with further increase the cost of service provision,<sup>17</sup> making it more difficult to ascertain absence of competing claims to titled land. Together with foreclosure costs of 48% of property value (World Bank 2008), this increases the cost of using land as collateral for any bank that would be interested in doing so.

# **3. Data and descriptive statistics**

To gain a better understanding of the size of Zambia’s medium and large farm sector and its temporal and spatial evolution, we combine a listing and mapping of large farms with digitized administrative records and a detailed large farm performance survey for the country’s Eastern Province. We find that at most 26% of owned and 12% of cultivated land is accounted for by large farms; that formalized holdings are clustered in blocks with better soil quality and infrastructure access though neither yields nor profits are higher inside as compared to outside blocks. While titled land does not seem to enjoy a productivity advantage, there is considerable unsatisfied demand for title.

# **3.1 Emergent farmer census**

To obtain a complete enumeration of all large farms in Eastern Province, a farm module was added to the mapping exercise for the 2020 population census conducted between January and March 2020. Computer assisted personal interviewing was used to list all structures, their purpose, and for those that were inhabited, administer a short questionnaire to residents. At the end of this questionnaire, a question was added asking respondents to indicate if they owned, operated, or guarded an agricultural holding greater than 5 ha.

For those answering in the affirmative, basic questions on the nature of the property were asked and boundaries of farms in the same district mapped using high resolution satellite imagery pre-loaded on enumerators’ tablets as a base map.<sup>18</sup> The listing identified 8,301 farms in 1,729 enumeration areas (EAs) of which 6,782 were mapped (and 6,703 had a mapped area above 5 ha). To generate a sample frame for a more detailed farm performance survey, we dropped all wards<sup>19</sup> with fewer than 30 farms as these would have been too costly to visit, resulting in a frame of 5,620 farms in 1,066 EAs from 62 wards. To attain our target sample size of 3,000, we include all farms greater than 20 ha and a random sample of farms below 20 ha.<sup>20</sup> This provides the basis for studying the extent to which farms’ productivity, level of land-related investment, and self-assessed land values are affected by access to formal documentation.

> 17 In principle, the Zambia Integrated Land Information and Management System (ZILMIS) created in 2003 on an Oracle platform should allow fully digital document processing. However, the system is not operational, and the Ministry has neither access to source code nor capacity to even execute basic queries. The largely textual information in the system is of poor quality. While all spatial records for Eastern Province were digitized with World Bank support, the Ministry of Lands continues to run paper-based and digital systems in parallel so that absence of a competing claim in the electronic system cannot provide conclusive evidence of property ownership, failing the basic requirement of a titling system.

> 18 Mapping was limited to farms located in the same district as loading imagery beyond the district would have exceeded tablets’ storage capacity. 19 After provinces, districts, and constituencies, wards are the fourth tier in Zambia’s system of administrative divisions. They are used for census and election purposes.

> 20 We include all 1,451 farms above 20 ha from the listing and randomly select 1,549 of the 4,169 farms in the 5-20 ha category. Enumerators managed to interview 2,903 (96.8%) of the original sampled farms and they ended up replacing 42 (from a randomly selected replacement list) of the 97 missing cases. The final sample size is thus 2,945 farms, resulting in roughly less than 2% attrition rate.

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