This section discusses the 2017 study by Stein T. Holden and Mesfin Tilahun, “Land Distribution in Northern Ethiopia from 1998 to 2016: Gender-disaggregated, Spatial and Intertemporal Variation”.1
This study uses land registry data from the First and Second Stage Land Registration Reforms that took place in 1998 and 2016 in sampled districts and communities in the Tigray region of Ethiopia.
There are few studies that have looked at land ownership distribution within male-headed and female-headed households. This is the first such study in Africa. The authors use the SSLR (Second Stage Land Registration) data for gender disaggregated analysis after aggregating parcel data by gender to the household level and categorizing households in male- and female-headed households. Data from 11 municipalities (tabias) in four districts (woredas) were used, covering 78,700 parcels in the SSLR database allocated to 31,500 households.
- The study tried to answer three main questions. In the sampled communities in Tigray, Ethiopia:
- What share of the documented land rights do women hold and what share do men hold? (Did all the effort to document both women and men’s rights to land within a household pay off—do women have documented rights to land and how do those rights compare to men’s?)
- What is the measure of inequality of land access and how has this changed from 1998 to 2016 within and across communities?
- How reliable is the FSLR (First Stage Land Registration) data and to what extent were there measurement errors, and did this bias land distribution measures when comparing FSLR and SSLR data?
Description of intervention
Our focus will be questions one and two above.
Tigray was the first region to implement low-cost land registration and certification in Ethiopia and provided household level land certificates in the names of household heads. Second Stage Land Registration and Certification (SSLRC) has been scaled up since 2015 and provides households with parcel-based certificates with maps. The SSLRC lists all holders of parcels by name and gender.
Context of findings
Tigray is mostly highlands made up of small family farms. Both women and men fought for the Tigray People’s Liberation Front against the Derg regime, and under the Derg regime, land was collectivized. Within families, the law calls for both women and men’s names to be on land documents.
The SSLRC has been scaled to other regions.
The authors found that from the total sample of SSLR data, which represents an area of 30,000 ha, female ownership shares for the land was as high as 48.8%.
The Gini-coefficient for land distribution among women is lower than that among men (0.45 versus 0.57) (less skewed).
In looking at the gender distribution within households, the share of male-headed households with no female landowners varied from 25% to 60% across communities. Close to 45% of male-headed households have zero female land ownership while close to 35% have 50-50 female and male land ownership. Close to 15% have a female share between zero and 50%, and about 5% have a female share between 50 and 100%. For female-headed households the female share is 100% for more than 90% of the households.
Male-headed households had on average 34% more land than female-headed households but this difference was reduced to less than 10% in terms of land per capita (after correcting for differences in family size between male-headed and female-headed households).
There is a clear trend towards smaller farm sizes from the FSLR in 1998 to the SSLR in 2016. The share of farms below one ha varies from 0.50 to 0.90 across communities in the SSLR data.
Thus, while almost 50% of the land is held by women, almost 45% of male headed households do not share ownership with women.
- What is different about the communities or households where women share ownership of land with their husbands vs. the communities or households where women have no land ownership rights within the male headed household?
Holden, Stein T. & Tilahun, Mesfin. (2017). Land Distribution in Northern Ethiopia from 1998 to 2016: Gender-disaggregated, Spatial and Intertemporal Variation