Equity (generally)

This indicator draws on the conceptual framework for gender equity indicators described elsewhere in this section. Often there may be a reason to focus on equity concerns across specific groups such as by livelihood strategy (crop growers, livestock herders, fishermen) or by ethnicity. In other cases, the focus may be on comparing how the technology performs across wealth and age groups. Usually these comparisons can be done across households, which reduces much of the complexity from intra-household decision making that is essential for gender equity analysis.

Access to resources

These metrics are concerned with fair allocation of physical resources. They measure differential access to resources for agriculture.

Capacity

These metrics are concerned with fair allocation of information and training resources. They measure differential access to information about markets or agricultural practices.

Agency

These metrics are concerned with fair procedures. They measure differential levels of control over resources.

Achievements

These metrics are concerned with fair exchange. They measure differences in how various benefits from agriculture are realized.

Often there may be a reason to focus on equity concerns across specific groups such as by livelihood strategy (crop growers, livestock herders, fishermen) or by ethnicity.  In other cases, the focus may be on comparing how the technology performs across wealth and age groups. Usually these comparisons can be done across households.

However, gender equity analysis requires considering intra-household decision-making, and for this reason gender equity metrics are detailed separately with the gender equity indicator.

Quantitative assessment of equity can be calculated in various ways that combine the average values for each of the groups of interest (Group A and Group B). The following formulas are adapted from work by Rao (2016) on gender equity:

Parity = A/B

A ratio of the Group A to Group B measure, where 1 signals no difference, <1 indicates B is favored and >1 indicates A is favored.

Gap = A ‒ B

The difference between Group A and Group B measures, where 0 signals no difference, <0 indicates B is favored, and >0 indicates A is favored.

Normalized Gap = 100* (A ‒ B)/B

The percentage difference between the Group A and Group B measures, with the B measure as the base: where 0 signals no difference, <0 signals Group B is favored, and >0 signals Group A is favored. The size of the differential is normalized against the Group B value.

When there are more than two groups of interest, then one group is selected as the base for comparison (Group B in the above equations). The base for comparison may be the largest group, the average group, or the most favored group, depending on the situation.

These quantitative measures provide a starting point for equity assessment that can be collected through interviews, focus group discussions, or participatory exercises.  However, equity assessment will be much richer and informative if the quantitative values are accompanied by qualitative information about how and why the observed differences across groups came to be and how fair or just the situation is perceived to be by various types of stakeholders.

For example, imagine two contexts where youths age 17 to 30 have a significant gap in land ownership compared to middle-aged adults.  In one context, youth may not feel it unfair to have less access to land because they are fairly compensated for their contributions while they wait to inherit. But in another context, youth with the same gap in land access may have little hope of inheritance and feel that the status quo is unjust. 

Thus, qualitative methods, such as focus group discussions and in-depth interviews, are critical for correctly interpreting these equity metrics.