# Information and Communication Technologies and Agricultural Production: New Evidence from Africa
## 4 Results and Discussion
### Granger Test for Panel Causality
In view of this, mobile phones come handy in this sector; they enable farmers to disseminate information at all levels in knowledge exchange, agricultural trade, and agricultural products [100; 102]. Per the data, it can be found that there existed a bidirectional causality between crop production and net national income, whereas the relationship type that was found between livestock production and net national income is unidirectional. Thus, livestock  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Hypothesis** & **Z-Bar** & **Z-Bar Tilde** & **Conclusion** \\ \hline Inx1 \(\rightarrow\) Inx1 & 4.5283 \(\rightarrow\) **14** & 14.1133 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and individuals using internet \\ Inx1 \(\rightarrow\) Inx1 & 5.2503 \(\rightarrow\) **13** & 3.1627 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and individuals using internet \\ Inx1 \(\rightarrow\) Inx2 & 14.7412 \(\rightarrow\) **9** & 9.9076 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and mobile phone subscriptions \\ Inx2 \(\rightarrow\) Inx1 & 3.3658 \(\rightarrow\) **1** & 1.8234 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and mobile phone subscriptions \\ Inx3 \(\rightarrow\) Inx3 & 7.8396 \(\rightarrow\) **1** & 5.0028 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and fixed telephone subscriptions \\ Inx3 \(\rightarrow\) Inx1 & 3.9543 \(\rightarrow\) **2** & 2.2417 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and net national income \\ Inx3 \(\rightarrow\) Inx4 & 5.4957 \(\rightarrow\) **3** & 3.337 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and net national income \\ Inx4 \(\rightarrow\) Inx5 & 3.4107 \(\rightarrow\) **1** & 1.8549 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and net national income \\ Inx5 \(\rightarrow\) Inx5 & 6.8778 \(\rightarrow\) **4** & 3.4193 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and domestic credit to the private sector \\ Inx5 \(\rightarrow\) Inx7 & 2.9895 \(\rightarrow\) **1** & 1.5553 \(\rightarrow\) **1** & Bidirectional causality identified between crop production and domestic credit to the private sector \\ Inx1 \(\rightarrow\) Inx3 & 1.3643 \(\rightarrow\) **9** & 9.5684 \(\rightarrow\) **1** & Bidirectional causality identified between domestic credit to the private sector \\ Inx5 \(\rightarrow\) Inx5 & 7.0510 \(\rightarrow\) **1** & 1.8263 \(\rightarrow\) **1** & Bidirectional causality identified between network  
production does not Granger cause net national income, but net national income does Granger cause livestock production. [PERSON] et al. [103] studied the effect of agriculture on the environment, conditional upon the level of income in a panel of 11 Central and West African countries for the period 1996 to 2015, using Pooled Mean Group (PMG), Mean Group (MG), and Augmented Mean Group (AMG) techniques; the literature establishes a long-run relationship between net national income and agriculture production. With regards to the rural population variable, the relationship type that was found with both crop and livestock production was unidirectional. Thus, crop production Granger causes rural population, while rural population does not. Moreover, livestock production Granger causes rural population, while rural population does not Granger cause livestock production. [PERSON] and [PERSON] [94] studied the effect of the rising rural population density on smallholder agriculture in Kenya. The authors established that there was a relationship between agriculture production and rural population.