r-imfweo

Seamless Access to IMF World Economic Outlook (WEO) Data

https://github.com/teal-insights/r-imfweo

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Repository

Seamless Access to IMF World Economic Outlook (WEO) Data

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# imfweo



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`imfweo` is an R package to access and analyze the International Monetary Fund's World Economic Outlook (WEO) publications. WEO provides comprehensive analysis and forecasts of the global economy and is published twice a year - typically in April and October. 

The package is designed to work seamlessly with World Bank's International Debt Statistics (IDS) and World Development Indicators (WDI) provided through the [wbids](https://github.com/teal-insights/r-wbids) and [wbwdi](https://github.com/tidy-intelligence/r-wbwdi) package, respectively. It follows the principles of the [EconDataverse](https://www.econdataverse.org/).

This package is a product of Teal Insights and not sponsored by or affiliated with the IMF in any way, except for the use of the WEO data.

> :bulb: This package currently does not use the IMF Data API for several reasons: (i) the API’s SDMX format is complex and difficult to parse; (ii) leveraging the `rsdmx` package would require releasing `imfweo` under the GPL license; and (iii) it’s unclear whether the API provides access to historical WEO publications.

## Installation

You can install `imfweo` from [CRAN](https://CRAN.R-project.org/package=imfweo) via:

``` r
install.packages("imfweo")
```

You can install the development version of `imfweo` from [GitHub](https://github.com/teal-insights/r-imfweo) with:

``` r
# install.packages("pak")
pak::pak("teal-insights/r-imfweo")
```

## Usage

The main function `weo_get()` provides a simple interface to download data from the latest World Economic Outlook (WEO) publication:

```{r}
library(imfweo)

weo_get()
```

Note: On the first run of each R session, the function may take a few seconds to execute as the package checks which WEO publication is currently the latest. This information is put into a cache, which is reset whenever your session restarts. 

To explicitly retrieve the most recent publication metadata, use:

```{r}
weo_get_latest_publication()
```

To fetch data from a specific publication, or to filter by country, indicator, or time range, you can use the available parameters:

```{r}
weo_get(
  entities = c("USA", "GBR", "DEU"),
  series = "NGDP_RPCH",
  start_year = 2015,
  end_year = 2020,
  year = 2023,
  release = "Spring"
)
```

Even when filtering, the full dataset for the selected publication must be downloaded, as the WEO data is distributed in Excel format.

To explore available publications:

```{r}
weo_list_publications()
```

To list the available entities (countries or country groups) for the latest publication:

```{r}
weo_get_entities()
```

To list the available data series:

```{r}
weo_get_series()
```

## Contributing

Contributions to `imfweo` are welcome! If you'd like to contribute, please follow these steps:

1. **Create an issue**: Before making changes, create an issue describing the bug or feature you're addressing.
2. **Fork the repository**: After receiving supportive feedback from the package authors, fork the repository to your GitHub account.
3. **Create a branch**: Create a branch for your changes with a descriptive name.
4. **Make your changes**: Implement your bug fix or feature.
5. **Test your changes**: Run tests to ensure your changes don't break existing functionality.
6. **Submit a pull request**: Push your changes to your fork and submit a pull request to the main repository.

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