As the frequency and severity of climate and other shocks increase governments and development agencies undertake myriad actions intended to improve households’ economic resilience. However, they lack a common metric to measure economic resilience, and sometimes do not measure actual economic experience.

The Feed the Future Innovation Lab for Markets, Risk and Resilience developed a new metric to allow policymakers to answer questions like: Is a population’s resilience growing or falling over time? Did an intervention increase resilience, and by how much? What is the benefit cost ratio of the intervention?

A New Method for Measuring Economic Resilience

MRR developed the Cumulative Avoided Losses (CAL) Metric, a single number that quantifies the economic resilience of households (or other economic unit) over time.  The CAL Metric quantifies economic resilience in terms of the total compromise of current and future economic well-being as the result of a shock.

With reference to Figure 1, the CAL Metric is calculated using the area between shocked households’ recovery path and two other lines:

1. The ‘counterfactual’ pathway of non-shocked households. The area between the two pathways, L reflects the cumulative Losses shocked household experienced.

2. The Zero Resilience Line, which illustrates no recovery at all from the shock. The area, R reflects Recovery.

The CAL Metric over time period, t is the proportion of the area between the counterfactual no-shock and zero resilience lines that is in area R; that is:

Resilient populations maintain well-being close to the no-shock counterfactual and their CAL Metric approaches 1. The CAL Metric lowers for populations with deeper losses and slower recoveries closer to the Zero Resilience Line. Negative resilience occurs if households’ situation further deteriorates post-shock.

Income is an obvious economic metric to use, though other metrics of well-being (e.g., assets, spending, nutritional intake) can be applied, as relevant to the program or policymakers, so long as the data is thoughtfully interpreted.

Evaluating Intervention Impacts

Plotting the experience of households receiving a humanitarian or development intervention shows the strategy’s impact on recovery. In Figure 2, the green line shows the path of households that received a hypothetical insurance payout. The area marked G shows resilience Gains made by an intervention, in comparison to non-treatment households that experienced the shock.

To compare interventions’ impact on resilience, policymakers can compare Gains across them. The G measure also allows calculation of programs’ benefit cost ratio, with Gains as the benefit. 

The CAL Metric in Tanzania

To test the measure, MRR used data collected from 2015 to 2018 in Tanzania, as part of a study following the introduction of insured, stress-tolerant maize seeds. Drought and other shocks hit a portion of farmers in the sample. As shown in Figure 3, farmers without access to the insured seeds lost nearly half their crop and undertook coping strategies that reduced their farms’ capital; over two years,¹ they have a CAL Metric of .08. Farmers who had grown drought-tolerant seeds did not fall as far and were able to start recovering almost immediately with their insurance payout. Their CAL Metric is .82. Comparing these calculated Gains to the cost of the intervention yields a benefit cost ratio of 6.6; that is, each $1 spent would lead to $6.6 in reduced shock losses.

In Tanzania, farmers’ realization of increased resilience prompted them to expand and intensify their cultivation. As a result, their maize income surpasses that of the counterfactual population. We call this phenomenon the Resilience Dividend, or Resilience+.

¹With only a single year of post-shock data available, we have extrapolated possible data points for a second year for illustrative purposes.

Learn more about the Drought Tolerant Maize seed + Index Insurance bundle in Tanzania and Mozambique here.