This study examines the determinants influencing the likelihood of Sub-Saharan African (SSA) countries seeking assistance from the International Monetary Fund (IMF). The IMF, as a global institution, aims to promote sustainable growth and prosperity among its member countries by supporting economic strategies that foster financial stability and collaboration in monetary affairs. Utilising panel-probit regression, this study analyses data from thirty-nine SSA countries spanning from 2000 to 2022, focusing on twelve factors: Current Account Balance (CAB), inflation, corruption, General Government Net Lending and Borrowing (GGNLB), General Government Gross Debt (GGGD), Gross Domestic Product Growth (GDPG), United Nations Security Council (UNSC) involvement, regime types (Closed Autocracy, Electoral Democracy, Electoral Autocracy, Liberal Democracy) and China Loan. The results indicate that corruption and GDP growth rate have the most significant influence on the likelihood of SSA countries seeking IMF assistance. Conversely, factors such as CAB, UNSC involvement, LD and inflation show inconsequential effects. Notable, countries like Sudan, Burundi, and Guinea consistently rank high in seeking IMF assistance over various time frames within the observed period. Sudan emerges with a probability of more than 44% in seeking IMF assistance, holding the highest ranking. Study emphasises the importance of understanding SSA region rankings and the variability of variables for policymakers, investors, and international organisations to effectively address economic challenges and provide financial assistance.

Panel de indicadores TiVA: Total domestic value added, by exporting country, embodied in total exports of other EU-27 countries. Annual. National.

Panel de indicadores TiVA: Total foreign value added by country, embodied in total Spanish exports. Annual. National.

The COKI Open Access Dataset measures open access performance for 142 countries and 5117 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/.

The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution.

Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, Microsoft Academic Graph, Unpaywall and the Research Organization Registry.

After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count.

See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week.

Code

• The COKI Academic Observatory data collection pipeline is used to create the dataset.
• The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here.

License
COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0.

Attributions
This work contains information from:

• Microsoft Academic Graph which is made available under the ODC Attribution Licence.
• Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details.
• Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed.
• Research Organization Registry which is made available under a CC0 licence.

Odds ratios from an unordered logit model of sustainable development in European Union countries.

Odds ratios from an unordered logit model of the standard of living in European Union countries.

The type of development positions are determined by the level of sustainable development and standard of living and corresponding development scenarios for European countries in 2017.

Distribución del gasto realizado por los residentes en sus visitas al Extranjero según país de destino: Distribution of touristic expenditure and average daily expenditure made according to country of destination - Monthly top. Monthly. National.

Values of synthetic measures for the level of standard of living for European Union countries in 2017–2023.

Values of synthetic measures for the level of sustainable development for European Union countries in 2017–2023.

Panel de indicadores TiVA: Total domestic value added, by importing country, embodied in total Spanish exports. Annual. National.

Producing countries of the films programmed in the Official Selection of San Sebastián International Film Festival during 1953-2019.Relación de los países productores de las películas presentadas en la Sección Oficial del Festival Internacional de San Sebastián entre 1953-2019.

Panel probit model estimated results with marginal effect.

Core indicators for measuring progress towards the SDG targets and related 2020 targets.

Residents Travel Survey: Excursions, excursions by person and index over the average by Autonomous Community of residence of the excursionists. Quarterly. Autonomous Communities and Cities.

Residents Travel Survey: Excursions, excursions by person and index over the average by Autonomous Community of residence of the travellers. Quarterly. Autonomous Communities and Cities.

Residents Travel Survey: Travels, overnight stays, average stay and expenditure by Autonomous Community of residence of the travellers. Quarterly. Autonomous Communities and Cities.