Updating and estimating a Social Account Matrix using cross entropy methods
| cg.authorship.types | CGIAR single centre | en |
| cg.coverage.country | Mozambique | |
| cg.coverage.iso3166-alpha2 | MZ | |
| cg.coverage.region | Africa | |
| cg.coverage.region | Eastern Africa | |
| cg.creator.identifier | Sherman Robinson: 0000-0002-5478-9372 | |
| cg.identifier.project | IFPRI - Archive | |
| cg.number | 58 | en |
| cg.place | Washington, DC | en |
| cg.reviewStatus | Internal Review | en |
| dc.contributor.author | Robinson, Sherman | en |
| dc.contributor.author | Cattaneo, Andrea | en |
| dc.contributor.author | El-Said, Moataz | en |
| dc.date.accessioned | 2024-10-24T12:45:13Z | en |
| dc.date.available | 2024-10-24T12:45:13Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/156718 | |
| dc.title | Updating and estimating a Social Account Matrix using cross entropy methods | en |
| dcterms.abstract | The problem in estimating a social accounting matrix (SAM) for a recent year is to find an efficient and cost-effective way to incorporate and reconcile information from a variety of sources, including data from prior years. Based on information theory, the paper presents a flexible “cross entropy” (CE) approach to estimating a consistent SAM starting from inconsistent data estimated with error, a common experience in many countries. The method represents an efficient information processing rule—using only and all information available. It allows incorporating errors in variables, inequality constraints, and prior knowledge about any part of the SAM. An example is presented applying the CE approach to data from Mozambique, using a Monte Carlo approach to compare the CE approach to the standard RAS method and to evaluate the gains in precision from utilizing additional information. | en |
| dcterms.accessRights | Open Access | |
| dcterms.bibliographicCitation | Robinson, Sherman; Cattaneo, Andrea; El-Said, Moataz. 2000. Updating and estimating a Social Account Matrix using cross entropy methods. TMD Discussion Paper 58. https://hdl.handle.net/10568/156718 | en |
| dcterms.extent | 37 p. | en |
| dcterms.isPartOf | TMD Discussion Paper | en |
| dcterms.issued | 2000 | |
| dcterms.language | en | |
| dcterms.publisher | International Food Policy Research Institute | en |
| dcterms.replaces | https://ebrary.ifpri.org/digital/collection/p15738coll2/id/125447 | en |
| dcterms.subject | social impact assessment | en |
| dcterms.subject | mathematical models | en |
| dcterms.subject | economics | en |
| dcterms.subject | models | en |
| dcterms.subject | entropy | en |
| dcterms.type | Working Paper |
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