Table 6.
Difference-in differences analysis of food insecurity in Ethiopia and Nigeria.
| (1) | (2) | |
|---|---|---|
| Variables | Food insecurity | Food insecurity |
| Post pandemic | 0.122*** | 0.0737*** |
| (0.0172) | (0.0266) | |
| Stopped working | 0.0109 | −0.0284 |
| (0.0248) | (0.0448) | |
| Post-pandemic*Stopped working | 0.00402 | |
| (0.0276) | ||
| Income decreased | 0.0134 | |
| (0.0248) | ||
| Post-pandemic*Income decreased | 0.0555* | |
| (0.0302) | ||
| Country dummies | Yes | Yes |
| Subnational dummies | Yes | Yes |
| Pseudo R Sq. | 0.121 | 0.127 |
| Observations | 8263 | 9943 |
Notes: “Food insecurity” takes on 1 if at least one adult in the household did not eat for a whole day due to a lack of resources. This variable was observed both before and after the pandemic. Results are marginal effects for discrete variables (the percentage point change in the likelihood of the dependent variable if the discrete indicator is true). Other variables included in the regressions are household size, education, sex and age of the respondent, urban vs rural location, and a dummy indicating whether or not the household is below the poverty line. Data are weighted by sample weights that are re-scaled to give each country in the sample equal weight. Standard errors are robust. ***: Statistically significant at 1%; **: Statistically significant at 5%; *: Statistically significant at 10%.