

0.000

0.001

0.66

0.001

Extension contacts

0.254***

6.13

0.100

0.249***

5.93

0.097

Credit access

0.225*

1.81

0.089

0.224*

1.79

0.088

Farmer groups

0.265**

2.04

0.104

0.264**

2.03

0.103

Distance to district market

0.005

0.96

0.002

0.005

0.94

0.002

Occurrence of drought

0.109*

1.94

0.043

0.106*

1.84

0.041

Risk aversion

0.227*

1.69

0.088

0.219

1.63

0.085

Regional dummy

0.005

0.03

0.002

0.005

0.03

0.002

Constant

− 1.966

− 7.3

 

− 1.895

− 6.77

 

Wald chi2(18)

120.66***

  

97.03***

  

Pseudo-R2

0.179

  

0.147

  

Count R2

67.80%

  

66.93%

  

Log pseudo-likelihood

− 299.286

  

− 298.222

  

No. of observations

531

  

511

  
  1. ***, **, and * denote significance at 1%, 5%, and 10% levels, respectively