The Land Matrix, Phase I

The Land Matrix database is a constantly updated data set that includes deals made for agricultural production (for food or agrofuel production), timber extraction, carbon-trading, mineral extraction, conservation and tourism. Deals included in the database must meet the following criteria:* They entail a transfer of rights to use, control or own land through sale, lease or concession.* They were signed sometime since 2000, when the annualized value of the FAO real food price index was at its lowest level.* They cover an area of 200 hectares or more.* They entail the conversion of land from local community use or from important ecosystem-service provision to commercial production.Records are derived from a variety of sources: media reports; reports by international and local organisations, NGOs, and field-based research projects; company websites; and government records. Sources are partly accessed through two active internet portals dealing with land transactions: [www.commercialpressuresonland.org](http://www.commercialpressuresonland.org/) and [www.farmlandgrab.org](http://www.farmlandgrab.org/). Company websites and governmentrecords are also used where these are available. Moreover, the "crowdsourcing" function plays an increasingly important role.

The project focuses on the impacts of LSLAs, with both a qualitative and a quantitative component. Certain impact dimensions – for example, investment-related benefits and compensations – will be examined on a case-study basis using qualitative approaches. The proposed studies will build on earlier fieldwork. Other impact dimensions – for example, employment and productivity – can be better analysed using quantitative techniques. For these analyses, we will select case study countries. The selection will be informed by the Land Matrix database and will depend on the availability of spatial information on land deals in combination with socio-economic baseline data. Methodologically, we will rely on standard impact evaluation techniques – in particular, differences-in-differences estimates on a small geographical scale (community, village).