Share of domestic and foreign monetary flows between sectors of a country In multiregional input-output analysis, monetary flows between or within economic sectors are given in a transaction matrix T. Both, the rows and the columns, have the same index (Region 1 Sector 1, Region 1 Sector 2, ... Region 2 Sector 1, Region 2 Sector 2, ... ). The diagonal of the T matrix contains the intra-sectoral monetary flows. Analagously, the diagonal of the &quot;regional blocks&quot; (all sectors from one region) contains the intra-regional monetary flows between sectors.
I figured that in the database with which I am working, the share of intra-regional monetary flows (all flows belong to region 1) compared to all monetary flows of a region (all flows from region 1 to region 2 or vice versa) are rather low. Let's say around 20% on average. To me (non-expert), this seems plausible. However, I would like to crosscheck my findings with &quot;real world data&quot;.
Question: Is there an indicator which compares intra-regional monetary flows with total extra-regional monetary flows? ... in other words: How much monetary flows between sectors take place within a country and how much monetary flows between sectors of a country take place with sectors from other countries?
I came across &quot;Trade (% of GDP)&quot; (https://data.worldbank.org/indicator/NE.TRD.GNFS.ZS). However, 1) in input-output analysis I understand GDP to be given by the final demand vector/matrix and 2) the given figures of about 50 to 60% are completly different to my findings of around 20%.
The exports and imports in an input-output analysis should correspond to imports and exports as components of GDP so you can use those or some measures derived from them.
For example, trade as a $\%$ of GDP is the sum of exports plus imports over GDP (i.e. $\frac{E+M}{Y}$, where $E$ is export, $M$ import and $Y$ GDP/output).
Hence to calculate any comparable measure from input output table you would have to take the import and export variables from your study (your input-output table should have import row and export column), sum them together and then divide them by output.
You can also find data for $E$, $M$ and $Y$ separately and compare those to the measure you constructed. Based on the question I guess you came to $20\%$ by perhaps doing something like $\frac{E-M}{Y}$?
In addition input-output analysis is not necessary accurate and you should not be surprised to find discrepancies between what your input-output model shows and what holds in real world. Especially, if your input-output model has too many sectors small errors introduced by rounding and linearization can add up and produce results that will not be accurate.