Table 13 reports average input statistics across the highest level of administrative disaggregation in each country for which the statistics remain representative, accompanied by the weighted number of cultivating households found in that region to provide an indication of the relative importance of each area to national-level agriculture. Even more so than the agro-ecological zone distinction, regional variation in input use within countries is immense, likely due to factors like input and output prices, accessibility, and past investments in infrastructure, agricultural extension services, etc. Unlike the macro-level statistics, the LSMS-ISA data allow us to uncover this sub-national heterogeneity and identify where input intensification efforts may be taking hold within countries, even when country-level statistics show overall low rates of use and especially where countries are large and/or populous.

In certain countries, particularly Ethiopia, this level of disaggregation illuminates the tremendous heterogeneity in input use across regions. With an average unconditional fertilizer application rate of 45 kg/ha, we find three regions far surpass this average (Tigray, SNNP, Harari), while five regions fall well below even 10 kg/ha (Afar, Somalie, Benshagul G., Gambelia, Diredwa). This large spread is also evident for other inputs, with ranges from 0 to 50 percent of households using agro-chemicals by region (relative to a national average of 31 percent) and 0 to 47 percent of households using irrigation (relative to 9 percent nationwide). To a slightly lesser extent, regional variation in Nigeria is also considerable. The northern regions are far more likely to use inorganic fertilizer and agro-chemicals, with the highest percentage of organic and inorganic fertilizer users found in the North West. In much smaller Malawi, regional disaggregation provides little interesting variation around the country’s relatively high input use rates.

In relatively lower input countries, like Niger and Uganda, we also find some sub-national variation and patches where input use is far greater than national averages suggest. In Niger, those regions with fewer cultivating households (Agadez, Diffa, Niamey) have relatively higher input use levels than the more prominent agricultural areas; however, even Dosso has two times the proportion of inorganic fertilizer users relative to the national average. In Uganda, the largest amount of within-country variation is observed in agro-chemical use, with the major agricultural areas having lower percentages of users than the minor cultivating areas, likely due to sample selection and size.

# **_4.3. Household level input use_**

In this section, we further disaggregate input use statistics at the household level, exploring a range of household characteristics that are often thought to be correlated with input use, including socio-demographic and farm characteristics. Because the LSMS effort, dating back to the 1980s, has largely focused on estimating and understanding poverty and welfare, a huge number of other household-level socio-economic and demographic characteristics are available through the LSMS-ISA surveys. While we limit our discussion to a fairly narrow set of covariates, much more detailed disaggregation remains possible for those who wish to pursue this line of analysis in greater depth.

# <u>Household demographics</u>

One of the most often inferred constraints to modern input use is household purchasing power and socio-economic status. We investigate the difference across consumption quintiles between 21