Risk Rationing in Agricultural Credit Markets

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In Simple Words

Imagine a delivery driver who is offered a loan to buy a high-capacity truck, but if an unpredictable hailstorm wrecks the truck, the bank will seize their family home. Even though operating the truck could double daily earnings, the driver refuses the loan because the threat of losing their home in a storm is far too dangerous.

Surveyed farm households

No reported credit-risk constraint
Comparison group
Reported credit-risk constraint
Less likely to buy fertilizer

Observed baseline association after accounting for other measured factors. The coefficient is not a percentage-point effect; no credit intervention was tested here.

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Research question

Smallholder farmers reject productive agricultural credit even when loans are available because credit contracts leave un-hedged risk on the borrower. If a severe drought occurs, smallholders fear losing collateral or productive assets to settle debts.

Participants

N = 2,399 rural households (average household size 5.3) across 120 Kebeles in 4 zones (North Shewa, West Gojam, South Wello, North Wello) of Amhara, Ethiopia.

Study Design

Baseline survey analysis and a linear Heckman two-step consistent estimator modeling fertilizer purchase decisions.

Results

Risk credit constraint significantly decreases the probability of purchasing inorganic fertilizer (coefficient = -0.275, p < 0.01). Quantity credit constraint also significantly reduces fertilizer purchase probability (coefficient = -0.251, p < 0.01).

Takeaway

Design credit contracts bundled with state-contingent debt forgiveness or index insurance to shield smallholders from asset loss following severe weather shocks.

Source and citation

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Plain-English glossary

Original explanations, informed by the references below. Examples are illustrations, not data from the studies above. The research text stays unchanged.

Baseline

The starting measurements in a study. Researchers use these to compare what participants were like at the start with what happens later.

ExampleBefore a training programme starts, researchers measure workers’ earnings. That first measurement is the baseline.

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