Ayamena, Hans Tino Mpenya
African Economic Research Consortium
Human actions are the major causes of environmental changes and land seems to be the common element in all human activities. The main objective of this work is to study the data and stakes related to land issues in Cameroon. Specifically, it entails (1) carrying out an inventory of socio-economic data on issues related to land; (2) identifying the possibility of cross-matching between these databases and with other sources of data; and (3) making suggestions that could enable a better understanding of stakes and an improvement of land data collection and management. The methodology used consists in document analysis and nterviews with public and private institutions involved in these issues. In Cameroon, it can be observed that, in the household surveys (ECAM 1, 2, 3 and 4) conducted by the National Institute of Statistics (NIS), the agriculture and rural development component includes land-related issues. The nation-wide scope of these surveys and their comparability make it possible for information from ECAM databases to be cross-matched with that from other data sources. A better understanding of the stakes inherent to land certainly requires a cross disciplinary approach which brings together environmental sciences, economic sciences, legal sciences, and practitioners drawn from the Ministries in charge land tenure, agriculture, and protection of the environment. Given the shortcomings of the current land laws, it is necessary that they be reformed. A unified approach of data collection in which the different ministries concerned with land issues are included in the designing of questionnaires for socio economic surveys, would contribute in improving the quality of information available on land. Improving the internal system for the management and processing of data from different ministries involved in land management, may equally help in improving the collection of socio-economic land data.
Land, human actions, cross disciplinary, socio-economic data