Rural cooperative livestock auctions in Kenyan wards set commission rates that vary across wards and over time, and smallholders decide when to sell animals in response to the fees they face. Because fee schedules are not randomly assigned and because unobserved herd quality and local demand conditions jointly determine both the fee a cooperative can sustain and the timing of liquidation, an ordinary least-squares comparison of sale timing across fee regimes cannot recover a causal effect. The design is characterised analytically rather than estimated: under a declared variance structure with a between-cluster standard deviation of 6.0, a residual standard deviation of 4.5 and an intraclass correlation of 0.64, a before-after-control-impact estimator was evaluated across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. Power reached conventional levels at 56 clusters for a 5-percentage-point effect. Fee exposure is a plausible lever on liquidation timing, that the instrument is defensible only under explicit exclusion restrictions, and that the design's operating characteristics bound what a ward-level evaluation can credibly claim.
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Ochieng et al. (2026) studied this question.
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