The Nexus Project is a collaboration between IFPRI and its partners, including national statistical agencies and research institutions. Our aim is to improve the quality of social accounting matrices (SAMs) used for computable general equilibrium (CGE) modeling. The Nexus Project develops toolkits and establishes common data standards, procedures, and classification systems for constructing and updating national SAMs. This addresses the need for greater transparency and consistency in SAM construction to strengthen model-based research and policy analysis in developing countries. Nexus SAMs allow for more robust cross-country comparisons of national economic structure, especially agriculture-food systems. The Nexus Project’s guiding principles are that all data should be traceable to original sources and/or assumptions, and that all SAMs should be freely available online. Greater transparency and accessibility should facilitate more data validation and participation of the modeling community. Statistics are continuously being revised and errors are often only identified when data is used for analysis, and so we welcome your suggestions on how the SAMs can be improved to reflect new and/or better information.

The open access versions of Nexus SAMs separate domestic production into 42 activities. Factors are disaggregated into labor, agricultural land, and capital. Labor is further disaggregated across three education categories. The Nexus SAM defines household groups, namely rural and urban households disaggregated by per capita expenditure quintiles. The remaining accounts include enterprises, government, taxes, savings-and-investment, and the rest of the word.

Nexus SAMs are constructed using a Nexus SAM Building Toolkit developed by IFPRI. During the first stage, a Macro SAM is constructed from and fully consistent with official National Accounts, Government Finance Statistics, and Balance of Payments data. During the second stage, income and expenditure shares derived from household surveys and other sources are used to disaggregate the Macro SAM across multiple activities, commodities, factors, and households. Account imbalances are corrected through cross-entropy estimation.

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181 to 190 of 219 Results
Tabular Data - 5.2 KB - 9 Variables, 86 Observations - UNF:6:gObjC1jRb10xuIJ8lNHaUQ==
CodebookDocumentation
Tabular Data - 133.7 KB - 206 Variables, 363 Observations - UNF:6:yRNipPw9AL31cjz0TqQnQw==
Data
Plain Text - 24.8 KB - MD5: f25727c3f19a40d41f122a5385add292
DocumentationReadme
Nov 16, 2021 - IFPRI Dataverse
International Food Policy Research Institute (IFPRI), 2021, "2014 Social Accounting Matrix for Yemen", https://doi.org/10.7910/DVN/KTFIP5, Harvard Dataverse, V1, UNF:6:9DsvOfyJRwtUxiCEdnlCCA== [fileUNF]
This new regional SAM for Yemen includes 57 productive sectors – including 20 agricultural, 25 industrial, and 12 services activities – in four subnational regions: Highlands, Tihama, Aden, and Hadramaut. The regional SAM has 10 factors of production. Labor is differentiated by three educational levels and between the public and private sectors. Ca...
Tabular Data - 5.8 KB - 20 Variables, 70 Observations - UNF:6:59ug3YOoGEBU69FYGKyVJw==
CodebookDocumentation
Tabular Data - 654.1 KB - 658 Variables, 727 Observations - UNF:6:A/frJvfwmgZtb1aGfEfjFg==
Data
Plain Text - 24.2 KB - MD5: f0c86b01843d180499befc9ab095678e
DocumentationReadme
Nov 16, 2021 - IFPRI Dataverse
Institut Tunisien de la Compétitivité et des Etudes Quantitatives (ITCEQ); International Food Policy Research Institute (IFPRI), 2021, "2015 Social Accounting Matrix for Tunisia", https://doi.org/10.7910/DVN/ELK4P3, Harvard Dataverse, V1, UNF:6:ZBw4I03E31g5WmEMWGnETw== [fileUNF]
The Tunisian regionalized SAM is built using the national accounts statistics, the Supply and Use Tables for 2015 that were produced by National Institute of Statistics (NIS). The regionalized matrix is constructed in three steps that are national, household and regional. The national 2015 SAM for Tunisia includes 46 sectors and 46 products. For th...
Tabular Data - 5.7 KB - 20 Variables, 70 Observations - UNF:6:aYJWvD3HDVXnaMf7zEItYg==
CodebookDocumentation
Tabular Data - 747.0 KB - 658 Variables, 727 Observations - UNF:6:4Hu4X1pjOVfbky47rIam1Q==
Data
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