level (except in Uganda and Niger), implying a relatively high amount of chemicals used in agriculture in these households. Owning agricultural equipment and having some fields under irrigation also are not consistently highly correlated across countries, and irrigation and machine ownership, separately, are only highly correlated with inorganic fertilizer use in half of the countries. Ethiopia seems to have the highest amount of joint correlation, and Uganda the least. Generally speaking, we find some areas of low correlation between “paired” input use patterns, suggesting that there are still yield gains to be exploited by using inputs together.

Because the hypothesized complementarities among inputs are primarily biophysical, we would expect that households use synergistic inputs together on the same plot, not just on the same farm. Table 27 explores this hypothesis using the same methodology as the household-level statistics found in Table 26. At the plot level, we find far less correlation than at the household level, with only a handful of instances where two inputs are used together in high percentages and with no noticeable patterns across countries. There are a few instances where chemicals – inorganic fertilizers and agro-chemicals like pesticides – are used together, providing further evidence that their use may be higher than expected by policy makers and analysts alike.

Table 27: Probability that a “paired” input would be used conditional on another input used at the <u>plot level in main season</u>

|||Conditional<br>|on the observed use of the<br>|se inputs(columns)<br>||
|---|---|---|---|---|---|
||Organic fertilizer|Inorganic fertilizer|Improved seeds|Agro-chemicals|Irrigation|
|Ethiopia||||||
|Organic fertilizer|-|15|21|10|30|
|Inorganic fertilizer<br>|30<br>|-<br>|83|64<br>|23<br>|
|Improved seeds|10|19|-|11|7|
|Agro-chemicals|11|37|29|-|8|
|Irrigation|2|1|1|<1|-|
|Malawi||||||
|Organic fertilizer|-|15|-|10|4|
|Inorganic fertilizer|79|-|-|39|37|
|Agro-chemicals<br>|2<br>|1<br>|-|-<br>|1|
|Irrigation|<1|<1|-|<1|-|
|Niger<br>||||||
|Organic fertilizer<br>|-<br>|54|35<br>|47<br>|22<br>|
|Inorganic fertilizer|18|-|12|25|27|
|Improved seeds|2|2|-|2|6|
|Agro-chemicals|9|14|10|-|18|
|Irrigation|1|3|5|4|-|
|Nigeria||||||
|Organic fertilizer|-|1|-|2|8|
|Inorganic fertilizer<br>|13<br>|-<br>|-|51|60<br>|
|Agro-chemicals<br>|20<br>|56<br>|-|-<br>|71|
|Irrigation|6|4|-|4|-|
|Tanzania||||||
|Organic fertilizer<br>|-<br>|14|-|18<br>|23<br>|
|Inorganic fertilizer|18|-|-|43|41|
|Agro-chemicals|28|33|-|-|36|
|Irrigation|4|5|-|6|-|
|Uganda||||||
|Organic fertilizer|-|27|-|23|13|
|Inorganic fertilizer|8|-|-|22|4|
|Agro-chemicals<br>|23<br>|71<br>|-|-<br>|8|
|Irrigation|4|4|-|3|-|

Note: This table should be read: “conditional on one of the inputs in a column being used, x% of plots in the main season also have an input in the row.” All percentages are based on a binary input use decision and do not consider application rates or any other continuous measure. Arbitrarily chosen categories to help with overview: low correlation<=25%, high correlation>=50%.

Because the “improved seed variety” category lumps all seeds together in Ethiopia and Niger, we separately explored the correlation between improved maize seed usage in Ethiopia and Malawi (maize production is very minor in Niger). We find that, of the plots with improved maize seeds 38