Resilience Measurement for Development
Also known as: RIMA, Resilience Index Measurement and Analysis, Resilience Capacity Index, Development Resilience Measurement, Food Security Resilience Analysis
Resilience Measurement and Analysis is a family of methods for quantifying the ability of households and communities to withstand, recover from, and adapt to shocks and stresses while maintaining or improving their well-being, especially food security. Exemplified by the FAO's Resilience Index Measurement and Analysis (RIMA-II) and informed by Béné and colleagues' critical conceptual work, it treats resilience as a latent capacity inferred from observable assets, access to services, and adaptive behaviours, estimated statistically and tracked over time to inform and evaluate resilience-building interventions.
Key highlights
- Makes an abstract, latent capacity measurable, allowing the least resilient to be identified and targeted before shocks occur.
- Decomposes resilience into pillars and capacities (absorptive, adaptive, transformative), showing which drivers to strengthen rather than just an overall score.
- When built on panel data, it can be validated against realised outcomes and used to evaluate the impact of resilience-building programmes.
- Provides a standardised, comparable framework (e.g., FAO RIMA) used across countries and agencies, supporting cross-context learning and benchmarking.
Intuition
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How it works
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When to use it
Use resilience measurement when a programme aims to strengthen households' or communities' capacity to deal with recurrent shocks — drought, conflict, price spikes, displacement — and you need to baseline that capacity, target the least resilient, and evaluate whether interventions improved it. It suits food-security and humanitarian-development contexts with household survey or panel data. It is less appropriate where shocks and outcomes cannot be observed, where panel data are unavailable to validate the index against realised resilience, or where the underlying concept of resilience has not been clearly bounded to specific shocks and well-being outcomes, in which case the measure risks being arbitrary.
Strengths & limitations
- Makes an abstract, latent capacity measurable, allowing the least resilient to be identified and targeted before shocks occur.
- Decomposes resilience into pillars and capacities (absorptive, adaptive, transformative), showing which drivers to strengthen rather than just an overall score.
- When built on panel data, it can be validated against realised outcomes and used to evaluate the impact of resilience-building programmes.
- Provides a standardised, comparable framework (e.g., FAO RIMA) used across countries and agencies, supporting cross-context learning and benchmarking.
- Resilience is a contested, normatively loaded concept; different definitions yield different indices, and Béné and others warn it can mask power and structural causes of poverty.
- Robust measurement and validation require panel data linking pre-shock determinants to post-shock outcomes, which are costly and often unavailable.
- Index estimates depend on the choice of pillars, variables, and statistical model, and the latent-variable approach can obscure how the number was produced.
- Objective indices may diverge from people's own sense of their ability to cope, so subjective and objective measures can give different and even conflicting pictures.
Common pitfalls
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Applications
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Frequently asked
What are absorptive, adaptive, and transformative capacities?
Absorptive capacity is the ability to prepare for, mitigate, and cope with the impact of a shock so that well-being is maintained — for example, drawing on savings, reserves, or insurance to weather a drought. Adaptive capacity is the ability to make proactive and incremental adjustments to livelihoods in response to changing conditions, such as diversifying income sources. Transformative capacity is the ability to make fundamental, structural changes — in institutions, systems, or behaviours — when the existing way of life is no longer viable. Together they describe an escalating set of responses from coping through adjusting to transforming.
How does FAO's RIMA estimate resilience if it cannot be observed directly?
RIMA-II treats resilience as a latent (unobserved) variable inferred from observable pillars: Access to Basic Services, Assets, Social Safety Nets, and Adaptive Capacity. It first reduces the variables within each pillar to a score using factor or principal-component analysis, then uses a multiple indicators multiple causes (MIMIC) structural-equation model in which the pillars cause the latent resilience and the latent resilience is reflected in observed outcomes such as food security. This produces a Resilience Capacity Index for each household and shows how strongly each pillar contributes.
What is subjective resilience measurement?
Subjective resilience measurement asks people to assess their own ability to anticipate, absorb, and recover from shocks, rather than inferring resilience from external indicators of their assets and services. Using survey questions about perceived coping ability, it captures dimensions — confidence, aspirations, self-assessed capacity — that objective indices may miss, and can be quicker and cheaper to collect. It is increasingly used alongside objective approaches such as RIMA, since the two can diverge and together give a fuller picture of resilience.
Sources
- 1.FAO (2016). RIMA-II: Resilience Index Measurement and Analysis-II. Food and Agriculture Organization of the United Nations, Rome.
- 2.Béné, C., Wood, R. G., Newsham, A., & Davies, M. (2012). Resilience: New Utopia or New Tyranny? Reflection about the Potentials and Limits of the Concept of Resilience in Relation to Vulnerability Reduction Programmes. IDS Working Paper 405. Institute of Development Studies, Brighton.
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Cite this page
ScholarGate. (2026, June 22). Resilience Measurement for Development. ScholarGate. https://scholargate.app/development-studies/resilience-measurement-development