Discussion
Our results indicate that while the marginal and average agronomic
returns to inorganic fertilizer use are generally positive, there are
strong variations in these returns over our sample. We have shown that
both early-season rainfall and available soil carbon are important
conditioners of yield responses to nitrogen. Building on these agronomic
response estimates, our economic analysis has stark implications. Even
under relatively modest assumptions of last-mile transportation costs,
the inclusion of estimated farmgate prices in relative profitability
calculations reduces the attractiveness of fertilizer investments for a
large share of our sample.
Our findings are likely to overestimate Tanzanian smallholders’
agronomic responses to fertilizer use and hence their economic
incentives to use fertilizer, for several reasons. First of all, our
sample consists of farmers in Tanzania’s maize belt, where
agroecological conditions are generally more favorable than in most
other parts of the country. Secondly, the fact that this analysis is
based on focal plots, rather than on all plots, means that our analysis
cannot be taken as representative of all maize production conditions,
but rather of preferential conditions within the smallholder maize
system. Farmer preferential allocation of maize crops to higher
fertility, adequate soil organic carbon status field has been well
documented (Mhango et al., 2013; Tittonell et al., 2008). As such, our
estimates of agronomic and economic returns to fertilizer use are likely
an upward bound on the true values for the system. Problems with acute
soil organic carbon depletion and other soil fertility issues are likely
to be much worse on average over the farming system as a whole.
Thirdly, our analysis uses the most favorable production function
estimates, i.e. those resulting from the Fixed Effects estimation.
Profitability analysis using the POLS and CRE estimators is even less
profitable on average (although in most other respects estimation
results are remarkably consistent). When we re-run the same economic
analysis using the estimates of agronomic returns generated from the
POLS and CRE estimation results, the share of farmers for with MVCR and
AVCR estimates exceeding 2 is much lower.11For example, Table 7
shows that 71% of the sample has estimated AVCR values greater than
1.5. When we use POLS and CRE estimates corresponding to columns 2 and
4 in Table 2 as the basis of the calculation, the corresponding share
of the sample with AVCR values great than 1.5 is just 13% and 1%,
respectively.
Fourth, our estimates of farmgate maize/nitrogen price ratios, upon
which profitability estimates critically depend, are conservative and
likely to overestimate the ratio for many farmers. Our price ratio
assumptions are somewhat higher than those used in other empirical
analysis in the region. Sheahan et al. (2013) find an average
maize/nitrogen price ratio of 0.083 for Kenya. Matsumoto and Yamano
(2011) find ratios of 0.063-0.075 in Kenya and 0.044-0.027 in Uganda.
The price ratio assumptions we employ in our analysis are likely to be
optimistic; many farmers in Tanzania are likely to regularly face
less-favorable farmgate price ratios. As such, our profitability
analysis is likely biased upwards.
Finally, our results highlight important sources of uncertainty in both
agronomic and economic returns to fertilizer investments. We see this
particularly in the role of seasonal rainfall and rainfall distribution
parameters in the production functions, but may also note that the large
uncertainty around input, output and transportation prices faced by
farmers means that calculating expected returns on fertilizer
investments is highly uncertain even under optimal biophysical
production contexts. The fact that soil carbon stocks have such a strong
effect on yield responses in our sample is all the more striking given
these considerations. What this means is that even for the most
productive smallholders, the agronomic and economic returns to
fertilizer use are quite variable, which would further impede the
incentives of risk averse farmers to incur high capital outlays on
fertilizers.
Taken together, these results indicate that efforts to spur fertilizer
usage by smallholder farmers in Tanzania should not focus exclusively on
blanket agronomic targets, which are based on average responses over
large areas, but rather should carefully consider localized response
rates. This is in alignment with conclusions from other studies, e.g.
Nord & Snapp (2020), who studied soil fertility variability in the same
geography. Investments in extension and promotion of integrated use of
organic management practices in combination with fertilizer are urgently
required if maize based systems are to be productive, which has clear
implications for reform of input-based agricultural subsidies (Lal 2006;
Adowla et al., 2019). Such policies will often miss the mark, as there
is growing evidence – including this study – regarding the
accumulation of active soil carbon as being necessary to raise yield
responses sufficiently for nitrogen fertilizer to become economically
attractive. This may be particularly valid for risk adverse farmers in
areas facing high transport costs to regional input and output markets.
Failure to address these issues may continue to stall the process of
sustainably raising fertilizer use on the majority of Africa’s
smallholder farms. There is rising urgency in this challenge, as the
closure of the land frontier in many African farming areas has led to
more frequent continuous cropping of plots, which, without greater usage
of fertilizers, will certainly contribute to land degradation and rural
poverty (Barbier and Hochard, 2012).
Success in investing in soil organic carbon can also help mitigate the
variability of yields in the face of highly variable weather and a
changing climate (Williams et al., 2016). Our analysis suggests that
agronomic returns to nitrogen will have to increase substantially in
order to offset the low and variable price margins that smallholder
farmers typically face in countries like Tanzania.