<div> From Mobilised Savings to Delivered Financial Services:  </div> <div> A Stochastic-Frontier Framework for Measuring the Institutional Conversion Gap in African Financial Systems </div> <br>

The rapid expansion of bank accounts, mobile money, digital payments, agent networks, deposit-taking institutions and domestic securities markets has enlarged the visible perimeter of finance in Africa. Yet the collection of savings and the multiplication of access instruments do not by themselves establish that financial systems transform available resources into services that households and firms can use. This article develops and tests a quantitative framework for measuring that missing transformation. The Institutional Conversion Gap (ICG) is defined as the distance between observed financial inclusion and a conditional potential frontier supported by mobilised savings, access infrastructure and prudential capacity. The empirical architecture distinguishes the realised outcome, represented by Block 1 (transformation, usage and allocation), from lagged structural inputs—Block 2 (savings and funding), Block 3 (access infrastructure) and Block 4 (prudential capacity)—and from conversion conditions represented by Block 5 (monetary environment) and Block 6 (fiscal environment). The structural frontier is estimated with a panel stochastic-frontier model whose production kernel is first specified as Cobb–Douglas and then tested against a constant-elasticity-of-substitution (CES) alternative.

The database covers 50 African countries over 2010–2024, or 750 possible country-year cells. Because no fictitious observation is introduced and incomplete lagged records are excluded, the complete estimation sample contains 464 observations from 47 countries. The selected Cobb–Douglas stochastic frontier produces an average observed-inclusion score of 26.83, an average conditional potential of 39.37, an average absolute gap of 14.82 points and average institutional conversion efficiency of 59.23 percent. Access infrastructure receives a large estimated share in the structural kernel, but this result is interpreted cautiously because Block 3 is currently built from only two sufficiently available direct annual series. Better monetary conditions are associated with a lower inefficiency scale; the fiscal coefficient is less stable and its bootstrap interval crosses zero. A CES specification yields a slightly lower Bayesian information criterion but fails the admissibility test because the optimizer does not converge and the substitution parameter reaches its upper boundary. A proposed instrument for the fiscal block is weak, the 999-replication country-cluster bootstrap converges in only 62.16 percent of replications, and the dynamic model does not outperform a last-observation benchmark in the 2022–2024 test period. The results therefore support an exploratory structural benchmark, not a validated causal ranking or superior forecasting model.

The article contributes a transparent distinction between financial presence, structural potential and realised inclusion; a reproducible mathematical chain from economic indicators to block scores, frontier potential and conversion gaps; and a governance framework for linking a multi-country econometric foundation to a subsequent country-level monitoring workbook. The findings show why savings mobilisation should be evaluated jointly with access, prudential capacity, monetary transmission and fiscal absorption, while also demonstrating that scientific validation depends as much on measurement quality, identification and stability as on a coherent theoretical model.