Comments (7)
Congrats, by the way, this library looks like a nice piece of code 👍
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Hi,
In essence, the regions are just strings. Any method you would use would be tied to a specific MRIO - I tried to be as generic as possible in pymrio. For the countries, I developed coco (https://github.com/konstantinstadler/country_converter ) which should just do that. I was thinking to extend coco with more country information (e.g. GDP, population, ...) but then decided to not do that:
This would either require some database backend which needs to be maintained (e.g. for new population data, GDP, ... which might be conflicting between data sources) OR some API access to the data sources to retrieve the information. There are already tools out there doing that, so I decided to not reinvent the tool there - basically, I did not come across a use case which wasn't handled by any other tool yet. Anyway, if you encounter a missing functionality, feel free to implement.
from pymrio.
OK thanks for the answer,
Just the possibility of return the full names together with the ultra-short 2-letter strings would be nice, I don't recognize of all them.
From a first look it seems that country_converter can do that, so I'll just go for this already-existing solution and come back to you if a use-case requires more.
Thanks
from pymrio.
Yeah, I know it is confusing sometimes. But these are the letters used by the MRIO compiliers. For EXIOBASE we tried to follow ISO2 + some custom ones. Other MRIOS (e.g. Eora) use 3 letters which often follows ISO 3 but not always - thats why there are separate categories in coco.
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I get from the following output that Exiobase 3 considers 250 countries, of which many are grouped into a single general area (like WF for example which groups Zambia, Zimbabwe, Western Sahara...)
Does that mean that there is no country not taken into account in Exiobase 3 ? Are all existing countries either considered individually or in a group, or are there missing countries not taken into account at all ?
from pymrio.
Thanks. Yes, the point of the global MRIOs is to cover the global economy. Of course, it is tricky to say if actually cover everything as there are conflicting statistics. We use the global GDP from the UN as the total and scale the remaining countries to it - is the global GDP of the UN correct? Who knows... Same for countries - how many are there? Who knows... (even in the countries we model explicitly - we get comments by Chinese Profs that Taiwan is not a country and we should label it a "Region of China" ...)
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feel free to reopen if necessary and thanks for your continuous help and suggestions 👍🏽
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Related Issues (20)
- add dates to releases in changelog
- Calculating consumption based GHG emission intensities HOT 2
- Fix badges
- column/index name hardcoded as strings - move to constants HOT 1
- Emissions per capita HOT 1
- Potential typos in Exiobase3 industry names HOT 1
- Some data point in the S matrix do not look very reasonable HOT 1
- EXIOBASE downloader
- Developing a parser for the GLORIA MRIO database HOT 5
- concate extension sets name to indicator
- file_parameters.json not found
- pymrio.download_exiobase3 not working
- OECD 2023 release HOT 5
- get_index grouping pattern broken for multiindex
- Ghosh implementation for downstream scope 3 HOT 1
- D_imp/D_exp description in the documentation (matematical background) is wrong
- Regional totals for impact footprints?
- Structural Path Analysis tooling HOT 1
- Output files from IOSystem.calc_all()
- Remove top version restriction for openpyxl
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