2012 Social Accounting Matrix (SAM) for Sudan
2018
International Agricultural Trade and Development Group, Humboldt-Universität zu Berlin | Departments of Agricultural Economics, Khartoum University | Department of Agricultural Economics, Sudan University of Science and Technology | IFPRI-KM | Siddig, Khalid (International Agricultural Trade and Development Group, Humboldt-Universität zu Berlin, Germany and Departments of Agricultural Economics, Khartoum University, the Sudan) | Elagra, Samir (Departments of Agricultural Economics, Sudan University of Science and Technology) | Grethe, Harald (International Agricultural Trade and Development Group, Humboldt-Universität zu Berlin, Germany) | Mubarak, Amel (Departments of Agricultural Economics, Khartoum University, the Sudan)
The 2012 Social Accounting Matrix (SAM) for the Sudan, with a special focus on agriculture, water, and energy, is built using data from domestic sources in the Sudan, including the Central Bureau of Statistics, the Ministry of Agriculture, the Ministry of Finance and Economic Planning, and the Central Bank of Sudan, besides other external sources. Major data sets used include the 2012 National Accounts and Trade Statistics of the CBS, the 53rd Annual Report of the Central Bank of the Sudan, the 2011 Labor Force Survey, the 2009 Household Income and Expenditure Survey, the 2009-2012 Agricultural Production Cost Survey, and the 2005 Industrial Survey. Data from external sources are used to complement national sources. These sources include IMF studies on government finances, FAO reports and data on agriculture, and ILO reports on labor. The SAM distinguishes between agricultural activities based on modes of irrigation, energy based on its major source, and water based on modes of production and types of uses. Land is divided into irrigated and non-irrigated, while natural water resources are added in a separate account. Households are categorized by state, location (rural and urban), and income quintiles. Labor accounts are differentiated based on location (rural and urban), skill level, and gender.
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