Friendly & Fast Input-Output Analysis
{fio} (Friendly Input-Output) is a R package designed for
input-output analysis, emphasizing usability for Excel users and
performance. It includes an RStudio
Addin and a suite of
functions for straightforward import of input-output tables from Excel,
either programmatically or directly from the clipboard.
The package is optimized for speed and efficiency. It leverages the R6 class for clean, memory-efficient object-oriented programming. Furthermore, all linear algebra computations are implemented in Rust to achieve highly optimized performance.
You can install the latest stable release of {fio} from CRAN with:
install.packages("fio")install the latest tested but unreleased version from the main branch, use the precompiled binaries available on R-universe:
install.packages("fio", repos = c("https://albersonmiranda.r-universe.dev", "https://cloud.r-project.org"))For the cutting-edge development version from the dev branch, you’ll need to compile it from source. This requires Rust to be installed on your system. You can install Rust using the following commands:
- Debian/Ubuntu:
apt-get install cargo - Fedora/CentOS:
dnf install cargo - macOS:
brew install rustc - Windows: https://www.rust-lang.org/tools/install
If you are just getting started with {fio}, we recommend you to read
the
vignettes
for a comprehensive overview of the package.
Calculate Leontief’s inverse from brazilian 2020 input-output matrix:
# load included dataset
iom_br <- fio::br_2020
# calculate technical coefficients matrix
iom_br$compute_tech_coeff()
# calculate Leontief's inverse
iom_br$compute_leontief_inverse()And pronto! 🎉, you’re all good to carry on with your analysis. You can
evoke the Data Viewer to inspect the results with
iom_br$technical_coefficients_matrix |> View() and
iom_br$leontief_inverse_matrix |> View().
Leontief’s inverse
from brazilian 2020 input-output matrix
Other great tools for input-output analysis in R include: