Table 3 Determinants of digital training participation: instrument Variables.

From: Leveraging internet use for sustainable agriculture: the impact of digital training on adoption of energy-smart agricultural practices and welfare

 

IV – 1

IV – 2

IV – 3

Interaction term (1*2*3)

Digital training participation

1.729*** (0.351)

3.042* (1.697)

1.636** (0.885)

2.395*** (0.716)

Cragg-Donald Wald F Statistic

27.65**

44.73***

29.28***

35.72***

Wu-Hausman F test

11.37***

17.91***

8.52**

13.71***

Anderson canonical correlation LM statistic

249.7**

218.6***

164.4***

281.4***

VIF

1.37

2.25

1.83

1.41

Breusch-Pagan test statistic

5.28

(P-value 0.071)

4.84

(P-value 0.063)

6.26

(P-value 0.151)

5.19

(P-value 0.107)

Hansen J statistic

4.35

(P-value 0.29)

3.29

(P-value 0.27)

3.94

(P-value 0.35)

2.46

(P-value 0.31)

  1. N = 723, endogenous variable (digital training participation), three IVs (1) access to internet connection (ATC) (2) distance to training center, and (3) farm radius, and additional explanatory variables included: household head age, education of household head, access to market, livestock ownership, off-farm income, access to credit, skill development, tenancy status, farming experience, marital status. The Cragg-Donald Wald F Statistic measures the relevance of the instruments used (F-stat > 10 = ***p < 0.01). *p < 0.1; **p < 0.05; ***p < 0.01. A Variance Inflation Factor (VIF) greater than 10 indicates potential multicollinearity. The Hansen J test assesses over-identification, with a statistic greater than 0.15 suggesting that we fail to reject the null hypothesis, supporting the validity of the instruments. The Breusch-Pagan test measures heteroscedasticity, and a p-value greater than 0.05 indicates no evidence of heteroscedasticity.
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