‘idle’ estate land. Obtaining a more reliable estimate of the extent to which land currently assigned to estates is unused or underused, though beyond the scope of this paper, would be desirable given the size of estimated economic impacts and the fact that such analysis is no longer too difficult.<sup>20</sup> Such information would be an important basis for policy decisions, e.g. whether (or when) to let estate land that is not used revert to customary authorities.

# **4. Exploring estates’ contribution to agricultural productivity**

We use georeferenced survey data from NACAL to assess whether estates help to increase the productivity of land use either directly or indirectly. Direct effects are approximated by comparing levels of yield, input use, and land use intensity between estates and smallholders. Indirect effects are identified by exploring if smallholders’ location on or in close proximity to estates affects their levels of input use, output, or profit.

# **4.1 Comparing land use and productivity between smallholders and estates**

While administrative data on estate boundaries allow a rough assessment of land under crops via overlays with satellite imagery, information on production and yields requires survey-based information. We use the 2006/07 National Census of Agriculture and Livestock (NACAL).<sup>21</sup> This survey contains information for the 12-month period starting in October 2006 for both smallholders and estates: estates were drawn from a nation-wide list and the survey identified smallholder farms in a two-stage process. Enumeration areas (EAs) were first randomly selected by district with stratification by agro-ecological zone. In selected EAs, a listing was then undertaken and farm households were drawn randomly from the list aiming for 10 small (< 2 acres) and 5 medium sized (≥ 2 acres) farms per EA.

For smallholders, information on household composition, assets, and plot-level production as well as GPS coordinates was collected. Useable data on GPS coordinates are available for 20,677 observations. Information on socio-economic characteristics and production in appendix tables 3 and 4 shows that nationally about 9% -from 16% in the Center to 3% in the South- live as tenants or squatters on an estate. Compared to the rest, the latter cultivate a slightly larger area (1.05 vs. 0.67 ha) and devote a higher share of their land to tobacco, but there is little evidence of differences in terms of intensity of input use, and profits for maize are actually slightly lower.

Table 5 illustrates that on average the 868 estates in the sample had an age of 19 years with largest estates the oldest. Most (73%) are owned by Malawian persons, 11% by ‘others’ -most likely legal entities- and

> 20 Availability of free imagery (sentinel 1/2) at higher temporal and spatial resolution, together with algorithms that can be run on platforms such as Google Earth Engine (GEE) makes analysis much easier.

> 21 The main reason for using the NACAL is that, in contrast to other surveys such as the recent Integrated Household Surveys, it covers estates and smallholders. While we were unable to access the frame used to draw the estate sample (or estate coordinates), we assume that only functioning estates were interviewed, implying that there is some selection that needs to be accounted for when interpreting the results. Although the age of the survey and these shortcomings suggest that a new survey of estates’ productive performance would be highly desirable, fieldwork conducted in a number of regions leads us to believe that the general conclusions derived here are still valid.

11