Data · dataset · 2018
The Multi-sectoral Thirlwall’s Law with capital flows: an analysis of the national export plan (2015-2018) using computational simulations
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Description
ABSTRACT This paper aims to advance the debate on Multi-sectoral Thirlwall’s Law, including sectorial capital flows and its implications for the new Brazilian economy’s growth strategy, which aims to stimulate exports through diversification of products, the aggregation value and increased technology intensity of Brazilian exports. To this end, it develops a multi-sectoral model with sectorial capital flows and, as a result, are carried out some computer simulations considering the main sectors and economic partners of the country (China, United States and the Euro Block).
The results suggest that the best strategy is to encourage specific sectors, that is, increase the participation of the sectors that the country has comparative advantage in relation to each of its trading partners (Manufactured - US, Semi-manufatured - Europe, Primary - China). Despite the results obtained in the simulation, the model templates proposed by Hausmann et al. (2004), can generate the acceleration of economic growth.
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Thus, the National Plan for Exports (2015-2018) should give preference to the expansion of incentives to sectors that have high ratios of elasticity in the sense of Thirlwall.
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Where it is published
- Repository landing page scielo.figshare.com/articles/dataset/The_Multi-sectoral_Thirlwall_s_Law_with_capit… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.5791830 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1590/0101-31572017v37n03a10 doi.org/10.1590/0101-31572017v37n03a10 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.5791830 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.5791830 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Political science
- From keywords
- Economics & Finance
- Inferred from text
- Simulation 75%
Related
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.5791830 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| byte_size | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:political-science | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Economics'] |
| concepts[method].local:method:simulation | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| updated_date | source · DataCite | connector:datacite@1.0.0 |