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No observational data are used or claimed; the analysis characterises the design's power to detect threshold effects across agent density levels under a declared variance structure (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.640). Power was estimated across 2000 design cells defined by cluster counts of 8, 16, 24, and 32 and effect sizes of 3, 5, and 8 percentage points. The design achieves 80% power at 54 clusters for a 5-percentage-point effect. The BACI estimator's validity for threshold detection depends on the interaction between agent density and float rebalancing frequency, and that the intraclass correlation of 0.64 imposes a cluster-count floor that village-level studies of remittance intermediation must respect. The contribution is a design-theoretic account of when difference-in-differences can identify agent density thresholds, not an empirical estimate of fee levels.
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Rotich et al. (2026) studied this question.
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