There is a video briefly expaining how to perform this in RStudio.
Now that the package is installed, we can proceed with loading the application and opening the help file for information.
In the following example, we use a fictional dataset (leather data) to illustrate the necessary commands for decomposing
input-output tables. Alternatively, it is possible to use any other available inter-country input-output table (ICIO).
To this end, it is necessary to split the new input-output table into five separate files (for example using excel) and load them into R.
The five files are output (a file with only the output values of the countries and industries),
countries (a list of countries included in the IO table),
industries (a list of industries included in the IO table),
intermediate demand (the part of the IO table stating the flows between industries),
and final demand (the part of the IO table stating the industries’ production values for final demand).
It is important that the last two files only include values but no countries or industries.
If need be, the results can now be exported to a file format that can be processed by other data processing software such as Stata or simply Excel. Below you find an example for exporting the output to basic .csv files.
This YouTube videos gives a brief overwiew into the usage of the package as shown above.
The usage is also described in the R documentation included in the package.
In addition, the contruction of the arrays and computations can be done separately using the atomic functions.
Below is an advanced example of looping the process and using the underlying functions to break the process into smaller steps. It is assumed that the data is stored in csv files.