Article: A global dataset on subsidies to the fisheries sector
Data in Brief. 2019 Dec., v. 27
2019
Abstract: This article contains data on subsidies provided to the fisheries sector by maritime countries. The dataset is the culmination of extensive data collection efforts using peer-reviewed and grey literature, national budgets, online databases, websites and ... ...
| Abstract | This article contains data on subsidies provided to the fisheries sector by maritime countries. The dataset is the culmination of extensive data collection efforts using peer-reviewed and grey literature, national budgets, online databases, websites and other relevant sources (e.g. OECD, World Bank and WTO), in order to estimate the scope and magnitude of global fisheries subsidies. For subsidies where we found evidence of expenditure by a country, we record the total amount alongside the source references and refer to these as ‘reported’ data. Where evidence is found that a country provides a subsidy but no amount reported, we estimate using various approaches and refer to these as ‘modeled’ data. Where evidence exists that no subsidy is provided by a country we refer to these null values as ‘not found evidence of subsidy’. All amounts were converted to constant 2018 USD using 2017 exchange rates and annual Consumer Price Index averages. The final dataset of ‘reported’, ‘modeled’ and ‘not found’ subsidies for 2018 consists of 13 subsidy types across 152 maritime countries. The dataset, first developed in the early 2000s, now forms part of the global fisheries management infrastructure and is a central tool used by WTO negotiators. The data we provide may be used to support local, regional and global fisheries management decision-making and may have further uses when analysed in combination with other fisheries related data. Interpretation of these data can be found in the associated research article titled “Updated estimates and analysis of global fisheries subsidies” [1]. |
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| Keywords | Consumer Price Index ; Internet ; World Bank ; data collection ; decision making ; infrastructure |
| Language | English |
| Dates of publication | 2019-12 |
| Publishing place | Elsevier Inc. |
| Document type | Article |
| ZDB-ID | 2786545-9 |
| ISSN | 2352-3409 |
| ISSN | 2352-3409 |
| DOI | 10.1016/j.dib.2019.104706 |
| Database | NAL-Catalogue (AGRICOLA) |
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