Originally published on Ali Moutaïb’s blog: read the original on Substack.
There is a version of the African agricultural investment story that doesn’t make sense on paper.
The instruments exist. Blended finance vehicles, concessional loans, index-based insurance, output-linked credit. Development finance institutions have spent the better part of two decades designing mechanisms to bring capital into smallholder markets. The operators exist too – agtech companies, cooperatives, input distributors with real reach. And the demand is not in question: the gap between what African agricultural systems produce and what they could produce is one of the most documented inefficiencies in global development economics.
So why don’t more deals close? Why do interventions that work at pilot scale so rarely travel?
The answer I keep coming back to is not capital. It’s calibration.
A financing instrument is a structured bet on a set of parameters. For agricultural finance, those parameters are specific: crop yield distributions across agro-ecological zones, household income volatility across seasons, input adoption rates and their effect on productivity. A DFI structuring a risk-sharing facility or an insurer pricing an index product needs these numbers to be reliable – statistically sound, methodologically consistent across years, and connected to the decision-making systems of the governments and markets they’re trying to serve.
In most African agricultural markets, these numbers don’t exist in that form.
Agricultural surveys happen, but infrequently. Methodologies shift between cycles, making year-on-year comparison unreliable. The data that does exist often lives in research pipelines – published, cited, then shelved – rather than embedded in the national statistical systems that governments and investors actually use. The result is that financing instruments are being calibrated against a baseline that was never designed for that purpose. They are pricing risk on proxies and assumptions, and then wondering why the outcomes don’t hold !
What 50×2030 has been doing across 28 countries is not primarily producing agricultural statistics. It is integrating agricultural measurement into national statistical systems – making surveys timelier, more methodologically stable, and connected to the administrative processes through which governments make land, investment, and trade decisions.
At the Paris Peace Forum, the conversation on African agricultural innovation was framed around ecosystems and scale. Those are the right ambitions. But they require a foundation that most of the discussion takes for granted.
Data infrastructure is not a supporting input to agricultural investment. It is the precondition. Until that is treated seriously – as a public good requiring sustained institutional commitment, not a one-time research exercise – calibration will remain the silent constraint behind every deal that almost closed.
