Figures 1 and 2 are heat maps, showing the proportion of the population in the region who are farmers (Figure 1) and youths (Figure 2) respectively. Note that in the case of farmers, we measure the proportion of people between the ages of 15 and 65 who say their profession is farming. Youth here is defined as any person between the age of 15 and 35. In the maps below, lighter colors mean lower values and darker colors mean higher values. For example, in Figure 1, Banjul has the lowest proportion of workers who are farmers, whilst CRR have the highest proportion of farmers.
Figure 1: Proportion of Farmers by Region
Figure 2: Proportion of Youths by Region
Our interest in this case is comparing the two graphs and looking at the implications. The trend in Figure 1 is an increase in the proportion of farmers as we go further in land, but in Figure 2 the trend is in reverse. We see a lower proportion of youths to total population in the regions as we move further inland. This tracks well with other data showing that farming is increasingly becoming an occupation for old people. Gambian youth are moving away from farming and towards retail/ wholesale trade. This does not bode well for the agricultural sector moving forward.
What is the best way forward? Push Gambian youth in peri-urban areas towards agriculture or lean in on the current trend and push Gambian youth towards vocational training?
Table 1: Average education years by LGA
We added Table 1 as the start of another conversation on education. Our next post will be dealing with occupations, education and incomes. The table above shows the average education years by LGA. As expected, average education years deceases as we move away from the coast, with a sharp drop once we move from Kanifing (6.63) to Brikama (3.68). The two LGAs with the lowest education years are Kuntaur and Basse. A similar pattern can also be observed when looking at the results by gender. In addition, average education years is higher for males than females, across all LGAs.
I would like to note that these are in sample averages (non-weighted averages), but the pattern is the same as would be observed in a weighted average.